Science.gov

Sample records for large sharing networks

  1. Building a Shared Information Network.

    ERIC Educational Resources Information Center

    Stanat, Ruth

    1991-01-01

    Discussion of information needs in a business environment focuses on how to build a shared information network. Highlights include the evolution of corporate intelligence systems; results of a survey that examined the information networking needs of large corporations; and a case study of the development of an information network at Citibank N.A.…

  2. Evolving Research Data Sharing Networks to Clinical App Sharing Networks

    PubMed Central

    Wagholikar, Kavishwar B.; Jain, Rahul; Oliveira, Eliel; Mandel, Joshua; Klann, Jeffery; Colas, Ricardo; Patil, Prasad; Yadav, Kuladip; Mandl, Kenneth D.; Carton, Thomas; Murphy, Shawn N.

    2017-01-01

    Research networks for data sharing are growing into a large platform for pragmatic clinical trials to generate quality evidence for shared medical decision-making. Institutions partnering in the networks have made large investments in developing the infrastructure for sharing data. We investigate whether institutions partnering on Patient-Centered Outcomes Research Institute’s (PCORI) network can share clinical apps. At two different sites, we imported patient data in PCORI’s clinical data model (CDM) format into i2b2 repositories, and adapted the SMART-on-FHIR cell to perform CDM-to-FHIR translation, serving demographics, laboratory results and diagnoses. We performed manual validations and tested the platform using four apps from the SMART app gallery. Our study demonstrates an approach to extend the research infrastructure to allow the partnering institutions to run shared clinical apps, and highlights the involved challenges. Our results, tooling and publically accessible data service can potentially transform research networks into clinical app sharing networks and pave the way towards a learning health system. PMID:28815145

  3. Evolving Research Data Sharing Networks to Clinical App Sharing Networks.

    PubMed

    Wagholikar, Kavishwar B; Jain, Rahul; Oliveira, Eliel; Mandel, Joshua; Klann, Jeffery; Colas, Ricardo; Patil, Prasad; Yadav, Kuladip; Mandl, Kenneth D; Carton, Thomas; Murphy, Shawn N

    2017-01-01

    Research networks for data sharing are growing into a large platform for pragmatic clinical trials to generate quality evidence for shared medical decision-making. Institutions partnering in the networks have made large investments in developing the infrastructure for sharing data. We investigate whether institutions partnering on Patient-Centered Outcomes Research Institute's (PCORI) network can share clinical apps. At two different sites, we imported patient data in PCORI's clinical data model (CDM) format into i2b2 repositories, and adapted the SMART-on-FHIR cell to perform CDM-to-FHIR translation, serving demographics, laboratory results and diagnoses. We performed manual validations and tested the platform using four apps from the SMART app gallery. Our study demonstrates an approach to extend the research infrastructure to allow the partnering institutions to run shared clinical apps, and highlights the involved challenges. Our results, tooling and publically accessible data service can potentially transform research networks into clinical app sharing networks and pave the way towards a learning health system.

  4. Fixed Access Network Sharing

    NASA Astrophysics Data System (ADS)

    Cornaglia, Bruno; Young, Gavin; Marchetta, Antonio

    2015-12-01

    Fixed broadband network deployments are moving inexorably to the use of Next Generation Access (NGA) technologies and architectures. These NGA deployments involve building fiber infrastructure increasingly closer to the customer in order to increase the proportion of fiber on the customer's access connection (Fibre-To-The-Home/Building/Door/Cabinet… i.e. FTTx). This increases the speed of services that can be sold and will be increasingly required to meet the demands of new generations of video services as we evolve from HDTV to "Ultra-HD TV" with 4k and 8k lines of video resolution. However, building fiber access networks is a costly endeavor. It requires significant capital in order to cover any significant geographic coverage. Hence many companies are forming partnerships and joint-ventures in order to share the NGA network construction costs. One form of such a partnership involves two companies agreeing to each build to cover a certain geographic area and then "cross-selling" NGA products to each other in order to access customers within their partner's footprint (NGA coverage area). This is tantamount to a bi-lateral wholesale partnership. The concept of Fixed Access Network Sharing (FANS) is to address the possibility of sharing infrastructure with a high degree of flexibility for all network operators involved. By providing greater configuration control over the NGA network infrastructure, the service provider has a greater ability to define the network and hence to define their product capabilities at the active layer. This gives the service provider partners greater product development autonomy plus the ability to differentiate from each other at the active network layer.

  5. Multi-modal analysis of functional connectivity and cerebral blood flow reveals shared and unique effects of propofol in large-scale brain networks.

    PubMed

    Qiu, Maolin; Scheinost, Dustin; Ramani, Ramachandran; Constable, R Todd

    2017-03-01

    Anesthesia-induced changes in functional connectivity and cerebral blow flow (CBF) in large-scale brain networks have emerged as key markers of reduced consciousness. However, studies of functional connectivity disagree on which large-scale networks are altered or preserved during anesthesia, making it difficult to find a consensus amount studies. Additionally, pharmacological alterations in CBF could amplify or occlude changes in connectivity due to the shared variance between CBF and connectivity. Here, we used data-driven connectivity methods and multi-modal imaging to investigate shared and unique neural correlates of reduced consciousness for connectivity in large-scale brain networks. Rs-fMRI and CBF data were collected from the same subjects during an awake and deep sedation condition induced by propofol. We measured whole-brain connectivity using the intrinsic connectivity distribution (ICD), a method not reliant on pre-defined seed regions, networks of interest, or connectivity thresholds. The shared and unique variance between connectivity and CBF were investigated. Finally, to account for shared variance, we present a novel extension to ICD that incorporates cerebral blood flow (CBF) as a scaling factor in the calculation of global connectivity, labeled CBF-adjusted ICD). We observed altered connectivity in multiple large-scale brain networks including the default mode (DMN), salience, visual, and motor networks and reduced CBF in the DMN, frontoparietal network, and thalamus. Regional connectivity and CBF were significantly correlated during both the awake and propofol condition. Nevertheless changes in connectivity and CBF between the awake and deep sedation condition were only significantly correlated in a subsystem of the DMN, suggesting that, while there is significant shared variance between the modalities, changes due to propofol are relatively unique. Similar, but less significant, results were observed in the CBF-adjusted ICD analysis, providing

  6. Expansible quantum secret sharing network

    NASA Astrophysics Data System (ADS)

    Sun, Ying; Xu, Sheng-Wei; Chen, Xiu-Bo; Niu, Xin-Xin; Yang, Yi-Xian

    2013-08-01

    In the practical applications, member expansion is a usual demand during the development of a secret sharing network. However, there are few consideration and discussion on network expansibility in the existing quantum secret sharing schemes. We propose an expansible quantum secret sharing scheme with relatively simple and economical quantum resources and show how to split and reconstruct the quantum secret among an expansible user group in our scheme. Its trait, no requirement of any agent's assistant during the process of member expansion, can help to prevent potential menaces of insider cheating. We also give a discussion on the security of this scheme from three aspects.

  7. Data sharing and intellectual property in a genomic epidemiology network: policies for large-scale research collaboration.

    PubMed Central

    Chokshi, Dave A.; Parker, Michael; Kwiatkowski, Dominic P.

    2006-01-01

    Genomic epidemiology is a field of research that seeks to improve the prevention and management of common diseases through an understanding of their molecular origins. It involves studying thousands of individuals, often from different populations, with exacting techniques. The scale and complexity of such research has required the formation of research consortia. Members of these consortia need to agree on policies for managing shared resources and handling genetic data. Here we consider data-sharing and intellectual property policies for an international research consortium working on the genomic epidemiology of malaria. We outline specific guidelines governing how samples and data are transferred among its members; how results are released into the public domain; when to seek protection for intellectual property; and how intellectual property should be managed. We outline some pragmatic solutions founded on the basic principles of promoting innovation and access. PMID:16710548

  8. Analysis and improvement of vehicle information sharing networks

    NASA Astrophysics Data System (ADS)

    Gong, Hang; He, Kun; Qu, Yingchun; Wang, Pu

    2016-06-01

    Based on large-scale mobile phone data, mobility demand was estimated and locations of vehicles were inferred in the Boston area. Using the spatial distribution of vehicles, we analyze the vehicle information sharing network generated by the vehicle-to-vehicle (V2V) communications. Although a giant vehicle cluster is observed, the coverage and the efficiency of the information sharing network remain limited. Consequently, we propose a method to extend the information sharing network's coverage by adding long-range connections between targeted vehicle clusters. Furthermore, we employ the optimal design strategy discovered in square lattice to improve the efficiency of the vehicle information sharing network.

  9. Traffic sharing algorithms for hybrid mobile networks

    NASA Technical Reports Server (NTRS)

    Arcand, S.; Murthy, K. M. S.; Hafez, R.

    1995-01-01

    In a hybrid (terrestrial + satellite) mobile personal communications networks environment, a large size satellite footprint (supercell) overlays on a large number of smaller size, contiguous terrestrial cells. We assume that the users have either a terrestrial only single mode terminal (SMT) or a terrestrial/satellite dual mode terminal (DMT) and the ratio of DMT to the total terminals is defined gamma. It is assumed that the call assignments to and handovers between terrestrial cells and satellite supercells take place in a dynamic fashion when necessary. The objectives of this paper are twofold, (1) to propose and define a class of traffic sharing algorithms to manage terrestrial and satellite network resources efficiently by handling call handovers dynamically, and (2) to analyze and evaluate the algorithms by maximizing the traffic load handling capability (defined in erl/cell) over a wide range of terminal ratios (gamma) given an acceptable range of blocking probabilities. Two of the algorithms (G & S) in the proposed class perform extremely well for a wide range of gamma.

  10. Traffic sharing algorithms for hybrid mobile networks

    NASA Technical Reports Server (NTRS)

    Arcand, S.; Murthy, K. M. S.; Hafez, R.

    1995-01-01

    In a hybrid (terrestrial + satellite) mobile personal communications networks environment, a large size satellite footprint (supercell) overlays on a large number of smaller size, contiguous terrestrial cells. We assume that the users have either a terrestrial only single mode terminal (SMT) or a terrestrial/satellite dual mode terminal (DMT) and the ratio of DMT to the total terminals is defined gamma. It is assumed that the call assignments to and handovers between terrestrial cells and satellite supercells take place in a dynamic fashion when necessary. The objectives of this paper are twofold, (1) to propose and define a class of traffic sharing algorithms to manage terrestrial and satellite network resources efficiently by handling call handovers dynamically, and (2) to analyze and evaluate the algorithms by maximizing the traffic load handling capability (defined in erl/cell) over a wide range of terminal ratios (gamma) given an acceptable range of blocking probabilities. Two of the algorithms (G & S) in the proposed class perform extremely well for a wide range of gamma.

  11. Sharing Clouds: Showing, Distributing, and Sharing Large Point Datasets

    NASA Astrophysics Data System (ADS)

    Grigsby, S.

    2012-12-01

    Sharing large data sets with colleagues and the general public presents a unique technological challenge for scientists. In addition to large data volumes, there are significant challenges in representing data that is often irregular, multidimensional and spatial in nature. For derived data products, additional challenges exist in displaying and providing provenance data. For this presentation, several open source technologies are demonstrated for the remote display and access of large irregular point data sets. These technologies and techniques include the remote viewing of point data using HTML5 and OpenGL, which provides a highly accessible preview of the data sets for a range of audiences. Intermediate levels of accessibility and high levels of interactivity are accomplished with technologies such as wevDAV, which allows collaborators to run analysis on local clients, using data stored and administered on remote servers. Remote processing and analysis, including provenance tracking, will be discussed at the workgroup level. The data sets used for this presentation include data acquired from the NSF funded National Center for Airborne Laser Mapping (NCALM), and data acquired for research and instructional use in NASA's Student Airborne Research Program (SARP). These datasets include Light Ranging And Detection (LiDAR) point clouds ranging in size from several hundred thousand to several hundred million data points; the techniques and technologies discussed are applicable to other forms of irregular point data.

  12. Network Adaptive Deadband: NCS Data Flow Control for Shared Networks

    PubMed Central

    Díaz-Cacho, Miguel; Delgado, Emma; Prieto, José A. G.; López, Joaquín

    2012-01-01

    This paper proposes a new middleware solution called Network Adaptive Deadband (NAD) for long time operation of Networked Control Systems (NCS) through the Internet or any shared network based on IP technology. The proposed middleware takes into account the network status and the NCS status, to improve the global system performance and to share more effectively the network by several NCS and sensor/actuator data flows. Relationship between network status and NCS status is solved with a TCP-friendly transport flow control protocol and the deadband concept, relating deadband value and transmission throughput. This creates a deadband-based flow control solution. Simulation and experiments in shared networks show that the implemented network adaptive deadband has better performance than an optimal constant deadband solution in the same circumstances. PMID:23208556

  13. Sagnac secret sharing over telecom fiber networks.

    PubMed

    Bogdanski, Jan; Ahrens, Johan; Bourennane, Mohamed

    2009-01-19

    We report the first Sagnac quantum secret sharing (in three-and four-party implementations) over 1550 nm single mode fiber (SMF) networks, using a single qubit protocol with phase encoding. Our secret sharing experiment has been based on a single qubit protocol, which has opened the door to practical secret sharing implementation over fiber telecom channels and in free-space. The previous quantum secret sharing proposals were based on multiparticle entangled states, difficult in the practical implementation and not scalable. Our experimental data in the three-party implementation show stable (in regards to birefringence drift) quantum secret sharing transmissions at the total Sagnac transmission loop distances of 55-75 km with the quantum bit error rates (QBER) of 2.3-2.4% for the mean photon number micro?= 0.1 and 1.7-2.1% for micro= 0.3. In the four-party case we have achieved quantum secret sharing transmissions at the total Sagnac transmission loop distances of 45-55 km with the quantum bit error rates (QBER) of 3.0-3.7% for the mean photon number micro= 0.1 and 1.8-3.0% for micro?= 0.3. The stability of quantum transmission has been achieved thanks to our new concept for compensation of SMF birefringence effects in Sagnac, based on a polarization control system and a polarization insensitive phase modulator. The measurement results have showed feasibility of quantum secret sharing over telecom fiber networks in Sagnac configuration, using standard fiber telecom components.

  14. Creating, documenting and sharing network models.

    PubMed

    Crook, Sharon M; Bednar, James A; Berger, Sandra; Cannon, Robert; Davison, Andrew P; Djurfeldt, Mikael; Eppler, Jochen; Kriener, Birgit; Furber, Steve; Graham, Bruce; Plesser, Hans E; Schwabe, Lars; Smith, Leslie; Steuber, Volker; van Albada, Sacha

    2012-01-01

    As computational neuroscience matures, many simulation environments are available that are useful for neuronal network modeling. However, methods for successfully documenting models for publication and for exchanging models and model components among these projects are still under development. Here we briefly review existing software and applications for network model creation, documentation and exchange. Then we discuss a few of the larger issues facing the field of computational neuroscience regarding network modeling and suggest solutions to some of these problems, concentrating in particular on standardized network model terminology, notation, and descriptions and explicit documentation of model scaling. We hope this will enable and encourage computational neuroscientists to share their models more systematically in the future.

  15. Data sharing in the Undiagnosed Diseases Network

    PubMed Central

    Brownstein, Catherine A.; Holm, Ingrid A.; Ramoni, Rachel; Goldstein, David B.

    2015-01-01

    The Undiagnosed Diseases Network (UDN), builds on the successes of the Undiagnosed Diseases Program at the National Institutes of Health (NIH UDP). Through support from the NIH Common Fund, a coordinating center, six additional clinical sites, and two sequencing cores comprise the UDN. The objectives of the UDN are to: (1) improve the level of diagnosis and care for patients with undiagnosed diseases through the development of common protocols designed by an enlarged community of investigators across the Network; (2) facilitate research into the etiology of undiagnosed diseases, by collecting and sharing standardized, high-quality clinical and laboratory data including genotyping, phenotyping, and environmental exposure data; and (3) create an integrated and collaborative research community across multiple clinical sites, and among laboratory and clinical investigators, to investigate the pathophysiology of these rare diseases and to identify options for patient management. Broad-based data sharing is at the core of achieving these objectives, and the UDN is establishing the policies and governance structure to support broad data sharing. PMID:26220576

  16. 47 CFR 27.1310 - Network sharing agreement.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 47 Telecommunication 2 2010-10-01 2010-10-01 false Network sharing agreement. 27.1310 Section 27... MISCELLANEOUS WIRELESS COMMUNICATIONS SERVICES 700 MHz Public/Private Partnership § 27.1310 Network sharing..., and related entities as the Commission may require or allow will be governed by the Network Sharing...

  17. 47 CFR 27.1310 - Network sharing agreement.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 47 Telecommunication 2 2012-10-01 2012-10-01 false Network sharing agreement. 27.1310 Section 27... MISCELLANEOUS WIRELESS COMMUNICATIONS SERVICES 700 MHz Public/Private Partnership § 27.1310 Network sharing..., and related entities as the Commission may require or allow will be governed by the Network Sharing...

  18. 47 CFR 90.1410 - Network sharing agreement.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 47 Telecommunication 5 2012-10-01 2012-10-01 false Network sharing agreement. 90.1410 Section 90... PRIVATE LAND MOBILE RADIO SERVICES 700 MHz Public/Private Partnership § 90.1410 Network sharing agreement... related entities as the Commission may require or allow will be governed by the Network Sharing Agreement...

  19. 47 CFR 90.1410 - Network sharing agreement.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 47 Telecommunication 5 2010-10-01 2010-10-01 false Network sharing agreement. 90.1410 Section 90... PRIVATE LAND MOBILE RADIO SERVICES 700 MHz Public/Private Partnership § 90.1410 Network sharing agreement... related entities as the Commission may require or allow will be governed by the Network Sharing Agreement...

  20. 47 CFR 27.1310 - Network sharing agreement.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 47 Telecommunication 2 2011-10-01 2011-10-01 false Network sharing agreement. 27.1310 Section 27... MISCELLANEOUS WIRELESS COMMUNICATIONS SERVICES 700 MHz Public/Private Partnership § 27.1310 Network sharing..., and related entities as the Commission may require or allow will be governed by the Network Sharing...

  1. 47 CFR 90.1410 - Network sharing agreement.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 47 Telecommunication 5 2011-10-01 2011-10-01 false Network sharing agreement. 90.1410 Section 90... PRIVATE LAND MOBILE RADIO SERVICES 700 MHz Public/Private Partnership § 90.1410 Network sharing agreement... related entities as the Commission may require or allow will be governed by the Network Sharing Agreement...

  2. 47 CFR 27.1305 - Shared wireless broadband network.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 47 Telecommunication 2 2012-10-01 2012-10-01 false Shared wireless broadband network. 27.1305... broadband network. The Shared Wireless Broadband Network developed by the 700 MHz Public/Private Partnership must be designed to meet requirements associated with a nationwide, public safety broadband network. At...

  3. 47 CFR 90.1405 - Shared wireless broadband network.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 47 Telecommunication 5 2011-10-01 2011-10-01 false Shared wireless broadband network. 90.1405... broadband network. The Shared Wireless Broadband Network developed by the 700 MHz Public/Private Partnership must be designed to meet requirements associated with a nationwide, public safety broadband network. At...

  4. 47 CFR 90.1405 - Shared wireless broadband network.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 47 Telecommunication 5 2010-10-01 2010-10-01 false Shared wireless broadband network. 90.1405... broadband network. The Shared Wireless Broadband Network developed by the 700 MHz Public/Private Partnership must be designed to meet requirements associated with a nationwide, public safety broadband network. At...

  5. 47 CFR 90.1405 - Shared wireless broadband network.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 47 Telecommunication 5 2012-10-01 2012-10-01 false Shared wireless broadband network. 90.1405... broadband network. The Shared Wireless Broadband Network developed by the 700 MHz Public/Private Partnership must be designed to meet requirements associated with a nationwide, public safety broadband network. At...

  6. 47 CFR 27.1305 - Shared wireless broadband network.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 47 Telecommunication 2 2010-10-01 2010-10-01 false Shared wireless broadband network. 27.1305... broadband network. The Shared Wireless Broadband Network developed by the 700 MHz Public/Private Partnership must be designed to meet requirements associated with a nationwide, public safety broadband network. At...

  7. 47 CFR 27.1305 - Shared wireless broadband network.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 47 Telecommunication 2 2011-10-01 2011-10-01 false Shared wireless broadband network. 27.1305... broadband network. The Shared Wireless Broadband Network developed by the 700 MHz Public/Private Partnership must be designed to meet requirements associated with a nationwide, public safety broadband network. At...

  8. Secure Peer-to-Peer Networks for Scientific Information Sharing

    NASA Technical Reports Server (NTRS)

    Karimabadi, Homa

    2012-01-01

    The most common means of remote scientific collaboration today includes the trio of e-mail for electronic communication, FTP for file sharing, and personalized Web sites for dissemination of papers and research results. With the growth of broadband Internet, there has been a desire to share large files (movies, files, scientific data files) over the Internet. Email has limits on the size of files that can be attached and transmitted. FTP is often used to share large files, but this requires the user to set up an FTP site for which it is hard to set group privileges, it is not straightforward for everyone, and the content is not searchable. Peer-to-peer technology (P2P), which has been overwhelmingly successful in popular content distribution, is the basis for development of a scientific collaboratory called Scientific Peer Network (SciPerNet). This technology combines social networking with P2P file sharing. SciPerNet will be a standalone application, written in Java and Swing, thus insuring portability to a number of different platforms. Some of the features include user authentication, search capability, seamless integration with a data center, the ability to create groups and social networks, and on-line chat. In contrast to P2P networks such as Gnutella, Bit Torrent, and others, SciPerNet incorporates three design elements that are critical to application of P2P for scientific purposes: User authentication, Data integrity validation, Reliable searching SciPerNet also provides a complementary solution to virtual observatories by enabling distributed collaboration and sharing of downloaded and/or processed data among scientists. This will, in turn, increase scientific returns from NASA missions. As such, SciPerNet can serve a two-fold purpose for NASA: a cost-savings software as well as a productivity tool for scientists working with data from NASA missions.

  9. Querying Large Biological Network Datasets

    ERIC Educational Resources Information Center

    Gulsoy, Gunhan

    2013-01-01

    New experimental methods has resulted in increasing amount of genetic interaction data to be generated every day. Biological networks are used to store genetic interaction data gathered. Increasing amount of data available requires fast large scale analysis methods. Therefore, we address the problem of querying large biological network datasets.…

  10. Querying Large Biological Network Datasets

    ERIC Educational Resources Information Center

    Gulsoy, Gunhan

    2013-01-01

    New experimental methods has resulted in increasing amount of genetic interaction data to be generated every day. Biological networks are used to store genetic interaction data gathered. Increasing amount of data available requires fast large scale analysis methods. Therefore, we address the problem of querying large biological network datasets.…

  11. Learning Theory for Collaborative Large Shared Digital Spaces

    ERIC Educational Resources Information Center

    McGivern, Daniela; Morgan, Michael; Butler, Matthew

    2012-01-01

    This research applies Socio-Cultural theory and Distributed Cognition/Activity theory to conceptualize the design of collaborative learning activities in large shared digital spaces. The paper begins by providing a summary of previous work in the creation of a technology platform for large shared digital spaces. It then details how Socio-Cultural…

  12. Learning Theory for Collaborative Large Shared Digital Spaces

    ERIC Educational Resources Information Center

    McGivern, Daniela; Morgan, Michael; Butler, Matthew

    2012-01-01

    This research applies Socio-Cultural theory and Distributed Cognition/Activity theory to conceptualize the design of collaborative learning activities in large shared digital spaces. The paper begins by providing a summary of previous work in the creation of a technology platform for large shared digital spaces. It then details how Socio-Cultural…

  13. Shared Access Optical Networks For The Local Loop

    NASA Astrophysics Data System (ADS)

    Payne, D. B.; Stern, J. R.

    1988-09-01

    The application of single mode fibre to the local network environment opens up major opportunities for service provision via shared access networks. Previous technologies (copper pair, coaxial cable and multimode fibre) had bandwidth limitation problems that placed a severe restriction on both the level of resource sharing and the service package that could be delivered. The enormous bandwidth capability of single mode fibre can be used to provide significant resource sharing without incurring fundamental restrictions on the capacity of the services carried. The paper briefly outlines some of the activities within British Telecom on shared access systems. Early systems concepts were either based on fibre feeders to remote multiplexers for the delivery of telephony and data services to large customers or the use of advanced wavelength multiplexing techniques over passive optical networks for the transmission of wideband services to business and residential customers. Recently activity has concentrated on a passive optical network that shows good potential for the economic provision of telephony services. The structure of the network allows the later addition of broadband services via additional wavelengths without disturbing existing telephony/data customers. The basic network has a fibre feeder from the exchange to passive optical splitters housed at the Cabinet and Distribution Points (DP). Each customer receives a fibre from DP and via this a TDM multiplex broadcast from the exchange which carries the customer's traffic. The customer equipment accesses the time slots destined for the customer and delivers the data via a suitable interface to provide the services required. Customers transmit back to the exchange in a time multiplex synchronised by a ranging protocol that sets an appropriate delay in the customer equipment to avoid collisions at the optical combiners in the DPs and Cabinet. Present studies are considering a total optical split of 128 ways with a

  14. Mission Networks: An Evolution in Information Sharing

    DTIC Science & Technology

    2012-03-20

    organizational change in information sharing culture and anchoring the need to share will dictate its future. This paper examines key strategic guidance on information sharing mandates, the evolution of net-centricity, the current operating environment, the AMN, and DoD organizational change and associated

  15. Detecting communities in large networks

    NASA Astrophysics Data System (ADS)

    Capocci, A.; Servedio, V. D. P.; Caldarelli, G.; Colaiori, F.

    2005-07-01

    We develop an algorithm to detect community structure in complex networks. The algorithm is based on spectral methods and takes into account weights and link orientation. Since the method detects efficiently clustered nodes in large networks even when these are not sharply partitioned, it turns to be specially suitable for the analysis of social and information networks. We test the algorithm on a large-scale data-set from a psychological experiment of word association. In this case, it proves to be successful both in clustering words, and in uncovering mental association patterns.

  16. Impact of network sharing in multi-core architectures.

    SciTech Connect

    Narayanaswamy, G.; Balaji, P.; Feng, W.; Mathematics and Computer Science; Virginia Tech

    2008-01-01

    As commodity components continue to dominate the realm of high-end computing, two hardware trends have emerged as major contributors-high-speed networking technologies and multi-core architectures. Communication middleware such as the Message Passing Interface (MPI) uses the network technology for communicating between processes that reside on different physical nodes, while using shared memory for communicating between processes on different cores within the same node. Thus, two conflicting possibilities arise: (i) with the advent of multi-core architectures, the number of processes that reside on the same physical node and hence share the same physical network can potentially increase significantly, resulting in increased network usage, and (ii) given the increase in intra-node shared-memory communication for processes residing on the same node, the network usage can potentially decrease significantly. In this paper, we address these two conflicting possibilities and study the behavior of network usage in multi-core environments with sample scientific applications. Specifically, we analyze trends that result in increase or decrease of network usage, and we derive insights into application performance based on these. We also study the sharing of different resources in the system in multi-core environments and identify the contribution of the network in this mix. In addition, we study different process allocation strategies and analyze their impact on such network sharing.

  17. Sharing Information the Cheap Way: A Look at "Caveman Networking."

    ERIC Educational Resources Information Center

    Ekhaml, Leticia

    1994-01-01

    Describes four peer networking projects initiated by school library media specialists in Georgia that promoted curriculum development, collection development and library services, cooperation between school and public libraries to share online resources, and cooperation between public and school libraries to share magazine articles. (LRW)

  18. 77 FR 50712 - Information Collection: Southern Alaska Sharing Network and Subsistence Study; Proposed...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-08-22

    ... Bureau of Ocean Energy Management Information Collection: Southern Alaska Sharing Network and Subsistence... in Alaska, ``Southern Alaska Sharing Network and Subsistence Study.'' DATES: Submit written comments.... Title: Southern Alaska Sharing Network and Subsistence Study. Abstract: The Bureau of Ocean Energy...

  19. Food-Sharing Networks in Lamalera, Indonesia: Status, Sharing, and Signaling.

    PubMed

    Nolin, David A

    2012-07-01

    Costly signaling has been proposed as a possible mechanism to explain food sharing in foraging populations. This sharing-as-signaling hypothesis predicts an association between sharing and status. Using exponential random graph modeling (ERGM), this prediction is tested on a social network of between-household food-sharing relationships in the fishing and sea-hunting village of Lamalera, Indonesia. Previous analyses (Nolin 2010) have shown that most sharing in Lamalera is consistent with reciprocal altruism. The question addressed here is whether any additional variation may be explained as sharing-as-signaling by high-status households. The results show that high-status households both give and receive more than other households, a pattern more consistent with reciprocal altruism than costly signaling. However, once the propensity to reciprocate and household productivity are controlled, households of men holding leadership positions show greater odds of unreciprocated giving when compared to households of non-leaders. This pattern of excessive giving by leaders is consistent with the sharing-as-signaling hypothesis. Wealthy households show the opposite pattern, giving less and receiving more than other households. These households may reciprocate in a currency other than food or their wealth may attract favor-seeking behavior from others. Overall, status covariates explain little variation in the sharing network as a whole, and much of the sharing observed by high-status households is best explained by the same factors that explain sharing by other households. This pattern suggests that multiple mechanisms may operate simultaneously to promote sharing in Lamalera and that signaling may motivate some sharing by some individuals even within sharing regimes primarily maintained by other mechanisms.

  20. Food-Sharing Networks in Lamalera, Indonesia: Status, Sharing, and Signaling

    PubMed Central

    Nolin, David A.

    2012-01-01

    Costly signaling has been proposed as a possible mechanism to explain food sharing in foraging populations. This sharing-as-signaling hypothesis predicts an association between sharing and status. Using exponential random graph modeling (ERGM), this prediction is tested on a social network of between-household food-sharing relationships in the fishing and sea-hunting village of Lamalera, Indonesia. Previous analyses (Nolin 2010) have shown that most sharing in Lamalera is consistent with reciprocal altruism. The question addressed here is whether any additional variation may be explained as sharing-as-signaling by high-status households. The results show that high-status households both give and receive more than other households, a pattern more consistent with reciprocal altruism than costly signaling. However, once the propensity to reciprocate and household productivity are controlled, households of men holding leadership positions show greater odds of unreciprocated giving when compared to households of non-leaders. This pattern of excessive giving by leaders is consistent with the sharing-as-signaling hypothesis. Wealthy households show the opposite pattern, giving less and receiving more than other households. These households may reciprocate in a currency other than food or their wealth may attract favor-seeking behavior from others. Overall, status covariates explain little variation in the sharing network as a whole, and much of the sharing observed by high-status households is best explained by the same factors that explain sharing by other households. This pattern suggests that multiple mechanisms may operate simultaneously to promote sharing in Lamalera and that signaling may motivate some sharing by some individuals even within sharing regimes primarily maintained by other mechanisms. PMID:22822299

  1. Complex Dynamics in Information Sharing Networks

    NASA Astrophysics Data System (ADS)

    Cronin, Bruce

    This study examines the roll-out of an electronic knowledge base in a medium-sized professional services firm over a six year period. The efficiency of such implementation is a key business problem in IT systems of this type. Data from usage logs provides the basis for analysis of the dynamic evolution of social networks around the depository during this time. The adoption pattern follows an "s-curve" and usage exhibits something of a power law distribution, both attributable to network effects, and network position is associated with organisational performance on a number of indicators. But periodicity in usage is evident and the usage distribution displays an exponential cut-off. Further analysis provides some evidence of mathematical complexity in the periodicity. Some implications of complex patterns in social network data for research and management are discussed. The study provides a case study demonstrating the utility of the broad methodological approach.

  2. Sharing the Wealth: Towards Ocean Sensing Networks

    DTIC Science & Technology

    2012-08-01

    an overarching data network can provide persistent presence and access to information for a wide audi - ence of users. There is a possible prac...Obviously, there are significant man- power and resource savings to be Figure 1 • The UNDER NET is a Multi-Environmental, End·to·End Communications Network...information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and

  3. Enhanced pool sharing: a constraint-based routing algorithm for shared mesh restoration networks [Invited

    NASA Astrophysics Data System (ADS)

    Naser, Hassan; Mouftah, Hussein

    2004-05-01

    We investigate the availability performance of networks with shared mesh restoration and demonstrate that these networks cannot provide highly available protection services. A major factor in the poor performance of shared mesh restoration is that the resources at backup links are shared among demands. If multiple service-affecting failures occur in the network a multitude of these demands will rush to utilize the spare resources on backup links. These resources are not adequate to serve all of these demands simultaneously. We propose a heuristic routing algorithm that attempts to improve the availability performance of shared mesh restoration. We measure the likelihood that a backup link will not be available to restore a newly arrived demand if or when more than one failure occurs in the network. We adjust the backup bandwidth on that link if the measured likelihood exceeds a preset threshold. As a typical representative, we show that the downtime improves by 7%, 11%, and 18% when the total backup bandwidth in the network is increased by 5%, 10%, and 20%, respectively. These values are obtained through a series of fitting experiments.

  4. Information Sharing in a Nonprofit Network

    ERIC Educational Resources Information Center

    Stoll, Jennifer

    2012-01-01

    The civil rights and other social justice movements, neighborhood watches, local garden cooperatives, and so forth are examples of a grassroots context that is largely understudied in CSCW. In recent history, movements to fight child sex trafficking, end hunger in New York City, advocate for financial reform, or even overthrow governments have…

  5. Information Sharing in a Nonprofit Network

    ERIC Educational Resources Information Center

    Stoll, Jennifer

    2012-01-01

    The civil rights and other social justice movements, neighborhood watches, local garden cooperatives, and so forth are examples of a grassroots context that is largely understudied in CSCW. In recent history, movements to fight child sex trafficking, end hunger in New York City, advocate for financial reform, or even overthrow governments have…

  6. Networked Resource Sharing of CD-ROM Information Banks.

    ERIC Educational Resources Information Center

    Gey, Fredric C.

    1992-01-01

    Proposes an infrastructure to provide organizationwide access in a large university to government statistical databases issued on CD-ROM. Topics addressed include characteristics of government numeric data on CD-ROM, networked options, desired characteristics of networked CD-ROM access, hardware and network configurations, a prototype system, and…

  7. User Expectations for Media Sharing Practices in Open Display Networks

    PubMed Central

    Jose, Rui; Cardoso, Jorge C. S.; Hong, Jason

    2015-01-01

    Open Display Networks have the potential to allow many content creators to publish their media to an open-ended set of screen displays. However, this raises the issue of how to match that content to the right displays. In this study, we aim to understand how the perceived utility of particular media sharing scenarios is affected by three independent variables, more specifically: (a) the locativeness of the content being shared; (b) how personal that content is and (c) the scope in which it is being shared. To assess these effects, we composed a set of 24 media sharing scenarios embedded with different treatments of our three independent variables. We then asked 100 participants to express their perception of the relevance of those scenarios. The results suggest a clear preference for scenarios where content is both local and directly related to the person that is publishing it. This is in stark contrast to the types of content that are commonly found in public displays, and confirms the opportunity that open displays networks may represent a new media for self-expression. This novel understanding may inform the design of new publication paradigms that will enable people to share media across the display networks. PMID:26153770

  8. A physical layer perspective on access network sharing

    NASA Astrophysics Data System (ADS)

    Pfeiffer, Thomas

    2015-12-01

    Unlike in copper or wireless networks, there is no sharing of resources in fiber access networks yet, other than bit stream access or cable sharing, in which the fibers of a cable are let to one or multiple operators. Sharing optical resources on a single fiber among multiple operators or different services has not yet been applied. While this would allow for a better exploitation of installed infrastructures, there are operational issues which still need to be resolved, before this sharing model can be implemented in networks. Operating multiple optical systems and services over a common fiber plant, autonomously and independently from each other, can result in mutual distortions on the physical layer. These distortions will degrade the performance of the involved systems, unless precautions are taken in the infrastructure hardware to eliminate or to reduce them to an acceptable level. Moreover, the infrastructure needs to be designed such as to support different system technologies and to ensure a guaranteed quality of the end-to-end connections. In this paper, suitable means are proposed to be introduced in fiber access infrastructures that will allow for shared utilization of the fibers while safeguarding the operational needs and business interests of the involved parties.

  9. User Expectations for Media Sharing Practices in Open Display Networks.

    PubMed

    Jose, Rui; Cardoso, Jorge C S; Hong, Jason

    2015-07-06

    Open Display Networks have the potential to allow many content creators to publish their media to an open-ended set of screen displays. However, this raises the issue of how to match that content to the right displays. In this study, we aim to understand how the perceived utility of particular media sharing scenarios is affected by three independent variables, more specifically: (a) the locativeness of the content being shared; (b) how personal that content is and (c) the scope in which it is being shared. To assess these effects, we composed a set of 24 media sharing scenarios embedded with different treatments of our three independent variables. We then asked 100 participants to express their perception of the relevance of those scenarios. The results suggest a clear preference for scenarios where content is both local and directly related to the person that is publishing it. This is in stark contrast to the types of content that are commonly found in public displays, and confirms the opportunity that open displays networks may represent a new media for self-expression. This novel understanding may inform the design of new publication paradigms that will enable people to share media across the display networks.

  10. Distributed simulation using a real-time shared memory network

    NASA Technical Reports Server (NTRS)

    Simon, Donald L.; Mattern, Duane L.; Wong, Edmond; Musgrave, Jeffrey L.

    1993-01-01

    The Advanced Control Technology Branch of the NASA Lewis Research Center performs research in the area of advanced digital controls for aeronautic and space propulsion systems. This work requires the real-time implementation of both control software and complex dynamical models of the propulsion system. We are implementing these systems in a distributed, multi-vendor computer environment. Therefore, a need exists for real-time communication and synchronization between the distributed multi-vendor computers. A shared memory network is a potential solution which offers several advantages over other real-time communication approaches. A candidate shared memory network was tested for basic performance. The shared memory network was then used to implement a distributed simulation of a ramjet engine. The accuracy and execution time of the distributed simulation was measured and compared to the performance of the non-partitioned simulation. The ease of partitioning the simulation, the minimal time required to develop for communication between the processors and the resulting execution time all indicate that the shared memory network is a real-time communication technique worthy of serious consideration.

  11. The challenges of shared decision making in dementia care networks.

    PubMed

    Groen-van de Ven, Leontine; Smits, Carolien; Span, Marijke; Jukema, Jan; Coppoolse, Krista; de Lange, Jacomine; Eefsting, Jan; Vernooij-Dassen, Myrra

    2016-09-09

    Decision making is an important part of managing one's life with dementia. Shared decision making is the preferred way of involving people in decisions. Our study aimed to describe the challenges of shared decision making in dementia care networks. A multi-perspective qualitative study using face-to-face interviews with 113 respondents in 23 care networks in the Netherlands consisting of 23 people with dementia, 44 of their informal caregivers, and 46 of their professional caregivers. The interview guide addressed the decision topics, who were involved in the decision making and their contributions to the decision making. We used content analysis to delineate categories and themes. The themes and categories that emerged are: (1) adapting to a situation of diminishing independence, which includes the continuous changes in the care network, resulting in shifting decision-making roles and the need for anticipating future decisions; and (2) tensions in network interactions which result from different perspectives and interests and which require reaching agreement about what constitutes a problem by exchanging information in the care network. The challenges in dementia care networks relate to all dimensions of social health. They have implications for a model of shared decision making in dementia care networks. Such a model requires flexibility regarding changing capabilities to preserve the autonomy of the person with dementia. It needs working towards a shared view about what constitutes a problem in the situation. It asks for professionals to advocate for the involvement of people with dementia by helping them participate in ways that strengthen their remaining capacities.

  12. Reservation information sharing enhancement for deflection routing in OBS network.

    PubMed

    Gao, Donghui; Zhang, Hanyi; Zhou, Zhiyu

    2005-03-07

    The resource contention problem is critical in Just-Enough-Time (JET) based optical burst switching (OBS) networks. Although deflection routing (DR) reduces the contention probability in some degree, it does not give much improvement under heavy traffic load. This paper analyzed the inducement causing contention in OBS networks, and proposed Resource Information Sharing Enhancement (RISE) scheme. Theoretical analysis shows that this scheme achieves shorter length of the detour path than normal DR. We simulated this scheme on both full mesh network and practical 14-node NSFNET. The simulation results show that it gives at best 2 orders magnitude improvement in reducing the burst contention probability over its previous routing approaches.

  13. esyN: Network Building, Sharing and Publishing

    PubMed Central

    Bean, Daniel M.; Heimbach, Joshua; Ficorella, Lorenzo; Micklem, Gos; Oliver, Stephen G.; Favrin, Giorgio

    2014-01-01

    The construction and analysis of networks is increasingly widespread in biological research. We have developed esyN (“easy networks”) as a free and open source tool to facilitate the exchange of biological network models between researchers. esyN acts as a searchable database of user-created networks from any field. We have developed a simple companion web tool that enables users to view and edit networks using data from publicly available databases. Both normal interaction networks (graphs) and Petri nets can be created. In addition to its basic tools, esyN contains a number of logical templates that can be used to create models more easily. The ability to use previously published models as building blocks makes esyN a powerful tool for the construction of models and network graphs. Users are able to save their own projects online and share them either publicly or with a list of collaborators. The latter can be given the ability to edit the network themselves, allowing online collaboration on network construction. esyN is designed to facilitate unrestricted exchange of this increasingly important type of biological information. Ultimately, the aim of esyN is to bring the advantages of Open Source software development to the construction of biological networks. PMID:25181461

  14. Colorado Library Network Plan. A Network for Sharing.

    ERIC Educational Resources Information Center

    Boucher, Virginia

    A brief history of library development in Colorado is followed by the outline of a plan which delineates four network programs: materials selection, interlibrary loan, reference/information, and communications. Though these programs are interrelated in numerous ways, they are considered here one by one. For each program, the purpose and need, the…

  15. Survivable Lightpath Provisioning in WDM Mesh Networks Under Shared Path Protection and Signal Quality Constraints

    NASA Astrophysics Data System (ADS)

    Yang, Xi; Shen, Lu; Ramamurthy, Byrav

    2005-04-01

    This paper addresses the problem of survivable lightpath provisioning in wavelength-division-multiplexing (WDM) mesh networks, taking into consideration optical-layer protection and some realistic optical signal quality constraints. The investigated networks use sparsely placed optical-electrical-optical (O/E/O) modules for regeneration and wavelength conversion. Given a fixed network topology with a number of sparsely placed O/E/O modules and a set of connection requests, a pair of link-disjoint lightpaths is established for each connection. Due to physical impairments and wavelength continuity,both the working and protection lightpaths need to be regenerated at some intermediate nodes to overcome signal quality degradation and wavelength contention. In the present paper, resource-efficient provisioning solutions are achieved with the objective of maximizing resource sharing. The authors propose a resource-sharing scheme that supports three kinds of resource-sharing scenarios, including a conventional wavelength-link sharing scenario, which shares wavelength links between protection lightpaths, and two new scenarios, which share O/E/O modules between protection lightpaths and between working and protection lightpaths. An integer linear programming (ILP)-based solution approach is used to find optimal solutions. The authors also propose a local optimization heuristic approach and a tabu search heuristic approach to solve this problem for real-world,large mesh networks. Numerical results show that our solution approaches work well under a variety of network settings and achieves a high level of resource-sharing rates (over 60% for O/E/O modules and over 30% for wavelength links), which translate into great savings in network costs.

  16. Four health data networks illustrate the potential for a shared national multipurpose big-data network.

    PubMed

    Curtis, Lesley H; Brown, Jeffrey; Platt, Richard

    2014-07-01

    Information in electronic health data that are drawn from large populations of patients is transforming health care, public health practice, and clinical research. This article describes our experience in developing data networks that repurpose electronic health records and administrative data. The four programs we feature are the Food and Drug Administration's Mini-Sentinel program (which focuses on medical product safety), the National Patient-Centered Clinical Research Network (PCORnet, comparative effectiveness research), the National Institutes of Health's Health Care Systems Research Collaboratory Distributed Research Network (biomedical research), and ESPnet (public health surveillance). Challenges to these uses of electronic health data include understanding the factors driving the collection, coding, and preservation of the data; the extensive customization of different systems that collect similar data; the fragmentation of the US health care delivery system and its records; and privacy and proprietary considerations. We view these four programs as examples of the first stage in the development of a shared national big-data resource that leverages the investments of many agencies and organizations for the benefit of multiple networks and users. Project HOPE—The People-to-People Health Foundation, Inc.

  17. Shared molecular networks in orofacial and neural tube development.

    PubMed

    Kousa, Youssef A; Mansour, Tamer A; Seada, Haitham; Matoo, Samaneh; Schutte, Brian C

    2017-01-30

    Single genetic variants can affect multiple tissues during development. Thus it is possible that disruption of shared gene regulatory networks might underlie syndromic presentations. In this study, we explore this idea through examination of two critical developmental programs that control orofacial and neural tube development and identify shared regulatory factors and networks. Identification of these networks has the potential to yield additional candidate genes for poorly understood developmental disorders and assist in modeling and perhaps managing risk factors to prevent morbidly and mortality. We reviewed the literature to identify genes common between orofacial and neural tube defects and development. We then conducted a bioinformatic analysis to identify shared molecular targets and pathways in the development of these tissues. Finally, we examine publicly available RNA-Seq data to identify which of these genes are expressed in both tissues during development. We identify common regulatory factors in orofacial and neural tube development. Pathway enrichment analysis shows that folate, cancer and hedgehog signaling pathways are shared in neural tube and orofacial development. Developing neural tissues differentially express mouse exencephaly and cleft palate genes, whereas developing orofacial tissues were enriched for both clefting and neural tube defect genes. These data suggest that key developmental factors and pathways are shared between orofacial and neural tube defects. We conclude that it might be most beneficial to focus on common regulatory factors and pathways to better understand pathology and develop preventative measures for these birth defects. Birth Defects Research 109:169-179, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  18. Experimental circular quantum secret sharing over telecom fiber network.

    PubMed

    Wei, Ke-Jin; Ma, Hai-Qiang; Yang, Jian-Hui

    2013-07-15

    We present a robust single photon circular quantum secret sharing (QSS) scheme with phase encoding over 50 km single mode fiber network using a circular QSS protocol. Our scheme can automatically provide a perfect compensation of birefringence and remain stable for a long time. A high visibility of 99.3% is obtained. Furthermore, our scheme realizes a polarization insensitive phase modulators. The visibility of this system can be maintained perpetually without any adjustment to the system every time we test the system.

  19. Graph theoretic modeling of large-scale semantic networks.

    PubMed

    Bales, Michael E; Johnson, Stephen B

    2006-08-01

    During the past several years, social network analysis methods have been used to model many complex real-world phenomena, including social networks, transportation networks, and the Internet. Graph theoretic methods, based on an elegant representation of entities and relationships, have been used in computational biology to study biological networks; however they have not yet been adopted widely by the greater informatics community. The graphs produced are generally large, sparse, and complex, and share common global topological properties. In this review of research (1998-2005) on large-scale semantic networks, we used a tailored search strategy to identify articles involving both a graph theoretic perspective and semantic information. Thirty-one relevant articles were retrieved. The majority (28, 90.3%) involved an investigation of a real-world network. These included corpora, thesauri, dictionaries, large computer programs, biological neuronal networks, word association networks, and files on the Internet. Twenty-two of the 28 (78.6%) involved a graph comprised of words or phrases. Fifteen of the 28 (53.6%) mentioned evidence of small-world characteristics in the network investigated. Eleven (39.3%) reported a scale-free topology, which tends to have a similar appearance when examined at varying scales. The results of this review indicate that networks generated from natural language have topological properties common to other natural phenomena. It has not yet been determined whether artificial human-curated terminology systems in biomedicine share these properties. Large network analysis methods have potential application in a variety of areas of informatics, such as in development of controlled vocabularies and for characterizing a given domain.

  20. Enabling Interoperable and Selective Data Sharing among Social Networking Sites

    NASA Astrophysics Data System (ADS)

    Shin, Dongwan; Lopes, Rodrigo

    With the widespread use of social networking (SN) sites and even introduction of a social component in non-social oriented services, there is a growing concern over user privacy in general, how to handle and share user profiles across SN sites in particular. Although there have been several proprietary or open source-based approaches to unifying the creation of third party applications, the availability and retrieval of user profile information are still limited to the site where the third party application is run, mostly devoid of the support for data interoperability. In this paper we propose an approach to enabling interopearable and selective data sharing among SN sites. To support selective data sharing, we discuss an authenticated dictionary (ADT)-based credential which enables a user to share only a subset of her information certified by external SN sites with applications running on an SN site. For interoperable data sharing, we propose an extension to the OpenSocial API so that it can provide an open source-based framework for allowing the ADT-based credential to be used seamlessly among different SN sites.

  1. To share or not to share: Drivers and barriers for sharing data via online amateur weather networks

    NASA Astrophysics Data System (ADS)

    Gharesifard, Mohammad; Wehn, Uta

    2016-04-01

    Increasing attention is being paid to the importance and potential of crowd-sourced data to complement current environmental data-streams (i.e. in-situ observations and RS data). In parallel, the diffusion of Information Communication Technologies (ICTs) that are interactive and easy to use have provided a way forward in facing extreme climatic events and the threatening hazards resulting from those. The combination of these two trends is referred to as ICT-enabled 'citizen observatories' of the environment. Nevertheless, the success of these citizen observatories hinges on the continued involvement of citizens as central actors of these initiatives. Developing strategies to (further) engage citizens requires in-depth understanding of the behavioral determinants that encourage or impede individuals to collect and share environment-related data. This paper takes the case of citizen-sensed weather data using Personal Weather Stations (PWSs) and looks at the drivers and barriers for sharing such data via online amateur weather networks. This is done employing a behavioral science lens that considers data sharing a decision and systematically investigates the influential factors that affect this decision. The analysis and findings are based on qualitative empirical research carried out in the Netherlands, United Kingdom and Italy. Subsequently, a model was developed that depicts the main drivers and barriers for citizen participation in weather observatories. This resulting model can be utilized as a tool to develop strategies for further enhancing ICT-enabled citizen participation in climatic observations and, consequently, in environmental management.

  2. Mission Command in the Age of Network-Enabled Operations: Social Network Analysis of Information Sharing and Situation Awareness.

    PubMed

    Buchler, Norbou; Fitzhugh, Sean M; Marusich, Laura R; Ungvarsky, Diane M; Lebiere, Christian; Gonzalez, Cleotilde

    2016-01-01

    A common assumption in organizations is that information sharing improves situation awareness and ultimately organizational effectiveness. The sheer volume and rapid pace of information and communications received and readily accessible through computer networks, however, can overwhelm individuals, resulting in data overload from a combination of diverse data sources, multiple data formats, and large data volumes. The current conceptual framework of network enabled operations (NEO) posits that robust networking and information sharing act as a positive feedback loop resulting in greater situation awareness and mission effectiveness in military operations (Alberts and Garstka, 2004). We test this assumption in a large-scale, 2-week military training exercise. We conducted a social network analysis of email communications among the multi-echelon Mission Command staff (one Division and two sub-ordinate Brigades) and assessed the situational awareness of every individual. Results from our exponential random graph models challenge the aforementioned assumption, as increased email output was associated with lower individual situation awareness. It emerged that higher situation awareness was associated with a lower probability of out-ties, so that broadly sending many messages decreased the likelihood of attaining situation awareness. This challenges the hypothesis that increased information sharing improves situation awareness, at least for those doing the bulk of the sharing. In addition, we observed two trends that reflect a compartmentalizing of networked information sharing as email links were more commonly formed among members of the command staff with both similar functions and levels of situation awareness, than between two individuals with dissimilar functions and levels of situation awareness; both those findings can be interpreted to reflect effects of homophily. Our results have major implications that challenge the current conceptual framework of NEO. In

  3. Mission Command in the Age of Network-Enabled Operations: Social Network Analysis of Information Sharing and Situation Awareness

    PubMed Central

    Buchler, Norbou; Fitzhugh, Sean M.; Marusich, Laura R.; Ungvarsky, Diane M.; Lebiere, Christian; Gonzalez, Cleotilde

    2016-01-01

    A common assumption in organizations is that information sharing improves situation awareness and ultimately organizational effectiveness. The sheer volume and rapid pace of information and communications received and readily accessible through computer networks, however, can overwhelm individuals, resulting in data overload from a combination of diverse data sources, multiple data formats, and large data volumes. The current conceptual framework of network enabled operations (NEO) posits that robust networking and information sharing act as a positive feedback loop resulting in greater situation awareness and mission effectiveness in military operations (Alberts and Garstka, 2004). We test this assumption in a large-scale, 2-week military training exercise. We conducted a social network analysis of email communications among the multi-echelon Mission Command staff (one Division and two sub-ordinate Brigades) and assessed the situational awareness of every individual. Results from our exponential random graph models challenge the aforementioned assumption, as increased email output was associated with lower individual situation awareness. It emerged that higher situation awareness was associated with a lower probability of out-ties, so that broadly sending many messages decreased the likelihood of attaining situation awareness. This challenges the hypothesis that increased information sharing improves situation awareness, at least for those doing the bulk of the sharing. In addition, we observed two trends that reflect a compartmentalizing of networked information sharing as email links were more commonly formed among members of the command staff with both similar functions and levels of situation awareness, than between two individuals with dissimilar functions and levels of situation awareness; both those findings can be interpreted to reflect effects of homophily. Our results have major implications that challenge the current conceptual framework of NEO. In

  4. Power-aware provisioning strategy with shared path protection in optical WDM networks

    NASA Astrophysics Data System (ADS)

    Bao, Ning-Hai; Li, Le-Min; Yu, Hong-Fang; Zhang, Zhi-Zhong; Luo, Hong-Bin

    2012-03-01

    As the Internet continues to grow, the power consumption of telecommunication networks is rising at a considerable speed, which seriously increases the operational expenditure and greenhouse gas emission. Since optical Wavelength Division Multiplexing (WDM) networks are currently the most promising network infrastructures, power saving issue on these networks has received more attention in recent years. In traditional optical WDM networks, a large amount of power is drained by the redundant idle resources and reserved backup resources although these powered on resources do not carry traffic in most of the time. In order to reduce the network power consumption, turning off the corresponding network components or switching them to a low-power, standby state (or called sleep mode) is a promising greening approach. In this paper, we study the power-aware provisioning strategies and propose a sleep mode based Power-Aware Shared Path Protection (PASPP) heuristic algorithm to achieve the power efficiency of optical WDM networks. By jointly utilizing link-cost and fiber-cost in path routing, resource assignment, and resource release, PASPP makes working paths and backup paths converge on different fibers as much as possible, and switch idle and backup components to sleep mode to realize power saving. Simulation results show that our PASPP can obtain notable power saving and achieve satisfactory tradeoff between power efficiency and blocking probability with respect to Power-Unaware Shared Path Protection (PUSPP).

  5. Online Community Detection for Large Complex Networks

    PubMed Central

    Pan, Gang; Zhang, Wangsheng; Wu, Zhaohui; Li, Shijian

    2014-01-01

    Complex networks describe a wide range of systems in nature and society. To understand complex networks, it is crucial to investigate their community structure. In this paper, we develop an online community detection algorithm with linear time complexity for large complex networks. Our algorithm processes a network edge by edge in the order that the network is fed to the algorithm. If a new edge is added, it just updates the existing community structure in constant time, and does not need to re-compute the whole network. Therefore, it can efficiently process large networks in real time. Our algorithm optimizes expected modularity instead of modularity at each step to avoid poor performance. The experiments are carried out using 11 public data sets, and are measured by two criteria, modularity and NMI (Normalized Mutual Information). The results show that our algorithm's running time is less than the commonly used Louvain algorithm while it gives competitive performance. PMID:25061683

  6. Large-scale quantum networks based on graphs

    NASA Astrophysics Data System (ADS)

    Epping, Michael; Kampermann, Hermann; Bruß, Dagmar

    2016-05-01

    Society relies and depends increasingly on information exchange and communication. In the quantum world, security and privacy is a built-in feature for information processing. The essential ingredient for exploiting these quantum advantages is the resource of entanglement, which can be shared between two or more parties. The distribution of entanglement over large distances constitutes a key challenge for current research and development. Due to losses of the transmitted quantum particles, which typically scale exponentially with the distance, intermediate quantum repeater stations are needed. Here we show how to generalise the quantum repeater concept to the multipartite case, by describing large-scale quantum networks, i.e. network nodes and their long-distance links, consistently in the language of graphs and graph states. This unifying approach comprises both the distribution of multipartite entanglement across the network, and the protection against errors via encoding. The correspondence to graph states also provides a tool for optimising the architecture of quantum networks.

  7. Network Analysis of an Emergent Massively Collaborative Creation on Video Sharing Website

    NASA Astrophysics Data System (ADS)

    Hamasaki, Masahiro; Takeda, Hideaki; Nishimura, Takuichi

    The Web technology enables numerous people to collaborate in creation. We designate it as massively collaborative creation via the Web. As an example of massively collaborative creation, we particularly examine video development on Nico Nico Douga, which is a video sharing website that is popular in Japan. We specifically examine videos on Hatsune Miku, a version of a singing synthesizer application software that has inspired not only song creation but also songwriting, illustration, and video editing. As described herein, creators of interact to create new contents through their social network. In this paper, we analyzed the process of developing thousands of videos based on creators' social networks and investigate relationships among creation activity and social networks. The social network reveals interesting features. Creators generate large and sparse social networks including some centralized communities, and such centralized community's members shared special tags. Different categories of creators have different roles in evolving the network, e.g., songwriters gather more links than other categories, implying that they are triggers to network evolution.

  8. Refuge sharing network predicts ectoparasite load in a lizard

    PubMed Central

    Kappeler, Peter M.; Bull, C. Michael

    2010-01-01

    Living in social groups facilitates cross-infection by parasites. However, empirical studies on indirect transmission within wildlife populations are scarce. We investigated whether asynchronous overnight refuge sharing among neighboring sleepy lizards, Tiliqua rugosa, facilitates indirect transmission of its ectoparasitic tick, Amblyomma limbatum. We fitted 18 neighboring lizards with GPS recorders, observed their overnight refuge use each night over 3 months, and counted their ticks every fortnight. We constructed a transmission network to estimate the cross-infection risk based on asynchronous refuge sharing frequencies among all lizards and the life history traits of the tick. Although self-infection was possible, the network provided a powerful predictor of measured tick loads. Highly connected lizards that frequently used their neighbors’ refuges were characterized by higher tick loads. Thus, indirect contact had a major influence on transmission pathways and parasite loads. Furthermore, lizards that used many different refuges had lower cross- and self-infection risks and lower tick loads than individuals that used relatively fewer refuges. Increasing the number of refuges used by a lizard may be an important defense mechanism against ectoparasite transmission in this species. Our study provides important empirical data to further understand how indirectly transmitted parasites move through host populations and influence individual parasite loads. PMID:20802788

  9. Refuge sharing network predicts ectoparasite load in a lizard.

    PubMed

    Leu, Stephan T; Kappeler, Peter M; Bull, C Michael

    2010-09-01

    Living in social groups facilitates cross-infection by parasites. However, empirical studies on indirect transmission within wildlife populations are scarce. We investigated whether asynchronous overnight refuge sharing among neighboring sleepy lizards, Tiliqua rugosa, facilitates indirect transmission of its ectoparasitic tick, Amblyomma limbatum. We fitted 18 neighboring lizards with GPS recorders, observed their overnight refuge use each night over 3 months, and counted their ticks every fortnight. We constructed a transmission network to estimate the cross-infection risk based on asynchronous refuge sharing frequencies among all lizards and the life history traits of the tick. Although self-infection was possible, the network provided a powerful predictor of measured tick loads. Highly connected lizards that frequently used their neighbors' refuges were characterized by higher tick loads. Thus, indirect contact had a major influence on transmission pathways and parasite loads. Furthermore, lizards that used many different refuges had lower cross- and self-infection risks and lower tick loads than individuals that used relatively fewer refuges. Increasing the number of refuges used by a lizard may be an important defense mechanism against ectoparasite transmission in this species. Our study provides important empirical data to further understand how indirectly transmitted parasites move through host populations and influence individual parasite loads.

  10. Integrative Biology Identifies Shared Transcriptional Networks in CKD

    PubMed Central

    Martini, Sebastian; Nair, Viji; Keller, Benjamin J.; Eichinger, Felix; Hawkins, Jennifer J.; Randolph, Ann; Böger, Carsten A.; Gadegbeku, Crystal A.; Fox, Caroline S.; Cohen, Clemens D.

    2014-01-01

    A previous meta-analysis of genome-wide association data by the Cohorts for Heart and Aging Research in Genomic Epidemiology and CKDGen consortia identified 16 loci associated with eGFR. To define how each of these single-nucleotide polymorphisms (SNPs) could affect renal function, we integrated GFR-associated loci with regulatory pathways, producing a molecular map of CKD. In kidney biopsy specimens from 157 European subjects representing nine different CKDs, renal transcript levels for 18 genes in proximity to the SNPs significantly correlated with GFR. These 18 genes were mapped into their biologic context by testing coregulated transcripts for enriched pathways. A network of 97 pathways linked by shared genes was constructed and characterized. Of these pathways, 56 pathways were reported previously to be associated with CKD; 41 pathways without prior association with CKD were ranked on the basis of the number of candidate genes connected to the respective pathways. All pathways aggregated into a network of two main clusters comprising inflammation- and metabolism-related pathways, with the NRF2-mediated oxidative stress response pathway serving as the hub between the two clusters. In all, 78 pathways and 95% of the connections among those pathways were verified in an independent North American biopsy cohort. Disease-specific analyses showed that most pathways are shared between sets of three diseases, with closest interconnection between lupus nephritis, IgA nephritis, and diabetic nephropathy. Taken together, the network integrates candidate genes from genome-wide association studies into their functional context, revealing interactions and defining established and novel biologic mechanisms of renal impairment in renal diseases. PMID:24925724

  11. Integrative biology identifies shared transcriptional networks in CKD.

    PubMed

    Martini, Sebastian; Nair, Viji; Keller, Benjamin J; Eichinger, Felix; Hawkins, Jennifer J; Randolph, Ann; Böger, Carsten A; Gadegbeku, Crystal A; Fox, Caroline S; Cohen, Clemens D; Kretzler, Matthias

    2014-11-01

    A previous meta-analysis of genome-wide association data by the Cohorts for Heart and Aging Research in Genomic Epidemiology and CKDGen consortia identified 16 loci associated with eGFR. To define how each of these single-nucleotide polymorphisms (SNPs) could affect renal function, we integrated GFR-associated loci with regulatory pathways, producing a molecular map of CKD. In kidney biopsy specimens from 157 European subjects representing nine different CKDs, renal transcript levels for 18 genes in proximity to the SNPs significantly correlated with GFR. These 18 genes were mapped into their biologic context by testing coregulated transcripts for enriched pathways. A network of 97 pathways linked by shared genes was constructed and characterized. Of these pathways, 56 pathways were reported previously to be associated with CKD; 41 pathways without prior association with CKD were ranked on the basis of the number of candidate genes connected to the respective pathways. All pathways aggregated into a network of two main clusters comprising inflammation- and metabolism-related pathways, with the NRF2-mediated oxidative stress response pathway serving as the hub between the two clusters. In all, 78 pathways and 95% of the connections among those pathways were verified in an independent North American biopsy cohort. Disease-specific analyses showed that most pathways are shared between sets of three diseases, with closest interconnection between lupus nephritis, IgA nephritis, and diabetic nephropathy. Taken together, the network integrates candidate genes from genome-wide association studies into their functional context, revealing interactions and defining established and novel biologic mechanisms of renal impairment in renal diseases.

  12. Fair sharing of resources in a supply network with constraints.

    PubMed

    Carvalho, Rui; Buzna, Lubos; Just, Wolfram; Helbing, Dirk; Arrowsmith, David K

    2012-04-01

    This paper investigates the effect of network topology on the fair allocation of network resources among a set of agents, an all-important issue for the efficiency of transportation networks all around us. We analyze a generic mechanism that distributes network capacity fairly among existing flow demands. The problem can be solved by semianalytical methods on a nearest-neighbor graph with one source and sink pair, when transport occurs over shortest paths. For this setup, we uncover a broad range of patterns of intersecting shortest paths as a function of the distance between the source and the sink. When the number of intersections is the maximum and the distance between the source and the sink is large, we find that a fair allocation implies a decrease of at least 50% from the maximum throughput. We also find that the histogram of the flow allocations assigned to the agents decays as a power law with exponent -1. Our semianalytical framework suggests possible explanations for the well-known reduction of the throughput in fair allocations. It also suggests that the combination of network topology and routing rules can lead to highly uneven (but fair) distributions of resources, a remark of caution to network designers.

  13. Data sharing in large research consortia: experiences and recommendations from ENGAGE.

    PubMed

    Budin-Ljøsne, Isabelle; Isaeva, Julia; Knoppers, Bartha Maria; Tassé, Anne Marie; Shen, Huei-yi; McCarthy, Mark I; Harris, Jennifer R

    2014-03-01

    Data sharing is essential for the conduct of cutting-edge research and is increasingly required by funders concerned with maximising the scientific yield from research data collections. International research consortia are encouraged to share data intra-consortia, inter-consortia and with the wider scientific community. Little is reported regarding the factors that hinder or facilitate data sharing in these different situations. This paper provides results from a survey conducted in the European Network for Genetic and Genomic Epidemiology (ENGAGE) that collected information from its participating institutions about their data-sharing experiences. The questionnaire queried about potential hurdles to data sharing, concerns about data sharing, lessons learned and recommendations for future collaborations. Overall, the survey results reveal that data sharing functioned well in ENGAGE and highlight areas that posed the most frequent hurdles for data sharing. Further challenges arise for international data sharing beyond the consortium. These challenges are described and steps to help address these are outlined.

  14. Perceived serosorting of injection paraphernalia sharing networks among injection drug users in Baltimore, MD.

    PubMed

    Yang, C; Tobin, K; Latkin, C

    2011-01-01

    We examined perceived serosorting of injection paraphernalia sharing networks among a sample of 572 injection drug users (IDUs). There was evidence for serosorting of high-risk injection behaviors among HIV-negative IDUs, as 94% of HIV-negative IDUs shared injection paraphernalia exclusively with perceived HIV-negative networks. However, 82% of HIV-positive IDUs shared injection paraphernalia with perceived HIV-negative networks. The findings indicate a potential risk of rapid HIV transmission. Future prevention efforts targeting IDUs should address the limitation of serosorting, and focus on preventing injection paraphernalia sharing regardless of potential sharing networks' perceived HIV status.

  15. Image transmission in tactical radio frequency shared network propagation environments

    NASA Astrophysics Data System (ADS)

    White, Kent H.; Wagner, Kerry A.; O'Hanian, Scott

    1997-06-01

    The need to transmit images across tactical radio frequency (rf) links has been identified in army digitization applications. For example, military doctrine requires that tactical functions like identification of battlefield entities as potential targets and battle damage assessment be performed by the soldier. Currently, a key input to these processes is imagery. Therefore, the quality and timeliness of the image directly impact tactical performance. The military is investigating the employment of remote sensors and advanced communications systems to meet this requirement as part of its digitization effort. Army communications systems exist that partially meet this requirement. However, many existing solutions employ these legacy systems in the context of a point-to-point communications architecture. Solutions to the problem of transmitting images across a rf network have not been fully explored. The term network implies that the rf transmission media is common to and shared by multiple subscribers. It is a suite of capabilities that collectively manage media access and information transfer for its subscribers thus providing substantial improvements in effectiveness, efficiency, and robustness. This paper discusses the challenges of transmitting images using one army legacy communications system in a tactical rf network, presents a conceptual framework for attacking the problem, and discusses one solution.

  16. Information sharing and relationships on social networking sites.

    PubMed

    Steijn, Wouter M P; Schouten, Alexander P

    2013-08-01

    This article investigates the relationship between sharing personal information and relationship development in the context of social networking sites (SNSs). Information disclosed on these sites could affect relationships in a different manner compared to more traditional interactions, such as instant messaging or face-to-face interaction. Respondents in the age range of 12 to 83 were surveyed about experiences of relationship development as a consequence of contact through Facebook or Hyves-the most popular Dutch SNSs. Results showed a primarily positive effect of information sharing on SNSs on our relationships. Furthermore, relationship development mainly occurs among acquaintances and friends, and public posts are most strongly related to relationship development. These findings suggest that SNSs might affect relationships in a distinct fashion as acquaintances and friends gain access to public self-disclosures that might normally only be reserved for close friends and family. Overall, this study provides an insight into some of the positive aspects of the public nature of SNSs in contrast with the general negative associations.

  17. Large-scale cortical networks and cognition.

    PubMed

    Bressler, S L

    1995-03-01

    The well-known parcellation of the mammalian cerebral cortex into a large number of functionally distinct cytoarchitectonic areas presents a problem for understanding the complex cortical integrative functions that underlie cognition. How do cortical areas having unique individual functional properties cooperate to accomplish these complex operations? Do neurons distributed throughout the cerebral cortex act together in large-scale functional assemblages? This review examines the substantial body of evidence supporting the view that complex integrative functions are carried out by large-scale networks of cortical areas. Pathway tracing studies in non-human primates have revealed widely distributed networks of interconnected cortical areas, providing an anatomical substrate for large-scale parallel processing of information in the cerebral cortex. Functional coactivation of multiple cortical areas has been demonstrated by neurophysiological studies in non-human primates and several different cognitive functions have been shown to depend on multiple distributed areas by human neuropsychological studies. Electrophysiological studies on interareal synchronization have provided evidence that active neurons in different cortical areas may become not only coactive, but also functionally interdependent. The computational advantages of synchronization between cortical areas in large-scale networks have been elucidated by studies using artificial neural network models. Recent observations of time-varying multi-areal cortical synchronization suggest that the functional topology of a large-scale cortical network is dynamically reorganized during visuomotor behavior.

  18. 47 CFR 27.1315 - Establishment, execution, and application of the network sharing agreement.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... the network sharing agreement. 27.1315 Section 27.1315 Telecommunication FEDERAL COMMUNICATIONS.../Private Partnership § 27.1315 Establishment, execution, and application of the network sharing agreement... Upper 700 MHz D Block licensee, the Network Assets Holder, and the Operating Company, as these entities...

  19. 47 CFR 90.1415 - Establishment, execution, and application of the network sharing agreement.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... the network sharing agreement. 90.1415 Section 90.1415 Telecommunication FEDERAL COMMUNICATIONS.../Private Partnership § 90.1415 Establishment, execution, and application of the network sharing agreement... to the NSA must also include the Upper 700 MHz D Block licensee, the Network Assets Holder, and the...

  20. 47 CFR 27.1315 - Establishment, execution, and application of the network sharing agreement.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... the network sharing agreement. 27.1315 Section 27.1315 Telecommunication FEDERAL COMMUNICATIONS.../Private Partnership § 27.1315 Establishment, execution, and application of the network sharing agreement... Upper 700 MHz D Block licensee, the Network Assets Holder, and the Operating Company, as these entities...

  1. 47 CFR 27.1315 - Establishment, execution, and application of the network sharing agreement.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... the network sharing agreement. 27.1315 Section 27.1315 Telecommunication FEDERAL COMMUNICATIONS.../Private Partnership § 27.1315 Establishment, execution, and application of the network sharing agreement... Upper 700 MHz D Block licensee, the Network Assets Holder, and the Operating Company, as these entities...

  2. 78 FR 3447 - Information Collection: Southern Alaska Sharing Network and Subsistence Study; Submitted for OMB...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-01-16

    ... Bureau of Ocean Energy Management Information Collection: Southern Alaska Sharing Network and Subsistence... networks in coastal Alaska. This notice provides the public a second opportunity to comment on the...: 1010-0181. Title: Southern Alaska Sharing Network and Subsistence Study. Abstract: The Bureau of Ocean...

  3. 47 CFR 90.1415 - Establishment, execution, and application of the network sharing agreement.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... the network sharing agreement. 90.1415 Section 90.1415 Telecommunication FEDERAL COMMUNICATIONS.../Private Partnership § 90.1415 Establishment, execution, and application of the network sharing agreement... to the NSA must also include the Upper 700 MHz D Block licensee, the Network Assets Holder, and the...

  4. 47 CFR 90.1415 - Establishment, execution, and application of the network sharing agreement.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... the network sharing agreement. 90.1415 Section 90.1415 Telecommunication FEDERAL COMMUNICATIONS.../Private Partnership § 90.1415 Establishment, execution, and application of the network sharing agreement... to the NSA must also include the Upper 700 MHz D Block licensee, the Network Assets Holder, and the...

  5. [Study on network architecture of a tele-medical information sharing platform].

    PubMed

    Pan, Lin; Yu, Lun; Chen, Jin-xiong

    2006-07-01

    In the article,a plan of network construction which satisfies the demand of applications for a telemedical information sharing platform is proposed. We choice network access plans in view of user actual situation, through the analysis of the service demand and many kinds of network access technologies. Hospital servers that locate in LAN link sharing platform with node servers, should separate from the broadband network of sharing platform in order to ensure the security of the internal hospital network and the administration management. We use the VPN technology to realize the safe transmission of information in the platform network. Preliminary experiments have proved the plan is practicable.

  6. Cellular neuron and large wireless neural network

    NASA Astrophysics Data System (ADS)

    Jannson, Tomasz; Forrester, Thomas; Ambrose, Barry; Kazantzidis, Matheos; Lin, Freddie

    2006-05-01

    A new approach to neural networks is proposed, based on wireless interconnects (synapses) and cellular neurons, both software and hardware; with the capacity of 10 10 neurons, almost fully connected. The core of the system is Spatio-Temporal-Variant (STV) kernel and cellular axon with synaptic plasticity variable in time and space. The novel large neural network hardware is based on two established wireless technologies: RF-cellular and IR-wireless.

  7. Social Network Analysis of Patient Sharing Among Hospitals in Orange County, California

    PubMed Central

    McGlone, Sarah M.; Song, Yeohan; Avery, Taliser R.; Eubank, Stephen; Chang, Chung-Chou; Bailey, Rachel R.; Wagener, Diane K.; Burke, Donald S.; Platt, Richard; Huang, Susan S.

    2011-01-01

    Objectives. We applied social network analyses to determine how hospitals within Orange County, California, are interconnected by patient sharing, a system which may have numerous public health implications. Methods. Our analyses considered 2 general patient-sharing networks: uninterrupted patient sharing (UPS; i.e., direct interhospital transfers) and total patient sharing (TPS; i.e., all interhospital patient sharing, including patients with intervening nonhospital stays). We considered these networks at 3 thresholds of patient sharing: at least 1, at least 10, and at least 100 patients shared. Results. Geographically proximate hospitals were somewhat more likely to share patients, but many hospitals shared patients with distant hospitals. Number of patient admissions and percentage of cancer patients were associated with greater connectivity across the system. The TPS network revealed numerous connections not seen in the UPS network, meaning that direct transfers only accounted for a fraction of total patient sharing. Conclusions. Our analysis demonstrated that Orange County's 32 hospitals were highly and heterogeneously interconnected by patient sharing. Different hospital populations had different levels of influence over the patient-sharing network. PMID:21330578

  8. Information Sharing Challenges For Large Multi-Jurisdiction Issues

    SciTech Connect

    Millard, W. David; Carter, Richard J.

    2002-07-29

    In order for decision-makers to effectively handle the complexity of the multi-jurisdiction issues, automation tools must be provided that can operate effectively in a multi-jurisdictional environment. Decision support systems that span multiple users, agencies, and jurisdictions should provide users with the information needed to make decisions and the ability to disseminate those decisions. To do so, such systems need the capability to 1) control the ownership of information, 2) control how information is shared, 3) display highly dynamic geographic information from multiple jurisdictions, 4) disseminate dynamic status information between jurisdictions, and 5) notify appropriate users across jurisdictions of changes to decisions and information

  9. Shared and Distributed Memory Parallel Security Analysis of Large-Scale Source Code and Binary Applications

    SciTech Connect

    Quinlan, D; Barany, G; Panas, T

    2007-08-30

    Many forms of security analysis on large scale applications can be substantially automated but the size and complexity can exceed the time and memory available on conventional desktop computers. Most commercial tools are understandably focused on such conventional desktop resources. This paper presents research work on the parallelization of security analysis of both source code and binaries within our Compass tool, which is implemented using the ROSE source-to-source open compiler infrastructure. We have focused on both shared and distributed memory parallelization of the evaluation of rules implemented as checkers for a wide range of secure programming rules, applicable to desktop machines, networks of workstations and dedicated clusters. While Compass as a tool focuses on source code analysis and reports violations of an extensible set of rules, the binary analysis work uses the exact same infrastructure but is less well developed into an equivalent final tool.

  10. Predictive Control of Large Complex Networks

    NASA Astrophysics Data System (ADS)

    Haber, Aleksandar; Motter, Adilson E.

    Networks of coupled dynamical subsystems are increasingly used to represent complex natural and engineered systems. While recent technological developments give us improved means to actively control the dynamics of individual subsystems in various domains, network control remains a challenging problem due to difficulties imposed by intrinsic nonlinearities, control constraints, and the large-scale nature of the systems. In this talk, we will present a model predictive control approach that is effective while accounting for these realistic properties of complex networks. Our method can systematically identify control interventions that steer the trajectory to a desired state, even in the presence of strong nonlinearities and constraints. Numerical tests show that the method is applicable to a variety of networks, ranging from power grids to chemical reaction systems.

  11. Bibliographic Automation of Large Library Operations Using a Time-Sharing System: Phase I. Final Report.

    ERIC Educational Resources Information Center

    Epstein, A. H.; And Others

    The first phase of an ongoing library automation project at Stanford University is described. Project BALLOTS (Bibliographic Automation of Large Library Operations Using a Time-Sharing System) seeks to automate the acquisition and cataloging functions of a large library using an on-line time-sharing computer. The main objectives are to control…

  12. Composition and Structure of a Large Online Social Network in the Netherlands

    PubMed Central

    Corten, Rense

    2012-01-01

    Limitations in data collection have long been an obstacle in research on friendship networks. Most earlier studies use either a sample of ego-networks, or complete network data on a relatively small group (e.g., a single organization). The rise of online social networking services such as Friendster and Facebook, however, provides researchers with opportunities to study friendship networks on a much larger scale. This study uses complete network data from Hyves, a popular online social networking service in the Netherlands, comprising over eight million members and over 400 million online friendship relations. In the first study of its kind for the Netherlands, I examine the structure of this network in terms of the degree distribution, characteristic path length, clustering, and degree assortativity. Results indicate that this network shares features of other large complex networks, but also deviates in other respects. In addition, a comparison with other online social networks shows that these networks show remarkable similarities. PMID:22523557

  13. The Development and Evaluation of a Network for Producing and Sharing Video Presentations

    ERIC Educational Resources Information Center

    Sadik, Alaa

    2014-01-01

    This paper describes the technology and methodology used in the development and evaluation of an online network to help the instructors to produce and share video presentations in a new and innovative way. The network offers an application and platform for recording and sharing video presentations. The application allows instructors to narrate and…

  14. Data Validation and Sharing in a Large Research Program

    EPA Science Inventory

    Appropriate data handling practices are important in the support of large research teams with shifting and competing priorities. Determining those best practices is an ongoing effort for the US EPA’s National Aquatic Resource Surveys. We focus on the well understood data ...

  15. Data Validation and Sharing in a Large Research Program

    EPA Science Inventory

    Appropriate data handling practices are important in the support of large research teams with shifting and competing priorities. Determining those best practices is an ongoing effort for the US EPA’s National Aquatic Resource Surveys. We focus on the well understood data ...

  16. In situ exploration of large dynamic networks.

    PubMed

    Hadlak, Steffen; Schulz, Hans-Jörg; Schumann, Heidrun

    2011-12-01

    The analysis of large dynamic networks poses a challenge in many fields, ranging from large bot-nets to social networks. As dynamic networks exhibit different characteristics, e.g., being of sparse or dense structure, or having a continuous or discrete time line, a variety of visualization techniques have been specifically designed to handle these different aspects of network structure and time. This wide range of existing techniques is well justified, as rarely a single visualization is suitable to cover the entire visual analysis. Instead, visual representations are often switched in the course of the exploration of dynamic graphs as the focus of analysis shifts between the temporal and the structural aspects of the data. To support such a switching in a seamless and intuitive manner, we introduce the concept of in situ visualization--a novel strategy that tightly integrates existing visualization techniques for dynamic networks. It does so by allowing the user to interactively select in a base visualization a region for which a different visualization technique is then applied and embedded in the selection made. This permits to change the way a locally selected group of data items, such as nodes or time points, are shown--right in the place where they are positioned, thus supporting the user's overall mental map. Using this approach, a user can switch seamlessly between different visual representations to adapt a region of a base visualization to the specifics of the data within it or to the current analysis focus. This paper presents and discusses the in situ visualization strategy and its implications for dynamic graph visualization. Furthermore, it illustrates its usefulness by employing it for the visual exploration of dynamic networks from two different fields: model versioning and wireless mesh networks.

  17. Metabolic network alignment in large scale by network compression.

    PubMed

    Ay, Ferhat; Dang, Michael; Kahveci, Tamer

    2012-03-21

    Metabolic network alignment is a system scale comparative analysis that discovers important similarities and differences across different metabolisms and organisms. Although the problem of aligning metabolic networks has been considered in the past, the computational complexity of the existing solutions has so far limited their use to moderately sized networks. In this paper, we address the problem of aligning two metabolic networks, particularly when both of them are too large to be dealt with using existing methods. We develop a generic framework that can significantly improve the scale of the networks that can be aligned in practical time. Our framework has three major phases, namely the compression phase, the alignment phase and the refinement phase. For the first phase, we develop an algorithm which transforms the given networks to a compressed domain where they are summarized using fewer nodes, termed supernodes, and interactions. In the second phase, we carry out the alignment in the compressed domain using an existing network alignment method as our base algorithm. This alignment results in supernode mappings in the compressed domain, each of which are smaller instances of network alignment problem. In the third phase, we solve each of the instances using the base alignment algorithm to refine the alignment results. We provide a user defined parameter to control the number of compression levels which generally determines the tradeoff between the quality of the alignment versus how fast the algorithm runs. Our experiments on the networks from KEGG pathway database demonstrate that the compression method we propose reduces the sizes of metabolic networks by almost half at each compression level which provides an expected speedup of more than an order of magnitude. We also observe that the alignments obtained by only one level of compression capture the original alignment results with high accuracy. Together, these suggest that our framework results in

  18. Draft Proposal for the Development of an Australian Bibliographic Network. Development of Resource Sharing Networks. Networks Study No. 15.

    ERIC Educational Resources Information Center

    National Library of Australia, Canberra.

    As part of its responsibility for the development of bibliographic services in Australia, the Australian National Library presents this draft proposal for a national online shared cataloging facility to be known as the Australian Bibliographic Network or ABN. A preface describes ABN's historical background and relationship to BIBDATA, a previously…

  19. The Double-Stranded DNA Virosphere as a Modular Hierarchical Network of Gene Sharing

    PubMed Central

    Iranzo, Jaime

    2016-01-01

    ABSTRACT Virus genomes are prone to extensive gene loss, gain, and exchange and share no universal genes. Therefore, in a broad-scale study of virus evolution, gene and genome network analyses can complement traditional phylogenetics. We performed an exhaustive comparative analysis of the genomes of double-stranded DNA (dsDNA) viruses by using the bipartite network approach and found a robust hierarchical modularity in the dsDNA virosphere. Bipartite networks consist of two classes of nodes, with nodes in one class, in this case genomes, being connected via nodes of the second class, in this case genes. Such a network can be partitioned into modules that combine nodes from both classes. The bipartite network of dsDNA viruses includes 19 modules that form 5 major and 3 minor supermodules. Of these modules, 11 include tailed bacteriophages, reflecting the diversity of this largest group of viruses. The module analysis quantitatively validates and refines previously proposed nontrivial evolutionary relationships. An expansive supermodule combines the large and giant viruses of the putative order “Megavirales” with diverse moderate-sized viruses and related mobile elements. All viruses in this supermodule share a distinct morphogenetic tool kit with a double jelly roll major capsid protein. Herpesviruses and tailed bacteriophages comprise another supermodule, held together by a distinct set of morphogenetic proteins centered on the HK97-like major capsid protein. Together, these two supermodules cover the great majority of currently known dsDNA viruses. We formally identify a set of 14 viral hallmark genes that comprise the hubs of the network and account for most of the intermodule connections. PMID:27486193

  20. Latest developments in advanced network management and cross-sharing of next-generation flux stations

    NASA Astrophysics Data System (ADS)

    Burba, George; Johnson, Dave; Velgersdyk, Michael; Begashaw, Israel; Allyn, Douglas

    2016-04-01

    be merged into a single quality-control file (v) Multiple flux stations can be linked into an automated time-synchronized network (vi) Flux network managers, or PI's, can see all stations in real-time, including fluxes, supporting data, automated reports, and email alerts (vii) PI's can assign rights, allow or restrict access to stations and data: selected stations can be shared via rights-managed access internally or with external institutions (viii) Researchers without stations could form "virtual networks" for specific projects by collaborating with PIs from different actual networks This presentation provides detailed examples of FluxSuite currently utilized to manage two large flux networks in China (National Academy of Sciences and Agricultural Academy of Sciences), and smaller networks with stations in the USA, Germany, Ireland, Malaysia and other locations around the globe. Very latest 2016 developments and expanded functionality are also discussed.

  1. Bounded link prediction in very large networks

    NASA Astrophysics Data System (ADS)

    Cui, Wei; Pu, Cunlai; Xu, Zhongqi; Cai, Shimin; Yang, Jian; Michaelson, Andrew

    2016-09-01

    Evaluating link prediction methods is a hard task in very large complex networks due to the prohibitive computational cost. However, if we consider the lower bound of node pairs' similarity scores, this task can be greatly optimized. In this paper, we study CN index in the bounded link prediction framework, which is applicable to enormous heterogeneous networks. Specifically, we propose a fast algorithm based on the parallel computing scheme to obtain all node pairs with CN values larger than the lower bound. Furthermore, we propose a general measurement, called self-predictability, to quantify the performance of similarity indices in link prediction, which can also indicate the link predictability of networks with respect to given similarity indices.

  2. Time geography for ad-hoc shared-ride trip planning in mobile geosensor networks

    NASA Astrophysics Data System (ADS)

    Raubal, Martin; Winter, Stephan; Teβmann, Sven; Gaisbauer, Christian

    Ad-hoc shared-ride trip planning in an urban environment is a complex task within a non-deterministic transportation network. Mobile geosensor networks provide the technical environment for realizing ad-hoc shared-ride trip planning: Network nodes are autonomous agents that interact locally by ad-hoc short-range communication and arrange for shared rides. In a mobile geosensor network, communication costs are critical because of constraints regarding bandwidth, available energy, and memory. This paper introduces spatio-temporal concepts from time geography, which can be employed during the planning process to significantly reduce communication costs. We will integrate network-based algorithms and different wayfinding strategies to assist both shared-ride clients and hosts in finding optimal travel assignments. Multi-agent geosimulation in a real street network is used to demonstrate the applicability of the approach and quantitatively confirm the theoretically foreseen reduction in communication costs.

  3. Network issues for large mass storage requirements

    NASA Technical Reports Server (NTRS)

    Perdue, James

    1992-01-01

    File Servers and Supercomputing environments need high performance networks to balance the I/O requirements seen in today's demanding computing scenarios. UltraNet is one solution which permits both high aggregate transfer rates and high task-to-task transfer rates as demonstrated in actual tests. UltraNet provides this capability as both a Server-to-Server and Server-to-Client access network giving the supercomputing center the following advantages highest performance Transport Level connections (to 40 MBytes/sec effective rates); matches the throughput of the emerging high performance disk technologies, such as RAID, parallel head transfer devices and software striping; supports standard network and file system applications using SOCKET's based application program interface such as FTP, rcp, rdump, etc.; supports access to the Network File System (NFS) and LARGE aggregate bandwidth for large NFS usage; provides access to a distributed, hierarchical data server capability using DISCOS UniTree product; supports file server solutions available from multiple vendors, including Cray, Convex, Alliant, FPS, IBM, and others.

  4. Future large broadband switched satellite communications networks

    NASA Technical Reports Server (NTRS)

    Staelin, D. H.; Harvey, R. R.

    1979-01-01

    Critical technical, market, and policy issues relevant to future large broadband switched satellite networks are summarized. Our market projections for the period 1980 to 2000 are compared. Clusters of switched satellites, in lieu of large platforms, etc., are shown to have significant advantages. Analysis of an optimum terrestrial network architecture suggests the proper densities of ground stations and that link reliabilities 99.99% may entail less than a 10% cost premium for diversity protection at 20/30 GHz. These analyses suggest that system costs increase as the 0.6 power of traffic. Cost estimates for nominal 20/30 GHz satellite and ground facilities suggest optimum system configurations might employ satellites with 285 beams, multiple TDMA bands each carrying 256 Mbps, and 16 ft ground station antennas. A nominal development program is outlined.

  5. Coupled cluster algorithms for networks of shared memory parallel processors

    NASA Astrophysics Data System (ADS)

    Bentz, Jonathan L.; Olson, Ryan M.; Gordon, Mark S.; Schmidt, Michael W.; Kendall, Ricky A.

    2007-05-01

    As the popularity of using SMP systems as the building blocks for high performance supercomputers increases, so too increases the need for applications that can utilize the multiple levels of parallelism available in clusters of SMPs. This paper presents a dual-layer distributed algorithm, using both shared-memory and distributed-memory techniques to parallelize a very important algorithm (often called the "gold standard") used in computational chemistry, the single and double excitation coupled cluster method with perturbative triples, i.e. CCSD(T). The algorithm is presented within the framework of the GAMESS [M.W. Schmidt, K.K. Baldridge, J.A. Boatz, S.T. Elbert, M.S. Gordon, J.J. Jensen, S. Koseki, N. Matsunaga, K.A. Nguyen, S. Su, T.L. Windus, M. Dupuis, J.A. Montgomery, General atomic and molecular electronic structure system, J. Comput. Chem. 14 (1993) 1347-1363]. (General Atomic and Molecular Electronic Structure System) program suite and the Distributed Data Interface [M.W. Schmidt, G.D. Fletcher, B.M. Bode, M.S. Gordon, The distributed data interface in GAMESS, Comput. Phys. Comm. 128 (2000) 190]. (DDI), however, the essential features of the algorithm (data distribution, load-balancing and communication overhead) can be applied to more general computational problems. Timing and performance data for our dual-level algorithm is presented on several large-scale clusters of SMPs.

  6. A Networked NMR Spectrometer: Configuring a Shared Instrument

    ERIC Educational Resources Information Center

    Alonso, David; Mutch, G. William; Wong, Peter; Warren, Steven; Barot, Bal; Kosinski, Jan; Sinton, Mark

    2005-01-01

    A model for a shared nuclear magnetic resonance spectroscopy (NMR) facility between a private university and two local community colleges is presented. The discussion of the components required for the shared facility, modes of data distribution, and overall effect on the curriculum is presented.

  7. A Networked NMR Spectrometer: Configuring a Shared Instrument

    ERIC Educational Resources Information Center

    Alonso, David; Mutch, G. William; Wong, Peter; Warren, Steven; Barot, Bal; Kosinski, Jan; Sinton, Mark

    2005-01-01

    A model for a shared nuclear magnetic resonance spectroscopy (NMR) facility between a private university and two local community colleges is presented. The discussion of the components required for the shared facility, modes of data distribution, and overall effect on the curriculum is presented.

  8. Fuzzy-rule-based Adaptive Resource Control for Information Sharing in P2P Networks

    NASA Astrophysics Data System (ADS)

    Wu, Zhengping; Wu, Hao

    With more and more peer-to-peer (P2P) technologies available for online collaboration and information sharing, people can launch more and more collaborative work in online social networks with friends, colleagues, and even strangers. Without face-to-face interactions, the question of who can be trusted and then share information with becomes a big concern of a user in these online social networks. This paper introduces an adaptive control service using fuzzy logic in preference definition for P2P information sharing control, and designs a novel decision-making mechanism using formal fuzzy rules and reasoning mechanisms adjusting P2P information sharing status following individual users' preferences. Applications of this adaptive control service into different information sharing environments show that this service can provide a convenient and accurate P2P information sharing control for individual users in P2P networks.

  9. Sharing from Scratch: How To Network CD-ROM.

    ERIC Educational Resources Information Center

    Doering, David

    1998-01-01

    Examines common CD-ROM networking architectures: via existing operating systems (OS), thin server towers, and dedicated servers. Discusses digital video disc (DVD) and non-CD/DVD optical storage solutions and presents case studies of networks that work. (PEN)

  10. Sharing from Scratch: How To Network CD-ROM.

    ERIC Educational Resources Information Center

    Doering, David

    1998-01-01

    Examines common CD-ROM networking architectures: via existing operating systems (OS), thin server towers, and dedicated servers. Discusses digital video disc (DVD) and non-CD/DVD optical storage solutions and presents case studies of networks that work. (PEN)

  11. Local Area Networks: Vehicles for Connecting and Sharing Information.

    ERIC Educational Resources Information Center

    Lipman, Art

    1993-01-01

    Describes local area networks (LANs) and discusses advantages of their use in schools for students and teachers, including networking in labs, media centers, and classrooms. Roles of the network supervisor and/or technician are explained, including making decisions about the rights of users and instruction and assistance. (LRW)

  12. Sharing by Design: Understanding and Supporting Personal Health Information Sharing and Collaboration within Social Networks

    ERIC Educational Resources Information Center

    Skeels, Meredith McLain

    2010-01-01

    Friends, family, and community provide important support and help to patients who face an illness. Unfortunately, keeping a social network informed about a patient's health status and needs takes effort, making it difficult for people who are sick and exhausted from illness. Members of a patient's social network are often eager to help, but can be…

  13. Sharing by Design: Understanding and Supporting Personal Health Information Sharing and Collaboration within Social Networks

    ERIC Educational Resources Information Center

    Skeels, Meredith McLain

    2010-01-01

    Friends, family, and community provide important support and help to patients who face an illness. Unfortunately, keeping a social network informed about a patient's health status and needs takes effort, making it difficult for people who are sick and exhausted from illness. Members of a patient's social network are often eager to help, but can be…

  14. Attitudes towards Social Networking and Sharing Behaviors among Consumers of Direct-to-Consumer Personal Genomics.

    PubMed

    Lee, Sandra Soo-Jin; Vernez, Simone L; Ormond, K E; Granovetter, Mark

    2013-10-14

    Little is known about how consumers of direct-to-consumer personal genetic services share personal genetic risk information. In an age of ubiquitous online networking and rapid development of social networking tools, understanding how consumers share personal genetic risk assessments is critical in the development of appropriate and effective policies. This exploratory study investigates how consumers share personal genetic information and attitudes towards social networking behaviors. Adult participants aged 23 to 72 years old who purchased direct-to-consumer genetic testing from a personal genomics company were administered a web-based survey regarding their sharing activities and social networking behaviors related to their personal genetic test results. 80 participants completed the survey; of those, 45% shared results on Facebook and 50.9% reported meeting or reconnecting with more than 10 other individuals through the sharing of their personal genetic information. For help interpreting test results, 70.4% turned to Internet websites and online sources, compared to 22.7% who consulted their healthcare providers. Amongst participants, 51.8% reported that they believe the privacy of their personal genetic information would be breached in the future. Consumers actively utilize online social networking tools to help them share and interpret their personal genetic information. These findings suggest a need for careful consideration of policy recommendations in light of the current ambiguity of regulation and oversight of consumer initiated sharing activities.

  15. Attitudes towards Social Networking and Sharing Behaviors among Consumers of Direct-to-Consumer Personal Genomics

    PubMed Central

    Lee, Sandra Soo-Jin; Vernez, Simone L.; Ormond, K.E.; Granovetter, Mark

    2013-01-01

    Little is known about how consumers of direct-to-consumer personal genetic services share personal genetic risk information. In an age of ubiquitous online networking and rapid development of social networking tools, understanding how consumers share personal genetic risk assessments is critical in the development of appropriate and effective policies. This exploratory study investigates how consumers share personal genetic information and attitudes towards social networking behaviors. Methods: Adult participants aged 23 to 72 years old who purchased direct-to-consumer genetic testing from a personal genomics company were administered a web-based survey regarding their sharing activities and social networking behaviors related to their personal genetic test results. Results: 80 participants completed the survey; of those, 45% shared results on Facebook and 50.9% reported meeting or reconnecting with more than 10 other individuals through the sharing of their personal genetic information. For help interpreting test results, 70.4% turned to Internet websites and online sources, compared to 22.7% who consulted their healthcare providers. Amongst participants, 51.8% reported that they believe the privacy of their personal genetic information would be breached in the future. Conclusion: Consumers actively utilize online social networking tools to help them share and interpret their personal genetic information. These findings suggest a need for careful consideration of policy recommendations in light of the current ambiguity of regulation and oversight of consumer initiated sharing activities. PMID:25562728

  16. Large-scale Heterogeneous Network Data Analysis

    DTIC Science & Technology

    2012-07-31

    Data for Multi-Player Influence Maximization on Social Networks.” KDD 2012 (Demo).  Po-Tzu Chang , Yen-Chieh Huang, Cheng-Lun Yang, Shou-De Lin, Pu...Jen Cheng. “Learning-Based Time-Sensitive Re-Ranking for Web Search.” SIGIR 2012 (poster)  Hung -Che Lai, Cheng-Te Li, Yi-Chen Lo, and Shou-De Lin...Exploiting and Evaluating MapReduce for Large-Scale Graph Mining.” ASONAM 2012 (Full, 16% acceptance ratio).  Hsun-Ping Hsieh , Cheng-Te Li, and Shou

  17. Empirical Models of Social Learning in a Large, Evolving Network

    PubMed Central

    Bener, Ayşe Başar; Çağlayan, Bora; Henry, Adam Douglas; Prałat, Paweł

    2016-01-01

    This paper advances theories of social learning through an empirical examination of how social networks change over time. Social networks are important for learning because they constrain individuals’ access to information about the behaviors and cognitions of other people. Using data on a large social network of mobile device users over a one-month time period, we test three hypotheses: 1) attraction homophily causes individuals to form ties on the basis of attribute similarity, 2) aversion homophily causes individuals to delete existing ties on the basis of attribute dissimilarity, and 3) social influence causes individuals to adopt the attributes of others they share direct ties with. Statistical models offer varied degrees of support for all three hypotheses and show that these mechanisms are more complex than assumed in prior work. Although homophily is normally thought of as a process of attraction, people also avoid relationships with others who are different. These mechanisms have distinct effects on network structure. While social influence does help explain behavior, people tend to follow global trends more than they follow their friends. PMID:27701430

  18. Empirical Models of Social Learning in a Large, Evolving Network.

    PubMed

    Bener, Ayşe Başar; Çağlayan, Bora; Henry, Adam Douglas; Prałat, Paweł

    2016-01-01

    This paper advances theories of social learning through an empirical examination of how social networks change over time. Social networks are important for learning because they constrain individuals' access to information about the behaviors and cognitions of other people. Using data on a large social network of mobile device users over a one-month time period, we test three hypotheses: 1) attraction homophily causes individuals to form ties on the basis of attribute similarity, 2) aversion homophily causes individuals to delete existing ties on the basis of attribute dissimilarity, and 3) social influence causes individuals to adopt the attributes of others they share direct ties with. Statistical models offer varied degrees of support for all three hypotheses and show that these mechanisms are more complex than assumed in prior work. Although homophily is normally thought of as a process of attraction, people also avoid relationships with others who are different. These mechanisms have distinct effects on network structure. While social influence does help explain behavior, people tend to follow global trends more than they follow their friends.

  19. Potential Parasite Transmission in Multi-Host Networks Based on Parasite Sharing

    PubMed Central

    Pilosof, Shai; Morand, Serge; Krasnov, Boris R.; Nunn, Charles L.

    2015-01-01

    Epidemiological networks are commonly used to explore dynamics of parasite transmission among individuals in a population of a given host species. However, many parasites infect multiple host species, and thus multi-host networks may offer a better framework for investigating parasite dynamics. We investigated the factors that influence parasite sharing – and thus potential transmission pathways – among rodent hosts in Southeast Asia. We focused on differences between networks of a single host species and networks that involve multiple host species. In host-parasite networks, modularity (the extent to which the network is divided into subgroups of rodents that interact with similar parasites) was higher in the multi-species than in the single-species networks. This suggests that phylogeny affects patterns of parasite sharing, which was confirmed in analyses showing that it predicted affiliation of individuals to modules. We then constructed “potential transmission networks” based on the host-parasite networks, in which edges depict the similarity between a pair of individuals in the parasites they share. The centrality of individuals in these networks differed between multi- and single-species networks, with species identity and individual characteristics influencing their position in the networks. Simulations further revealed that parasite dynamics differed between multi- and single-species networks. We conclude that multi-host networks based on parasite sharing can provide new insights into the potential for transmission among hosts in an ecological community. In addition, the factors that determine the nature of parasite sharing (i.e. structure of the host-parasite network) may impact transmission patterns. PMID:25748947

  20. Good Samaritans in Networks: An Experiment on How Networks Influence Egalitarian Sharing and the Evolution of Inequality.

    PubMed

    Chiang, Yen-Sheng

    2015-01-01

    The fact that the more resourceful people are sharing with the poor to mitigate inequality-egalitarian sharing-is well documented in the behavioral science research. How inequality evolves as a result of egalitarian sharing is determined by the structure of "who gives whom". While most prior experimental research investigates allocation of resources in dyads and groups, the paper extends the research of egalitarian sharing to networks for a more generalized structure of social interaction. An agent-based model is proposed to predict how actors, linked in networks, share their incomes with neighbors. A laboratory experiment with human subjects further shows that income distributions evolve to different states in different network topologies. Inequality is significantly reduced in networks where the very rich and the very poor are connected so that income discrepancy is salient enough to motivate the rich to share their incomes with the poor. The study suggests that social networks make a difference in how egalitarian sharing influences the evolution of inequality.

  1. Large-Scale Organization of Glycosylation Networks

    NASA Astrophysics Data System (ADS)

    Kim, Pan-Jun; Lee, Dong-Yup; Jeong, Hawoong

    2009-03-01

    Glycosylation is a highly complex process to produce a diverse repertoire of cellular glycans that are frequently attached to proteins and lipids. Glycans participate in fundamental biological processes including molecular trafficking and clearance, cell proliferation and apoptosis, developmental biology, immune response, and pathogenesis. N-linked glycans found on proteins are formed by sequential attachments of monosaccharides with the help of a relatively small number of enzymes. Many of these enzymes can accept multiple N-linked glycans as substrates, thus generating a large number of glycan intermediates and their intermingled pathways. Motivated by the quantitative methods developed in complex network research, we investigate the large-scale organization of such N-glycosylation pathways in a mammalian cell. The uncovered results give the experimentally-testable predictions for glycosylation process, and can be applied to the engineering of therapeutic glycoproteins.

  2. Supporting the Maritime Information Dominance: Optimizing Tactical Network for Biometric Data Sharing in Maritime Interdiction Operations

    DTIC Science & Technology

    2015-03-01

    information dominance in the maritime domain by optimizing tactical mobile ad hoc network (MANET) systems for wireless sharing of biometric data in maritime interdiction operations (MIO). Current methods for sharing biometric data in MIO are unnecessarily slow and do not leverage wireless networks at the tactical edge to maximize information dominance . Field experiments allow students to test wireless MANETs at the tactical edge. Analysis is focused on determining optimal MANET design and implementation. It considers various implementations with

  3. Decision Support System in the Management of Resource-Sharing Networks.

    ERIC Educational Resources Information Center

    Dubey, Yogendra P.

    1984-01-01

    Reports on emergence of decision support system (DSS) as a practical approach for applying computers and information to problems facing management. Information processing and decision making in organizations, simulation-model-based DSS in management of library resource sharing networks, and a resource-sharing simulation system are highlighted.…

  4. Oklahoma Library Technology Network Plan for Information Sharing and Telecommunications.

    ERIC Educational Resources Information Center

    Oklahoma State Dept. of Libraries, Oklahoma City.

    This plan sets forth approaches for state-level assistance for Oklahoma libraries to exchange information and to share or acquire machine-readable information from public and private sources through telecommunications, as well as for access to these libraries for existing and future state informational databases. Objectives and requirements are…

  5. Public Attitudes toward Consent and Data Sharing in Biobank Research: A Large Multi-site Experimental Survey in the US.

    PubMed

    Sanderson, Saskia C; Brothers, Kyle B; Mercaldo, Nathaniel D; Clayton, Ellen Wright; Antommaria, Armand H Matheny; Aufox, Sharon A; Brilliant, Murray H; Campos, Diego; Carrell, David S; Connolly, John; Conway, Pat; Fullerton, Stephanie M; Garrison, Nanibaa' A; Horowitz, Carol R; Jarvik, Gail P; Kaufman, David; Kitchner, Terrie E; Li, Rongling; Ludman, Evette J; McCarty, Catherine A; McCormick, Jennifer B; McManus, Valerie D; Myers, Melanie F; Scrol, Aaron; Williams, Janet L; Shrubsole, Martha J; Schildcrout, Jonathan S; Smith, Maureen E; Holm, Ingrid A

    2017-03-02

    Individuals participating in biobanks and other large research projects are increasingly asked to provide broad consent for open-ended research use and widespread sharing of their biosamples and data. We assessed willingness to participate in a biobank using different consent and data sharing models, hypothesizing that willingness would be higher under more restrictive scenarios. Perceived benefits, concerns, and information needs were also assessed. In this experimental survey, individuals from 11 US healthcare systems in the Electronic Medical Records and Genomics (eMERGE) Network were randomly allocated to one of three hypothetical scenarios: tiered consent and controlled data sharing; broad consent and controlled data sharing; or broad consent and open data sharing. Of 82,328 eligible individuals, exactly 13,000 (15.8%) completed the survey. Overall, 66% (95% CI: 63%-69%) of population-weighted respondents stated they would be willing to participate in a biobank; willingness and attitudes did not differ between respondents in the three scenarios. Willingness to participate was associated with self-identified white race, higher educational attainment, lower religiosity, perceiving more research benefits, fewer concerns, and fewer information needs. Most (86%, CI: 84%-87%) participants would want to know what would happen if a researcher misused their health information; fewer (51%, CI: 47%-55%) would worry about their privacy. The concern that the use of broad consent and open data sharing could adversely affect participant recruitment is not supported by these findings. Addressing potential participants' concerns and information needs and building trust and relationships with communities may increase acceptance of broad consent and wide data sharing in biobank research.

  6. Sharing the Wealth: Towards an Ocean Sensing Network

    DTIC Science & Technology

    2012-07-01

    an overarching data network can provide persistent presence and access to information for a wide audi - ence of users. There is a possible prac...Obviously, there are significant man- power and resource savings to be Figure 1 • The UNDER NET is a Multi-Environmental, End·to·End Communications Network...information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and

  7. Dynamic Spectrum Sharing with Limited Network State Information

    DTIC Science & Technology

    2010-11-01

    possibly different) messages to a set of mobile receivers . We have studied limited feedback schemes for both single-user Orthogonal Frequency...in which the broadcast node sequentially receives feedback from the mobiles and decides when to stop receiving additional feedback and begin data...concerned with the costs and benefits of learning and exchanging Network State Information (NSI) among cooperative nodes in a wireless network. NSI

  8. Synchronization of coupled large-scale Boolean networks

    SciTech Connect

    Li, Fangfei

    2014-03-15

    This paper investigates the complete synchronization and partial synchronization of two large-scale Boolean networks. First, the aggregation algorithm towards large-scale Boolean network is reviewed. Second, the aggregation algorithm is applied to study the complete synchronization and partial synchronization of large-scale Boolean networks. Finally, an illustrative example is presented to show the efficiency of the proposed results.

  9. Synchronization of coupled large-scale Boolean networks

    NASA Astrophysics Data System (ADS)

    Li, Fangfei

    2014-03-01

    This paper investigates the complete synchronization and partial synchronization of two large-scale Boolean networks. First, the aggregation algorithm towards large-scale Boolean network is reviewed. Second, the aggregation algorithm is applied to study the complete synchronization and partial synchronization of large-scale Boolean networks. Finally, an illustrative example is presented to show the efficiency of the proposed results.

  10. Micro-to-Micro Communications: Local Networks Help Personal Computers Share Information.

    ERIC Educational Resources Information Center

    Byers, T. J.

    1984-01-01

    Discusses major features of an effective local network of microcomputers within a business: (1) particular transmission medium used; (2) the way data is transmitted over that medium; and (3) the way access to the network is shared among the devices. A data communications glossary is provided. (MBR)

  11. Categorical Structure among Shared Features in Networks of Early-Learned Nouns

    ERIC Educational Resources Information Center

    Hills, Thomas T.; Maouene, Mounir; Maouene, Josita; Sheya, Adam; Smith, Linda

    2009-01-01

    The shared features that characterize the noun categories that young children learn first are a formative basis of the human category system. To investigate the potential categorical information contained in the features of early-learned nouns, we examine the graph-theoretic properties of noun-feature networks. The networks are built from the…

  12. Horizontal Evaluation: Fostering Knowledge Sharing and Program Improvement within a Network

    ERIC Educational Resources Information Center

    Thiele, Graham; Devaux, Andre; Velasco, Claudio; Horton, Douglas

    2007-01-01

    Horizontal evaluation combines self-assessment and external evaluation by peers. Papa Andina, a regional network that works to reduce rural poverty in the Andean region by fostering innovation in potato production and marketing, has used horizontal evaluations to improve the work of local project teams and to share knowledge within the network. In…

  13. Sharing, Privacy and Trust in Our Networked World. A Report to the OCLC Membership

    ERIC Educational Resources Information Center

    Storey, Tom, Ed.

    2007-01-01

    The practice of using a social network to establish and enhance relationships based on some common ground--shared interests, related skills, or a common geographic location--is as old as human societies, but social networking has flourished due to the ease of connecting on the Web. This OCLC membership report explores this web of social…

  14. Horizontal Evaluation: Fostering Knowledge Sharing and Program Improvement within a Network

    ERIC Educational Resources Information Center

    Thiele, Graham; Devaux, Andre; Velasco, Claudio; Horton, Douglas

    2007-01-01

    Horizontal evaluation combines self-assessment and external evaluation by peers. Papa Andina, a regional network that works to reduce rural poverty in the Andean region by fostering innovation in potato production and marketing, has used horizontal evaluations to improve the work of local project teams and to share knowledge within the network. In…

  15. Mission Command in the Age of Network-Enabled Operations: Social Network Analysis of Information Sharing and Situation Awareness

    DTIC Science & Technology

    2016-06-22

    Ungvarsky DM, Lebiere C and Gonzalez C (2016) Mission Command in the Age of Network-Enabled Operations: Social Network Analysis of Information...Sharing and Situation Awareness. Front. Psychol. 7:937. doi: 10.3389/fpsyg.2016.00937 Mission Command in the Age of Network-Enabled Operations: Social ...Christian Lebiere 2 and Cleotilde Gonzalez 2 1 U.S. Army Research Laboratory, Aberdeen Proving Ground, MD, USA, 2 Department of Social and Decision Sciences

  16. Enhancing topology adaptation in information-sharing social networks

    NASA Astrophysics Data System (ADS)

    Cimini, Giulio; Chen, Duanbing; Medo, Matúš; Lü, Linyuan; Zhang, Yi-Cheng; Zhou, Tao

    2012-04-01

    The advent of the Internet and World Wide Web has led to unprecedent growth of the information available. People usually face the information overload by following a limited number of sources which best fit their interests. It has thus become important to address issues like who gets followed and how to allow people to discover new and better information sources. In this paper we conduct an empirical analysis of different online social networking sites and draw inspiration from its results to present different source selection strategies in an adaptive model for social recommendation. We show that local search rules which enhance the typical topological features of real social communities give rise to network configurations that are globally optimal. These rules create networks which are effective in information diffusion and resemble structures resulting from real social systems.

  17. Social network analysis of food sharing among households in opisthorchiasis endemic villages of Lawa Lake, Thailand.

    PubMed

    Phimpraphai, Waraphon; Tangkawattana, Sirikachorn; Sereerak, Piya; Kasemsuwan, Suwicha; Sripa, Banchob

    2017-05-01

    Consumption of raw fish is a well-documented risk factor for Opisthorchis viverrini infection. Sharing of food, especially raw fish recipes may influence the spread of disease through a community. Using social network analysis of an ego network, we investigated food sharing among households in an Opisthorchis-endemic area. Network centrality properties were used to explain the differences in O. viverrini transmission and control between villages with a low and high prevalence of infection. Information on demography and O. viverrini infection in 2008 from villagers in the Lawa Lake area was extracted from the Tropical Disease Research Center database. The two villages that had the lowest and the highest O. viverrini infection at the household level were recruited. Ten percent of households of each village were randomly sampled. Participatory epidemiology and face-to-face structured interviews guided by a social network questionnaire were used to collect data on livelihood, agricultural patterns, food sources, raw fish eating habits, and other food sharing during daily life and social gatherings. The number of contacts including in-degree and out-degree varied from 0 to 7 in the low-infection village and 0 to 4 in the high-infection village. The mean number of contacts for the food-sharing network among the low- and high-infection villages was 1.64 and 0.73 contacts per household, respectively. Between these villages, the mean number of out-degree (p=0.0125), but not in-degree (p=0.065), was significantly different. Food-sharing differed in numbers of sharing-in and sharing-out between the two villages. Network analysis of food sharing may be of value in designing strategies for opisthorchiasis control at the community level.

  18. Quantum synchronization and quantum state sharing in an irregular complex network

    NASA Astrophysics Data System (ADS)

    Li, Wenlin; Li, Chong; Song, Heshan

    2017-02-01

    We investigate the quantum synchronization phenomenon of the complex network constituted by coupled optomechanical systems and prove that the unknown identical quantum states can be shared or distributed in the quantum network even though the topology is varying. Considering a channel constructed by quantum correlation, we show that quantum synchronization can sustain and maintain high levels in Markovian dissipation for a long time. We also analyze the state-sharing process between two typical complex networks, and the results predict that linked nodes can be directly synchronized, but the whole network will be synchronized only if some specific synchronization conditions are satisfied. Furthermore, we give the synchronization conditions analytically through analyzing network dynamics. This proposal paves the way for studying multi-interaction synchronization and achieving effective quantum information processing in a complex network.

  19. The intellectual property management for data sharing in a German liver cancer research network.

    PubMed

    He, Shan; Ganzinger, Matthias; Knaup, Petra

    2012-01-01

    Sharing data in biomedical research networks has great potential benefits including efficient use of resources, avoiding duplicate experiments and promoting collaboration. However, concerns from data producers about difficulties of getting proper acknowledgement for their contributions are becoming obstacles for efficient and network wide data sharing in reality. Effective and convenient ways of intellectual property management and acknowledging contributions to the data producers are required. This paper analyzed the system requirements for intellectual property management in a German liver cancer research network and proposed solutions for facilitating acknowledgement of data contributors using informatics tools instead of pure policy level strategies.

  20. The long term agroecosystem research network - shared research strategy

    Treesearch

    Jean L. Steiner; Timothy Strickland; Peter J.A. Kleinman; Kris Havstad; Thomas B. Moorman; M.Susan Moran; Phil Hellman; Ray B. Bryant; David Huggins; Greg McCarty

    2016-01-01

    While current weather patterns and rapidly accelerated changes in technology often focus attention on short-term trends in agriculture, the fundamental demands on modern agriculture to meet society food, feed, fuel and fiber production while providing the foundation for a healthy environment requires long-term perspective. The Long- Term Agroecoystem Research Network...

  1. Freedom and Sharing in the Global Network Society

    ERIC Educational Resources Information Center

    Lankshear, Colin

    2006-01-01

    This article focuses on some ideas from social and political philosophy concerning the ideal of freedom that may be useful for thinking about issues associated with the rise of network societies. The tendency for "freedom" to mean very different things to different people has carried over to the context of thinking about issues associated with new…

  2. Library Resource-Sharing in the Network-Centric World.

    ERIC Educational Resources Information Center

    McGee, Rob

    This paper discusses changes in services, technology, and organization as libraries prepare to enter the "network-centric library world." Part 1 addresses the transition from the analog era to the digital age, and the convergence of libraries and education, including opportunities for library leadership in Internet access, digital…

  3. Knowledge Sharing via Social Networking Platforms in Organizations

    ERIC Educational Resources Information Center

    Kettles, Degan

    2012-01-01

    Knowledge Management Systems have been actively promoted for decades within organizations but have frequently failed to be used. Recently, deployments of enterprise social networking platforms used for knowledge management have become commonplace. These platforms help harness the knowledge of workers by serving as repositories of knowledge as well…

  4. Shared Authority Control at the Western Library Network.

    ERIC Educational Resources Information Center

    Coyne, Fumiko H.; Mifflin, Ingrid

    1990-01-01

    Examines the cooperative efforts of the Western Library Network (WLN) and its members to maintain authority control over its central bibliographic database. The first section describes authority maintenance activities performed by WLN centrally, and the second describes the contribution of an individual member library--the Washington State…

  5. Knowledge Sharing via Social Networking Platforms in Organizations

    ERIC Educational Resources Information Center

    Kettles, Degan

    2012-01-01

    Knowledge Management Systems have been actively promoted for decades within organizations but have frequently failed to be used. Recently, deployments of enterprise social networking platforms used for knowledge management have become commonplace. These platforms help harness the knowledge of workers by serving as repositories of knowledge as well…

  6. Networking Biology: The Origins of Sequence-Sharing Practices in Genomics.

    PubMed

    Stevens, Hallam

    2015-10-01

    The wide sharing of biological data, especially nucleotide sequences, is now considered to be a key feature of genomics. Historians and sociologists have attempted to account for the rise of this sharing by pointing to precedents in model organism communities and in natural history. This article supplements these approaches by examining the role that electronic networking technologies played in generating the specific forms of sharing that emerged in genomics. The links between early computer users at the Stanford Artificial Intelligence Laboratory in the 1960s, biologists using local computer networks in the 1970s, and GenBank in the 1980s, show how networking technologies carried particular practices of communication, circulation, and data distribution from computing into biology. In particular, networking practices helped to transform sequences themselves into objects that had value as a community resource.

  7. HydroShare: Applying professional software engineering to a new NSF-funded large software project

    NASA Astrophysics Data System (ADS)

    Idaszak, R.; Tarboton, D. G.; Ames, D.; Saleem Arrigo, J. A.; Band, L. E.; Bedig, A.; Castronova, A. M.; Christopherson, L.; Coposky, J.; Couch, A.; Dash, P.; Gan, T.; Goodall, J.; Gustafson, K.; Heard, J.; Hooper, R. P.; Horsburgh, J. S.; Jackson, S.; Johnson, H.; Maidment, D. R.; Mbewe, P.; Merwade, V.; Miles, B.; Reeder, S.; Russell, T.; Song, C.; Taylor, A.; Thakur, S.; Valentine, D. W.; Whiteaker, T. L.

    2013-12-01

    HydroShare is an online, collaborative system being developed for sharing hydrologic data and models as part of the NSF's Software Infrastructure for Sustained Innovation (SI2) program (NSF collaborative award numbers 1148453 and 1148090). HydroShare involves a large software development effort requiring cooperative research and distributed software development between domain scientists, professional software engineers (here 'professional' denotes previous commercial experience in the application of modern software engineering), and university software developers. HydroShare expands upon the data sharing capabilities of the Hydrologic Information System of the Consortium of Universities for the Advancement of Hydrologic Sciences, Inc. (CUAHSI) by broadening the classes of data accommodated, expanding capability to include the sharing of models and model components, and taking advantage of emerging social media functionality to enhance information about and collaboration around hydrologic data and models. With a goal of enabling better science concomitant with improved sustainable software practices, we will describe our approach, experiences, and lessons learned thus-far in applying professional software engineering to a large NSF-funded software project from the project's onset.

  8. Developing A Large-Scale, Collaborative, Productive Geoscience Education Network

    NASA Astrophysics Data System (ADS)

    Manduca, C. A.; Bralower, T. J.; Egger, A. E.; Fox, S.; Ledley, T. S.; Macdonald, H.; Mcconnell, D. A.; Mogk, D. W.; Tewksbury, B. J.

    2012-12-01

    Over the past 15 years, the geoscience education community has grown substantially and developed broad and deep capacity for collaboration and dissemination of ideas. While this community is best viewed as emergent from complex interactions among changing educational needs and opportunities, we highlight the role of several large projects in the development of a network within this community. In the 1990s, three NSF projects came together to build a robust web infrastructure to support the production and dissemination of on-line resources: On The Cutting Edge (OTCE), Earth Exploration Toolbook, and Starting Point: Teaching Introductory Geoscience. Along with the contemporaneous Digital Library for Earth System Education, these projects engaged geoscience educators nationwide in exploring professional development experiences that produced lasting on-line resources, collaborative authoring of resources, and models for web-based support for geoscience teaching. As a result, a culture developed in the 2000s in which geoscience educators anticipated that resources for geoscience teaching would be shared broadly and that collaborative authoring would be productive and engaging. By this time, a diverse set of examples demonstrated the power of the web infrastructure in supporting collaboration, dissemination and professional development . Building on this foundation, more recent work has expanded both the size of the network and the scope of its work. Many large research projects initiated collaborations to disseminate resources supporting educational use of their data. Research results from the rapidly expanding geoscience education research community were integrated into the Pedagogies in Action website and OTCE. Projects engaged faculty across the nation in large-scale data collection and educational research. The Climate Literacy and Energy Awareness Network and OTCE engaged community members in reviewing the expanding body of on-line resources. Building Strong

  9. Identification of cross-species shared transcriptional networks of diabetic nephropathy in human and mouse glomeruli.

    PubMed

    Hodgin, Jeffrey B; Nair, Viji; Zhang, Hongyu; Randolph, Ann; Harris, Raymond C; Nelson, Robert G; Weil, E Jennifer; Cavalcoli, James D; Patel, Jignesh M; Brosius, Frank C; Kretzler, Matthias

    2013-01-01

    Murine models are valuable instruments in defining the pathogenesis of diabetic nephropathy (DN), but they only partially recapitulate disease manifestations of human DN, limiting their utility. To define the molecular similarities and differences between human and murine DN, we performed a cross-species comparison of glomerular transcriptional networks. Glomerular gene expression was profiled in patients with early type 2 DN and in three mouse models (streptozotocin DBA/2, C57BLKS db/db, and eNOS-deficient C57BLKS db/db mice). Species-specific transcriptional networks were generated and compared with a novel network-matching algorithm. Three shared human-mouse cross-species glomerular transcriptional networks containing 143 (Human-DBA STZ), 97 (Human-BKS db/db), and 162 (Human-BKS eNOS(-/-) db/db) gene nodes were generated. Shared nodes across all networks reflected established pathogenic mechanisms of diabetes complications, such as elements of Janus kinase (JAK)/signal transducer and activator of transcription (STAT) and vascular endothelial growth factor receptor (VEGFR) signaling pathways. In addition, novel pathways not previously associated with DN and cross-species gene nodes and pathways unique to each of the human-mouse networks were discovered. The human-mouse shared glomerular transcriptional networks will assist DN researchers in selecting mouse models most relevant to the human disease process of interest. Moreover, they will allow identification of new pathways shared between mice and humans.

  10. Quantitative Imaging Network: Data Sharing and Competitive AlgorithmValidation Leveraging The Cancer Imaging Archive1

    PubMed Central

    Kalpathy-Cramer, Jayashree; Freymann, John Blake; Kirby, Justin Stephen; Kinahan, Paul Eugene; Prior, Fred William

    2014-01-01

    The Quantitative Imaging Network (QIN), supported by the National Cancer Institute, is designed to promote research and development of quantitative imaging methods and candidate biomarkers for the measurement of tumor response in clinical trial settings. An integral aspect of the QIN mission is to facilitate collaborative activities that seek to develop best practices for the analysis of cancer imaging data. The QIN working groups and teams are developing new algorithms for image analysis and novel biomarkers for the assessment of response to therapy. To validate these algorithms and biomarkers and translate them into clinical practice, algorithms need to be compared and evaluated on large and diverse data sets. Analysis competitions, or “challenges,” are being conducted within the QIN as a means to accomplish this goal. The QIN has demonstrated, through its leveraging of The Cancer Imaging Archive (TCIA), that data sharing of clinical images across multiple sites is feasible and that it can enable and support these challenges. In addition to Digital Imaging and Communications in Medicine (DICOM) imaging data, many TCIA collections provide linked clinical, pathology, and “ground truth” data generated by readers that could be used for further challenges. The TCIA-QIN partnership is a successful model that provides resources for multisite sharing of clinical imaging data and the implementation of challenges to support algorithm and biomarker validation. PMID:24772218

  11. Competitive Spectrum Sharing in Wireless Networks: A Dynamic Non-cooperative Game Approach

    NASA Astrophysics Data System (ADS)

    Raoof, Omar; Al-Banna, Zaineb; Al-Raweshidy, H. S.

    “Game Theory” is a promising mathematical tool to improve the utilization of radio frequency spectrum in wireless networks. In this paper, we consider the problem of spectrum sharing between a primary user and a group of secondary users. We formulate our solution in such a way that one of the secondary users will be a secondary primary user by sharing the spectrum offered from the primary user and offer his share to be shared by the rest of the secondary users in the network. A theoretical non-cooperative game model is introduced to study node behavior in wireless networks based on their reputation. The only way for a node to guarantee a share in the spectrum is by enhancing its reputation, which is done by serving other nodes in the network. Game theory can be used by individual selfish nodes to determine their optimal strategy for participation level in the network. Furthermore, game theory produces information about the overall nature of nodes’ interaction and system efficiency, showing how system efficiency can be improved.

  12. Robust Large Margin Deep Neural Networks

    NASA Astrophysics Data System (ADS)

    Sokolic, Jure; Giryes, Raja; Sapiro, Guillermo; Rodrigues, Miguel R. D.

    2017-08-01

    The generalization error of deep neural networks via their classification margin is studied in this work. Our approach is based on the Jacobian matrix of a deep neural network and can be applied to networks with arbitrary non-linearities and pooling layers, and to networks with different architectures such as feed forward networks and residual networks. Our analysis leads to the conclusion that a bounded spectral norm of the network's Jacobian matrix in the neighbourhood of the training samples is crucial for a deep neural network of arbitrary depth and width to generalize well. This is a significant improvement over the current bounds in the literature, which imply that the generalization error grows with either the width or the depth of the network. Moreover, it shows that the recently proposed batch normalization and weight normalization re-parametrizations enjoy good generalization properties, and leads to a novel network regularizer based on the network's Jacobian matrix. The analysis is supported with experimental results on the MNIST, CIFAR-10, LaRED and ImageNet datasets.

  13. Dyspnea and pain share emotion-related brain network.

    PubMed

    von Leupoldt, Andreas; Sommer, Tobias; Kegat, Sarah; Baumann, Hans Jörg; Klose, Hans; Dahme, Bernhard; Büchel, Christian

    2009-10-15

    The early detection of stimuli signalling threat to an organism is a crucial evolutionary advantage. For example, the perception of aversive bodily sensations such as dyspnea and pain strongly motivates fast adaptive behaviour to ensure survival. Their similarly threatening and motivating characters led to the speculation that both sensations are mediated by common brain areas, which has also been suggested by neuroimaging studies on either dyspnea or pain. By using functional magnetic resonance imaging (fMRI), we formally tested this hypothesis and compared the cortical processing of perceived heat pain and resistive load induced dyspnea in the same group of participants. Here we show that the perception of both aversive sensations is processed in similar brain areas including the insula, dorsal anterior cingulate cortex, amygdala and medial thalamus. These areas have a documented role in the processing of emotions such as fear and anxiety. Thus, the current study highlights the role of a common emotion-related human brain network which underlies the perception of aversive bodily sensations such as dyspnea and pain. This network seems crucial for translating the threatening character of different bodily signals into behavioural consequences that promote survival.

  14. Accelerated Training for Large Feedforward Neural Networks

    NASA Technical Reports Server (NTRS)

    Stepniewski, Slawomir W.; Jorgensen, Charles C.

    1998-01-01

    In this paper we introduce a new training algorithm, the scaled variable metric (SVM) method. Our approach attempts to increase the convergence rate of the modified variable metric method. It is also combined with the RBackprop algorithm, which computes the product of the matrix of second derivatives (Hessian) with an arbitrary vector. The RBackprop method allows us to avoid computationally expensive, direct line searches. In addition, it can be utilized in the new, 'predictive' updating technique of the inverse Hessian approximation. We have used directional slope testing to adjust the step size and found that this strategy works exceptionally well in conjunction with the Rbackprop algorithm. Some supplementary, but nevertheless important enhancements to the basic training scheme such as improved setting of a scaling factor for the variable metric update and computationally more efficient procedure for updating the inverse Hessian approximation are presented as well. We summarize by comparing the SVM method with four first- and second- order optimization algorithms including a very effective implementation of the Levenberg-Marquardt method. Our tests indicate promising computational speed gains of the new training technique, particularly for large feedforward networks, i.e., for problems where the training process may be the most laborious.

  15. Survivable VON mapping with ambiguity similitude for differentiable maximum shared capacity in elastic optical networks

    NASA Astrophysics Data System (ADS)

    Yang, Hui; Zhu, Xiaoxu; Bai, Wei; Zhao, Yongli; Zhang, Jie; Liu, Zhu; Zhou, Ziguan; Ou, Qinghai

    2016-09-01

    Virtualization is considered to be a promising solution to support various emerging applications. This paper illustrates the problem of virtual mapping from a new perspective, and mainly focuses on survivable mapping of virtual networks and the potential trade-off between spectral resource usage effectiveness and failure resilience level. We design an optimum shared protection mapping (OSPM) scheme in elastic optical networks. A differentiable maximum shared capacity of each frequency slot is defined to more efficiently shared protection resource. In order to satisfy various assessment standards, a metric called ambiguity similitude is defined for the first time to give insight on the optimizing difficulty. Simulation results are presented to compare the outcome of the novel OSPM algorithm with traditional dedicated link protection and maximum shared protection mapping. By synthetic analysis, OSPM outperforms the other two schemes in terms of striking a perfect balance among blocking probability, resources utilization, protective success rate, and spectrum redundancy.

  16. Sharing clinical decisions for multimorbidity case management using social network and open-source tools.

    PubMed

    Martínez-García, Alicia; Moreno-Conde, Alberto; Jódar-Sánchez, Francisco; Leal, Sandra; Parra, Carlos

    2013-12-01

    Social networks applied through Web 2.0 tools have gained importance in health domain, because they produce improvements on the communication and coordination capabilities among health professionals. This is highly relevant for multimorbidity patients care because there is a large number of health professionals in charge of patient care, and this requires to obtain clinical consensus in their decisions. Our objective is to develop a tool for collaborative work among health professionals for multimorbidity patient care. We describe the architecture to incorporate decision support functionalities in a social network tool to enable the adoption of shared decisions among health professionals from different care levels. As part of the first stage of the project, this paper describes the results obtained in a pilot study about acceptance and use of the social network component in our healthcare setting. At Virgen del Rocío University Hospital we have designed and developed the Shared Care Platform (SCP) to provide support in the continuity of care for multimorbidity patients. The SCP has two consecutively developed components: social network component, called Clinical Wall, and Clinical Decision Support (CDS) system. The Clinical Wall contains a record where health professionals are able to debate and define shared decisions. We conducted a pilot study to assess the use and acceptance of the SCP by healthcare professionals through questionnaire based on the theory of the Technology Acceptance Model. In March 2012 we released and deployed the SCP, but only with the social network component. The pilot project lasted 6 months in the hospital and 2 primary care centers. From March to September 2012 we created 16 records in the Clinical Wall, all with a high priority. A total of 10 professionals took part in the exchange of messages: 3 internists and 7 general practitioners generated 33 messages. 12 of the 16 record (75%) were answered by the destination health professionals

  17. Validating Large Scale Networks Using Temporary Local Scale Networks

    USDA-ARS?s Scientific Manuscript database

    The USDA NRCS Soil Climate Analysis Network and NOAA Climate Reference Networks are nationwide meteorological and land surface data networks with soil moisture measurements in the top layers of soil. There is considerable interest in scaling these point measurements to larger scales for validating ...

  18. User Generated Content Consumption and Social Networking in Knowledge-Sharing OSNs

    NASA Astrophysics Data System (ADS)

    Lussier, Jake T.; Raeder, Troy; Chawla, Nitesh V.

    Knowledge-sharing online social networks are becoming increasingly pervasive and popular. While the user-to-user interactions in these networks have received substantial attention, the consumption of user generated content has not been studied extensively. In this work, we use data gathered from digg.com to present novel findings and draw important sociological conclusions regarding the intimate relationship between consumption and social networking. We first demonstrate that individuals' consumption habits influence their friend networks, consistent with the concept of homophily. We then show that one's social network can also influence the consumption of a submission through the activation of an extended friend network. Finally, we investigate the level of reciprocity, or balance, in the network and uncover relationships that are significantly less balanced than expected.

  19. Provider Patient-Sharing Networks and Multiple-Provider Prescribing of Benzodiazepines.

    PubMed

    Ong, Mei-Sing; Olson, Karen L; Cami, Aurel; Liu, Chunfu; Tian, Fang; Selvam, Nandini; Mandl, Kenneth D

    2016-02-01

    Prescription benzodiazepine overdose continues to cause significant morbidity and mortality in the US. Multiple-provider prescribing, due to either fragmented care or "doctor-shopping," contributes to the problem. To elucidate the effect of provider professional relationships on multiple-provider prescribing of benzodiazepines, using social network analytics. A retrospective analysis of commercial healthcare claims spanning the years 2008 through 2011. Provider patient-sharing networks were modelled using social network analytics. Care team cohesion was measured using care density, defined as the ratio between the total number of patients shared by provider pairs within a patient's care team and the total number of provider pairs in the care team. Relationships within provider pairs were further quantified using a range of network metrics, including the number and proportion of patients or collaborators shared. The relationship between patient-sharing network metrics and the likelihood of multiple prescribing of benzodiazepines. Patients between the ages of 18 and 64 years who received two or more benzodiazepine prescriptions from multiple providers, with overlapping coverage of more than 14 days. A total of 5659 patients and 1448 provider pairs were included in our study. Among these, 1028 patients (18.2 %) received multiple prescriptions of benzodiazepines, involving 445 provider pairs (30.7 %). Patients whose providers rarely shared patients had a higher risk of being prescribed overlapping benzodiazepines; the median care density was 8.1 for patients who were prescribed overlapping benzodiazepines and 10.1 for those who were not (p < 0.0001). Provider pairs who shared a greater number of patients and collaborators were less likely to co-prescribe overlapping benzodiazepines. Our findings demonstrate the importance of care team cohesion in addressing multiple-provider prescribing of controlled substances. Furthermore, we illustrate the potential of the

  20. A proxy technique for media content sharing among UPnP-enabled home networks

    NASA Astrophysics Data System (ADS)

    Lee, HyunRyong; Kim, JongWon

    2005-10-01

    We propose a proxy-based scheme for segment-based distributed streaming services among UPnP(universal plug and play)-enabled home networks. We design a "SHARE" module that extends HG (home gateway) with a UPnP-compatible protocol. By relaying SSDP (simple service discovery protocol) messages defined in the UPnP device architecture, the SHARE module provides connectivity that is needed to control other UPnP devices for streaming services among home networks. To provide the streaming services, the SHARE module tries to coordinate the distribution of streaming loads among multiple senders by using many-to-one distributed streaming service. It also tries to minimize the quality degradation of streaming services based on the system and network resource status of each sender by leveraging the UPnP QoS services. That is, pre-allocation of HG resources according to the UPnP QoS services can be used to improve the quality of streaming services. Based on the UPnP components, the SHARE module provides the transparent content sharing to users. Through design-level verifications and partial implementations of the proposed SHARE module, we validate the feasibility of our work.

  1. Analyzing large biological datasets with association networks

    SciTech Connect

    Karpinets, T. V.; Park, B. H.; Uberbacher, E. C.

    2012-05-25

    Due to advances in high throughput biotechnologies biological information is being collected in databases at an amazing rate, requiring novel computational approaches for timely processing of the collected data into new knowledge. In this study we address this problem by developing a new approach for discovering modular structure, relationships and regularities in complex data. These goals are achieved by converting records of biological annotations of an object, like organism, gene, chemical, sequence, into networks (Anets) and rules (Arules) of the associated annotations. Anets are based on similarity of annotation profiles of objects and can be further analyzed and visualized providing a compact birds-eye view of most significant relationships in the collected data and a way of their clustering and classification. Arules are generated by Apriori considering each record of annotations as a transaction and augmenting each annotation item by its type. Arules provide a way to validate relationships discovered by Anets producing comprehensive statistics on frequently associated annotations and specific confident relationships among them. A combination of Anets and Arules represents condensed information on associations among the collected data, helping to discover new knowledge and generate hypothesis. As an example we have applied the approach to analyze bacterial metadata from the Genomes OnLine Database. The analysis allowed us to produce a map of sequenced bacterial and archaeal organisms based on their genomic, metabolic and physiological characteristics with three major clusters of metadata representing bacterial pathogens, environmental isolates, and plant symbionts. A signature profile of clustered annotations of environmental bacteria if compared with pathogens linked the aerobic respiration, the high GC content and the large genome size to diversity of metabolic activities and physiological features of the organisms.

  2. Sharing of Alcohol-Related Content on Social Networking Sites: Frequency, Content, and Correlates.

    PubMed

    Erevik, Eilin K; Torsheim, Torbjørn; Vedaa, Øystein; Andreassen, Cecilie S; Pallesen, Ståle

    2017-05-01

    The present study aimed to explore students' reports of their sharing of alcohol-related content on different social networking sites (i.e., frequency of sharing and connotations of alcohol-related posts), and to identify indicators of such posting. Students at the four largest institutions for higher education in Bergen, Norway, were invited to participate in an Internet-based survey. The sample size was 11,236 (a 39.4% response rate). The survey included questions about disclosure of alcohol-related content on social networking sites, alcohol use (using the Alcohol Use Disorders Identification Test), personality factors (using the Mini-IPIP), and demographic characteristics. Binary logistic regressions were used to analyze indicators of frequent sharing of alcohol-related content depicting positive and negative aspects of alcohol use. A majority of the students had posted alcohol-related content (71.0%), although few reported having done so frequently. Positive aspects of alcohol use (e.g., enjoyment or social community) were most frequently shared. Young, single, and extroverted students with high alcohol consumption were more likely to report frequent sharing of alcohol-related content. Positive attitudes toward posting alcohol-related content and reports of exposure to such content particularly increased the likelihood of one's own posting of alcohol-related content. Positive aspects of alcohol use seem to be emphasized on social networking sites. Sharing of alcohol-related content is associated with heightened alcohol use, which implies that such sites can be relevant for prevention agents. Social influence from social networking sites, such as exposure to others' alcohol-related content, is associated with one's own sharing of similar content.

  3. Sight and sound of actions share a common neural network.

    PubMed

    Giusti, M A; Bozzacchi, C; Pizzamiglio, L; Di Russo, F

    2010-11-01

    The mirror-neuron system (MNS) connects sensory information that describes an action with a motor plan for performing that action. Recently, studies using the repetition-suppression paradigm have shown that strong activation occurs in the left premotor and superior temporal areas in response to action-related, but not non-action-related, stimuli. However, few studies have investigated the mirror system by using event-related potentials (ERPs) and employing more than one sensory modality in the same sample. In the present study, we compared ERPs that occurred in response to visual and auditory action/non-action-related stimuli to search for evidence of overlapping activations for the two modalities. The results confirmed previous studies that investigated auditory MNS and extended these studies by showing that similar activity existed for the visual modality. Furthermore, we confirmed that the responses to action- and non-action-related stimuli were distinct by demonstrating that, in the case of action-related stimuli, activity was restricted mainly to the left hemisphere, whereas for non-action-related stimuli, activity tended to be more bilateral. The time course of ERP brain sources showed a clear sequence of events that subtended the processing of action-related stimuli. This activity seemed to occur in the left temporal lobe and, in agreement with findings from previous studies of the mirror-neuron network, the information involved appeared to be conveyed subsequently to the premotor area. The left temporo-parietal activity observed following a delay might reflect processing associated with stimulus-related motor preparation. © 2010 The Authors. European Journal of Neuroscience © 2010 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

  4. Heuristic approaches for energy-efficient shared restoration in WDM networks

    NASA Astrophysics Data System (ADS)

    Alilou, Shahab

    In recent years, there has been ongoing research on the design of energy-efficient Wavelength Division Multiplexing (WDM) networks. The explosive growth of Internet traffic has led to increased power consumption of network components. Network survivability has also been a relevant research topic, as it plays a crucial role in assuring continuity of service with no disruption, regardless of network component failure. Network survivability mechanisms tend to utilize considerable resources such as spare capacity in order to protect and restore information. This thesis investigates techniques for reducing energy demand and enhancing energy efficiency in the context of network survivability. We propose two novel heuristic energy-efficient shared protection approaches for WDM networks. These approaches intend to save energy by setting on sleep mode devices that are not being used while providing shared backup paths to satisfy network survivability. The first approach exploits properties of a math series in order to assign weight to the network links. It aims at reducing power consumption at the network indirectly by aggregating traffic on a set of nodes and links with high traffic load level. Routing traffic on links and nodes that are already under utilization makes it possible for the links and nodes with no load to be set on sleep mode. The second approach is intended to dynamically route traffic through nodes and links with high traffic load level. Similar to the first approach, this approach computes a pair of paths for every newly arrived demand. It computes these paths for every new demand by comparing the power consumption of nodes and links in the network before the demand arrives with their potential power consumption if they are chosen along the paths of this demand. Simulations of two different networks were used to compare the total network power consumption obtained using the proposed techniques against a standard shared-path restoration scheme. Shared

  5. Network Computing Infrastructure to Share Tools and Data in Global Nuclear Energy Partnership

    NASA Astrophysics Data System (ADS)

    Kim, Guehee; Suzuki, Yoshio; Teshima, Naoya

    CCSE/JAEA (Center for Computational Science and e-Systems/Japan Atomic Energy Agency) integrated a prototype system of a network computing infrastructure for sharing tools and data to support the U.S. and Japan collaboration in GNEP (Global Nuclear Energy Partnership). We focused on three technical issues to apply our information process infrastructure, which are accessibility, security, and usability. In designing the prototype system, we integrated and improved both network and Web technologies. For the accessibility issue, we adopted SSL-VPN (Security Socket Layer-Virtual Private Network) technology for the access beyond firewalls. For the security issue, we developed an authentication gateway based on the PKI (Public Key Infrastructure) authentication mechanism to strengthen the security. Also, we set fine access control policy to shared tools and data and used shared key based encryption method to protect tools and data against leakage to third parties. For the usability issue, we chose Web browsers as user interface and developed Web application to provide functions to support sharing tools and data. By using WebDAV (Web-based Distributed Authoring and Versioning) function, users can manipulate shared tools and data through the Windows-like folder environment. We implemented the prototype system in Grid infrastructure for atomic energy research: AEGIS (Atomic Energy Grid Infrastructure) developed by CCSE/JAEA. The prototype system was applied for the trial use in the first period of GNEP.

  6. Control of Large-Scale Boolean Networks via Network Aggregation.

    PubMed

    Zhao, Yin; Ghosh, Bijoy K; Cheng, Daizhan

    2016-07-01

    A major challenge to solve problems in control of Boolean networks is that the computational cost increases exponentially when the number of nodes in the network increases. We consider the problem of controllability and stabilizability of Boolean control networks, address the increasing cost problem by partitioning the network graph into several subnetworks, and analyze the subnetworks separately. Easily verifiable necessary conditions for controllability and stabilizability are proposed for a general aggregation structure. For acyclic aggregation, we develop a sufficient condition for stabilizability. It dramatically reduces the computational complexity if the number of nodes in each block of the acyclic aggregation is small enough compared with the number of nodes in the entire Boolean network.

  7. Social Networking Privacy Control: Exploring University Variables Related to Young Adults' Sharing of Personally Identifiable Information

    ERIC Educational Resources Information Center

    Zimmerman, Melisa S.

    2014-01-01

    The growth of the Internet, and specifically social networking sites (SNSs) like Facebook, create opportunities for individuals to share private and identifiable information with a closed or open community. Internet crime has been on the rise and research has shown that criminals are using individuals' personal information pulled from social…

  8. More than a Master: Developing, Sharing, and Using Knowledge in School-University Research Networks

    ERIC Educational Resources Information Center

    Cornelissen, Frank; Daly, Alan J.; Liou, Yi-Hwa; van Swet, Jacqueline; Beijaard, Douwe; Bergen, Theo C. M.

    2014-01-01

    Postgraduate master's programs for in-service teachers may be a promising new avenue in developing research partnership networks that link schools and university and enable collaborative development, sharing and use of knowledge of teacher research. This study explores the way these knowledge processes originating from master's students' research…

  9. Situated and Socially Shared Cognition in Practice. Designing a Collaborative Network Learning Experience for Adult Learners.

    ERIC Educational Resources Information Center

    Korhonen, Vesa

    The main purpose of this paper is to draw attention to assumptions that guide the instructional design process when implementing and organizing network-based learning environments in practice. In this case, the situated and socially shared cognition model and participation metaphor create the guiding paradigm for collaborative learning action,…

  10. Resource Sharing or Cost Shifting?--The Unequal Burden of Cooperative Cataloging and ILL in Network.

    ERIC Educational Resources Information Center

    Lowry, Charles B.

    1990-01-01

    Examines the dilemmas of participation in resource sharing library networks and proposes solutions based on shifting inducements toward contribution by remunerating the contributing library for the unit cost of original cataloging. A "contribution pricing" model recently announced by OCLC is also evaluated as a possible solution. (21…

  11. SOBR: A High-Performance Shared Output Buffered Router for Networks-on-Chip

    NASA Astrophysics Data System (ADS)

    Chen, Yancang; Xie, Lunguo

    This paper presents a single-cycle shared output buffered router for Networks-on-Chip. In output ports, each input port always has an output virtual-channel (VC) which can be exchanged by VC swapper. Its critical path is only 24 logic gates, and it reduces 9.4% area overhead compared with the classical router.

  12. Confucius Institutes: Distributed Leadership and Knowledge Sharing in a Worldwide Network

    ERIC Educational Resources Information Center

    Li, Hsi Chang; Mirmirani, Sam; Ilacqua, Joseph A.

    2009-01-01

    Purpose: The purpose of this paper is to focus on Confucius Institutes and assess the applicability of theories of leadership and knowledge sharing to multinational organizations and worldwide networks. Growth of multinational trade and decrease in international tension have facilitated the globalization of both profit-seeking and non-profit…

  13. Confucius Institutes: Distributed Leadership and Knowledge Sharing in a Worldwide Network

    ERIC Educational Resources Information Center

    Li, Hsi Chang; Mirmirani, Sam; Ilacqua, Joseph A.

    2009-01-01

    Purpose: The purpose of this paper is to focus on Confucius Institutes and assess the applicability of theories of leadership and knowledge sharing to multinational organizations and worldwide networks. Growth of multinational trade and decrease in international tension have facilitated the globalization of both profit-seeking and non-profit…

  14. 75 FR 6560 - Financial Crimes Enforcement Network; Expansion of Special Information Sharing Procedures To...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-02-10

    ... 31 CFR Part 103 RIN 1506-AB04 Financial Crimes Enforcement Network; Expansion of Special Information Sharing Procedures To Deter Money Laundering and Terrorist Activity AGENCY: Financial Crimes Enforcement...-related financial crimes are not limited by jurisdiction or geography. Detection and deterrence of...

  15. World Bank's Global Development Learning Network: Sharing Knowledge Electronically between Nations To "Fight Poverty."

    ERIC Educational Resources Information Center

    Lorenzo, George

    2002-01-01

    Describes the Global Development Learning Network (GDLN), a satellite-driven global communication system developed by the World Bank to help developing countries fight poverty and share in a global exchange of information. Explains Distance Learning Centers that are used by private and public organizations and institutions for distance education…

  16. More than a Master: Developing, Sharing, and Using Knowledge in School-University Research Networks

    ERIC Educational Resources Information Center

    Cornelissen, Frank; Daly, Alan J.; Liou, Yi-Hwa; van Swet, Jacqueline; Beijaard, Douwe; Bergen, Theo C. M.

    2014-01-01

    Postgraduate master's programs for in-service teachers may be a promising new avenue in developing research partnership networks that link schools and university and enable collaborative development, sharing and use of knowledge of teacher research. This study explores the way these knowledge processes originating from master's students' research…

  17. World Bank's Global Development Learning Network: Sharing Knowledge Electronically between Nations To "Fight Poverty."

    ERIC Educational Resources Information Center

    Lorenzo, George

    2002-01-01

    Describes the Global Development Learning Network (GDLN), a satellite-driven global communication system developed by the World Bank to help developing countries fight poverty and share in a global exchange of information. Explains Distance Learning Centers that are used by private and public organizations and institutions for distance education…

  18. Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking.

    PubMed

    Wang, Mingxun; Carver, Jeremy J; Phelan, Vanessa V; Sanchez, Laura M; Garg, Neha; Peng, Yao; Nguyen, Don Duy; Watrous, Jeramie; Kapono, Clifford A; Luzzatto-Knaan, Tal; Porto, Carla; Bouslimani, Amina; Melnik, Alexey V; Meehan, Michael J; Liu, Wei-Ting; Crüsemann, Max; Boudreau, Paul D; Esquenazi, Eduardo; Sandoval-Calderón, Mario; Kersten, Roland D; Pace, Laura A; Quinn, Robert A; Duncan, Katherine R; Hsu, Cheng-Chih; Floros, Dimitrios J; Gavilan, Ronnie G; Kleigrewe, Karin; Northen, Trent; Dutton, Rachel J; Parrot, Delphine; Carlson, Erin E; Aigle, Bertrand; Michelsen, Charlotte F; Jelsbak, Lars; Sohlenkamp, Christian; Pevzner, Pavel; Edlund, Anna; McLean, Jeffrey; Piel, Jörn; Murphy, Brian T; Gerwick, Lena; Liaw, Chih-Chuang; Yang, Yu-Liang; Humpf, Hans-Ulrich; Maansson, Maria; Keyzers, Robert A; Sims, Amy C; Johnson, Andrew R; Sidebottom, Ashley M; Sedio, Brian E; Klitgaard, Andreas; Larson, Charles B; P, Cristopher A Boya; Torres-Mendoza, Daniel; Gonzalez, David J; Silva, Denise B; Marques, Lucas M; Demarque, Daniel P; Pociute, Egle; O'Neill, Ellis C; Briand, Enora; Helfrich, Eric J N; Granatosky, Eve A; Glukhov, Evgenia; Ryffel, Florian; Houson, Hailey; Mohimani, Hosein; Kharbush, Jenan J; Zeng, Yi; Vorholt, Julia A; Kurita, Kenji L; Charusanti, Pep; McPhail, Kerry L; Nielsen, Kristian Fog; Vuong, Lisa; Elfeki, Maryam; Traxler, Matthew F; Engene, Niclas; Koyama, Nobuhiro; Vining, Oliver B; Baric, Ralph; Silva, Ricardo R; Mascuch, Samantha J; Tomasi, Sophie; Jenkins, Stefan; Macherla, Venkat; Hoffman, Thomas; Agarwal, Vinayak; Williams, Philip G; Dai, Jingqui; Neupane, Ram; Gurr, Joshua; Rodríguez, Andrés M C; Lamsa, Anne; Zhang, Chen; Dorrestein, Kathleen; Duggan, Brendan M; Almaliti, Jehad; Allard, Pierre-Marie; Phapale, Prasad; Nothias, Louis-Felix; Alexandrov, Theodore; Litaudon, Marc; Wolfender, Jean-Luc; Kyle, Jennifer E; Metz, Thomas O; Peryea, Tyler; Nguyen, Dac-Trung; VanLeer, Danielle; Shinn, Paul; Jadhav, Ajit; Müller, Rolf; Waters, Katrina M; Shi, Wenyuan; Liu, Xueting; Zhang, Lixin; Knight, Rob; Jensen, Paul R; Palsson, Bernhard O; Pogliano, Kit; Linington, Roger G; Gutiérrez, Marcelino; Lopes, Norberto P; Gerwick, William H; Moore, Bradley S; Dorrestein, Pieter C; Bandeira, Nuno

    2016-08-09

    The potential of the diverse chemistries present in natural products (NP) for biotechnology and medicine remains untapped because NP databases are not searchable with raw data and the NP community has no way to share data other than in published papers. Although mass spectrometry (MS) techniques are well-suited to high-throughput characterization of NP, there is a pressing need for an infrastructure to enable sharing and curation of data. We present Global Natural Products Social Molecular Networking (GNPS; http://gnps.ucsd.edu), an open-access knowledge base for community-wide organization and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. In GNPS, crowdsourced curation of freely available community-wide reference MS libraries will underpin improved annotations. Data-driven social-networking should facilitate identification of spectra and foster collaborations. We also introduce the concept of 'living data' through continuous reanalysis of deposited data.

  19. Beyond Networking: How Large-Scale Change Really Happens

    ERIC Educational Resources Information Center

    Wheatley, Margaret; Frieze, Deborah

    2007-01-01

    Despite the claims of a popular slogan, the world does not change one person at a time. It changes as networks of relationships form among people who share a common cause and vision of what is possible. This is good news for those who want to change public education. Making connections however is not the whole story. This article describes how a…

  20. Efficient File Sharing by Multicast - P2P Protocol Using Network Coding and Rank Based Peer Selection

    NASA Technical Reports Server (NTRS)

    Stoenescu, Tudor M.; Woo, Simon S.

    2009-01-01

    In this work, we consider information dissemination and sharing in a distributed peer-to-peer (P2P highly dynamic communication network. In particular, we explore a network coding technique for transmission and a rank based peer selection method for network formation. The combined approach has been shown to improve information sharing and delivery to all users when considering the challenges imposed by the space network environments.

  1. Efficient File Sharing by Multicast - P2P Protocol Using Network Coding and Rank Based Peer Selection

    NASA Technical Reports Server (NTRS)

    Stoenescu, Tudor M.; Woo, Simon S.

    2009-01-01

    In this work, we consider information dissemination and sharing in a distributed peer-to-peer (P2P highly dynamic communication network. In particular, we explore a network coding technique for transmission and a rank based peer selection method for network formation. The combined approach has been shown to improve information sharing and delivery to all users when considering the challenges imposed by the space network environments.

  2. Molecular analysis reveals high compartmentalization in aphid-primary parasitoid networks and low parasitoid sharing between crop and noncrop habitats.

    PubMed

    Derocles, Stephane A P; Le Ralec, Anne; Besson, Mathilde M; Maret, Marion; Walton, Alan; Evans, Darren M; Plantegenest, Manuel

    2014-08-01

    The ecosystem service of insect pest regulation by natural enemies, such as primary parasitoids, may be enhanced by the presence of uncultivated, semi-natural habitats within agro-ecosystems, although quantifying such host-parasitoid interactions is difficult. Here, we use rRNA 16S gene sequencing to assess both the level of parasitism by Aphidiinae primary parasitoids and parasitoid identity on a large sample of aphids collected in cultivated and uncultivated agricultural habitats in Western France. We used these data to construct ecological networks to assess the level of compartmentalization between aphid and parasitoid food webs of cultivated and uncultivated habitats. We evaluated the extent to which uncultivated margins provided a resource for parasitoids shared between pest and nonpest aphids. We compared the observed quantitative ecological network described by our molecular approach to an empirical qualitative network based on aphid-parasitoid interactions from traditional rearing data found in the literature. We found that the molecular network was highly compartmentalized and that parasitoid sharing is relatively rare between aphids, especially between crop and noncrop compartments. Moreover, the few cases of putative shared generalist parasitoids were questionable and could be due to the lack of discrimination of cryptic species or from intraspecific host specialization. Our results suggest that apparent competition mediated by Aphidiinae parasitoids is probably rare in agricultural areas and that the contribution of field margins as a source of these biocontrol agents is much more limited than expected. Further large-scale (spatial and temporal) studies on other crops and noncrop habitats are needed to confirm this. © 2014 John Wiley & Sons Ltd.

  3. A comparative analysis of the statistical properties of large mobile phone calling networks.

    PubMed

    Li, Ming-Xia; Jiang, Zhi-Qiang; Xie, Wen-Jie; Miccichè, Salvatore; Tumminello, Michele; Zhou, Wei-Xing; Mantegna, Rosario N

    2014-05-30

    Mobile phone calling is one of the most widely used communication methods in modern society. The records of calls among mobile phone users provide us a valuable proxy for the understanding of human communication patterns embedded in social networks. Mobile phone users call each other forming a directed calling network. If only reciprocal calls are considered, we obtain an undirected mutual calling network. The preferential communication behavior between two connected users can be statistically tested and it results in two Bonferroni networks with statistically validated edges. We perform a comparative analysis of the statistical properties of these four networks, which are constructed from the calling records of more than nine million individuals in Shanghai over a period of 110 days. We find that these networks share many common structural properties and also exhibit idiosyncratic features when compared with previously studied large mobile calling networks. The empirical findings provide us an intriguing picture of a representative large social network that might shed new lights on the modelling of large social networks.

  4. A comparative analysis of the statistical properties of large mobile phone calling networks

    PubMed Central

    Li, Ming-Xia; Jiang, Zhi-Qiang; Xie, Wen-Jie; Miccichè, Salvatore; Tumminello, Michele; Zhou, Wei-Xing; Mantegna, Rosario N.

    2014-01-01

    Mobile phone calling is one of the most widely used communication methods in modern society. The records of calls among mobile phone users provide us a valuable proxy for the understanding of human communication patterns embedded in social networks. Mobile phone users call each other forming a directed calling network. If only reciprocal calls are considered, we obtain an undirected mutual calling network. The preferential communication behavior between two connected users can be statistically tested and it results in two Bonferroni networks with statistically validated edges. We perform a comparative analysis of the statistical properties of these four networks, which are constructed from the calling records of more than nine million individuals in Shanghai over a period of 110 days. We find that these networks share many common structural properties and also exhibit idiosyncratic features when compared with previously studied large mobile calling networks. The empirical findings provide us an intriguing picture of a representative large social network that might shed new lights on the modelling of large social networks. PMID:24875444

  5. A comparative analysis of the statistical properties of large mobile phone calling networks

    NASA Astrophysics Data System (ADS)

    Li, Ming-Xia; Jiang, Zhi-Qiang; Xie, Wen-Jie; Miccichè, Salvatore; Tumminello, Michele; Zhou, Wei-Xing; Mantegna, Rosario N.

    2014-05-01

    Mobile phone calling is one of the most widely used communication methods in modern society. The records of calls among mobile phone users provide us a valuable proxy for the understanding of human communication patterns embedded in social networks. Mobile phone users call each other forming a directed calling network. If only reciprocal calls are considered, we obtain an undirected mutual calling network. The preferential communication behavior between two connected users can be statistically tested and it results in two Bonferroni networks with statistically validated edges. We perform a comparative analysis of the statistical properties of these four networks, which are constructed from the calling records of more than nine million individuals in Shanghai over a period of 110 days. We find that these networks share many common structural properties and also exhibit idiosyncratic features when compared with previously studied large mobile calling networks. The empirical findings provide us an intriguing picture of a representative large social network that might shed new lights on the modelling of large social networks.

  6. Food-Sharing Networks in Lamalera, Indonesia: Reciprocity, Kinship, and Distance.

    PubMed

    Nolin, David A

    2010-10-01

    Exponential random graph modeling (ERGM) is used here to test hypotheses derived from human behavioral ecology about the adaptive nature of human food sharing. Respondents in all (n=317) households in the fishing and sea-hunting village of Lamalera, Indonesia were asked to name those households to whom they had more frequently given (and from whom they had more frequently received) food during the preceding sea-hunting season. The responses were used to construct a social network of between-household food-sharing relationships in the village. The results show that kinship, proximity, and reciprocal sharing all strongly increase the probability of giving food to a household. The effects of kinship and distance are relatively independent of each other, while reciprocity is more common among residentially and genealogically close households. The results show support for reciprocal altruism as a motivation for food sharing while kinship and distance appear to be important partner-choice criteria.

  7. Food-Sharing Networks in Lamalera, Indonesia: Reciprocity, Kinship, and Distance

    PubMed Central

    Nolin, David A.

    2010-01-01

    Exponential random graph modeling (ERGM) is used here to test hypotheses derived from human behavioral ecology about the adaptive nature of human food sharing. Respondents in all (n=317) households in the fishing and sea-hunting village of Lamalera, Indonesia were asked to name those households to whom they had more frequently given (and from whom they had more frequently received) food during the preceding sea-hunting season. The responses were used to construct a social network of between-household food-sharing relationships in the village. The results show that kinship, proximity, and reciprocal sharing all strongly increase the probability of giving food to a household. The effects of kinship and distance are relatively independent of each other, while reciprocity is more common among residentially and genealogically close households. The results show support for reciprocal altruism as a motivation for food sharing while kinship and distance appear to be important partner-choice criteria. PMID:21218145

  8. SNAVI: Desktop application for analysis and visualization of large-scale signaling networks

    PubMed Central

    Ma'ayan, Avi; Jenkins, Sherry L; Webb, Ryan L; Berger, Seth I; Purushothaman, Sudarshan P; Abul-Husn, Noura S; Posner, Jeremy M; Flores, Tony; Iyengar, Ravi

    2009-01-01

    Background Studies of cellular signaling indicate that signal transduction pathways combine to form large networks of interactions. Viewing protein-protein and ligand-protein interactions as graphs (networks), where biomolecules are represented as nodes and their interactions are represented as links, is a promising approach for integrating experimental results from different sources to achieve a systematic understanding of the molecular mechanisms driving cell phenotype. The emergence of large-scale signaling networks provides an opportunity for topological statistical analysis while visualization of such networks represents a challenge. Results SNAVI is Windows-based desktop application that implements standard network analysis methods to compute the clustering, connectivity distribution, and detection of network motifs, as well as provides means to visualize networks and network motifs. SNAVI is capable of generating linked web pages from network datasets loaded in text format. SNAVI can also create networks from lists of gene or protein names. Conclusion SNAVI is a useful tool for analyzing, visualizing and sharing cell signaling data. SNAVI is open source free software. The installation may be downloaded from: . The source code can be accessed from: PMID:19154595

  9. Comparison of large networks with sub-sampling strategies

    NASA Astrophysics Data System (ADS)

    Ali, Waqar; Wegner, Anatol E.; Gaunt, Robert E.; Deane, Charlotte M.; Reinert, Gesine

    2016-07-01

    Networks are routinely used to represent large data sets, making the comparison of networks a tantalizing research question in many areas. Techniques for such analysis vary from simply comparing network summary statistics to sophisticated but computationally expensive alignment-based approaches. Most existing methods either do not generalize well to different types of networks or do not provide a quantitative similarity score between networks. In contrast, alignment-free topology based network similarity scores empower us to analyse large sets of networks containing different types and sizes of data. Netdis is such a score that defines network similarity through the counts of small sub-graphs in the local neighbourhood of all nodes. Here, we introduce a sub-sampling procedure based on neighbourhoods which links naturally with the framework of network comparisons through local neighbourhood comparisons. Our theoretical arguments justify basing the Netdis statistic on a sample of similar-sized neighbourhoods. Our tests on empirical and synthetic datasets indicate that often only 10% of the neighbourhoods of a network suffice for optimal performance, leading to a drastic reduction in computational requirements. The sampling procedure is applicable even when only a small sample of the network is known, and thus provides a novel tool for network comparison of very large and potentially incomplete datasets.

  10. Comparison of large networks with sub-sampling strategies

    PubMed Central

    Ali, Waqar; Wegner, Anatol E.; Gaunt, Robert E.; Deane, Charlotte M.; Reinert, Gesine

    2016-01-01

    Networks are routinely used to represent large data sets, making the comparison of networks a tantalizing research question in many areas. Techniques for such analysis vary from simply comparing network summary statistics to sophisticated but computationally expensive alignment-based approaches. Most existing methods either do not generalize well to different types of networks or do not provide a quantitative similarity score between networks. In contrast, alignment-free topology based network similarity scores empower us to analyse large sets of networks containing different types and sizes of data. Netdis is such a score that defines network similarity through the counts of small sub-graphs in the local neighbourhood of all nodes. Here, we introduce a sub-sampling procedure based on neighbourhoods which links naturally with the framework of network comparisons through local neighbourhood comparisons. Our theoretical arguments justify basing the Netdis statistic on a sample of similar-sized neighbourhoods. Our tests on empirical and synthetic datasets indicate that often only 10% of the neighbourhoods of a network suffice for optimal performance, leading to a drastic reduction in computational requirements. The sampling procedure is applicable even when only a small sample of the network is known, and thus provides a novel tool for network comparison of very large and potentially incomplete datasets. PMID:27380992

  11. Shared control on lunar spacecraft teleoperation rendezvous operations with large time delay

    NASA Astrophysics Data System (ADS)

    Ya-kun, Zhang; Hai-yang, Li; Rui-xue, Huang; Jiang-hui, Liu

    2017-08-01

    Teleoperation could be used in space on-orbit serving missions, such as object deorbits, spacecraft approaches, and automatic rendezvous and docking back-up systems. Teleoperation rendezvous and docking in lunar orbit may encounter bottlenecks for the inherent time delay in the communication link and the limited measurement accuracy of sensors. Moreover, human intervention is unsuitable in view of the partial communication coverage problem. To solve these problems, a shared control strategy for teleoperation rendezvous and docking is detailed. The control authority in lunar orbital maneuvers that involves two spacecraft as rendezvous and docking in the final phase was discussed in this paper. The predictive display model based on the relative dynamic equations is established to overcome the influence of the large time delay in communication link. We discuss and attempt to prove via consistent, ground-based simulations the relative merits of fully autonomous control mode (i.e., onboard computer-based), fully manual control (i.e., human-driven at the ground station) and shared control mode. The simulation experiments were conducted on the nine-degrees-of-freedom teleoperation rendezvous and docking simulation platform. Simulation results indicated that the shared control methods can overcome the influence of time delay effects. In addition, the docking success probability of shared control method was enhanced compared with automatic and manual modes.

  12. Visualization techniques and tools for large geo-physical networks

    NASA Astrophysics Data System (ADS)

    Nocke, Thomas; Buschmann, Stefan; Donges, Jonathan F.; Marwan, Norbert

    2016-04-01

    Network analysis is an important approach in studying complex phenomena within geophysical observation and simulation data. This field produces increasing numbers of large geo-referenced networks to be analyzed. Particular focus lies on the network analysis of the complex statistical interrelationship structure within climatological fields. The typical procedure for such network analyzes is the extraction of network measures in combination with static standard visualization methods. To analyze the visualization challenges within this field, we performed a questionnaire with climate and complex system scientists, and identified a strong requirement for solutions visualizing large and very large geo-referenced networks by providing alternative mappings for static plots and allowing for interactive visualization for networks with 100.000 or even millions of edges. In addition, the questionnaire revealed, that existing interactive visualization methods and tools for geo-referenced network exploration are often either not known to the analyst or their potential is not fully exploited. Within this presentation, we illustrate how interactive visual analytics methods in combination with geo-visualisation can be tailored for visual large climate network investigation (see as well Nocke et al. 2015). Therefore, we present a survey of requirements of network analysts and the related challenges and, as an overview for the interested practitioner, we review the state-of-the-art in climate network visualization techniques and tools, underpinned with concrete examples from climate network research and innovative solutions (e.g. alternative projections, 3D layered networks) implemented within the network visualization system GTX. References: Nocke, T., S. Buschmann, J. F. Donges, N. Marwan, H.-J. Schulz, and C. Tominski: Review: Visual analytics of climate networks, Nonlinear Processes in Geophysics, 22, 545-570, doi:10.5194/npg-22-545-2015, 2015

  13. Tractable Analysis for Large Social Networks

    ERIC Educational Resources Information Center

    Zhang, Bin

    2012-01-01

    Social scientists usually are more interested in consumers' dichotomous choice, such as purchase a product or not, adopt a technology or not, etc. However, up to date, there is nearly no model can help us solve the problem of multi-network effects comparison with a dichotomous dependent variable. Furthermore, the study of multi-network…

  14. Tractable Analysis for Large Social Networks

    ERIC Educational Resources Information Center

    Zhang, Bin

    2012-01-01

    Social scientists usually are more interested in consumers' dichotomous choice, such as purchase a product or not, adopt a technology or not, etc. However, up to date, there is nearly no model can help us solve the problem of multi-network effects comparison with a dichotomous dependent variable. Furthermore, the study of multi-network…

  15. Honeycomb: Visual Analysis of Large Scale Social Networks

    NASA Astrophysics Data System (ADS)

    van Ham, Frank; Schulz, Hans-Jörg; Dimicco, Joan M.

    The rise in the use of social network sites allows us to collect large amounts of user reported data on social structures and analysis of this data could provide useful insights for many of the social sciences. This analysis is typically the domain of Social Network Analysis, and visualization of these structures often proves invaluable in understanding them. However, currently available visual analysis tools are not very well suited to handle the massive scale of this network data, and often resolve to displaying small ego networks or heavily abstracted networks. In this paper, we present Honeycomb, a visualization tool that is able to deal with much larger scale data (with millions of connections), which we illustrate by using a large scale corporate social networking site as an example. Additionally, we introduce a new probability based network metric to guide users to potentially interesting or anomalous patterns and discuss lessons learned during design and implementation.

  16. A novel survivable traffic grooming algorithm with inter-layer sharing in IP/MPLS-over-WDM mesh networks

    NASA Astrophysics Data System (ADS)

    Gong, Dayue; Zhang, Xiaoning; Yu, Hongfang; Ling, Ximo; Liao, Dan; Luo, Hongbin

    2009-11-01

    We propose a Mixed Sharing Auxiliary Graph (MSAG) for dynamic traffic grooming in heterogeneous WDM mesh networks. Based on MSAG model, a novel heuristic named BLSW-ILMS (Backup LSP Shared Working Lightpath with Inter-layer Mixed Sharing) is proposed. Simulation results show that the proposed algorithm can efficiently decrease the blocking probability.

  17. Cooperation stimulation strategies for peer-to-peer wireless live video-sharing social networks.

    PubMed

    Lin, W Sabrina; Zhao, H Vicky; Liu, K J Ray

    2010-07-01

    Human behavior analysis in video sharing social networks is an emerging research area, which analyzes the behavior of users who share multimedia content and investigates the impact of human dynamics on video sharing systems. Users watching live streaming in the same wireless network share the same limited bandwidth of backbone connection to the Internet, thus, they might want to cooperate with each other to obtain better video quality. These users form a wireless live-streaming social network. Every user wishes to watch video with high quality while paying as little as possible cost to help others. This paper focuses on providing incentives for user cooperation. We propose a game-theoretic framework to model user behavior and to analyze the optimal strategies for user cooperation simulation in wireless live streaming. We first analyze the Pareto optimality and the time-sensitive bargaining equilibrium of the two-person game. We then extend the solution to the multiuser scenario. We also consider potential selfish users' cheating behavior and malicious users' attacking behavior and analyze the performance of the proposed strategies with the existence of cheating users and malicious attackers. Both our analytical and simulation results show that the proposed strategies can effectively stimulate user cooperation, achieve cheat free and attack resistance, and help provide reliable services for wireless live streaming applications.

  18. Does motor imagery share neural networks with executed movement: a multivariate fMRI analysis

    PubMed Central

    Sharma, Nikhil; Baron, Jean-Claude

    2013-01-01

    Introduction: Motor imagery (MI) is the mental rehearsal of a motor first person action-representation. There is interest in using MI to access the motor network after stroke. Conventional fMRI modeling has shown that MI and executed movement (EM) activate similar cortical areas but it remains unknown whether they share cortical networks. Proving this is central to using MI to access the motor network and as a form of motor training. Here we use multivariate analysis (tensor independent component analysis-TICA) to map the array of neural networks involved during MI and EM. Methods: Fifteen right-handed healthy volunteers (mean-age 28.4 years) were recruited and screened for their ability to carry out MI (Chaotic MI Assessment). fMRI consisted of an auditory-paced (1 Hz) right hand finger-thumb opposition sequence (2,3,4,5; 2…) with two separate runs acquired (MI & rest and EM & rest: block design). No distinction was made between MI and EM until the final stage of processing. This allowed TICA to identify independent-components (IC) that are common or distinct to both tasks with no prior assumptions. Results: TICA defined 52 ICs. Non-significant ICs and those representing artifact were excluded. Components in which the subject scores were significantly different to zero (for either EM or MI) were included. Seven IC remained. There were IC's shared between EM and MI involving the contralateral BA4, PMd, parietal areas and SMA. IC's exclusive to EM involved the contralateral BA4, S1 and ipsilateral cerebellum whereas the IC related exclusively to MI involved ipsilateral BA4 and PMd. Conclusion: In addition to networks specific to each task indicating a degree of independence, we formally demonstrate here for the first time that MI and EM share cortical networks. This significantly strengthens the rationale for using MI to access the motor networks, but the results also highlight important differences. PMID:24062666

  19. Experimental analysis of large belief networks for medical diagnosis.

    PubMed Central

    Pradhan, M.; Provan, G.; Henrion, M.

    1994-01-01

    We present an experimental analysis of two parameters that are important in knowledge engineering for large belief networks. We conducted the experiments on a network derived from the Internist-1 medical knowledge base. In this network, a generalization of the noisy-OR gate is used to model causal independence for the multivalued variables, and leak probabilities are used to represent the nonspecified causes of intermediate states and findings. We study two network parameters, (1) the parameter governing the assignment of probability values to the network, and (2) the parameter denoting whether the network nodes represent variables with two or more than two values. The experimental results demonstrate that the binary simplification computes diagnoses with similar accuracy to the full multivalued network. We discuss the implications of these parameters, as well other network parameters, for knowledge engineering for medical applications. PMID:7950030

  20. Finding shared decisions in stakeholder networks: An agent-based approach

    NASA Astrophysics Data System (ADS)

    Le Pira, Michela; Inturri, Giuseppe; Ignaccolo, Matteo; Pluchino, Alessandro; Rapisarda, Andrea

    2017-01-01

    We address the problem of a participatory decision-making process where a shared priority list of alternatives has to be obtained while avoiding inconsistent decisions. An agent-based model (ABM) is proposed to mimic this process in different social networks of stakeholders who interact according to an opinion dynamics model. Simulations' results show the efficacy of interaction in finding a transitive and, above all, shared decision. These findings are in agreement with real participation experiences regarding transport planning decisions and can give useful suggestions on how to plan an effective participation process for sustainable policy-making based on opinion consensus.

  1. Cross-species transcriptional network analysis defines shared inflammatory responses in murine and human lupus nephritis.

    PubMed

    Berthier, Celine C; Bethunaickan, Ramalingam; Gonzalez-Rivera, Tania; Nair, Viji; Ramanujam, Meera; Zhang, Weijia; Bottinger, Erwin P; Segerer, Stephan; Lindenmeyer, Maja; Cohen, Clemens D; Davidson, Anne; Kretzler, Matthias

    2012-07-15

    Lupus nephritis (LN) is a serious manifestation of systemic lupus erythematosus. Therapeutic studies in mouse LN models do not always predict outcomes of human therapeutic trials, raising concerns about the human relevance of these preclinical models. In this study, we used an unbiased transcriptional network approach to define, in molecular terms, similarities and differences among three lupus models and human LN. Genome-wide gene-expression networks were generated using natural language processing and automated promoter analysis and compared across species via suboptimal graph matching. The three murine models and human LN share both common and unique features. The 20 commonly shared network nodes reflect the key pathologic processes of immune cell infiltration/activation, endothelial cell activation/injury, and tissue remodeling/fibrosis, with macrophage/dendritic cell activation as a dominant cross-species shared transcriptional pathway. The unique nodes reflect differences in numbers and types of infiltrating cells and degree of remodeling among the three mouse strains. To define mononuclear phagocyte-derived pathways in human LN, gene sets activated in isolated NZB/W renal mononuclear cells were compared with human LN kidney profiles. A tissue compartment-specific macrophage-activation pattern was seen, with NF-κB1 and PPARγ as major regulatory nodes in the tubulointerstitial and glomerular networks, respectively. Our study defines which pathologic processes in murine models of LN recapitulate the key transcriptional processes active in human LN and suggests that there are functional differences between mononuclear phagocytes infiltrating different renal microenvironments.

  2. Incentive Mechanism for P2P Content Sharing over Heterogenous Access Networks

    NASA Astrophysics Data System (ADS)

    Sato, Kenichiro; Hashimoto, Ryo; Yoshino, Makoto; Shinkuma, Ryoichi; Takahashi, Tatsuro

    In peer-to-peer (P2P) content sharing, users can share their content by contributing their own resources to one another. However, since there is no incentive for contributing contents or resources to others, users may attempt to obtain content without any contribution. To motivate users to contribute their resources to the service, incentive-rewarding mechanisms have been proposed. On the other hand, emerging wireless technologies, such as IEEE 802.11 wireless local area networks, beyond third generation (B3G) cellular networks and mobile WiMAX, provide high-speed Internet access for wireless users. Using these high-speed wireless access, wireless users can use P2P services and share their content with other wireless users and with fixed users. However, this diversification of access networks makes it difficult to appropriately assign rewards to each user according to their contributions. This is because the cost necessary for contribution is different in different access networks. In this paper, we propose a novel incentive-rewarding mechanism called EMOTIVER that can assign rewards to users appropriately. The proposed mechanism uses an external evaluator and interactive learning agents. We also investigate a way of appropriately controlling rewards based on the system service's quality and managing policy.

  3. LARGE-SCALE TOPOLOGICAL PROPERTIES OF MOLECULAR NETWORKS.

    SciTech Connect

    MASLOV,S.SNEPPEN,K.

    2003-11-17

    Bio-molecular networks lack the top-down design. Instead, selective forces of biological evolution shape them from raw material provided by random events such as gene duplications and single gene mutations. As a result individual connections in these networks are characterized by a large degree of randomness. One may wonder which connectivity patterns are indeed random, while which arose due to the network growth, evolution, and/or its fundamental design principles and limitations? Here we introduce a general method allowing one to construct a random null-model version of a given network while preserving the desired set of its low-level topological features, such as, e.g., the number of neighbors of individual nodes, the average level of modularity, preferential connections between particular groups of nodes, etc. Such a null-model network can then be used to detect and quantify the non-random topological patterns present in large networks. In particular, we measured correlations between degrees of interacting nodes in protein interaction and regulatory networks in yeast. It was found that in both these networks, links between highly connected proteins are systematically suppressed. This effect decreases the likelihood of cross-talk between different functional modules of the cell, and increases the overall robustness of a network by localizing effects of deleterious perturbations. It also teaches us about the overall computational architecture of such networks and points at the origin of large differences in the number of neighbors of individual nodes.

  4. Learning from examples in large neural networks

    NASA Astrophysics Data System (ADS)

    Sompolinsky, H.; Tishby, N.; Seung, H. S.

    1990-09-01

    A statistical-mechanical theory of learning from examples in layered networks at finite temperature is studied. When the training error is a smooth function of continuously varying weights, the generalization error falls off asymptotically as the inverse number of examples. By analytical and numerical studies of single-layer perceptrons, we show that when the weights are discrete, the generalization error can exhibit a discontinuous transition to perfect generalization. For intermediate sizes of the example set, the state of perfect generalization coexists with a metastable spin-glass state.

  5. Advances in Exponential Random Graph (p*) Models Applied to a Large Social Network.

    PubMed

    Goodreau, Steven M

    2007-05-01

    Recent advances in statistical network analysis based on the family of exponential random graph (ERG) models have greatly improved our ability to conduct inference on dependence in large social networks (Snijders 2002, Pattison and Robins 2002, Handcock 2002, Handcock 2003, Snijders et al. 2006, Hunter et al. 2005, Goodreau et al. 2005, previous papers this issue). This paper applies advances in both model parameterizations and computational algorithms to an examination of the structure observed in an adolescent friendship network of 1,681 actors from the National Longitudinal Study of Adolescent Health (AddHealth). ERG models of social network structure are fit using the R package statnet, and their adequacy assessed through comparison of model predictions with the observed data for higher-order network statistics.For this friendship network, the commonly used model of Markov dependence leads to the problems of degeneracy discussed by Handcock (2002, 2003). On the other hand, model parameterizations introduced by Snijders et al (2006) and Hunter and Handcock (2006) avoid degeneracy and provide reasonable fit to the data. Degree-only models did a poor job of capturing observed network structure; those that did best included terms both for heterogeneous mixing on exogenous attributes (grade and self-reported race) as well as endogenous clustering. Networks simulated from this model were largely consistent with the observed network on multiple higher-order network statistics, including the number of triangles, the size of the largest component, the overall reachability, the distribution of geodesic distances, the degree distribution, and the shared partner distribution. The ability to fit such models to large datasets and to make inference about the underling processes generating the network represents a major advance in the field of statistical network analysis.

  6. A group based key sharing and management algorithm for vehicular ad hoc networks.

    PubMed

    Khan, Zeeshan Shafi; Moharram, Mohammed Morsi; Alaraj, Abdullah; Azam, Farzana

    2014-01-01

    Vehicular ad hoc networks (VANETs) are one special type of ad hoc networks that involves vehicles on roads. Typically like ad hoc networks, broadcast approach is used for data dissemination. Blind broadcast to each and every node results in exchange of useless and irrelevant messages and hence creates an overhead. Unicasting is not preferred in ad-hoc networks due to the dynamic topology and the resource requirements as compared to broadcasting. Simple broadcasting techniques create several problems on privacy, disturbance, and resource utilization. In this paper, we propose media mixing algorithm to decide what information should be provided to each user and how to provide such information. Results obtained through simulation show that fewer number of keys are needed to share compared to simple broadcasting. Privacy is also enhanced through this approach.

  7. A Group Based Key Sharing and Management Algorithm for Vehicular Ad Hoc Networks

    PubMed Central

    Moharram, Mohammed Morsi; Azam, Farzana

    2014-01-01

    Vehicular ad hoc networks (VANETs) are one special type of ad hoc networks that involves vehicles on roads. Typically like ad hoc networks, broadcast approach is used for data dissemination. Blind broadcast to each and every node results in exchange of useless and irrelevant messages and hence creates an overhead. Unicasting is not preferred in ad-hoc networks due to the dynamic topology and the resource requirements as compared to broadcasting. Simple broadcasting techniques create several problems on privacy, disturbance, and resource utilization. In this paper, we propose media mixing algorithm to decide what information should be provided to each user and how to provide such information. Results obtained through simulation show that fewer number of keys are needed to share compared to simple broadcasting. Privacy is also enhanced through this approach. PMID:24587749

  8. Country food sharing networks, household structure, and implications for understanding food insecurity in Arctic Canada.

    PubMed

    Collings, Peter; Marten, Meredith G; Pearce, Tristan; Young, Alyson G

    2016-01-01

    We examine the cultural context of food insecurity among Inuit in Ulukhaktok, Northwest Territories, Canada. An analysis of the social network of country food exchanges among 122 households in the settlement reveals that a household's betweenness centrality-a measure of brokerage-in the country food network is predicted by the age of the household. The households of married couples were better positioned within the sharing network than were the households of single females or single males. Households with an active hunter or elder were also better positioned in the network. The households of single men and women appear to experience limited access to country food, a considerable problem given the increasing number of single-adult households over time. We conclude that the differences between how single women and single men experience constrained access to country foods may partially account for previous findings that single women in arctic settlements appear to be at particular risk for food insecurity.

  9. Multisector Health Policy Networks in 15 Large US Cities

    PubMed Central

    Leider, J. P.; Carothers, Bobbi J.; Castrucci, Brian C.; Hearne, Shelley

    2016-01-01

    Context: Local health departments (LHDs) have historically not prioritized policy development, although it is one of the 3 core areas they address. One strategy that may influence policy in LHD jurisdictions is the formation of partnerships across sectors to work together on local public health policy. Design: We used a network approach to examine LHD local health policy partnerships across 15 large cities from the Big Cities Health Coalition. Setting/Participants: We surveyed the health departments and their partners about their working relationships in 5 policy areas: core local funding, tobacco control, obesity and chronic disease, violence and injury prevention, and infant mortality. Outcome Measures: Drawing on prior literature linking network structures with performance, we examined network density, transitivity, centralization and centrality, member diversity, and assortativity of ties. Results: Networks included an average of 21.8 organizations. Nonprofits and government agencies made up the largest proportions of the networks, with 28.8% and 21.7% of network members, whereas for-profits and foundations made up the smallest proportions in all of the networks, with just 1.2% and 2.4% on average. Mean values of density, transitivity, diversity, assortativity, centralization, and centrality showed similarity across policy areas and most LHDs. The tobacco control and obesity/chronic disease networks were densest and most diverse, whereas the infant mortality policy networks were the most centralized and had the highest assortativity. Core local funding policy networks had lower scores than other policy area networks by most network measures. Conclusion: Urban LHDs partner with organizations from diverse sectors to conduct local public health policy work. Network structures are similar across policy areas jurisdictions. Obesity and chronic disease, tobacco control, and infant mortality networks had structures consistent with higher performing networks, whereas

  10. On-demand Overlay Networks for Large Scientific Data Transfers

    SciTech Connect

    Ramakrishnan, Lavanya; Guok, Chin; Jackson, Keith; Kissel, Ezra; Swany, D. Martin; Agarwal, Deborah

    2009-10-12

    Large scale scientific data transfers are central to scientific processes. Data from large experimental facilities have to be moved to local institutions for analysis or often data needs to be moved between local clusters and large supercomputing centers. In this paper, we propose and evaluate a network overlay architecture to enable highthroughput, on-demand, coordinated data transfers over wide-area networks. Our work leverages Phoebus and On-demand Secure Circuits and AdvanceReservation System (OSCARS) to provide high performance wide-area network connections. OSCARS enables dynamic provisioning of network paths with guaranteed bandwidth and Phoebus enables the coordination and effective utilization of the OSCARS network paths. Our evaluation shows that this approach leads to improved end-to-end data transfer throughput with minimal overheads. The achievedthroughput using our overlay was limited only by the ability of the end hosts to sink the data.

  11. Sharing Data In The Global Alzheimer’s Association Interactive Network

    PubMed Central

    Neu, Scott C.; Crawford, Karen L.; Toga, Arthur W.

    2015-01-01

    The Global Alzheimer’s Association Interactive Network (GAAIN) aims to be a shared network of research data, analysis tools, and computational resources for studying the causes of Alzheimer’s disease. Central to its design are policies that honor data ownership, prevent unauthorized data distribution, and respect the boundaries of contributing institutions. The results of data queries are displayed in graphs and summary tables, which protects data ownership while providing sufficient information to view trends in aggregated data and discover new data sets. In this article we report on our progress in sharing data through the integration of geographically-separated and independently-operated Alzheimer’s disease research studies around the world. PMID:26049147

  12. Towards Online Multiresolution Community Detection in Large-Scale Networks

    PubMed Central

    Huang, Jianbin; Sun, Heli; Liu, Yaguang; Song, Qinbao; Weninger, Tim

    2011-01-01

    The investigation of community structure in networks has aroused great interest in multiple disciplines. One of the challenges is to find local communities from a starting vertex in a network without global information about the entire network. Many existing methods tend to be accurate depending on a priori assumptions of network properties and predefined parameters. In this paper, we introduce a new quality function of local community and present a fast local expansion algorithm for uncovering communities in large-scale networks. The proposed algorithm can detect multiresolution community from a source vertex or communities covering the whole network. Experimental results show that the proposed algorithm is efficient and well-behaved in both real-world and synthetic networks. PMID:21887325

  13. Joint accurate time and stable frequency distribution infrastructure sharing fiber footprint with research network

    NASA Astrophysics Data System (ADS)

    Vojtech, Josef; Slapak, Martin; Skoda, Pavel; Radil, Jan; Havlis, Ondrej; Altmann, Michal; Munster, Petr; Smotlacha, Vladimir; Kundrat, Jan; Velc, Radek; Altmannova, Lada; Hula, Miloslav

    2016-09-01

    In this paper, we present infrastructure for accurate time and stable frequency distribution. It is based on sharing of fibers of research and educational network carrying data traffic. Accurate time and stable frequency transmission uses mainly created dark channels amplified by special bidirectional amplifiers with the same propagation path for both directions. Paper also targets challenges joined with bidirectional transmission, which represents directional non-reciprocities and interaction with parallel data transmissions.

  14. Sharing Data for Public Health Research by Members of an International Online Diabetes Social Network

    PubMed Central

    Weitzman, Elissa R.; Adida, Ben; Kelemen, Skyler; Mandl, Kenneth D.

    2011-01-01

    Background Surveillance and response to diabetes may be accelerated through engaging online diabetes social networks (SNs) in consented research. We tested the willingness of an online diabetes community to share data for public health research by providing members with a privacy-preserving social networking software application for rapid temporal-geographic surveillance of glycemic control. Methods and Findings SN-mediated collection of cross-sectional, member-reported data from an international online diabetes SN entered into a software applicaction we made available in a “Facebook-like” environment to enable reporting, charting and optional sharing of recent hemoglobin A1c values through a geographic display. Self-enrollment by 17% (n = 1,136) of n = 6,500 active members representing 32 countries and 50 US states. Data were current with 83.1% of most recent A1c values reported obtained within the past 90 days. Sharing was high with 81.4% of users permitting data donation to the community display. 34.1% of users also displayed their A1cs on their SN profile page. Users selecting the most permissive sharing options had a lower average A1c (6.8%) than users not sharing with the community (7.1%, p = .038). 95% of users permitted re-contact. Unadjusted aggregate A1c reported by US users closely resembled aggregate 2007–2008 NHANES estimates (respectively, 6.9% and 6.9%, p = 0.85). Conclusions Success within an early adopter community demonstrates that online SNs may comprise efficient platforms for bidirectional communication with and data acquisition from disease populations. Advancing this model for cohort and translational science and for use as a complementary surveillance approach will require understanding of inherent selection and publication (sharing) biases in the data and a technology model that supports autonomy, anonymity and privacy. PMID:21556358

  15. Truthful Channel Sharing for Self Coexistence of Overlapping Medical Body Area Networks

    PubMed Central

    Dutkiewicz, Eryk; Zheng, Guanglou

    2016-01-01

    As defined by IEEE 802.15.6 standard, channel sharing is a potential method to coordinate inter-network interference among Medical Body Area Networks (MBANs) that are close to one another. However, channel sharing opens up new vulnerabilities as selfish MBANs may manipulate their online channel requests to gain unfair advantage over others. In this paper, we address this issue by proposing a truthful online channel sharing algorithm and a companion protocol that allocates channel efficiently and truthfully by punishing MBANs for misreporting their channel request parameters such as time, duration and bid for the channel. We first present an online channel sharing scheme for unit-length channel requests and prove that it is truthful. We then generalize our model to settings with variable-length channel requests, where we propose a critical value based channel pricing and preemption scheme. A bid adjustment procedure prevents unbeneficial preemption by artificially raising the ongoing winner’s bid controlled by a penalty factor λ. Our scheme can efficiently detect selfish behaviors by monitoring a trust parameter α of each MBAN and punish MBANs from cheating by suspending their requests. Our extensive simulation results show our scheme can achieve a total profit that is more than 85% of the offline optimum method in the typical MBAN settings. PMID:26844888

  16. Truthful Channel Sharing for Self Coexistence of Overlapping Medical Body Area Networks.

    PubMed

    Fang, Gengfa; Orgun, Mehmet A; Shankaran, Rajan; Dutkiewicz, Eryk; Zheng, Guanglou

    2016-01-01

    As defined by IEEE 802.15.6 standard, channel sharing is a potential method to coordinate inter-network interference among Medical Body Area Networks (MBANs) that are close to one another. However, channel sharing opens up new vulnerabilities as selfish MBANs may manipulate their online channel requests to gain unfair advantage over others. In this paper, we address this issue by proposing a truthful online channel sharing algorithm and a companion protocol that allocates channel efficiently and truthfully by punishing MBANs for misreporting their channel request parameters such as time, duration and bid for the channel. We first present an online channel sharing scheme for unit-length channel requests and prove that it is truthful. We then generalize our model to settings with variable-length channel requests, where we propose a critical value based channel pricing and preemption scheme. A bid adjustment procedure prevents unbeneficial preemption by artificially raising the ongoing winner's bid controlled by a penalty factor λ. Our scheme can efficiently detect selfish behaviors by monitoring a trust parameter α of each MBAN and punish MBANs from cheating by suspending their requests. Our extensive simulation results show our scheme can achieve a total profit that is more than 85% of the offline optimum method in the typical MBAN settings.

  17. Learning networks for sustainable, large-scale improvement.

    PubMed

    McCannon, C Joseph; Perla, Rocco J

    2009-05-01

    Large-scale improvement efforts known as improvement networks offer structured opportunities for exchange of information and insights into the adaptation of clinical protocols to a variety of settings.

  18. Optimization of communication network topology for navigation sharing among distributed satellites

    NASA Astrophysics Data System (ADS)

    Dang, Zhaohui; Zhang, Yulin

    2013-01-01

    Navigation sharing among distributed satellites is quite important for coordinated motion and collision avoidance. This paper proposes optimization methods of the communication network topology to achieve navigation sharing. The whole communication network constructing by inter-satellite links are considered as a topology graph. The aim of this paper is to find the communication network topology with minimum communication connections' number (MCCN) in different conditions. It has found that the communication capacity and the number of channels are two key parameters affecting the results. The model of MCCN topology for navigation sharing is established and corresponding method is designed. Two main scenarios, viz., homogeneous case and heterogeneous case, are considered. For the homogeneous case where each member has the same communication capacity, it designs a construction method (Algorithm 1) to find the MCCN topology. For the heterogeneous case, it introduces a modified genetic algorithm (Algorithm 2) to find the MCCN topology. When considering the fact that the number of channels is limited, the Algorithm 2 is further modified by adding a penalized term in the fitness function. The effectiveness of these algorithms is all proved in theoretical. Three examples are further tested to illustrate the methods developed in this paper.

  19. Generating community-built tools for data sharing and analysis in environmental networks

    USGS Publications Warehouse

    Read, Jordan S.; Gries, Corinna; Read, Emily K.; Klug, Jennifer; Hanson, Paul C.; Hipsey, Matthew R.; Jennings, Eleanor; O'Reilley, Catherine; Winslow, Luke A.; Pierson, Don; McBride, Christopher G.; Hamilton, David

    2016-01-01

    Rapid data growth in many environmental sectors has necessitated tools to manage and analyze these data. The development of tools often lags behind the proliferation of data, however, which may slow exploratory opportunities and scientific progress. The Global Lake Ecological Observatory Network (GLEON) collaborative model supports an efficient and comprehensive data–analysis–insight life cycle, including implementations of data quality control checks, statistical calculations/derivations, models, and data visualizations. These tools are community-built and openly shared. We discuss the network structure that enables tool development and a culture of sharing, leading to optimized output from limited resources. Specifically, data sharing and a flat collaborative structure encourage the development of tools that enable scientific insights from these data. Here we provide a cross-section of scientific advances derived from global-scale analyses in GLEON. We document enhancements to science capabilities made possible by the development of analytical tools and highlight opportunities to expand this framework to benefit other environmental networks.

  20. When Sharing Is a Bad Idea: The Effects of Online Social Network Engagement and Sharing Passwords with Friends on Cyberbullying Involvement.

    PubMed

    Meter, Diana J; Bauman, Sheri

    2015-08-01

    Every day, children and adolescents communicate online via social networking sites (SNSs). They also report sharing passwords with peers and friends, a potentially risky behavior in regard to cyber safety. This longitudinal study tested the hypotheses that social network engagement in multiple settings would predict more cyberbullying involvement over time, and that youth who reported sharing passwords would also experience an increase in cyberbullying involvement. Data were collected at two time points one year apart from 1,272 third through eighth grade students. In line with the first study hypothesis, participating in more online SNSs was associated with increased cyberbullying involvement over time, as well as sharing passwords over time. Cyberbullying involvement at T1 predicted decreases in sharing passwords over time, suggesting that youth become aware of the dangers of sharing passwords as a result of their experience. Sharing passwords at T1 was unrelated to cyberbullying involvement at T2. Although it seems that youth may be learning from their previous mistakes, due to the widespread use of social media and normality of sharing passwords among young people, it is important to continue to educate youth about cyber safety and risky online behavior.

  1. Variation in Patient-Sharing Networks of Physicians Across the United States

    PubMed Central

    Landon, Bruce E.; Keating, Nancy L.; Barnett, Michael L.; Onnela, Jukka-Pekka; Paul, Sudeshna; O’Malley, A. James; Keegan, Thomas; Christakis, Nicholas A.

    2012-01-01

    Context Physicians are embedded in informal networks that result in their sharing patients, information, and behaviors. Objective We use novel methods to identify professional networks among physicians, to examine how such networks vary across geographic regions, and to determine factors associated with physician connections. Design, Setting, and Participants Using methods adopted from social network analysis, we used Medicare administrative data from 2006 to study 4,586,044 Medicare beneficiaries seen by 68,288 active physicians practicing in 51 hospital referral regions (HRRs). Distinct networks depicting connections between physicians (defined based on shared patients) were constructed for each of the 51 HRRs. Main Outcomes Measures Variation in network characteristics across HRRs and factors associated with physicians being connected. Results The number of physicians per HRR ranged from 135 in Minot, ND to 8,197 in Boston, MA. There was substantial variation in network characteristics across HRRs. For example, the median adjusted degree (number of other physicians each physician was connected to, per 100 Medicare beneficiaries) across all HRRs was 27.3, and ranged from 11.7 to 54.4; also, primary care physician (PCP) relative centrality (how central PCPs were in the network relative to other physicians) ranged from 0.19 to 1.06. Physicians with ties to each other were far more likely to be based at the same hospital (96.0% of connected physician pairs versus 69.2% of unconnected pairs, p<.001, adjusted rate ratio=.12, 95% confidence interval .12,.12)), and were in closer geographic proximity (mean office distance of 13.2 miles for those with connections versus 24.2 for those without, p<.001). Connected physicians also had more similar patient panels, in terms of the race or illness burden, than unconnected physicians. For instance, connected physician pairs had an average difference of 8.8 points in the percentage of black patients in their two patient panels

  2. Analyzing large biological datasets with association networks.

    PubMed

    Karpinets, Tatiana V; Park, Byung H; Uberbacher, Edward C

    2012-09-01

    Due to advances in high-throughput biotechnologies biological information is being collected in databases at an amazing rate, requiring novel computational approaches that process collected data into new knowledge in a timely manner. In this study, we propose a computational framework for discovering modular structure, relationships and regularities in complex data. The framework utilizes a semantic-preserving vocabulary to convert records of biological annotations of an object, such as an organism, gene, chemical or sequence, into networks (Anets) of the associated annotations. An association between a pair of annotations in an Anet is determined by the similarity of their co-occurrence pattern with all other annotations in the data. This feature captures associations between annotations that do not necessarily co-occur with each other and facilitates discovery of the most significant relationships in the collected data through clustering and visualization of the Anet. To demonstrate this approach, we applied the framework to the analysis of metadata from the Genomes OnLine Database and produced a biological map of sequenced prokaryotic organisms with three major clusters of metadata that represent pathogens, environmental isolates and plant symbionts.

  3. Simulation of large systems with neural networks

    SciTech Connect

    Paez, T.L.

    1994-09-01

    Artificial neural networks (ANNs) have been shown capable of simulating the behavior of complex, nonlinear, systems, including structural systems. Under certain circumstances, it is desirable to simulate structures that are analyzed with the finite element method. For example, when we perform a probabilistic analysis with the Monte Carlo method, we usually perform numerous (hundreds or thousands of) repetitions of a response simulation with different input and system parameters to estimate the chance of specific response behaviors. In such applications, efficiency in computation of response is critical, and response simulation with ANNs can be valuable. However, finite element analyses of complex systems involve the use of models with tens or hundreds of thousands of degrees of freedom, and ANNs are practically limited to simulations that involve far fewer variables. This paper develops a technique for reducing the amount of information required to characterize the response of a general structure. We show how the reduced information can be used to train a recurrent ANN. Then the trained ANN can be used to simulate the reduced behavior of the original system, and the reduction transformation can be inverted to provide a simulation of the original system. A numerical example is presented.

  4. Secure NFV Orchestration Over an SDN-Controlled Optical Network With Time-Shared Quantum Key Distribution Resources

    NASA Astrophysics Data System (ADS)

    Aguado, Alejandro; Hugues-Salas, Emilio; Haigh, Paul Anthony; Marhuenda, Jaume; Price, Alasdair B.; Sibson, Philip; Kennard, Jake E.; Erven, Chris; Rarity, John G.; Thompson, Mark Gerard; Lord, Andrew; Nejabati, Reza; Simeonidou, Dimitra

    2017-04-01

    We demonstrate, for the first time, a secure optical network architecture that combines NFV orchestration and SDN control with quantum key distribution (QKD) technology. A novel time-shared QKD network design is presented as a cost-effective solution for practical networks.

  5. Predictive coding accounts of shared representations in parieto-insular networks.

    PubMed

    Ishida, Hiroaki; Suzuki, Keisuke; Grandi, Laura Clara

    2015-04-01

    The discovery of mirror neurons in the ventral premotor cortex (area F5) and inferior parietal cortex (area PFG) in the macaque monkey brain has provided the physiological evidence for direct matching of the intrinsic motor representations of the self and the visual image of the actions of others. The existence of mirror neurons implies that the brain has mechanisms reflecting shared self and other action representations. This may further imply that the neural basis self-body representations may also incorporate components that are shared with other-body representations. It is likely that such a mechanism is also involved in predicting other's touch sensations and emotions. However, the neural basis of shared body representations has remained unclear. Here, we propose a neural basis of body representation of the self and of others in both human and non-human primates. We review a series of behavioral and physiological findings which together paint a picture that the systems underlying such shared representations require integration of conscious exteroception and interoception subserved by a cortical sensory-motor network involving parieto-inner perisylvian circuits (the ventral intraparietal area [VIP]/inferior parietal area [PFG]-secondary somatosensory cortex [SII]/posterior insular cortex [pIC]/anterior insular cortex [aIC]). Based on these findings, we propose a computational mechanism of the shared body representation in the predictive coding (PC) framework. Our mechanism proposes that processes emerging from generative models embedded in these specific neuronal circuits play a pivotal role in distinguishing a self-specific body representation from a shared one. The model successfully accounts for normal and abnormal shared body phenomena such as mirror-touch synesthesia and somatoparaphrenia. In addition, it generates a set of testable experimental predictions. Copyright © 2014 Elsevier Ltd. All rights reserved.

  6. Assessment on knowledge network sharing capability of industrial cluster based on dempster-shafer theory of evidence.

    PubMed

    Dai, Shengli; Zhang, Hailin

    2014-01-01

    Based on Theory of Evidence and reviewing research papers concerned, a concept model of knowledge sharing network among industrial cluster firms, which can be applied to assess knowledge sharing capacity, has been built. Next, the authors create a set of assessment index systems including twelve subindexes under four principle indexes. In this study, ten experts in the same field were invited to score all the indexes of knowledge sharing capacity concerning one certain industrial cluster. The research result shows relatively high knowledge network sharing capacity among the certain industrial cluster firms. Another conclusion is that the assessment method with Theory of Evidence is feasible to conduct such a research.

  7. Assessment on Knowledge Network Sharing Capability of Industrial Cluster Based on Dempster-Shafer Theory of Evidence

    PubMed Central

    Zhang, Hailin

    2014-01-01

    Based on Theory of Evidence and reviewing research papers concerned, a concept model of knowledge sharing network among industrial cluster firms, which can be applied to assess knowledge sharing capacity, has been built. Next, the authors create a set of assessment index systems including twelve subindexes under four principle indexes. In this study, ten experts in the same field were invited to score all the indexes of knowledge sharing capacity concerning one certain industrial cluster. The research result shows relatively high knowledge network sharing capacity among the certain industrial cluster firms. Another conclusion is that the assessment method with Theory of Evidence is feasible to conduct such a research. PMID:24795540

  8. A large deformation viscoelastic model for double-network hydrogels

    NASA Astrophysics Data System (ADS)

    Mao, Yunwei; Lin, Shaoting; Zhao, Xuanhe; Anand, Lallit

    2017-03-01

    We present a large deformation viscoelasticity model for recently synthesized double network hydrogels which consist of a covalently-crosslinked polyacrylamide network with long chains, and an ionically-crosslinked alginate network with short chains. Such double-network gels are highly stretchable and at the same time tough, because when stretched the crosslinks in the ionically-crosslinked alginate network rupture which results in distributed internal microdamage which dissipates a substantial amount of energy, while the configurational entropy of the covalently-crosslinked polyacrylamide network allows the gel to return to its original configuration after deformation. In addition to the large hysteresis during loading and unloading, these double network hydrogels also exhibit a substantial rate-sensitive response during loading, but exhibit almost no rate-sensitivity during unloading. These features of large hysteresis and asymmetric rate-sensitivity are quite different from the response of conventional hydrogels. We limit our attention to modeling the complex viscoelastic response of such hydrogels under isothermal conditions. Our model is restricted in the sense that we have limited our attention to conditions under which one might neglect any diffusion of the water in the hydrogel - as might occur when the gel has a uniform initial value of the concentration of water, and the mobility of the water molecules in the gel is low relative to the time scale of the mechanical deformation. We also do not attempt to model the final fracture of such double-network hydrogels.

  9. Optimal access to large databases via networks

    SciTech Connect

    Munro, J.K.; Fellows, R.L.; Phifer, D. Carrick, M.R.; Tarlton, N.

    1997-10-01

    A CRADA with Stephens Engineering was undertaken in order to transfer knowledge and experience about access to information in large text databases, with results of queries and searches provided using the multimedia capabilities of the World Wide Web. Data access is optimized by the use of intelligent agents. Technology Logic Diagram documents published for the DOE facilities in Oak Ridge (K-25, X-10, Y-12) were chosen for this effort because of the large number of technologies identified, described, evaluated, and ranked for possible use in the environmental remediation of these facilities. Fast, convenient access to this information is difficult because of the volume and complexity of the data. WAIS software used to provide full-text, field-based search capability can also be used, through the development of an appropriate hierarchy of menus, to provide tabular summaries of technologies satisfying a wide range of criteria. The menu hierarchy can also be used to regenerate dynamically many of the tables that appeared in the original hardcopy publications, all from a single text database of the technology descriptions. Use of the Web environment permits linking many of the Technology Logic Diagram references to on-line versions of these publications, particularly the DOE Orders and related directives providing the legal requirements that were the basis for undertaking the Technology Logic Diagram studies in the first place.

  10. Share2Quit: Online Social Network Peer Marketing of Tobacco Cessation Systems.

    PubMed

    Sadasivam, Rajani S; Cutrona, Sarah L; Luger, Tana M; Volz, Erik; Kinney, Rebecca; Rao, Sowmya R; Allison, Jeroan J; Houston, Thomas K

    2017-03-01

    Although technology-assisted tobacco interventions (TATIs) are effective, they are underused due to recruitment challenges. We tested whether we could successfully recruit smokers to a TATI using peer marketing through a social network (Facebook). We recruited smokers on Facebook using online advertisements. These recruited smokers (seeds) and subsequent waves of smokers (peer recruits) were provided the Share2Quit peer recruitment Facebook app and other tools. Smokers were incentivized for up to seven successful peer recruitments and had 30 days to recruit from date of registration. Successful peer recruitment was defined as a peer recruited smoker completing the registration on the TATI following a referral. Our primary questions were (1) whether smokers would recruit other smokers and (2) whether peer recruitment would extend the reach of the intervention to harder-to-reach groups, including those not ready to quit and minority smokers. Overall, 759 smokers were recruited (seeds: 190; peer recruits: 569). Fifteen percent (n = 117) of smokers successfully recruited their peers (seeds: 24.7%; peer recruits: 7.7%) leading to four recruitment waves. Compared to seeds, peer recruits were less likely to be ready to quit (peer recruits 74.2% vs. seeds 95.1%), more likely to be male (67.1% vs. 32.9%), and more likely to be African American (23.8% vs. 10.8%) (p < .01 for all comparisons). Peer marketing quadrupled our engaged smokers and enriched the sample with not-ready-to-quit and African American smokers. Peer recruitment is promising, and our study uncovered several important challenges for future research. This study demonstrates the successful recruitment of smokers to a TATI using a Facebook-based peer marketing strategy. Smokers on Facebook were willing and able to recruit other smokers to a TATI, yielding a large and diverse population of smokers.

  11. Benefit of adaptive FEC in shared backup path protected elastic optical network.

    PubMed

    Guo, Hong; Dai, Hua; Wang, Chao; Li, Yongcheng; Bose, Sanjay K; Shen, Gangxiang

    2015-07-27

    We apply an adaptive forward error correction (FEC) allocation strategy to an Elastic Optical Network (EON) operated with shared backup path protection (SBPP). To maximize the protected network capacity that can be carried, an Integer Linear Programing (ILP) model and a spectrum window plane (SWP)-based heuristic algorithm are developed. Simulation results show that the FEC coding overhead required by the adaptive FEC scheme is significantly lower than that needed by a fixed FEC allocation strategy resulting in higher network capacity for the adaptive strategy. The adaptive FEC allocation strategy can also significantly outperform the fixed FEC allocation strategy both in terms of the spare capacity redundancy and the average FEC coding overhead needed per optical channel. The proposed heuristic algorithm is efficient and not only performs closer to the ILP model but also does much better than the shortest-path algorithm.

  12. One dimensional modeling of blood flow in large networks

    NASA Astrophysics Data System (ADS)

    Wang, Xiaofei; Lagree, Pierre-Yves; Fullana, Jose-Maria; Lorthois, Sylvie; Institut de Mecanique des Fluides de Toulouse Collaboration

    2014-11-01

    A fast and valid simulation of blood flow in large networks of vessels can be achieved with a one-dimensional viscoelastic model. In this paper, we developed a parallel code with this model and computed several networks: a circle of arteries, a human systemic network with 55 arteries and a vascular network of mouse kidney with more than one thousand segments. The numerical results were verified and the speedup of parallel computing was tested on multi-core computers. The evolution of pressure distributions in all the networks were visualized and we can see clearly the propagation patterns of the waves. This provides us a convenient tool to simulate blood flow in networks.

  13. PKI security in large-scale healthcare networks.

    PubMed

    Mantas, Georgios; Lymberopoulos, Dimitrios; Komninos, Nikos

    2012-06-01

    During the past few years a lot of PKI (Public Key Infrastructures) infrastructures have been proposed for healthcare networks in order to ensure secure communication services and exchange of data among healthcare professionals. However, there is a plethora of challenges in these healthcare PKI infrastructures. Especially, there are a lot of challenges for PKI infrastructures deployed over large-scale healthcare networks. In this paper, we propose a PKI infrastructure to ensure security in a large-scale Internet-based healthcare network connecting a wide spectrum of healthcare units geographically distributed within a wide region. Furthermore, the proposed PKI infrastructure facilitates the trust issues that arise in a large-scale healthcare network including multi-domain PKI infrastructures.

  14. Revealing Shared and Distinct Gene Network Organization in Arabidopsis Immune Responses by Integrative Analysis1

    PubMed Central

    Dong, Xiaobao; Jiang, Zhenhong; Peng, You-Liang; Zhang, Ziding

    2015-01-01

    Pattern-triggered immunity (PTI) and effector-triggered immunity (ETI) are two main plant immune responses to counter pathogen invasion. Genome-wide gene network organizing principles leading to quantitative differences between PTI and ETI have remained elusive. We combined an advanced machine learning method and modular network analysis to systematically characterize the organizing principles of Arabidopsis (Arabidopsis thaliana) PTI and ETI at three network resolutions. At the single network node/edge level, we ranked genes and gene interactions based on their ability to distinguish immune response from normal growth and successfully identified many immune-related genes associated with PTI and ETI. Topological analysis revealed that the top-ranked gene interactions tend to link network modules. At the subnetwork level, we identified a subnetwork shared by PTI and ETI encompassing 1,159 genes and 1,289 interactions. This subnetwork is enriched in interactions linking network modules and is also a hotspot of attack by pathogen effectors. The subnetwork likely represents a core component in the coordination of multiple biological processes to favor defense over development. Finally, we constructed modular network models for PTI and ETI to explain the quantitative differences in the global network architecture. Our results indicate that the defense modules in ETI are organized into relatively independent structures, explaining the robustness of ETI to genetic mutations and effector attacks. Taken together, the multiscale comparisons of PTI and ETI provide a systems biology perspective on plant immunity and emphasize coordination among network modules to establish a robust immune response. PMID:25614062

  15. Episodic memory in aspects of large-scale brain networks

    PubMed Central

    Jeong, Woorim; Chung, Chun Kee; Kim, June Sic

    2015-01-01

    Understanding human episodic memory in aspects of large-scale brain networks has become one of the central themes in neuroscience over the last decade. Traditionally, episodic memory was regarded as mostly relying on medial temporal lobe (MTL) structures. However, recent studies have suggested involvement of more widely distributed cortical network and the importance of its interactive roles in the memory process. Both direct and indirect neuro-modulations of the memory network have been tried in experimental treatments of memory disorders. In this review, we focus on the functional organization of the MTL and other neocortical areas in episodic memory. Task-related neuroimaging studies together with lesion studies suggested that specific sub-regions of the MTL are responsible for specific components of memory. However, recent studies have emphasized that connectivity within MTL structures and even their network dynamics with other cortical areas are essential in the memory process. Resting-state functional network studies also have revealed that memory function is subserved by not only the MTL system but also a distributed network, particularly the default-mode network (DMN). Furthermore, researchers have begun to investigate memory networks throughout the entire brain not restricted to the specific resting-state network (RSN). Altered patterns of functional connectivity (FC) among distributed brain regions were observed in patients with memory impairments. Recently, studies have shown that brain stimulation may impact memory through modulating functional networks, carrying future implications of a novel interventional therapy for memory impairment. PMID:26321939

  16. Prekindergarten teachers' verbal references to print during classroom-based, large-group shared reading.

    PubMed

    Zucker, Tricia A; Justice, Laura M; Piasta, Shayne B

    2009-10-01

    The frequency with which adults reference print when reading with preschool-age children is associated with growth in children's print knowledge (e.g., L.M. Justice & H.K. Ezell, 2000, 2002). This study examined whether prekindergarten (pre-K) teachers naturally reference print during classroom shared reading and if verbal print references occur at similar rates across different types of books. The relation between frequency of print referencing and quality of teachers' language instruction was also studied. Seventeen pre-K teachers were randomly assigned to a regular reading condition as part of a larger study, and 92 videos of their large-group, shared-reading sessions were analyzed for print-referencing utterances and quality of language instruction. Teachers' verbal print references were compared across texts that were purposefully sampled to include different levels of print salience. Teachers discussed all domains of print studied; however, their rate of print referencing was relatively low. More verbal print references were observed when the teachers read books exhibiting higher amounts of print-salient features. When reading books, there was no apparent relation between teachers' use of print referencing and their quality of language instruction. It is unclear whether this low rate of explicit, verbal print referencing would impact children's print knowledge. Nonetheless, print-salient books appear to offer a natural context for discussions about print. Implications for educational practice are considered.

  17. The Deep Space Network Large Array

    NASA Astrophysics Data System (ADS)

    Gatti, M. S.

    2004-05-01

    In recent years it has become evident that, if future science needs are to be met, the capacity of the telecommunications link between planetary spacecraft and the Earth must be increased by orders of magnitude. Both the number of spacecraft and higher data rates demand the increased capacity. Technologies to support the increased capacity include even larger antennas, optical receiving systems, or arrays of antennas. This article describes a large array of small antennas that would be implemented for a fraction of the cost of an equivalent 70-m aperture. Adding additional antennas can increase the sensitivity many fold over current capabilities. The array will consist of 400 parabolic reflector antennas, each of which will be 12 m in diameter. Each antenna will operate simultaneously at both X-band (8 to 8.8 GHz) and Ka-band (31 to 38 GHz) and will be configured with radio frequency (RF) electronics, including the feeds, low-noise amplifiers, and frequency converters, as well as the appropriate servo controls and drives. The array also includes the signal transmission and signal processing to enable the system to track from between 1 and 16 different signals. A significant feature of this system is that it will be done for relatively very low cost compared to the current antenna paradigms. This is made possible by the use of low-cost antenna reflector technology, the extensive use of monolithic microwave integrated circuits (MMICs), and, finally, by using commercially available equipment to the maximum extent possible. Cost can be further reduced by the acceptance of lower antenna element reliability. High system availability will be maintained by a design paradigm that provides for a marginal set of excess antenna elements for any particular tracking period. Thus, the same total system availability is achieved for lower element availability. The "plug-and-play" aspects of the assemblies will enhance maintainability and operability. The project plans include a

  18. Interactive, multiscale navigation of large and complicated biological networks.

    PubMed

    Praneenararat, Thanet; Takagi, Toshihisa; Iwasaki, Wataru

    2011-04-15

    Many types of omics data are compiled as lists of connections between elements and visualized as networks or graphs where the nodes and edges correspond to the elements and the connections, respectively. However, these networks often appear as 'hair-balls'-with a large number of extremely tangled edges-and cannot be visually interpreted. We present an interactive, multiscale navigation method for biological networks. Our approach can automatically and rapidly abstract any portion of a large network of interest to an immediately interpretable extent. The method is based on an ultrafast graph clustering technique that abstracts networks of about 100 000 nodes in a second by iteratively grouping densely connected portions and a biological-property-based clustering technique that takes advantage of biological information often provided for biological entities (e.g. Gene Ontology terms). It was confirmed to be effective by applying it to real yeast protein network data, and would greatly help modern biologists faced with large, complicated networks in a similar manner to how Web mapping services enable interactive multiscale navigation of geographical maps (e.g. Google Maps). Java implementation of our method, named NaviCluster, is available at http://navicluster.cb.k.u-tokyo.ac.jp/. thanet@cb.k.u-tokyo.ac.jp Supplementary data are available at Bioinformatics online.

  19. Genomic analysis of regulatory network dynamics reveals large topological changes

    NASA Astrophysics Data System (ADS)

    Luscombe, Nicholas M.; Madan Babu, M.; Yu, Haiyuan; Snyder, Michael; Teichmann, Sarah A.; Gerstein, Mark

    2004-09-01

    Network analysis has been applied widely, providing a unifying language to describe disparate systems ranging from social interactions to power grids. It has recently been used in molecular biology, but so far the resulting networks have only been analysed statically. Here we present the dynamics of a biological network on a genomic scale, by integrating transcriptional regulatory information and gene-expression data for multiple conditions in Saccharomyces cerevisiae. We develop an approach for the statistical analysis of network dynamics, called SANDY, combining well-known global topological measures, local motifs and newly derived statistics. We uncover large changes in underlying network architecture that are unexpected given current viewpoints and random simulations. In response to diverse stimuli, transcription factors alter their interactions to varying degrees, thereby rewiring the network. A few transcription factors serve as permanent hubs, but most act transiently only during certain conditions. By studying sub-network structures, we show that environmental responses facilitate fast signal propagation (for example, with short regulatory cascades), whereas the cell cycle and sporulation direct temporal progression through multiple stages (for example, with highly inter-connected transcription factors). Indeed, to drive the latter processes forward, phase-specific transcription factors inter-regulate serially, and ubiquitously active transcription factors layer above them in a two-tiered hierarchy. We anticipate that many of the concepts presented here-particularly the large-scale topological changes and hub transience-will apply to other biological networks, including complex sub-systems in higher eukaryotes.

  20. Uncovering disassortativity in large scale-free networks

    NASA Astrophysics Data System (ADS)

    Litvak, Nelly; van der Hofstad, Remco

    2013-02-01

    Mixing patterns in large self-organizing networks, such as the Internet, the World Wide Web, and social and biological networks, are often characterized by degree-degree dependencies between neighboring nodes. In this paper, we propose a new way of measuring degree-degree dependencies. One of the problems with the commonly used assortativity coefficient is that in disassortative networks its magnitude decreases with the network size. We mathematically explain this phenomenon and validate the results on synthetic graphs and real-world network data. As an alternative, we suggest to use rank correlation measures such as Spearman's ρ. Our experiments convincingly show that Spearman's ρ produces consistent values in graphs of different sizes but similar structure, and it is able to reveal strong (positive or negative) dependencies in large graphs. In particular, we discover much stronger negative degree-degree dependencies in Web graphs than was previously thought. Rank correlations allow us to compare the assortativity of networks of different sizes, which is impossible with the assortativity coefficient due to its genuine dependence on the network size. We conclude that rank correlations provide a suitable and informative method for uncovering network mixing patterns.

  1. Genomic analysis of regulatory network dynamics reveals large topological changes.

    PubMed

    Luscombe, Nicholas M; Babu, M Madan; Yu, Haiyuan; Snyder, Michael; Teichmann, Sarah A; Gerstein, Mark

    2004-09-16

    Network analysis has been applied widely, providing a unifying language to describe disparate systems ranging from social interactions to power grids. It has recently been used in molecular biology, but so far the resulting networks have only been analysed statically. Here we present the dynamics of a biological network on a genomic scale, by integrating transcriptional regulatory information and gene-expression data for multiple conditions in Saccharomyces cerevisiae. We develop an approach for the statistical analysis of network dynamics, called SANDY, combining well-known global topological measures, local motifs and newly derived statistics. We uncover large changes in underlying network architecture that are unexpected given current viewpoints and random simulations. In response to diverse stimuli, transcription factors alter their interactions to varying degrees, thereby rewiring the network. A few transcription factors serve as permanent hubs, but most act transiently only during certain conditions. By studying sub-network structures, we show that environmental responses facilitate fast signal propagation (for example, with short regulatory cascades), whereas the cell cycle and sporulation direct temporal progression through multiple stages (for example, with highly inter-connected transcription factors). Indeed, to drive the latter processes forward, phase-specific transcription factors inter-regulate serially, and ubiquitously active transcription factors layer above them in a two-tiered hierarchy. We anticipate that many of the concepts presented here--particularly the large-scale topological changes and hub transience--will apply to other biological networks, including complex sub-systems in higher eukaryotes.

  2. Impact of heuristics in clustering large biological networks.

    PubMed

    Shafin, Md Kishwar; Kabir, Kazi Lutful; Ridwan, Iffatur; Anannya, Tasmiah Tamzid; Karim, Rashid Saadman; Hoque, Mohammad Mozammel; Rahman, M Sohel

    2015-12-01

    Traditional clustering algorithms often exhibit poor performance for large networks. On the contrary, greedy algorithms are found to be relatively efficient while uncovering functional modules from large biological networks. The quality of the clusters produced by these greedy techniques largely depends on the underlying heuristics employed. Different heuristics based on different attributes and properties perform differently in terms of the quality of the clusters produced. This motivates us to design new heuristics for clustering large networks. In this paper, we have proposed two new heuristics and analyzed the performance thereof after incorporating those with three different combinations in a recently celebrated greedy clustering algorithm named SPICi. We have extensively analyzed the effectiveness of these new variants. The results are found to be promising.

  3. Making Large-Scale Networks from fMRI Data

    PubMed Central

    Schmittmann, Verena D.; Jahfari, Sara; Borsboom, Denny; Savi, Alexander O.; Waldorp, Lourens J.

    2015-01-01

    Pairwise correlations are currently a popular way to estimate a large-scale network (> 1000 nodes) from functional magnetic resonance imaging data. However, this approach generally results in a poor representation of the true underlying network. The reason is that pairwise correlations cannot distinguish between direct and indirect connectivity. As a result, pairwise correlation networks can lead to fallacious conclusions; for example, one may conclude that a network is a small-world when it is not. In a simulation study and an application to resting-state fMRI data, we compare the performance of pairwise correlations in large-scale networks (2000 nodes) against three other methods that are designed to filter out indirect connections. Recovery methods are evaluated in four simulated network topologies (small world or not, scale-free or not) in scenarios where the number of observations is very small compared to the number of nodes. Simulations clearly show that pairwise correlation networks are fragmented into separate unconnected components with excessive connectedness within components. This often leads to erroneous estimates of network metrics, like small-world structures or low betweenness centrality, and produces too many low-degree nodes. We conclude that using partial correlations, informed by a sparseness penalty, results in more accurate networks and corresponding metrics than pairwise correlation networks. However, even with these methods, the presence of hubs in the generating network can be problematic if the number of observations is too small. Additionally, we show for resting-state fMRI that partial correlations are more robust than correlations to different parcellation sets and to different lengths of time-series. PMID:26325185

  4. Large-scale P2P network based distributed virtual geographic environment (DVGE)

    NASA Astrophysics Data System (ADS)

    Tan, Xicheng; Yu, Liang; Bian, Fuling

    2007-06-01

    Virtual Geographic Environment has raised full concern as a kind of software information system that helps us understand and analyze the real geographic environment, and it has also expanded to application service system in distributed environment--distributed virtual geographic environment system (DVGE), and gets some achievements. However, limited by the factor of the mass data of VGE, the band width of network, as well as numerous requests and economic, etc. DVGE still faces some challenges and problems which directly cause the current DVGE could not provide the public with high-quality service under current network mode. The Rapid development of peer-to-peer network technology has offered new ideas of solutions to the current challenges and problems of DVGE. Peer-to-peer network technology is able to effectively release and search network resources so as to realize efficient share of information. Accordingly, this paper brings forth a research subject on Large-scale peer-to-peer network extension of DVGE as well as a deep study on network framework, routing mechanism, and DVGE data management on P2P network.

  5. Shared path protection through reconstructing sharable bandwidth based on spectrum segmentation for elastic optical networks

    NASA Astrophysics Data System (ADS)

    Liu, Huanlin; Zhang, Mingjia; Yi, Pengfei; Chen, Yong

    2016-12-01

    In order to address the problems of spectrum fragmentation and low sharing degree of spectrum resources in survivable elastic optical networks, an improved algorithm, called shared path protection by reconstructing sharable bandwidth based on spectrum segmentation (SPP-RSB-SS), is proposed in the paper. In the SPP-RSB-SS algorithm, for reducing the number of spectrum fragmentations and improving the success rate of spectrum allocation, the whole spectrum resource is partitioned into several spectrum segments. And each spectrum segment is allocated to the requests with the same bandwidth requirement in priority. Meanwhile, the protection path with higher spectrum sharing degree is selected through optimizing the link cost function and reconstructing sharable bandwidth. Hence, the protection path can maximize the sharable spectrum usage among multiple protection paths. The simulation results indicate that the SPP-RSB-SS algorithm can increase the sharing degree of protection spectrum effectively. Furthermore, the SPP-RSB-SS algorithm can enhance the spectrum utilization, and reduce the bandwidth blocking probability significantly.

  6. Unbreakable distributed storage with quantum key distribution network and password-authenticated secret sharing

    PubMed Central

    Fujiwara, M.; Waseda, A.; Nojima, R.; Moriai, S.; Ogata, W.; Sasaki, M.

    2016-01-01

    Distributed storage plays an essential role in realizing robust and secure data storage in a network over long periods of time. A distributed storage system consists of a data owner machine, multiple storage servers and channels to link them. In such a system, secret sharing scheme is widely adopted, in which secret data are split into multiple pieces and stored in each server. To reconstruct them, the data owner should gather plural pieces. Shamir’s (k, n)-threshold scheme, in which the data are split into n pieces (shares) for storage and at least k pieces of them must be gathered for reconstruction, furnishes information theoretic security, that is, even if attackers could collect shares of less than the threshold k, they cannot get any information about the data, even with unlimited computing power. Behind this scenario, however, assumed is that data transmission and authentication must be perfectly secure, which is not trivial in practice. Here we propose a totally information theoretically secure distributed storage system based on a user-friendly single-password-authenticated secret sharing scheme and secure transmission using quantum key distribution, and demonstrate it in the Tokyo metropolitan area (≤90 km). PMID:27363566

  7. Unbreakable distributed storage with quantum key distribution network and password-authenticated secret sharing.

    PubMed

    Fujiwara, M; Waseda, A; Nojima, R; Moriai, S; Ogata, W; Sasaki, M

    2016-07-01

    Distributed storage plays an essential role in realizing robust and secure data storage in a network over long periods of time. A distributed storage system consists of a data owner machine, multiple storage servers and channels to link them. In such a system, secret sharing scheme is widely adopted, in which secret data are split into multiple pieces and stored in each server. To reconstruct them, the data owner should gather plural pieces. Shamir's (k, n)-threshold scheme, in which the data are split into n pieces (shares) for storage and at least k pieces of them must be gathered for reconstruction, furnishes information theoretic security, that is, even if attackers could collect shares of less than the threshold k, they cannot get any information about the data, even with unlimited computing power. Behind this scenario, however, assumed is that data transmission and authentication must be perfectly secure, which is not trivial in practice. Here we propose a totally information theoretically secure distributed storage system based on a user-friendly single-password-authenticated secret sharing scheme and secure transmission using quantum key distribution, and demonstrate it in the Tokyo metropolitan area (≤90 km).

  8. Unbreakable distributed storage with quantum key distribution network and password-authenticated secret sharing

    NASA Astrophysics Data System (ADS)

    Fujiwara, M.; Waseda, A.; Nojima, R.; Moriai, S.; Ogata, W.; Sasaki, M.

    2016-07-01

    Distributed storage plays an essential role in realizing robust and secure data storage in a network over long periods of time. A distributed storage system consists of a data owner machine, multiple storage servers and channels to link them. In such a system, secret sharing scheme is widely adopted, in which secret data are split into multiple pieces and stored in each server. To reconstruct them, the data owner should gather plural pieces. Shamir’s (k, n)-threshold scheme, in which the data are split into n pieces (shares) for storage and at least k pieces of them must be gathered for reconstruction, furnishes information theoretic security, that is, even if attackers could collect shares of less than the threshold k, they cannot get any information about the data, even with unlimited computing power. Behind this scenario, however, assumed is that data transmission and authentication must be perfectly secure, which is not trivial in practice. Here we propose a totally information theoretically secure distributed storage system based on a user-friendly single-password-authenticated secret sharing scheme and secure transmission using quantum key distribution, and demonstrate it in the Tokyo metropolitan area (≤90 km).

  9. The structure of spatial networks and communities in bicycle sharing systems.

    PubMed

    Zaltz Austwick, Martin; O'Brien, Oliver; Strano, Emanuele; Viana, Matheus

    2013-01-01

    Bicycle sharing systems exist in hundreds of cities around the world, with the aim of providing a form of public transport with the associated health and environmental benefits of cycling without the burden of private ownership and maintenance. Five cities have provided research data on the journeys (start and end time and location) taking place in their bicycle sharing system. In this paper, we employ visualization, descriptive statistics and spatial and network analysis tools to explore system usage in these cities, using techniques to investigate features specific to the unique geographies of each, and uncovering similarities between different systems. Journey displacement analysis demonstrates similar journey distances across the cities sampled, and the (out)strength rank curve for the top 50 stands in each city displays a similar scaling law for each. Community detection in the derived network can identify local pockets of use, and spatial network corrections provide the opportunity for insight above and beyond proximity/popularity correlations predicted by simple spatial interaction models.

  10. Managing ISR sharing policies at the network edge using Controlled English

    NASA Astrophysics Data System (ADS)

    Parizas, Christos; Pizzocaro, Diego; Preece, Alun; Zerfos, Petros

    2013-05-01

    In domains such as emergency response and military operations the sharing of Intelligence, Surveillance and Reconnaissance (ISR) assets among different coalition partners is regulated through policies. Traditionally, poli­ cies are created at the center of a coalitions network by high-level decision makers and expressed in low-level policy languages (e.g. Common Information Model SPL) by technical personnel, which makes them difficult to be understood by non-technical users at the edge of the network. Moreover, policies must often be modified by negotiation among coalition partners, typically in rapid response to the changing operational situation. Com­ monly, the users who must cope first with situational changes are those on the edge, so it would be very effective if they were able to create and negotiate policies themselves. We investigate the use of Controlled English (CE) as a means to define a policy representation that is both human-friendly and machine processable. We show how a CE model can capture a variety of policy types, including those based on a traditional asset ownership model, and those defining team-based asset sharing across a coalition. The use of CE is intended to benefit coalition networks by bridging the gap between technical and non-technical users in terms of policy creation and negoti­ ation, while at the same time being directly processable by a policy-checking system without transformation to any other technical representation.

  11. The Structure of Spatial Networks and Communities in Bicycle Sharing Systems

    PubMed Central

    Zaltz Austwick, Martin; O’Brien, Oliver; Strano, Emanuele; Viana, Matheus

    2013-01-01

    Bicycle sharing systems exist in hundreds of cities around the world, with the aim of providing a form of public transport with the associated health and environmental benefits of cycling without the burden of private ownership and maintenance. Five cities have provided research data on the journeys (start and end time and location) taking place in their bicycle sharing system. In this paper, we employ visualization, descriptive statistics and spatial and network analysis tools to explore system usage in these cities, using techniques to investigate features specific to the unique geographies of each, and uncovering similarities between different systems. Journey displacement analysis demonstrates similar journey distances across the cities sampled, and the (out)strength rank curve for the top 50 stands in each city displays a similar scaling law for each. Community detection in the derived network can identify local pockets of use, and spatial network corrections provide the opportunity for insight above and beyond proximity/popularity correlations predicted by simple spatial interaction models. PMID:24040320

  12. Comparative Study of Message Passing and Shared Memory Parallel Programming Models in Neural Network Training

    SciTech Connect

    Vitela, J.; Gordillo, J.; Cortina, L; Hanebutte, U.

    1999-12-14

    It is presented a comparative performance study of a coarse grained parallel neural network training code, implemented in both OpenMP and MPI, standards for shared memory and message passing parallel programming environments, respectively. In addition, these versions of the parallel training code are compared to an implementation utilizing SHMEM the native SGI/CRAY environment for shared memory programming. The multiprocessor platform used is a SGI/Cray Origin 2000 with up to 32 processors. It is shown that in this study, the native CRAY environment outperforms MPI for the entire range of processors used, while OpenMP shows better performance than the other two environments when using more than 19 processors. In this study, the efficiency is always greater than 60% regardless of the parallel programming environment used as well as of the number of processors.

  13. Spectrum sharing between a surveillance radar and secondary Wi-Fi networks

    NASA Astrophysics Data System (ADS)

    Hessar, Farzad; Roy, Sumit

    2016-06-01

    Co-existence between unlicensed networks that share spectrum spatio-temporally with terrestrial (e.g. Air Traffic Control) and shipborne radars in 3-GHz band is attracting significant interest. Similar to every primary-secondary coexistence scenario, interference from unlicensed devices to a primary receiver must be within acceptable bounds. In this work, we formulate the spectrum sharing problem between a pulsed, search radar (primary) and 802.11 WLAN as the secondary. We compute the protection region for such a search radar for a) a single secondary user (initially) as well as b) a random spatial distribution of multiple secondary users. Furthermore, we also analyze the interference to the WiFi devices from the radar's transmissions to estimate the impact on achievable WLAN throughput as a function of distance to the primary radar.

  14. Implicit and explicit social mentalizing: dual processes driven by a shared neural network

    PubMed Central

    Van Overwalle, Frank; Vandekerckhove, Marie

    2013-01-01

    Recent social neuroscientific evidence indicates that implicit and explicit inferences on the mind of another person (i.e., intentions, attributions or traits), are subserved by a shared mentalizing network. Under both implicit and explicit instructions, ERP studies reveal that early inferences occur at about the same time, and fMRI studies demonstrate an overlap in core mentalizing areas, including the temporo-parietal junction (TPJ) and the medial prefrontal cortex (mPFC). These results suggest a rapid shared implicit intuition followed by a slower explicit verification processes (as revealed by additional brain activation during explicit vs. implicit inferences). These data provide support for a default-adjustment dual-process framework of social mentalizing. PMID:24062663

  15. Graceful fault tolerance in large networks of microcomputers

    SciTech Connect

    Agrawal, B.K.

    1984-01-01

    This work considers the problem of fault diagnosis in a network of distributed multicomputers, and a strategy for repeated reconfiguration is presented in detail to help improve the degree of fault tolerance. The overall system diagnosability is shown to be enhanced further by constructing a large network with small well-known graphs as its basis and then applying reconfiguration techniques locally in various system partitions and exchanging diagnostic information globally. A detailed description of this new attractive approach is presented along with the diagnostic algorithm suitable for large networks of microcomputers in VLSI based distributed systems. A systematic procedure for defining near-optimal fault-tolerance graph theoretic networks is investigated which is well suited for multicomputer structures. A distributed algorithm along with a new system diagnostic theory is proposed.

  16. Pythoscape: a framework for generation of large protein similarity networks.

    PubMed

    Barber, Alan E; Babbitt, Patricia C

    2012-11-01

    Pythoscape is a framework implemented in Python for processing large protein similarity networks for visualization in other software packages. Protein similarity networks are graphical representations of sequence, structural and other similarities among proteins for which pairwise all-by-all similarity connections have been calculated. Mapping of biological and other information to network nodes or edges enables hypothesis creation about sequence-structure-function relationships across sets of related proteins. Pythoscape provides several options to calculate pairwise similarities for input sequences or structures, applies filters to network edges and defines sets of similar nodes and their associated data as single nodes (termed representative nodes) for compression of network information and output data or formatted files for visualization.

  17. The US Culture Collection Network responding to the requirements of the Nagoya Protocol on Access and Benefit Sharing

    USDA-ARS?s Scientific Manuscript database

    The US Culture Collection Network held a meeting to share information about how collections are responding to the requirements of the recently enacted Nagoya Protocol on Access to Genetic Resources and the Fair and Equitable Sharing of Benefits Arising from their Utilization to the Convention on Bio...

  18. The U.S. Culture Collection Network Responding to the Requirements of the Nagoya Protocol on Access and Benefit Sharing

    Treesearch

    Kevin McCluskey; Katharine B. Barker; Hazel A. Barton; Kyria Boundy-Mills; Daniel R. Brown; Jonathan A. Coddington; Kevin Cook; Philippe Desmeth; David Geiser; Jessie A. Glaeser; Stephanie Greene; Seogchan Kang; Michael W. Lomas; Ulrich Melcher; Scott E. Miller; David R. Nobles; Kristina J. Owens; Jerome H. Reichman; Manuela da Silva; John Wertz; Cale Whitworth; David Smith; Steven E. Lindow

    2017-01-01

    The U.S. Culture Collection Network held a meeting to share information about how culture collections are responding to the requirements of the recently enacted Nagoya Protocol on Access to Genetic Resources and the Fair and Equitable Sharing of Benefits Arising from their Utilization to the Convention on Biological Diversity (CBD). The meeting included representatives...

  19. Distributed data networks: a blueprint for Big Data sharing and healthcare analytics.

    PubMed

    Popovic, Jennifer R

    2017-01-01

    This paper defines the attributes of distributed data networks and outlines the data and analytic infrastructure needed to build and maintain a successful network. We use examples from one successful implementation of a large-scale, multisite, healthcare-related distributed data network, the U.S. Food and Drug Administration-sponsored Sentinel Initiative. Analytic infrastructure-development concepts are discussed from the perspective of promoting six pillars of analytic infrastructure: consistency, reusability, flexibility, scalability, transparency, and reproducibility. This paper also introduces one use case for machine learning algorithm development to fully utilize and advance the portfolio of population health analytics, particularly those using multisite administrative data sources.

  20. Predicting Positive and Negative Relationships in Large Social Networks.

    PubMed

    Wang, Guan-Nan; Gao, Hui; Chen, Lian; Mensah, Dennis N A; Fu, Yan

    2015-01-01

    In a social network, users hold and express positive and negative attitudes (e.g. support/opposition) towards other users. Those attitudes exhibit some kind of binary relationships among the users, which play an important role in social network analysis. However, some of those binary relationships are likely to be latent as the scale of social network increases. The essence of predicting latent binary relationships have recently began to draw researchers' attention. In this paper, we propose a machine learning algorithm for predicting positive and negative relationships in social networks inspired by structural balance theory and social status theory. More specifically, we show that when two users in the network have fewer common neighbors, the prediction accuracy of the relationship between them deteriorates. Accordingly, in the training phase, we propose a segment-based training framework to divide the training data into two subsets according to the number of common neighbors between users, and build a prediction model for each subset based on support vector machine (SVM). Moreover, to deal with large-scale social network data, we employ a sampling strategy that selects small amount of training data while maintaining high accuracy of prediction. We compare our algorithm with traditional algorithms and adaptive boosting of them. Experimental results of typical data sets show that our algorithm can deal with large social networks and consistently outperforms other methods.

  1. Predicting Positive and Negative Relationships in Large Social Networks

    PubMed Central

    Wang, Guan-Nan; Gao, Hui; Chen, Lian; Mensah, Dennis N. A.; Fu, Yan

    2015-01-01

    In a social network, users hold and express positive and negative attitudes (e.g. support/opposition) towards other users. Those attitudes exhibit some kind of binary relationships among the users, which play an important role in social network analysis. However, some of those binary relationships are likely to be latent as the scale of social network increases. The essence of predicting latent binary relationships have recently began to draw researchers' attention. In this paper, we propose a machine learning algorithm for predicting positive and negative relationships in social networks inspired by structural balance theory and social status theory. More specifically, we show that when two users in the network have fewer common neighbors, the prediction accuracy of the relationship between them deteriorates. Accordingly, in the training phase, we propose a segment-based training framework to divide the training data into two subsets according to the number of common neighbors between users, and build a prediction model for each subset based on support vector machine (SVM). Moreover, to deal with large-scale social network data, we employ a sampling strategy that selects small amount of training data while maintaining high accuracy of prediction. We compare our algorithm with traditional algorithms and adaptive boosting of them. Experimental results of typical data sets show that our algorithm can deal with large social networks and consistently outperforms other methods. PMID:26075404

  2. Experimental single qubit quantum secret sharing in a fiber network configuration.

    PubMed

    Ma, Hai-Qiang; Wei, Ke-Jin; Yang, Jian-Hui

    2013-11-01

    We present a robust single-photon quantum secret sharing (QSS) scheme with phase encoding in three-party implementations and a design way of more parties over a 50 km single-mode fiber network using a single QSS protocol. This scheme automatically provides perfect compensation for birefringence. A high visibility of 99.4% is obtained over three hours in visibility and stability measurements without any system adjustments, showing good potential for practical systems. Furthermore, polarization-insensitive phase modulators are realized using this system.

  3. Avoiding and tolerating latency in large-scale next-generation shared-memory multiprocessors

    NASA Technical Reports Server (NTRS)

    Probst, David K.

    1993-01-01

    A scalable solution to the memory-latency problem is necessary to prevent the large latencies of synchronization and memory operations inherent in large-scale shared-memory multiprocessors from reducing high performance. We distinguish latency avoidance and latency tolerance. Latency is avoided when data is brought to nearby locales for future reference. Latency is tolerated when references are overlapped with other computation. Latency-avoiding locales include: processor registers, data caches used temporally, and nearby memory modules. Tolerating communication latency requires parallelism, allowing the overlap of communication and computation. Latency-tolerating techniques include: vector pipelining, data caches used spatially, prefetching in various forms, and multithreading in various forms. Relaxing the consistency model permits increased use of avoidance and tolerance techniques. Each model is a mapping from the program text to sets of partial orders on program operations; it is a convention about which temporal precedences among program operations are necessary. Information about temporal locality and parallelism constrains the use of avoidance and tolerance techniques. Suitable architectural primitives and compiler technology are required to exploit the increased freedom to reorder and overlap operations in relaxed models.

  4. Experimental performance evaluation of software defined networking (SDN) based data communication networks for large scale flexi-grid optical networks.

    PubMed

    Zhao, Yongli; He, Ruiying; Chen, Haoran; Zhang, Jie; Ji, Yuefeng; Zheng, Haomian; Lin, Yi; Wang, Xinbo

    2014-04-21

    Software defined networking (SDN) has become the focus in the current information and communication technology area because of its flexibility and programmability. It has been introduced into various network scenarios, such as datacenter networks, carrier networks, and wireless networks. Optical transport network is also regarded as an important application scenario for SDN, which is adopted as the enabling technology of data communication networks (DCN) instead of general multi-protocol label switching (GMPLS). However, the practical performance of SDN based DCN for large scale optical networks, which is very important for the technology selection in the future optical network deployment, has not been evaluated up to now. In this paper we have built a large scale flexi-grid optical network testbed with 1000 virtual optical transport nodes to evaluate the performance of SDN based DCN, including network scalability, DCN bandwidth limitation, and restoration time. A series of network performance parameters including blocking probability, bandwidth utilization, average lightpath provisioning time, and failure restoration time have been demonstrated under various network environments, such as with different traffic loads and different DCN bandwidths. The demonstration in this work can be taken as a proof for the future network deployment.

  5. The Climate-G testbed: towards a large scale data sharing environment for climate change

    NASA Astrophysics Data System (ADS)

    Aloisio, G.; Fiore, S.; Denvil, S.; Petitdidier, M.; Fox, P.; Schwichtenberg, H.; Blower, J.; Barbera, R.

    2009-04-01

    The Climate-G testbed provides an experimental large scale data environment for climate change addressing challenging data and metadata management issues. The main scope of Climate-G is to allow scientists to carry out geographical and cross-institutional climate data discovery, access, visualization and sharing. Climate-G is a multidisciplinary collaboration involving both climate and computer scientists and it currently involves several partners such as: Centro Euro-Mediterraneo per i Cambiamenti Climatici (CMCC), Institut Pierre-Simon Laplace (IPSL), Fraunhofer Institut für Algorithmen und Wissenschaftliches Rechnen (SCAI), National Center for Atmospheric Research (NCAR), University of Reading, University of Catania and University of Salento. To perform distributed metadata search and discovery, we adopted a CMCC metadata solution (which provides a high level of scalability, transparency, fault tolerance and autonomy) leveraging both on P2P and grid technologies (GRelC Data Access and Integration Service). Moreover, data are available through OPeNDAP/THREDDS services, Live Access Server as well as the OGC compliant Web Map Service and they can be downloaded, visualized, accessed into the proposed environment through the Climate-G Data Distribution Centre (DDC), the web gateway to the Climate-G digital library. The DDC is a data-grid portal allowing users to easily, securely and transparently perform search/discovery, metadata management, data access, data visualization, etc. Godiva2 (integrated into the DDC) displays 2D maps (and animations) and also exports maps for display on the Google Earth virtual globe. Presently, Climate-G publishes (through the DDC) about 2TB of data related to the ENSEMBLES project (also including distributed replicas of data) as well as to the IPCC AR4. The main results of the proposed work are: wide data access/sharing environment for climate change; P2P/grid metadata approach; production-level Climate-G DDC; high quality tools for

  6. The development and achievement of a healthy cities network in Taiwan: sharing leadership and partnership building.

    PubMed

    Hu, Susan C; Kuo, Hsien-Wen

    2016-03-01

    The World Health Organization (WHO) Healthy Cities (HC) projects are the best known of the settings-based approaches to health promotion. They engage local governments in health development through a process of political commitment, institutional change, capacity-building, partnership-based planning and innovative projects. Many cities have promoted HC projects in Taiwan since 2002. In 2008, the Taiwan Alliance for Healthy Cities (TAHC) was launched to assist local governments in effectively establishing, operating and promoting HC projects. In this article, we share our experiences of establishing a platform and network to promote the HC program in Taiwan. Based on individual city profiles and governance in Taiwan, the TAHC developed a well-organized framework and model to encourage strong leadership in local governments and to promote participation and engagement in their communities. In the last 6 years, leaders from Taiwan's local governments in HC networks have integrated the HC concepts into their governance models, actively engaging and combining various resources with practical expertise and private sectors. The network of health in Taiwan allows each city to develop its unique perspective on the HC projects. Using this method, not only local government meets its needs, but also increases governance efficiency and effectiveness, resulting in the promotion of its citizens' overall sustainable urban health development. This HC network in Taiwan has partnerships with government and non-governmental organizations (NGOs), with academic support and citizen involvement, a dynamic data collection system and demonstrated leadership in the sharing of information in the Asian region. © The Author(s) 2016.

  7. Congenital blindness is associated with large-scale reorganization of anatomical networks

    PubMed Central

    Hasson, Uri; Andric, Michael; Atilgan, Hicret; Collignon, Olivier

    2016-01-01

    Blindness is a unique model for understanding the role of experience in the development of the brain's functional and anatomical architecture. Documenting changes in the structure of anatomical networks for this population would substantiate the notion that the brain's core network-level organization may undergo neuroplasticity as a result of life-long experience. To examine this issue, we compared whole-brain networks of regional cortical-thickness covariance in early blind and matched sighted individuals. This covariance is thought to reflect signatures of integration between systems involved in similar perceptual/cognitive functions. Using graph-theoretic metrics, we identified a unique mode of anatomical reorganization in the blind that differed from that found for sighted. This was seen in that network partition structures derived from subgroups of blind were more similar to each other than they were to partitions derived from sighted. Notably, after deriving network partitions, we found that language and visual regions tended to reside within separate modules in sighted but showed a pattern of merging into shared modules in the blind. Our study demonstrates that early visual deprivation triggers a systematic large-scale reorganization of whole-brain cortical-thickness networks, suggesting changes in how occipital regions interface with other functional networks in the congenitally blind. PMID:26767944

  8. Congenital blindness is associated with large-scale reorganization of anatomical networks.

    PubMed

    Hasson, Uri; Andric, Michael; Atilgan, Hicret; Collignon, Olivier

    2016-03-01

    Blindness is a unique model for understanding the role of experience in the development of the brain's functional and anatomical architecture. Documenting changes in the structure of anatomical networks for this population would substantiate the notion that the brain's core network-level organization may undergo neuroplasticity as a result of life-long experience. To examine this issue, we compared whole-brain networks of regional cortical-thickness covariance in early blind and matched sighted individuals. This covariance is thought to reflect signatures of integration between systems involved in similar perceptual/cognitive functions. Using graph-theoretic metrics, we identified a unique mode of anatomical reorganization in the blind that differed from that found for sighted. This was seen in that network partition structures derived from subgroups of blind were more similar to each other than they were to partitions derived from sighted. Notably, after deriving network partitions, we found that language and visual regions tended to reside within separate modules in sighted but showed a pattern of merging into shared modules in the blind. Our study demonstrates that early visual deprivation triggers a systematic large-scale reorganization of whole-brain cortical-thickness networks, suggesting changes in how occipital regions interface with other functional networks in the congenitally blind.

  9. A Game-Theoretic Approach for Opportunistic Spectrum Sharing in Cognitive Radio Networks with Incomplete Information

    NASA Astrophysics Data System (ADS)

    Tan, Xuesong Jonathan; Li, Liang; Guo, Wei

    One important issue in cognitive transmission is for multiple secondary users to dynamically acquire spare spectrum from the single primary user. The existing spectrum sharing scheme adopts a deterministic Cournot game to formulate this problem, of which the solution is the Nash equilibrium. This formulation is based on two implicit assumptions. First, each secondary user is willing to fully exchange transmission parameters with all others and hence knows their complete information. Second, the unused spectrum of the primary user for spectrum sharing is always larger than the total frequency demand of all secondary users at the Nash equilibrium. However, both assumptions may not be true in general. To remedy this, the present paper considers a more realistic assumption of incomplete information, i.e., each secondary user may choose to conceal their private information for achieving higher transmission benefit. Following this assumption and given that the unused bandwidth of the primary user is large enough, we adopt a probabilistic Cournot game to formulate an opportunistic spectrum sharing scheme for maximizing the total benefit of all secondary users. Bayesian equilibrium is considered as the solution of this game. Moreover, we prove that a secondary user can improve their expected benefit by actively hiding its transmission parameters and increasing their variance. On the other hand, when the unused spectrum of the primary user is smaller than the maximal total frequency demand of all secondary users at the Bayesian equilibrium, we formulate a constrained optimization problem for the primary user to maximize its profit in spectrum sharing and revise the proposed spectrum sharing scheme to solve this problem heuristically. This provides a unified approach to overcome the aforementioned two limitations of the existing spectrum sharing scheme.

  10. Aberrant intra-salience network dynamic functional connectivity impairs large-scale network interactions in schizophrenia.

    PubMed

    Wang, Xiangpeng; Zhang, Wenwen; Sun, Yujing; Hu, Min; Chen, Antao

    2016-12-01

    Aberrant functional interactions between several large-scale networks, especially the central executive network (CEN), the default mode network (DMN) and the salience network (SN), have been postulated as core pathophysiologic features of schizophrenia; however, the attributing factors of which remain unclear. The study employed resting-state fMRI with 77 participants (42 patients and 35 controls). We performed dynamic functional connectivity (DFC) and functional connectivity (FC) analyses to explore the connectivity patterns of these networks. Furthermore, we performed a structural equation model (SEM) analysis to explore the possible role of the SN in modulating network interactions. The results were as follows: (1) The inter-network connectivity showed decreased connectivity strength and increased time-varying instability in schizophrenia; (2) The SN manifested schizophrenic intra-network dysfunctions in both the FC and DFC patterns; (3) The connectivity properties of the SN were effective in discriminating controls from patients; (4) In patients, the dynamic intra-SN connectivity negatively predicted the inter-network FC, and this effect was mediated by intra-SN connectivity strength. These findings suggest that schizophrenia show systematic deficits in temporal stability of large-scale network connectivity. Furthermore, aberrant network interactions in schizophrenia could be attributed to instable intra-SN connectivity and the dysfunction of the SN may be an intrinsic biomarker of the disease. Copyright © 2016 Elsevier Ltd. All rights reserved.

  11. States of mind: Emotions, body feelings, and thoughts share distributed neural networks

    PubMed Central

    Oosterwijk, Suzanne; Lindquist, Kristen A.; Anderson, Eric; Dautoff, Rebecca; Moriguchi, Yoshiya; Barrett, Lisa Feldman

    2012-01-01

    Scientists have traditionally assumed that different kinds of mental states (e.g., fear, disgust, love, memory, planning, concentration, etc.) correspond to different psychological faculties that have domain-specific correlates in the brain. Yet, growing evidence points to the constructionist hypothesis that mental states emerge from the combination of domain-general psychological processes that map to large-scale distributed brain networks. In this paper, we report a novel study testing a constructionist model of the mind in which participants generated three kinds of mental states (emotions, body feelings, or thoughts) while we measured activity within large-scale distributed brain networks using fMRI. We examined the similarity and differences in the pattern of network activity across these three classes of mental states. Consistent with a constructionist hypothesis, a combination of large-scale distributed networks contributed to emotions, thoughts, and body feelings, although these mental states differed in the relative contribution of those networks. Implications for a constructionist functional architecture of diverse mental states are discussed. PMID:22677148

  12. Semantic overlay network for large-scale spatial information indexing

    NASA Astrophysics Data System (ADS)

    Zou, Zhiqiang; Wang, Yue; Cao, Kai; Qu, Tianshan; Wang, Zhongmin

    2013-08-01

    The increased demand for online services of spatial information poses new challenges to the combined filed of Computer Science and Geographic Information Science. Amongst others, these include fast indexing of spatial data in distributed networks. In this paper we propose a novel semantic overlay network for large-scale multi-dimensional spatial information indexing, called SON_LSII, which has a hybrid structure integrating a semantic quad-tree and Chord ring. The SON_LSII is a small world overlay network that achieves a very competitive trade-off between indexing efficiency and maintenance overhead. To create SON_LSII, we use an effective semantic clustering strategy that considers two aspects, i.e., the semantic of spatial information that peer holds in overlay network and physical network performances. Based on SON_LSII, a mapping method is used to reduce the multi-dimensional features into a single dimension and an efficient indexing algorithm is presented to support complex range queries of the spatial information with a massive number of concurrent users. The results from extensive experiments demonstrate that SON_LSII is superior to existing overlay networks in various respects, including scalability, maintenance, rate of indexing hits, indexing logical hops, and adaptability. Thus, the proposed SON_LSII can be used for large-scale spatial information indexing.

  13. Spectrum sharing in cognitive radio networks--an auction-based approach.

    PubMed

    Wang, Xinbing; Li, Zheng; Xu, Pengchao; Xu, Youyun; Gao, Xinbo; Chen, Hsiao-Hwa

    2010-06-01

    Cognitive radio is emerging as a promising technique to improve the utilization of the radio frequency spectrum. In this paper, we consider the problem of spectrum sharing among primary (or "licensed") users (PUs) and secondary (or "unlicensed") users (SUs). We formulate the problem based on bandwidth auction, in which each SU makes a bid for the amount of spectrum and each PU may assign the spectrum among the SUs by itself according to the information from the SUs without degrading its own performance. We show that the auction is a noncooperative game and that Nash equilibrium (NE) can be its solution. We first consider a single-PU network to investigate the existence and uniqueness of the NE and further discuss the fairness among the SUs under given conditions. Then, we present a dynamic updating algorithm in which each SU achieves NE in a distributed manner. The stability condition of the dynamic behavior for this spectrum-sharing scheme is studied. The discussion is generalized to the case in which there are multiple PUs in the network, where the properties of the NE are shown under appropriate conditions. Simulations were used to evaluate the system performance and verify the effectiveness of the proposed algorithm.

  14. EPPS: Efficient and Privacy-Preserving Personal Health Information Sharing in Mobile Healthcare Social Networks.

    PubMed

    Jiang, Shunrong; Zhu, Xiaoyan; Wang, Liangmin

    2015-09-03

    Mobile healthcare social networks (MHSNs) have emerged as a promising next-generation healthcare system, which will significantly improve the quality of life. However, there are many security and privacy concerns before personal health information (PHI) is shared with other parities. To ensure patients' full control over their PHI, we propose a fine-grained and scalable data access control scheme based on attribute-based encryption (ABE). Besides, policies themselves for PHI sharing may be sensitive and may reveal information about underlying PHI or about data owners or recipients. In our scheme, we let each attribute contain an attribute name and its value and adopt the Bloom filter to efficiently check attributes before decryption. Thus, the data privacy and policy privacy can be preserved in our proposed scheme. Moreover, considering the fact that the computational cost grows with the complexity of the access policy and the limitation of the resource and energy in a smart phone, we outsource ABE decryption to the cloud while preventing the cloud from learning anything about the content and access policy. The security and performance analysis is carried out to demonstrate that our proposed scheme can achieve fine-grained access policies for PHI sharing in MHSNs.

  15. EPPS: Efficient and Privacy-Preserving Personal Health Information Sharing in Mobile Healthcare Social Networks

    PubMed Central

    Jiang, Shunrong; Zhu, Xiaoyan; Wang, Liangmin

    2015-01-01

    Mobile healthcare social networks (MHSNs) have emerged as a promising next-generation healthcare system, which will significantly improve the quality of life. However, there are many security and privacy concerns before personal health information (PHI) is shared with other parities. To ensure patients’ full control over their PHI, we propose a fine-grained and scalable data access control scheme based on attribute-based encryption (ABE). Besides, policies themselves for PHI sharing may be sensitive and may reveal information about underlying PHI or about data owners or recipients. In our scheme, we let each attribute contain an attribute name and its value and adopt the Bloom filter to efficiently check attributes before decryption. Thus, the data privacy and policy privacy can be preserved in our proposed scheme. Moreover, considering the fact that the computational cost grows with the complexity of the access policy and the limitation of the resource and energy in a smart phone, we outsource ABE decryption to the cloud while preventing the cloud from learning anything about the content and access policy. The security and performance analysis is carried out to demonstrate that our proposed scheme can achieve fine-grained access policies for PHI sharing in MHSNs. PMID:26404300

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-01-01

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

  18. Clustering algorithm for determining community structure in large networks

    NASA Astrophysics Data System (ADS)

    Pujol, Josep M.; Béjar, Javier; Delgado, Jordi

    2006-07-01

    We propose an algorithm to find the community structure in complex networks based on the combination of spectral analysis and modularity optimization. The clustering produced by our algorithm is as accurate as the best algorithms on the literature of modularity optimization; however, the main asset of the algorithm is its efficiency. The best match for our algorithm is Newman’s fast algorithm, which is the reference algorithm for clustering in large networks due to its efficiency. When both algorithms are compared, our algorithm outperforms the fast algorithm both in efficiency and accuracy of the clustering, in terms of modularity. Thus, the results suggest that the proposed algorithm is a good choice to analyze the community structure of medium and large networks in the range of tens and hundreds of thousand vertices.

  19. DESIGN OF LARGE-SCALE AIR MONITORING NETWORKS

    EPA Science Inventory

    The potential effects of air pollution on human health have received much attention in recent years. In the U.S. and other countries, there are extensive large-scale monitoring networks designed to collect data to inform the public of exposure risks to air pollution. A major crit...

  20. DESIGN OF LARGE-SCALE AIR MONITORING NETWORKS

    EPA Science Inventory

    The potential effects of air pollution on human health have received much attention in recent years. In the U.S. and other countries, there are extensive large-scale monitoring networks designed to collect data to inform the public of exposure risks to air pollution. A major crit...

  1. Multi-dimension and Comprehensive Assessment on the Utilizing and Sharing of Regional Large-Scale Scientific Equipment

    PubMed Central

    Li, Chen; Yongbo, Lv; Chi, Chen

    2015-01-01

    Based on the data from 30 provincial regions in China, an assessment and empirical analysis was carried out on the utilizing and sharing of the large-scale scientific equipment with a comprehensive assessment model established on the three dimensions, namely, equipment, utilization and sharing. The assessment results were interpreted in light of relevant policies. The results showed that on the whole, the overall development level in the provincial regions in eastern and central China is higher than that in western China. This is mostly because of the large gap among the different provincial regions with respect to the equipped level. But in terms of utilizing and sharing, some of the Western provincial regions, such as Ningxia, perform well, which is worthy of our attention. Policy adjustment targeting at the differentiation, elevation of the capacity of the equipment management personnel, perfection of the sharing and cooperation platform, and the promotion of the establishment of open sharing funds, are all important measures to promote the utilization and sharing of the large-scale scientific equipment and to narrow the gap among different regions. PMID:25937850

  2. Large-Capacity Three-Party Quantum Digital Secret Sharing Using Three Particular Matrices Coding

    NASA Astrophysics Data System (ADS)

    Lai, Hong; Luo, Ming-Xing; Pieprzyk, Josef; Tao, Li; Liu, Zhi-Ming; Orgun, Mehmet A.

    2016-11-01

    In this paper, we develop a large-capacity quantum digital secret sharing (QDSS) scheme, combined the Fibonacci- and Lucas-valued orbital angular momentum (OAM) entanglement with the recursive Fibonacci and Lucas matrices. To be exact, Alice prepares pairs of photons in the Fibonacci- and Lucas-valued OAM entangled states, and then allocates them to two participants, say, Bob and Charlie, to establish the secret key. Moreover, the available Fibonacci and Lucas values from the matching entangled states are used as the seed for generating the Fibonacci and Lucas matrices. This is achieved because the entries of the Fibonacci and Lucas matrices are recursive. The secret key can only be obtained jointly by Bob and Charlie, who can further recover the secret. Its security is based on the facts that nonorthogonal states are indistinguishable, and Bob or Charlie detects a Fibonacci number, there is still a twofold uncertainty for Charlie' (Bob') detected value. Supported by the Fundamental Research Funds for the Central Universities under Grant No. XDJK2016C043 and the Doctoral Program of Higher Education under Grant No. SWU115091, the National Natural Science Foundation of China under Grant No. 61303039, the Fundamental Research Funds for the Central Universities under Grant No. XDJK2015C153 and the Doctoral Program of Higher Education under Grant No. SWU114112, and the Financial Support the 1000-Plan of Chongqing by Southwest University under Grant No. SWU116007

  3. Folksonomical P2P File Sharing Networks Using Vectorized KANSEI Information as Search Tags

    NASA Astrophysics Data System (ADS)

    Ohnishi, Kei; Yoshida, Kaori; Oie, Yuji

    We present the concept of folksonomical peer-to-peer (P2P) file sharing networks that allow participants (peers) to freely assign structured search tags to files. These networks are similar to folksonomies in the present Web from the point of view that users assign search tags to information distributed over a network. As a concrete example, we consider an unstructured P2P network using vectorized Kansei (human sensitivity) information as structured search tags for file search. Vectorized Kansei information as search tags indicates what participants feel about their files and is assigned by the participant to each of their files. A search query also has the same form of search tags and indicates what participants want to feel about files that they will eventually obtain. A method that enables file search using vectorized Kansei information is the Kansei query-forwarding method, which probabilistically propagates a search query to peers that are likely to hold more files having search tags that are similar to the query. The similarity between the search query and the search tags is measured in terms of their dot product. The simulation experiments examine if the Kansei query-forwarding method can provide equal search performance for all peers in a network in which only the Kansei information and the tendency with respect to file collection are different among all of the peers. The simulation results show that the Kansei query forwarding method and a random-walk-based query forwarding method, for comparison, work effectively in different situations and are complementary. Furthermore, the Kansei query forwarding method is shown, through simulations, to be superior to or equal to the random-walk based one in terms of search speed.

  4. Development of Large-Scale Functional Brain Networks in Children

    PubMed Central

    Supekar, Kaustubh; Musen, Mark; Menon, Vinod

    2009-01-01

    The ontogeny of large-scale functional organization of the human brain is not well understood. Here we use network analysis of intrinsic functional connectivity to characterize the organization of brain networks in 23 children (ages 7–9 y) and 22 young-adults (ages 19–22 y). Comparison of network properties, including path-length, clustering-coefficient, hierarchy, and regional connectivity, revealed that although children and young-adults' brains have similar “small-world” organization at the global level, they differ significantly in hierarchical organization and interregional connectivity. We found that subcortical areas were more strongly connected with primary sensory, association, and paralimbic areas in children, whereas young-adults showed stronger cortico-cortical connectivity between paralimbic, limbic, and association areas. Further, combined analysis of functional connectivity with wiring distance measures derived from white-matter fiber tracking revealed that the development of large-scale brain networks is characterized by weakening of short-range functional connectivity and strengthening of long-range functional connectivity. Importantly, our findings show that the dynamic process of over-connectivity followed by pruning, which rewires connectivity at the neuronal level, also operates at the systems level, helping to reconfigure and rebalance subcortical and paralimbic connectivity in the developing brain. Our study demonstrates the usefulness of network analysis of brain connectivity to elucidate key principles underlying functional brain maturation, paving the way for novel studies of disrupted brain connectivity in neurodevelopmental disorders such as autism. PMID:19621066

  5. Using Agent Base Models to Optimize Large Scale Network for Large System Inventories

    NASA Technical Reports Server (NTRS)

    Shameldin, Ramez Ahmed; Bowling, Shannon R.

    2010-01-01

    The aim of this paper is to use Agent Base Models (ABM) to optimize large scale network handling capabilities for large system inventories and to implement strategies for the purpose of reducing capital expenses. The models used in this paper either use computational algorithms or procedure implementations developed by Matlab to simulate agent based models in a principal programming language and mathematical theory using clusters, these clusters work as a high performance computational performance to run the program in parallel computational. In both cases, a model is defined as compilation of a set of structures and processes assumed to underlie the behavior of a network system.

  6. Application of the EVEX resource to event extraction and network construction: Shared Task entry and result analysis

    PubMed Central

    2015-01-01

    Background Modern methods for mining biomolecular interactions from literature typically make predictions based solely on the immediate textual context, in effect a single sentence. No prior work has been published on extending this context to the information automatically gathered from the whole biomedical literature. Thus, our motivation for this study is to explore whether mutually supporting evidence, aggregated across several documents can be utilized to improve the performance of the state-of-the-art event extraction systems. In this paper, we describe our participation in the latest BioNLP Shared Task using the large-scale text mining resource EVEX. We participated in the Genia Event Extraction (GE) and Gene Regulation Network (GRN) tasks with two separate systems. In the GE task, we implemented a re-ranking approach to improve the precision of an existing event extraction system, incorporating features from the EVEX resource. In the GRN task, our system relied solely on the EVEX resource and utilized a rule-based conversion algorithm between the EVEX and GRN formats. Results In the GE task, our re-ranking approach led to a modest performance increase and resulted in the first rank of the official Shared Task results with 50.97% F-score. Additionally, in this paper we explore and evaluate the usage of distributed vector representations for this challenge. In the GRN task, we ranked fifth in the official results with a strict/relaxed SER score of 0.92/0.81 respectively. To try and improve upon these results, we have implemented a novel machine learning based conversion system and benchmarked its performance against the original rule-based system. Conclusions For the GRN task, we were able to produce a gene regulatory network from the EVEX data, warranting the use of such generic large-scale text mining data in network biology settings. A detailed performance and error analysis provides more insight into the relatively low recall rates. In the GE task we

  7. Think locally, act locally: Detection of small, medium-sized, and large communities in large networks

    NASA Astrophysics Data System (ADS)

    Jeub, Lucas G. S.; Balachandran, Prakash; Porter, Mason A.; Mucha, Peter J.; Mahoney, Michael W.

    2015-01-01

    It is common in the study of networks to investigate intermediate-sized (or "meso-scale") features to try to gain an understanding of network structure and function. For example, numerous algorithms have been developed to try to identify "communities," which are typically construed as sets of nodes with denser connections internally than with the remainder of a network. In this paper, we adopt a complementary perspective that communities are associated with bottlenecks of locally biased dynamical processes that begin at seed sets of nodes, and we employ several different community-identification procedures (using diffusion-based and geodesic-based dynamics) to investigate community quality as a function of community size. Using several empirical and synthetic networks, we identify several distinct scenarios for "size-resolved community structure" that can arise in real (and realistic) networks: (1) the best small groups of nodes can be better than the best large groups (for a given formulation of the idea of a good community); (2) the best small groups can have a quality that is comparable to the best medium-sized and large groups; and (3) the best small groups of nodes can be worse than the best large groups. As we discuss in detail, which of these three cases holds for a given network can make an enormous difference when investigating and making claims about network community structure, and it is important to take this into account to obtain reliable downstream conclusions. Depending on which scenario holds, one may or may not be able to successfully identify "good" communities in a given network (and good communities might not even exist for a given community quality measure), the manner in which different small communities fit together to form meso-scale network structures can be very different, and processes such as viral propagation and information diffusion can exhibit very different dynamics. In addition, our results suggest that, for many large realistic

  8. The new alchemy: Online networking, data sharing and research activity distribution tools for scientists

    PubMed Central

    Williams, Antony J.; Peck, Lou; Ekins, Sean

    2017-01-01

    There is an abundance of free online tools accessible to scientists and others that can be used for online networking, data sharing and measuring research impact. Despite this, few scientists know how these tools can be used or fail to take advantage of using them as an integrated pipeline to raise awareness of their research outputs. In this article, the authors describe their experiences with these tools and how they can make best use of them to make their scientific research generally more accessible, extending its reach beyond their own direct networks, and communicating their ideas to new audiences. These efforts have the potential to drive science by sparking new collaborations and interdisciplinary research projects that may lead to future publications, funding and commercial opportunities. The intent of this article is to: describe some of these freely accessible networking tools and affiliated products; demonstrate from our own experiences how they can be utilized effectively; and, inspire their adoption by new users for the benefit of science. PMID:28928951

  9. Spectrum Sharing Based on a Bertrand Game in Cognitive Radio Sensor Networks

    PubMed Central

    Zeng, Biqing; Zhang, Chi; Hu, Pianpian; Wang, Shengyu

    2017-01-01

    In the study of power control and allocation based on pricing, the utility of secondary users is usually studied from the perspective of the signal to noise ratio. The study of secondary user utility from the perspective of communication demand can not only promote the secondary users to meet the maximum communication needs, but also to maximize the utilization of spectrum resources, however, research in this area is lacking, so from the viewpoint of meeting the demand of network communication, this paper designs a two stage model to solve spectrum leasing and allocation problem in cognitive radio sensor networks (CRSNs). In the first stage, the secondary base station collects the secondary network communication requirements, and rents spectrum resources from several primary base stations using the Bertrand game to model the transaction behavior of the primary base station and secondary base station. The second stage, the subcarriers and power allocation problem of secondary base stations is defined as a nonlinear programming problem to be solved based on Nash bargaining. The simulation results show that the proposed model can satisfy the communication requirements of each user in a fair and efficient way compared to other spectrum sharing schemes. PMID:28067850

  10. The new alchemy: Online networking, data sharing and research activity distribution tools for scientists.

    PubMed

    Williams, Antony J; Peck, Lou; Ekins, Sean

    2017-01-01

    There is an abundance of free online tools accessible to scientists and others that can be used for online networking, data sharing and measuring research impact. Despite this, few scientists know how these tools can be used or fail to take advantage of using them as an integrated pipeline to raise awareness of their research outputs. In this article, the authors describe their experiences with these tools and how they can make best use of them to make their scientific research generally more accessible, extending its reach beyond their own direct networks, and communicating their ideas to new audiences. These efforts have the potential to drive science by sparking new collaborations and interdisciplinary research projects that may lead to future publications, funding and commercial opportunities. The intent of this article is to: describe some of these freely accessible networking tools and affiliated products; demonstrate from our own experiences how they can be utilized effectively; and, inspire their adoption by new users for the benefit of science.

  11. Spectrum Sharing Based on a Bertrand Game in Cognitive Radio Sensor Networks.

    PubMed

    Zeng, Biqing; Zhang, Chi; Hu, Pianpian; Wang, Shengyu

    2017-01-07

    In the study of power control and allocation based on pricing, the utility of secondary users is usually studied from the perspective of the signal to noise ratio. The study of secondary user utility from the perspective of communication demand can not only promote the secondary users to meet the maximum communication needs, but also to maximize the utilization of spectrum resources, however, research in this area is lacking, so from the viewpoint of meeting the demand of network communication, this paper designs a two stage model to solve spectrum leasing and allocation problem in cognitive radio sensor networks (CRSNs). In the first stage, the secondary base station collects the secondary network communication requirements, and rents spectrum resources from several primary base stations using the Bertrand game to model the transaction behavior of the primary base station and secondary base station. The second stage, the subcarriers and power allocation problem of secondary base stations is defined as a nonlinear programming problem to be solved based on Nash bargaining. The simulation results show that the proposed model can satisfy the communication requirements of each user in a fair and efficient way compared to other spectrum sharing schemes.

  12. Development of large-scale functional networks over the lifespan.

    PubMed

    Schlee, Winfried; Leirer, Vera; Kolassa, Stephan; Thurm, Franka; Elbert, Thomas; Kolassa, Iris-Tatjana

    2012-10-01

    The development of large-scale functional organization of the human brain across the lifespan is not well understood. Here we used magnetoencephalographic recordings of 53 adults (ages 18-89) to characterize functional brain networks in the resting state. Slow frequencies engage larger networks than higher frequencies and show different development over the lifespan. Networks in the delta (2-4 Hz) frequency range decrease, while networks in the beta/gamma frequency range (> 16 Hz) increase in size with advancing age. Results show that the right frontal lobe and the temporal areas in both hemispheres are important relay stations in the expanding high-frequency networks. Neuropsychological tests confirmed the tendency of cognitive decline with older age. The decrease in visual memory and visuoconstructive functions was strongly associated with the age-dependent enhancement of functional connectivity in both temporal lobes. Using functional network analysis this study elucidates important neuronal principles underlying age-related cognitive decline paving mental deterioration in senescence. Copyright © 2012 Elsevier Inc. All rights reserved.

  13. Call Admission Control on Single Node Networks under Output Rate-Controlled Generalized Processor Sharing (ORC-GPS) Scheduler

    NASA Astrophysics Data System (ADS)

    Hanada, Masaki; Nakazato, Hidenori; Watanabe, Hitoshi

    Multimedia applications such as music or video streaming, video teleconferencing and IP telephony are flourishing in packet-switched networks. Applications that generate such real-time data can have very diverse quality-of-service (QoS) requirements. In order to guarantee diverse QoS requirements, the combined use of a packet scheduling algorithm based on Generalized Processor Sharing (GPS) and leaky bucket traffic regulator is the most successful QoS mechanism. GPS can provide a minimum guaranteed service rate for each session and tight delay bounds for leaky bucket constrained sessions. However, the delay bounds for leaky bucket constrained sessions under GPS are unnecessarily large because each session is served according to its associated constant weight until the session buffer is empty. In order to solve this problem, a scheduling policy called Output Rate-Controlled Generalized Processor Sharing (ORC-GPS) was proposed in [17]. ORC-GPS is a rate-based scheduling like GPS, and controls the service rate in order to lower the delay bounds for leaky bucket constrained sessions. In this paper, we propose a call admission control (CAC) algorithm for ORC-GPS, for leaky-bucket constrained sessions with deterministic delay requirements. This CAC algorithm for ORC-GPS determines the optimal values of parameters of ORC-GPS from the deterministic delay requirements of the sessions. In numerical experiments, we compare the CAC algorithm for ORC-GPS with one for GPS in terms of schedulable region and computational complexity.

  14. 78 FR 7464 - Large Scale Networking (LSN)-Middleware And Grid Interagency Coordination (MAGIC) Team

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-02-01

    ... Large Scale Networking (LSN)--Middleware And Grid Interagency Coordination (MAGIC) Team AGENCY: The Networking and Information Technology Research and Development (NITRD) National Coordination Office (NCO... Team reports to the Large Scale Networking (LSN) Coordinating Group (CG). Public Comments: The...

  15. Developmental changes in large-scale network connectivity in autism.

    PubMed

    Nomi, Jason S; Uddin, Lucina Q

    2015-01-01

    Disrupted cortical connectivity is thought to underlie the complex cognitive and behavior profile observed in individuals with autism spectrum disorder (ASD). Previous neuroimaging research has identified patterns of both functional hypo- and hyper-connectivity in individuals with ASD. A recent theory attempting to reconcile conflicting results in the literature proposes that hyper-connectivity of brain networks may be more characteristic of young children with ASD, while hypo-connectivity may be more prevalent in adolescents and adults with the disorder when compared to typical development (TD) (Uddin etal., 2013). Previous work has examined only young children, mixed groups of children and adolescents, or adult cohorts in separate studies, leaving open the question of developmental influences on functional brain connectivity in ASD. The current study tests this developmental hypothesis by examining within- and between-network resting state functional connectivity in a large sample of 26 children, 28 adolescents, and 18 adults with ASD and age- and IQ-matchedTD individuals for the first time using an entirely data-driven approach. Independent component analyses (ICA) and dual regression was applied to data from three age cohorts to examine the effects of participant age on patterns of within-networkwhole-brain functional connectivity in individuals with ASD compared with TD individuals. Between-network connectivity differences were examined for each age cohort by comparing correlations between ICA components across groups. We find that in the youngest cohort (age 11 and under), children with ASD exhibit hyper-connectivity within large-scale brain networks as well as decreased between-network connectivity compared with age-matchedTD children. In contrast, adolescents with ASD (age 11-18) do not differ from TD adolescents in within-network connectivity, yet show decreased between-network connectivity compared with TD adolescents. Adults with ASD show no within- or

  16. Evidence for Large Complex Networks of Plant Short Silencing RNAs

    PubMed Central

    MacLean, Daniel; Elina, Nataliya; Havecker, Ericka R.; Heimstaedt, Susanne B.; Studholme, David J.; Baulcombe, David C.

    2010-01-01

    Background In plants and animals there are many classes of short RNAs that carry out a wide range of functions within the cell; short silencing RNAs (ssRNAs) of 21–25 nucleotides in length are produced from double-stranded RNA precursors by the protein Dicer and guide nucleases and other proteins to their RNA targets through base pairing interactions. The consequence of this process is degradation of the targeted RNA, suppression of its translation or initiation of secondary ssRNA production. The secondary ssRNAs in turn could then initiate further layers of ssRNA production to form extensive cascades and networks of interacting RNA [1]. Previous empirical analysis in plants established the existence of small secondary ssRNA cascade [2], in which a single instance of this event occurred but it was not known whether there are other more extensive networks of secondary sRNA production. Methodology/Principal Findings We generated a network by predicting targets of ssRNA populations obtained from high-throughput sequencing experiments. The topology of the network shows it to have power law connectivity distribution, to be dissortative, highly clustered and composed of multiple components. We also identify protein families, PPR and ULP1, that act as hubs within the network. Comparison of the repetition of genomic sub-sequences of ssRNA length between Arabidopsis and E.coli suggest that the network structure is made possible by the underlying repetitiveness in the genome sequence. Conclusions/Significance Together our results provide good evidence for the existence of a large, robust ssRNA interaction network with distinct regulatory function. Such a network could have a massive effect on the regulation of gene expression via mediation of transcript levels. PMID:20360863

  17. Effects of a cost-sharing exemption on use of preventive services at one large employer.

    PubMed

    Busch, Susan H; Barry, Colleen L; Vegso, Sally J; Sindelar, Jody L; Cullen, Mark R

    2006-01-01

    In 2004, Alcoa introduced a new health benefit for a portion of its workforce, which eliminated cost sharing for preventive care while increasing cost sharing for many other services. In this era of increased consumerism, Alcoa's benefit redesign constituted an effort to reduce health care costs while preserving use of targeted services. Taking advantage of a unique natural experiment, we find that Alcoa was able to maintain rates of preventive service use. This evidence suggests that differential cost sharing can be used to preserve the use of critical health care services.

  18. Dataworks for GNSS: Software for Supporting Data Sharing and Federation of Geodetic Networks

    NASA Astrophysics Data System (ADS)

    Boler, F. M.; Meertens, C. M.; Miller, M. M.; Wier, S.; Rost, M.; Matykiewicz, J.

    2015-12-01

    Continuously-operating Global Navigation Satellite System (GNSS) networks are increasingly being installed globally for a wide variety of science and societal applications. GNSS enables Earth science research in areas including tectonic plate interactions, crustal deformation in response to loading by tectonics, magmatism, water and ice, and the dynamics of water - and thereby energy transfer - in the atmosphere at regional scale. The many individual scientists and organizations that set up GNSS stations globally are often open to sharing data, but lack the resources or expertise to deploy systems and software to manage and curate data and metadata and provide user tools that would support data sharing. UNAVCO previously gained experience in facilitating data sharing through the NASA-supported development of the Geodesy Seamless Archive Centers (GSAC) open source software. GSAC provides web interfaces and simple web services for data and metadata discovery and access, supports federation of multiple data centers, and simplifies transfer of data and metadata to long-term archives. The NSF supported the dissemination of GSAC to multiple European data centers forming the European Plate Observing System. To expand upon GSAC to provide end-to-end, instrument-to-distribution capability, UNAVCO developed Dataworks for GNSS with NSF funding to the COCONet project, and deployed this software on systems that are now operating as Regional GNSS Data Centers as part of the NSF-funded TLALOCNet and COCONet projects. Dataworks consists of software modules written in Python and Java for data acquisition, management and sharing. There are modules for GNSS receiver control and data download, a database schema for metadata, tools for metadata handling, ingest software to manage file metadata, data file management scripts, GSAC, scripts for mirroring station data and metadata from partner GSACs, and extensive software and operator documentation. UNAVCO plans to provide a cloud VM

  19. Modeling Failure Propagation in Large-Scale Engineering Networks

    NASA Astrophysics Data System (ADS)

    Schläpfer, Markus; Shapiro, Jonathan L.

    The simultaneous unavailability of several technical components within large-scale engineering systems can lead to high stress, rendering them prone to cascading events. In order to gain qualitative insights into the failure propagation mechanisms resulting from independent outages, we adopt a minimalistic model representing the components and their interdependencies by an undirected, unweighted network. The failure dynamics are modeled by an anticipated accelerated “wearout” process being dependent on the initial degree of a node and on the number of failed nearest neighbors. The results of the stochastic simulations imply that the influence of the network topology on the speed of the cascade highly depends on how the number of failed nearest neighbors shortens the life expectancy of a node. As a formal description of the decaying networks we propose a continuous-time mean field approximation, estimating the average failure rate of the nearest neighbors of a node based on the degree-degree distribution.

  20. Distributed Coordinated Control of Large-Scale Nonlinear Networks

    DOE PAGES

    Kundu, Soumya; Anghel, Marian

    2015-11-08

    We provide a distributed coordinated approach to the stability analysis and control design of largescale nonlinear dynamical systems by using a vector Lyapunov functions approach. In this formulation the large-scale system is decomposed into a network of interacting subsystems and the stability of the system is analyzed through a comparison system. However finding such comparison system is not trivial. In this work, we propose a sum-of-squares based completely decentralized approach for computing the comparison systems for networks of nonlinear systems. Moreover, based on the comparison systems, we introduce a distributed optimal control strategy in which the individual subsystems (agents) coordinatemore » with their immediate neighbors to design local control policies that can exponentially stabilize the full system under initial disturbances.We illustrate the control algorithm on a network of interacting Van der Pol systems.« less

  1. Distributed Coordinated Control of Large-Scale Nonlinear Networks

    SciTech Connect

    Kundu, Soumya; Anghel, Marian

    2015-11-08

    We provide a distributed coordinated approach to the stability analysis and control design of largescale nonlinear dynamical systems by using a vector Lyapunov functions approach. In this formulation the large-scale system is decomposed into a network of interacting subsystems and the stability of the system is analyzed through a comparison system. However finding such comparison system is not trivial. In this work, we propose a sum-of-squares based completely decentralized approach for computing the comparison systems for networks of nonlinear systems. Moreover, based on the comparison systems, we introduce a distributed optimal control strategy in which the individual subsystems (agents) coordinate with their immediate neighbors to design local control policies that can exponentially stabilize the full system under initial disturbances.We illustrate the control algorithm on a network of interacting Van der Pol systems.

  2. The Fermi Large Area Telescope Flare Advocate Program: Rapid Sharing of Results with the Community

    NASA Astrophysics Data System (ADS)

    Thompson, David John; Ciprini, Stefano; Gasparrini, Dario; Fermi Large Area Telescope Collaboration

    2015-01-01

    The Fermi Flare Advocate (also known as Gamma-ray Sky Watcher) program provides a quick look and review of the gamma-ray sky observed daily by the Fermi Large Area Telescope (LAT) through on-duty LAT Flare Advocates and high-level software pipelines like the LAT Automatic Science Processing and the Fermi All-sky Variability Analysis. The FA-GSW service provides rapid alerts and communicates to the external scientific community potentially new gamma-ray sources, interesting transients and flares. News items are regularly posted through the Fermi multiwavelength mailing list, Astronomer's Telegrams and Gamma-ray Coordinates Network notices. A weekly digest containing the highlights about the variable LAT gamma-ray sky at E>100 MeV is published on the web ("Fermi Sky Blog"). From July 2008 to September 2014 more than 290 ATels and 90 GCNs have been published by the Fermi LAT Collaboration. Target of opportunity observing programs with other satellites and telescopes have been triggered by Flare Advocates based on gamma-ray flares from blazars and other kinds of sources.

  3. Coarse-Grain Bandwidth Estimation Scheme for Large-Scale Network

    NASA Technical Reports Server (NTRS)

    Cheung, Kar-Ming; Jennings, Esther H.; Sergui, John S.

    2013-01-01

    A large-scale network that supports a large number of users can have an aggregate data rate of hundreds of Mbps at any time. High-fidelity simulation of a large-scale network might be too complicated and memory-intensive for typical commercial-off-the-shelf (COTS) tools. Unlike a large commercial wide-area-network (WAN) that shares diverse network resources among diverse users and has a complex topology that requires routing mechanism and flow control, the ground communication links of a space network operate under the assumption of a guaranteed dedicated bandwidth allocation between specific sparse endpoints in a star-like topology. This work solved the network design problem of estimating the bandwidths of a ground network architecture option that offer different service classes to meet the latency requirements of different user data types. In this work, a top-down analysis and simulation approach was created to size the bandwidths of a store-and-forward network for a given network topology, a mission traffic scenario, and a set of data types with different latency requirements. These techniques were used to estimate the WAN bandwidths of the ground links for different architecture options of the proposed Integrated Space Communication and Navigation (SCaN) Network. A new analytical approach, called the "leveling scheme," was developed to model the store-and-forward mechanism of the network data flow. The term "leveling" refers to the spreading of data across a longer time horizon without violating the corresponding latency requirement of the data type. Two versions of the leveling scheme were developed: 1. A straightforward version that simply spreads the data of each data type across the time horizon and doesn't take into account the interactions among data types within a pass, or between data types across overlapping passes at a network node, and is inherently sub-optimal. 2. Two-state Markov leveling scheme that takes into account the second order behavior of

  4. Graph animals, subgraph sampling, and motif search in large networks.

    PubMed

    Baskerville, Kim; Grassberger, Peter; Paczuski, Maya

    2007-09-01

    We generalize a sampling algorithm for lattice animals (connected clusters on a regular lattice) to a Monte Carlo algorithm for "graph animals," i.e., connected subgraphs in arbitrary networks. As with the algorithm in [N. Kashtan et al., Bioinformatics 20, 1746 (2004)], it provides a weighted sample, but the computation of the weights is much faster (linear in the size of subgraphs, instead of superexponential). This allows subgraphs with up to ten or more nodes to be sampled with very high statistics, from arbitrarily large networks. Using this together with a heuristic algorithm for rapidly classifying isomorphic graphs, we present results for two protein interaction networks obtained using the tandem affinity purification (TAP) method: one of Escherichia coli with 230 nodes and 695 links, and one for yeast (Saccharomyces cerevisiae) with roughly ten times more nodes and links. We find in both cases that most connected subgraphs are strong motifs (Z scores >10) or antimotifs (Z scores <-10) when the null model is the ensemble of networks with fixed degree sequence. Strong differences appear between the two networks, with dominant motifs in E. coli being (nearly) bipartite graphs and having many pairs of nodes that connect to the same neighbors, while dominant motifs in yeast tend towards completeness or contain large cliques. We also explore a number of methods that do not rely on measurements of Z scores or comparisons with null models. For instance, we discuss the influence of specific complexes like the 26S proteasome in yeast, where a small number of complexes dominate the k cores with large k and have a decisive effect on the strongest motifs with 6-8 nodes. We also present Zipf plots of counts versus rank. They show broad distributions that are not power laws, in contrast to the case when disconnected subgraphs are included.

  5. Graph animals, subgraph sampling, and motif search in large networks

    NASA Astrophysics Data System (ADS)

    Baskerville, Kim; Grassberger, Peter; Paczuski, Maya

    2007-09-01

    We generalize a sampling algorithm for lattice animals (connected clusters on a regular lattice) to a Monte Carlo algorithm for “graph animals,” i.e., connected subgraphs in arbitrary networks. As with the algorithm in [N. Kashtan , Bioinformatics 20, 1746 (2004)], it provides a weighted sample, but the computation of the weights is much faster (linear in the size of subgraphs, instead of superexponential). This allows subgraphs with up to ten or more nodes to be sampled with very high statistics, from arbitrarily large networks. Using this together with a heuristic algorithm for rapidly classifying isomorphic graphs, we present results for two protein interaction networks obtained using the tandem affinity purification (TAP) method: one of Escherichia coli with 230 nodes and 695 links, and one for yeast (Saccharomyces cerevisiae) with roughly ten times more nodes and links. We find in both cases that most connected subgraphs are strong motifs ( Z scores >10 ) or antimotifs ( Z scores <-10 ) when the null model is the ensemble of networks with fixed degree sequence. Strong differences appear between the two networks, with dominant motifs in E. coli being (nearly) bipartite graphs and having many pairs of nodes that connect to the same neighbors, while dominant motifs in yeast tend towards completeness or contain large cliques. We also explore a number of methods that do not rely on measurements of Z scores or comparisons with null models. For instance, we discuss the influence of specific complexes like the 26S proteasome in yeast, where a small number of complexes dominate the k cores with large k and have a decisive effect on the strongest motifs with 6-8 nodes. We also present Zipf plots of counts versus rank. They show broad distributions that are not power laws, in contrast to the case when disconnected subgraphs are included.

  6. Altered functional-structural coupling of large-scale brain networks in idiopathic generalized epilepsy.

    PubMed

    Zhang, Zhiqiang; Liao, Wei; Chen, Huafu; Mantini, Dante; Ding, Ju-Rong; Xu, Qiang; Wang, Zhengge; Yuan, Cuiping; Chen, Guanghui; Jiao, Qing; Lu, Guangming

    2011-10-01

    The human brain is a large-scale integrated network in the functional and structural domain. Graph theoretical analysis provides a novel framework for analysing such complex networks. While previous neuroimaging studies have uncovered abnormalities in several specific brain networks in patients with idiopathic generalized epilepsy characterized by tonic-clonic seizures, little is known about changes in whole-brain functional and structural connectivity networks. Regarding functional and structural connectivity, networks are intimately related and share common small-world topological features. We predict that patients with idiopathic generalized epilepsy would exhibit a decoupling between functional and structural networks. In this study, 26 patients with idiopathic generalized epilepsy characterized by tonic-clonic seizures and 26 age- and sex-matched healthy controls were recruited. Resting-state functional magnetic resonance imaging signal correlations and diffusion tensor image tractography were used to generate functional and structural connectivity networks. Graph theoretical analysis revealed that the patients lost optimal topological organization in both functional and structural connectivity networks. Moreover, the patients showed significant increases in nodal topological characteristics in several cortical and subcortical regions, including mesial frontal cortex, putamen, thalamus and amygdala relative to controls, supporting the hypothesis that regions playing important roles in the pathogenesis of epilepsy may display abnormal hub properties in network analysis. Relative to controls, patients showed further decreases in nodal topological characteristics in areas of the default mode network, such as the posterior cingulate gyrus and inferior temporal gyrus. Most importantly, the degree of coupling between functional and structural connectivity networks was decreased, and exhibited a negative correlation with epilepsy duration in patients. Our findings

  7. [EHealth, health networks and electronic health record: towards a culture of sharing and trust].

    PubMed

    Nicolas, L

    2012-09-01

    In Belgium, the computerization of the ambulatory care sector and general practice in particular has been continuously progressing over the last ten years. Although regional differences exist, 75% of the Belgian general practitioners own today a software to assist them in the management of their patients. To date however, general practitioners have been hardly using their electronic system to share or communicate with other actors of the system. The silo culture remains the norm. Aside from certain group practices, computerization has thus not yet contributed to improve in a significant way the quality of care of the patient. The implementation in 2012 of the "shared electronic health record" thanks to the deployment in production of the 5 health networks connected via the federal directory of references is due to deeply change this situation. Communication flows between health care professionals will thus rapidly intensify and the amount of information available at the point of care will increase significantly. This is however only the first step. The future electronic patient record (EPR) will need to make room for a deep integration of the actors around the patient thanks--among other things--to the implementation of a global semantic interoperability strategy. This integration of actors together with the empowerment of the patient are indeed essential preliminary conditions in order to adapt our health system to the enormous challenges that we will all have to face in the next 10 years.

  8. Similarity in gene-regulatory networks suggests that cancer cells share characteristics of embryonic neural cells.

    PubMed

    Zhang, Zan; Lei, Anhua; Xu, Liyang; Chen, Lu; Chen, Yonglong; Zhang, Xuena; Gao, Yan; Yang, Xiaoli; Zhang, Min; Cao, Ying

    2017-08-04

    Cancer cells are immature cells resulting from cellular reprogramming by gene misregulation, and redifferentiation is expected to reduce malignancy. It is unclear, however, whether cancer cells can undergo terminal differentiation. Here, we show that inhibition of the epigenetic modification enzyme enhancer of zeste homolog 2 (EZH2), histone deacetylases 1 and 3 (HDAC1 and -3), lysine demethylase 1A (LSD1), or DNA methyltransferase 1 (DNMT1), which all promote cancer development and progression, leads to postmitotic neuron-like differentiation with loss of malignant features in distinct solid cancer cell lines. The regulatory effect of these enzymes in neuronal differentiation resided in their intrinsic activity in embryonic neural precursor/progenitor cells. We further found that a major part of pan-cancer-promoting genes and the signal transducers of the pan-cancer-promoting signaling pathways, including the epithelial-to-mesenchymal transition (EMT) mesenchymal marker genes, display neural specific expression during embryonic neurulation. In contrast, many tumor suppressor genes, including the EMT epithelial marker gene that encodes cadherin 1 (CDH1), exhibited non-neural or no expression. This correlation indicated that cancer cells and embryonic neural cells share a regulatory network, mediating both tumorigenesis and neural development. This observed similarity in regulatory mechanisms suggests that cancer cells might share characteristics of embryonic neural cells. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

  9. A cooperation mechanism for pure P2P file-sharing networks to improve application-level QoS

    NASA Astrophysics Data System (ADS)

    Wakamiya, Naoki; Konishi, Junjiro; Murata, Masayuki

    2006-10-01

    To provide application-oriented network services, a variety of overlay networks are deployed over physical IP networks. Since they share and compete for the same physical network resources, their selfish behaviors affect each other and, as a result, their performance deteriorates. In this paper, we propose a mechanism for pureP2P networks of file-sharing applications to cooperate with each other. In our proposal, a cooperative peer first finds another P2P network and establishes a logical link to a cooperative peer in the found network. Both ends of the logical link decide whether they cooperate or not from a viewpoint of the mutualism. When they consider they benefit from the cooperation, messages and files are exchanged among cooperative P2P networks through the logical link. For an efficient and effective cooperation, our mechanism has an algorithm for the selection of cooperative peers and a caching mechanism to avoid putting too much load on cooperative peers and cooperating networks. Simulation results showed that the number of discovered providing peers and the ratio of search hits increased about twice, while the load by the cooperation among P2P networks was reduced about half by caching.

  10. Large optical 3D MEMS switches in access networks

    NASA Astrophysics Data System (ADS)

    Madamopoulos, Nicholas; Kaman, Volkan; Yuan, Shifu; Jerphagnon, Olivier; Helkey, Roger; Bowers, John E.

    2007-09-01

    Interest is high among residential customers and businesses for advanced, broadband services such as fast Internet access, electronic commerce, video-on-demand, digital broadcasting, teleconferencing and telemedicine. In order to satisfy such growing demand of end-customers, access technologies such as fiber-to-the-home/building (FTTH/B) are increasingly being deployed. Carriers can reduce maintenance costs, minimize technology obsolescence and introduce new services easily by reducing active elements in the fiber access network. However, having a passive optical network (PON) also introduces operational and maintenance challenges. Increased diagnostic monitoring capability of the network becomes a necessity as more and more fibers are provisioned to deliver services to the end-customers. This paper demonstrates the clear advantages that large 3D optical MEMS switches offer in solving these access network problems. The advantages in preventative maintenance, remote monitoring, test and diagnostic capability are highlighted. The low optical insertion loss for all switch optical connections of the switch enables the monitoring, grooming and serving of a large number of PON lines and customers. Furthermore, the 3D MEMS switch is transparent to optical wavelengths and data formats, thus making it easy to incorporate future upgrades, such higher bit rates or DWDM overlay to a PON.

  11. Large-scale network-level processes during entrainment.

    PubMed

    Lithari, Chrysa; Sánchez-García, Carolina; Ruhnau, Philipp; Weisz, Nathan

    2016-03-15

    Visual rhythmic stimulation evokes a robust power increase exactly at the stimulation frequency, the so-called steady-state response (SSR). Localization of visual SSRs normally shows a very focal modulation of power in visual cortex and led to the treatment and interpretation of SSRs as a local phenomenon. Given the brain network dynamics, we hypothesized that SSRs have additional large-scale effects on the brain functional network that can be revealed by means of graph theory. We used rhythmic visual stimulation at a range of frequencies (4-30 Hz), recorded MEG and investigated source level connectivity across the whole brain. Using graph theoretical measures we observed a frequency-unspecific reduction of global density in the alpha band "disconnecting" visual cortex from the rest of the network. Also, a frequency-specific increase of connectivity between occipital cortex and precuneus was found at the stimulation frequency that exhibited the highest resonance (30 Hz). In conclusion, we showed that SSRs dynamically re-organized the brain functional network. These large-scale effects should be taken into account not only when attempting to explain the nature of SSRs, but also when used in various experimental designs. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

  12. Evolution of quality at the Organ Center of the Organ Procurement and Transplantation Network/United Network for Organ Sharing.

    PubMed

    Brown, Roger S; Belton, A Matthew; Martin, Judith M; Simmons, Dee Dee; Taylor, Gloria J; Willard, Ellie

    2009-09-01

    One of the goals of the Organ Center of the Organ Procurement and Transplantation Network/United Network for Organ Sharing is to increase the efficiency of equitable organ allocation in the United States. Recognizing the ever-growing need for organ donors and transplants, leaders at the Organ Center increased its commitment to quality improvement initiatives through the development of a quality management team in 2001. The Organ Center began to focus on ways to capture data on processes and pinpoint areas for improvement. As the collection and analysis of data evolved, the Organ Center embraced formal quality standards, such as improvement cycles. Using these cycles, the Organ Center has seen significant improvement. One initiative involving lifesaving heart, lung, and liver placement showed success by doubling the Organ Center's organ placement rate. Another project involving the validation of donor information demonstrated that the accuracy of organ allocation can be improved by 5% on a consistent basis. As stewards for the gift of life and leaders in organ allocation, the Organ Center uses continuous quality improvement to achieve the goal of increasing the efficiency of equitable organ allocation.

  13. Hybrid centralized pre-computing/local distributed optimization of shared disjoint-backup path approach to GMPLS optical mesh network intelligent restoration

    NASA Astrophysics Data System (ADS)

    Gong, Qian; Xu, Rong; Lin, Jintong

    2004-04-01

    Wavelength Division Multiplexed (WDM) networks that route optical connections using intelligent optical cross-connects (OXCs) is firmly established as the core constituent of next generation networks. Rapid failure recovery is fundamental to building reliable transport networks. Mesh restoration promises cost effective failure recovery compared with legacy ring networks, and is now seeing large-scale deployment. Many carriers are migrating away from SONET ring restoration for their core transport networks and replacing it with mesh restoration through "intelligent" O-E-O cross-connects (XC). The mesh restoration is typically provided via two fiber-disjoint paths: a service path and a restoration path. this scheme can restore any single link failure or node failure. And by used shared mesh restoration, although every service route is assigned a restoration route, no dedicated capacity needs to be reserved for the restoration route, resulting in capacity savings. The restoration approach we propose is Centralized Pre-computing, Local Distributed Optimization, and Shared Disjoint-backup Path. This approach combines the merits of centralized and distributed solutions. It avoids the scalability issues of centralized solutions by using a distributed control plane for disjoint service path computation and restoration path provisioning. Moreover, if the service routes of two demands are disjoint, no single failure will affect both demands simultaneously. This means that the restoration routes of these two demands can share link capacities, because these two routes will not be activated at the same time. So we can say, this restoration capacity sharing approach achieves low restoration capacity and fast restoration speed, while requiring few control plane changes.

  14. The stress response and immune system share, borrow, and reconfigure their physiological network elements: Evidence from the insects.

    PubMed

    Adamo, Shelley A

    2017-02-01

    The classic biomedical view is that stress hormone effects on the immune system are largely pathological, especially if the stress is chronic. However, more recent interpretations have focused on the potential adaptive function of these effects. This paper examines stress response-immune system interactions from a physiological network perspective, using insects because of their simpler physiology. For example, stress hormones can reduce disease resistance, yet activating an immune response results in the release of stress hormones in both vertebrates and invertebrates. From a network perspective, this phenomenon is consistent with the 'sharing' of the energy-releasing ability of stress hormones by both the stress response and the immune system. Stress-induced immunosuppression is consistent with the stress response 'borrowing' molecular components from the immune system to increase the capacity of stress-relevant physiological processes (i.e. a trade off). The insect stress hormones octopamine and adipokinetic hormone can also 'reconfigure' the immune system to help compensate for the loss of some of the immune system's molecular resources (e.g. apolipophorin III). This view helps explain seemingly maladaptive interactions between the stress response and immune system. The adaptiveness of stress hormone effects on individual immune components may be apparent only from the perspective of the whole organism. These broad principles will apply to both vertebrates and invertebrates. Copyright © 2016 Elsevier Inc. All rights reserved.

  15. Do friends share similar body image and eating problems? The role of social networks and peer influences in early adolescence.

    PubMed

    Hutchinson, Delyse M; Rapee, Ronald M

    2007-07-01

    This study examined the role of friendship networks and peer influences in body image concern, dietary restraint, extreme weight loss behaviours (EWLBs) and binge eating in a large community sample of young adolescent females. Based on girls' self-reported friendship groups, social network analysis was used to identify 173 friendship cliques. Results indicated that clique members shared similar scores on measures of dieting, EWLB and binge eating, but not body image concern. Average clique scores for dieting, EWLB and binge eating, were also correlated significantly with clique averages on measures of perceived peer influence, body mass index and psychological variables. Multiple regression analyses indicated that perceived peer influences in weight-related attitudes and behaviours were predictive of individual girls' level of body image concern, dieting, EWLB use and binge eating. Notably, an individual girl's dieting and EWLB use could be predicted from her friends' respective dieting and EWLB scores. Findings highlight the significance of the peer environment in body image and eating problems during early adolescence.

  16. The evaluation of the need to share medical data on the community medical ICT network service in Nagasaki, Japan.

    PubMed

    Matsumoto, Takehiro; Honda, Masayuki

    2013-01-01

    The Community Medical ICT Network service at the Nagasaki, Japan was established in 2009. Medical information network for sharing patients data was investigated focused on the access log data from April of 2009 and October of 2010. The total number of the access to the medical information was 30,914 of 2,213 patients. And the total number of access of the image including diagnostic imaging report, medical examination, treatment and medical documents was 10,278(33.2%), 8,949(28.9%), 6,896(22.3%) and 4,791(15.5%) respectively. These results showed that these medical information had enough valued for sharing in the regional medicine. In conclusion, many types of medical information should be required for sharing in the community medical ICT network in Japan.

  17. Mathematical modeling of local perfusion in large distensible microvascular networks

    NASA Astrophysics Data System (ADS)

    Causin, Paola; Malgaroli, Francesca

    2017-08-01

    Microvessels -blood vessels with diameter less than 200 microns- form large, intricate networks organized into arterioles, capillaries and venules. In these networks, the distribution of flow and pressure drop is a highly interlaced function of single vessel resistances and mutual vessel interactions. In this paper we propose a mathematical and computational model to study the behavior of microcirculatory networks subjected to different conditions. The network geometry is composed of a graph of connected straight cylinders, each one representing a vessel. The blood flow and pressure drop across the single vessel, further split into smaller elements, are related through a generalized Ohm's law featuring a conductivity parameter, function of the vessel cross section area and geometry, which undergo deformations under pressure loads. The membrane theory is used to describe the deformation of vessel lumina, tailored to the structure of thick-walled arterioles and thin-walled venules. In addition, since venules can possibly experience negative transmural pressures, a buckling model is also included to represent vessel collapse. The complete model including arterioles, capillaries and venules represents a nonlinear system of PDEs, which is approached numerically by finite element discretization and linearization techniques. We use the model to simulate flow in the microcirculation of the human eye retina, a terminal system with a single inlet and outlet. After a phase of validation against experimental measurements, we simulate the network response to different interstitial pressure values. Such a study is carried out both for global and localized variations of the interstitial pressure. In both cases, significant redistributions of the blood flow in the network arise, highlighting the importance of considering the single vessel behavior along with its position and connectivity in the network.

  18. A large fiber sensor network for an acoustic neutrino telescope

    NASA Astrophysics Data System (ADS)

    Buis, Ernst-Jan; Doppenberg, Ed; Lahmann, Robert; Toet, Peter

    2017-03-01

    The scientific prospects of detecting neutrinos with an energy close or even higher than the GKZ cut-off energy has been discussed extensively in literature. It is clear that due to their expected low flux, the detection of these ultra-high energy neutrinos (Ev > 1018 eV) requires a telescope larger than 100 km3. Acoustic detection may provide a way to observe these ultra-high energy cosmic neutrinos, as sound that they induce in the deep sea when neutrinos lose their energy travels undisturbed for many kilometers. To realize a large scale acoustic neutrino telescope, dedicated technology must be developed that allows for a deep sea sensor network. Fiber optic hydrophone technology provides a promising means to establish a large scale sensor network [1] with the proper sensitivity to detect the small signals from the neutrino interactions.

  19. Locating inefficient links in a large-scale transportation network

    NASA Astrophysics Data System (ADS)

    Sun, Li; Liu, Like; Xu, Zhongzhi; Jie, Yang; Wei, Dong; Wang, Pu

    2015-02-01

    Based on data from geographical information system (GIS) and daily commuting origin destination (OD) matrices, we estimated the distribution of traffic flow in the San Francisco road network and studied Braess's paradox in a large-scale transportation network with realistic travel demand. We measured the variation of total travel time Δ T when a road segment is closed, and found that | Δ T | follows a power-law distribution if Δ T < 0 or Δ T > 0. This implies that most roads have a negligible effect on the efficiency of the road network, while the failure of a few crucial links would result in severe travel delays, and closure of a few inefficient links would counter-intuitively reduce travel costs considerably. Generating three theoretical networks, we discovered that the heterogeneously distributed travel demand may be the origin of the observed power-law distributions of | Δ T | . Finally, a genetic algorithm was used to pinpoint inefficient link clusters in the road network. We found that closing specific road clusters would further improve the transportation efficiency.

  20. Host Immunity via Mutable Virtualized Large-Scale Network Containers

    DTIC Science & Technology

    2016-07-25

    migrate to different IP addresses multiple 6mes. We implement a virtual machine based system prototype and evaluate it using state-of-the-a1t scanning...entire !Pv4 address space within 5 Host Immunity via Mutable Virtualized Large-Scale Network Containers 45 minutes from a single machine . Second, when...that the attacker will be trapped into one decoy instead of the real server. We implement a virtual machine (VM)-based prototype that integrates

  1. Supporting large scale applications on networks of workstations

    NASA Technical Reports Server (NTRS)

    Cooper, Robert; Birman, Kenneth P.

    1989-01-01

    Distributed applications on networks of workstations are an increasingly common way to satisfy computing needs. However, existing mechanisms for distributed programming exhibit poor performance and reliability as application size increases. Extension of the ISIS distributed programming system to support large scale distributed applications by providing hierarchical process groups is discussed. Incorporation of hierarchy in the program structure and exploitation of this to limit the communication and storage required in any one component of the distributed system is examined.

  2. A Holistic Management Architecture for Large-Scale Adaptive Networks

    DTIC Science & Technology

    2007-09-01

    MANAGEMENT ARCHITECTURE FOR LARGE-SCALE ADAPTIVE NETWORKS by Michael R. Clement September 2007 Thesis Advisor: Alex Bordetsky Second Reader...TECHNOLOGY MANAGEMENT from the NAVAL POSTGRADUATE SCHOOL September 2007 Author: Michael R. Clement Approved by: Dr. Alex ...achieve in life is by His will. Ad Majorem Dei Gloriam. To my parents, my family, and Caitlin: For supporting me, listening to me when I got

  3. Implementation of Cyberinfrastructure and Data Management Workflow for a Large-Scale Sensor Network

    NASA Astrophysics Data System (ADS)

    Jones, A. S.; Horsburgh, J. S.

    2014-12-01

    Monitoring with in situ environmental sensors and other forms of field-based observation presents many challenges for data management, particularly for large-scale networks consisting of multiple sites, sensors, and personnel. The availability and utility of these data in addressing scientific questions relies on effective cyberinfrastructure that facilitates transformation of raw sensor data into functional data products. It also depends on the ability of researchers to share and access the data in useable formats. In addition to addressing the challenges presented by the quantity of data, monitoring networks need practices to ensure high data quality, including procedures and tools for post processing. Data quality is further enhanced if practitioners are able to track equipment, deployments, calibrations, and other events related to site maintenance and associate these details with observational data. In this presentation we will describe the overall workflow that we have developed for research groups and sites conducting long term monitoring using in situ sensors. Features of the workflow include: software tools to automate the transfer of data from field sites to databases, a Python-based program for data quality control post-processing, a web-based application for online discovery and visualization of data, and a data model and web interface for managing physical infrastructure. By automating the data management workflow, the time from collection to analysis is reduced and sharing and publication is facilitated. The incorporation of metadata standards and descriptions and the use of open-source tools enhances the sustainability and reusability of the data. We will describe the workflow and tools that we have developed in the context of the iUTAH (innovative Urban Transitions and Aridregion Hydrosustainability) monitoring network. The iUTAH network consists of aquatic and climate sensors deployed in three watersheds to monitor Gradients Along Mountain to Urban

  4. A Energy-Saving Path-Shared Protection Based on Diversity Network Coding for Multi-rate Multicast in WDM Mesh Networks

    NASA Astrophysics Data System (ADS)

    Zheng, Danling; Lv, Lei; Liu, Huanlin

    2017-08-01

    For improving the survivability and energy saving of multi-rate multicast, a novel energy-saving path-shared protection based on diversity network coding (EPP-DNC) for multi-rate multicast in wavelength division multiplexing (WDM) mesh networks is proposed in the paper. In the EPP-DNC algorithm, diversity network coding on the source node for multi-rate multicast is adopted to reduce the coding energy consumption by avoiding network coding on the network's intermediate nodes. To decrease the transmission energy, shortest path shared based on heuristic is proposed to transmit the protection information for the request. To provision request's working paths efficiency, the working paths are routed on the preselected P-cycles with minimum required links and minimum energy consumption. Simulation results show that the proposed EPP-DNC can save energy consumption and improve bandwidth utilization.

  5. Tunable self-seeding Fabry-Pérot laser diode for upstream multiwavelength shared ethernet passive optical network

    NASA Astrophysics Data System (ADS)

    Zhu, Min; Xiao, Shilin; Zhou, Zhao; Bi, Meihua

    2011-03-01

    We present a novel upstream multiwavelength shared ethernet passive optical network architecture, based on a proposed self-seeding Fabry-Pérot laser diode (FP-LD) at the optical network unit. The performances of the wavelength and power stability, side-mode suppression ratio, and tuning range for the proposed tunable self-seeding laser module are experimentally investigated. The bit-error-rate measurement is performed with direct modulation on FP-LD of 1.25 Gbps upstream data. The performance benefits from the upstream wavelengths sharing are showed via simulations.

  6. Mycorrhizal Networks: Common Goods of Plants Shared under Unequal Terms of Trade1[W][OA

    PubMed Central

    Walder, Florian; Niemann, Helge; Natarajan, Mathimaran; Lehmann, Moritz F.; Boller, Thomas; Wiemken, Andres

    2012-01-01

    Plants commonly live in a symbiotic association with arbuscular mycorrhizal fungi (AMF). They invest photosynthetic products to feed their fungal partners, which, in return, provide mineral nutrients foraged in the soil by their intricate hyphal networks. Intriguingly, AMF can link neighboring plants, forming common mycorrhizal networks (CMNs). What are the terms of trade in such CMNs between plants and their shared fungal partners? To address this question, we set up microcosms containing a pair of test plants, interlinked by a CMN of Glomus intraradices or Glomus mosseae. The plants were flax (Linum usitatissimum; a C3 plant) and sorghum (Sorghum bicolor; a C4 plant), which display distinctly different 13C/12C isotope compositions. This allowed us to differentially assess the carbon investment of the two plants into the CMN through stable isotope tracing. In parallel, we determined the plants’ “return of investment” (i.e. the acquisition of nutrients via CMN) using 15N and 33P as tracers. Depending on the AMF species, we found a strong asymmetry in the terms of trade: flax invested little carbon but gained up to 94% of the nitrogen and phosphorus provided by the CMN, which highly facilitated growth, whereas the neighboring sorghum invested massive amounts of carbon with little return but was barely affected in growth. Overall biomass production in the mixed culture surpassed the mean of the two monocultures. Thus, CMNs may contribute to interplant facilitation and the productivity boosts often found with intercropping compared with conventional monocropping. PMID:22517410

  7. Mycorrhizal networks: common goods of plants shared under unequal terms of trade.

    PubMed

    Walder, Florian; Niemann, Helge; Natarajan, Mathimaran; Lehmann, Moritz F; Boller, Thomas; Wiemken, Andres

    2012-06-01

    Plants commonly live in a symbiotic association with arbuscular mycorrhizal fungi (AMF). They invest photosynthetic products to feed their fungal partners, which, in return, provide mineral nutrients foraged in the soil by their intricate hyphal networks. Intriguingly, AMF can link neighboring plants, forming common mycorrhizal networks (CMNs). What are the terms of trade in such CMNs between plants and their shared fungal partners? To address this question, we set up microcosms containing a pair of test plants, interlinked by a CMN of Glomus intraradices or Glomus mosseae. The plants were flax (Linum usitatissimum; a C(3) plant) and sorghum (Sorghum bicolor; a C(4) plant), which display distinctly different (13)C/(12)C isotope compositions. This allowed us to differentially assess the carbon investment of the two plants into the CMN through stable isotope tracing. In parallel, we determined the plants' "return of investment" (i.e. the acquisition of nutrients via CMN) using (15)N and (33)P as tracers. Depending on the AMF species, we found a strong asymmetry in the terms of trade: flax invested little carbon but gained up to 94% of the nitrogen and phosphorus provided by the CMN, which highly facilitated growth, whereas the neighboring sorghum invested massive amounts of carbon with little return but was barely affected in growth. Overall biomass production in the mixed culture surpassed the mean of the two monocultures. Thus, CMNs may contribute to interplant facilitation and the productivity boosts often found with intercropping compared with conventional monocropping.

  8. The Origin of Large Molecules in Primordial Autocatalytic Reaction Networks

    PubMed Central

    Giri, Varun; Jain, Sanjay

    2012-01-01

    Large molecules such as proteins and nucleic acids are crucial for life, yet their primordial origin remains a major puzzle. The production of large molecules, as we know it today, requires good catalysts, and the only good catalysts we know that can accomplish this task consist of large molecules. Thus the origin of large molecules is a chicken and egg problem in chemistry. Here we present a mechanism, based on autocatalytic sets (ACSs), that is a possible solution to this problem. We discuss a mathematical model describing the population dynamics of molecules in a stylized but prebiotically plausible chemistry. Large molecules can be produced in this chemistry by the coalescing of smaller ones, with the smallest molecules, the ‘food set’, being buffered. Some of the reactions can be catalyzed by molecules within the chemistry with varying catalytic strengths. Normally the concentrations of large molecules in such a scenario are very small, diminishing exponentially with their size. ACSs, if present in the catalytic network, can focus the resources of the system into a sparse set of molecules. ACSs can produce a bistability in the population dynamics and, in particular, steady states wherein the ACS molecules dominate the population. However to reach these steady states from initial conditions that contain only the food set typically requires very large catalytic strengths, growing exponentially with the size of the catalyst molecule. We present a solution to this problem by studying ‘nested ACSs’, a structure in which a small ACS is connected to a larger one and reinforces it. We show that when the network contains a cascade of nested ACSs with the catalytic strengths of molecules increasing gradually with their size (e.g., as a power law), a sparse subset of molecules including some very large molecules can come to dominate the system. PMID:22238620

  9. Investigating the evolution of Shared Socioeconomic Pathways with a large number of scenarios

    NASA Astrophysics Data System (ADS)

    Schweizer, V. J.; Guivarch, C.; Rozenberg, J.

    2013-12-01

    The new scenario framework for climate change research includes alternative possible trends for socioeconomic development called Shared Socioeconomic Pathways (SSPs). The SSPs bear some similarities to other scenarios used for global change research, but they also have important differences. Like the IPCC Special Report on Emissions Scenarios or the Millennium Ecosystem Assessment, SSPs are defined by a scenario logic consisting of two axes. However, these axes define SSPs with respect to their location in an outcome space for challenges to mitigation and to adaptation rather than by their drivers. Open questions for the SSPs include what their drivers are and how the time dimension could be interpreted with the outcomes space. We present a new analytical approach for addressing both questions by studying large numbers of scenarios produced by an integrated assessment model, IMACLIM-R. We systematically generated 432 scenarios and used the SSP framework to classify them by typology. We then analyzed them dynamically, tracing their evolution through the SSP challenges space at annual time steps over the period 2010-2090. Through this approach, we found that many scenarios do not remain fixed to a particular SSP domain; they drift from one domain to another. In papers describing the framework for new scenarios, SSPs are envisioned as hypothetical (counter-factual) reference scenarios that remain fixed in one domain over some time period of interest. However, we conclude that it may be important to also research scenarios that shift across SSP domains. This is relevant for another open question, which is what scenarios are important to explore given their consequences. Through a data mining technique, we uncovered prominent drivers for scenarios that shift across SSP domains. Scenarios with different challenges for adaptation and mitigation (that is, mitigation and adaptation challenges that are not co-varying) were found to be the least stable, and the following

  10. Cellular computational networks--a scalable architecture for learning the dynamics of large networked systems.

    PubMed

    Luitel, Bipul; Venayagamoorthy, Ganesh Kumar

    2014-02-01

    Neural networks for implementing large networked systems such as smart electric power grids consist of multiple inputs and outputs. Many outputs lead to a greater number of parameters to be adapted. Each additional variable increases the dimensionality of the problem and hence learning becomes a challenge. Cellular computational networks (CCNs) are a class of sparsely connected dynamic recurrent networks (DRNs). By proper selection of a set of input elements for each output variable in a given application, a DRN can be modified into a CCN which significantly reduces the complexity of the neural network and allows use of simple training methods for independent learning in each cell thus making it scalable. This article demonstrates this concept of developing a CCN using dimensionality reduction in a DRN for scalability and better performance. The concept has been analytically explained and empirically verified through application. Copyright © 2013 Elsevier Ltd. All rights reserved.

  11. CytoKavosh: A Cytoscape Plug-In for Finding Network Motifs in Large Biological Networks

    PubMed Central

    Razaghi Moghadam Kashani, Zahra; Salehzadeh-Yazdi, Ali; Khakabimamaghani, Sahand

    2012-01-01

    Network motifs are small connected sub-graphs that have recently gathered much attention to discover structural behaviors of large and complex networks. Finding motifs with any size is one of the most important problems in complex and large networks. It needs fast and reliable algorithms and tools for achieving this purpose. CytoKavosh is one of the best choices for finding motifs with any given size in any complex network. It relies on a fast algorithm, Kavosh, which makes it faster than other existing tools. Kavosh algorithm applies some well known algorithmic features and includes tricky aspects, which make it an efficient algorithm in this field. CytoKavosh is a Cytoscape plug-in which supports us in finding motifs of given size in a network that is formerly loaded into the Cytoscape work-space (directed or undirected). High performance of CytoKavosh is achieved by dynamically linking highly optimized functions of Kavosh's C++ to the Cytoscape Java program, which makes this plug-in suitable for analyzing large biological networks. Some significant attributes of CytoKavosh is efficiency in time usage and memory and having no limitation related to the implementation in motif size. CytoKavosh is implemented in a visual environment Cytoscape that is convenient for the users to interact and create visual options to analyze the structural behavior of a network. This plug-in can work on any given network and is very simple to use and generates graphical results of discovered motifs with any required details. There is no specific Cytoscape plug-in, specific for finding the network motifs, based on original concept. So, we have introduced for the first time, CytoKavosh as the first plug-in, and we hope that this plug-in can be improved to cover other options to make it the best motif-analyzing tool. PMID:22952659

  12. Exploring the use of large clinical data to inform patients for shared decision making.

    PubMed

    Hill, Brent; Proulx, Joshua; Zeng-Treitler, Qing

    2013-01-01

    Barriers to patient participation in the shared decision making process prevent patients from fully participating in evaluating treatment options and treatment selection. Patients who use a decision aid are more informed and engaged in the shared decision making process. Patient decision aids do not use real clinical data for patient information and may not represent the data well. We designed an interface, for a shared decision making aid, that leverages clinical data to inform risk ratios and create patient stories, or vignettes, and present a visual representation of quantified treatment outcomes data. Usability testing was conducted with experts to evaluate the interface and the utility of using real clinical information that patients can explore. The experts' comments were transcribed and coded for themes. Themes were quantified and comments were interpreted for refinement and modification to the patient decision aid interface and data visualization.

  13. Geometric Origin of Scaling in Large Traffic Networks

    NASA Astrophysics Data System (ADS)

    Popović, Marko; Štefančić, Hrvoje; Zlatić, Vinko

    2012-11-01

    Large scale traffic networks are an indispensable part of contemporary human mobility and international trade. Networks of airport travel and cargo ship movements are invaluable for the understanding of human mobility patterns [R. Guimera , Proc. Natl. Acad. Sci. U.S.A. 102, 7794 (2005)PNASA60027-842410.1073/pnas.0407994102)], epidemic spreading [V. Colizza , Proc. Natl. Acad. Sci. U.S.A. 103, 2015 (2006)PNASA60027-842410.1073/pnas.0510525103], global trade [International Maritime Organization, http://www.imo.org/], and spread of invasive species [G. M. Ruiz , Nature (London) 408, 49 (2000)NATUAS0028-083610.1038/35040695]. Different studies [M. Barthelemy, Phys. Rept. 499, 1 (2011)0370-157310.1016/j.physrep.2010.11.002] point to the universal character of some of the exponents measured in such networks. Here we show that exponents which relate (i) the strength of nodes to their degree and (ii) weights of links to degrees of nodes that they connect have a geometric origin. We present a simple robust model which exhibits the observed power laws and relates exponents to the dimensionality of 2D space in which traffic networks are embedded. We show that the relation between weight strength and degree is s(k)˜k3/2, the relation between distance strength and degree is sd(k)˜k3/2, and the relation between weight of link and degrees of linked nodes is wij˜(kikj)1/2 on the plane 2D surface. We further analyze the influence of spherical geometry, relevant for the whole planet, on exact values of these exponents. Our model predicts that these exponents should be found in future studies of port networks and it imposes constraints on more refined models of port networks.

  14. Geometric origin of scaling in large traffic networks.

    PubMed

    Popović, Marko; Štefančić, Hrvoje; Zlatić, Vinko

    2012-11-16

    Large scale traffic networks are an indispensable part of contemporary human mobility and international trade. Networks of airport travel and cargo ship movements are invaluable for the understanding of human mobility patterns [R. Guimera et al., Proc. Natl. Acad. Sci. U.S.A. 102, 7794 (2005))], epidemic spreading [V. Colizza et al., Proc. Natl. Acad. Sci. U.S.A. 103, 2015 (2006)], global trade [International Maritime Organization, http://www.imo.org/], and spread of invasive species [G. M. Ruiz et al., Nature (London) 408, 49 (2000)]. Different studies [M. Barthelemy, Phys. Rept. 499, 1 (2011)] point to the universal character of some of the exponents measured in such networks. Here we show that exponents which relate (i) the strength of nodes to their degree and (ii) weights of links to degrees of nodes that they connect have a geometric origin. We present a simple robust model which exhibits the observed power laws and relates exponents to the dimensionality of 2D space in which traffic networks are embedded. We show that the relation between weight strength and degree is s(k)~k(3/2), the relation between distance strength and degree is s(d)(k)~k(3/2), and the relation between weight of link and degrees of linked nodes is w(ij)~(k(i)k(j))(1/2) on the plane 2D surface. We further analyze the influence of spherical geometry, relevant for the whole planet, on exact values of these exponents. Our model predicts that these exponents should be found in future studies of port networks and it imposes constraints on more refined models of port networks.

  15. High Fidelity Simulations of Large-Scale Wireless Networks

    SciTech Connect

    Onunkwo, Uzoma; Benz, Zachary

    2015-11-01

    The worldwide proliferation of wireless connected devices continues to accelerate. There are 10s of billions of wireless links across the planet with an additional explosion of new wireless usage anticipated as the Internet of Things develops. Wireless technologies do not only provide convenience for mobile applications, but are also extremely cost-effective to deploy. Thus, this trend towards wireless connectivity will only continue and Sandia must develop the necessary simulation technology to proactively analyze the associated emerging vulnerabilities. Wireless networks are marked by mobility and proximity-based connectivity. The de facto standard for exploratory studies of wireless networks is discrete event simulations (DES). However, the simulation of large-scale wireless networks is extremely difficult due to prohibitively large turnaround time. A path forward is to expedite simulations with parallel discrete event simulation (PDES) techniques. The mobility and distance-based connectivity associated with wireless simulations, however, typically doom PDES and fail to scale (e.g., OPNET and ns-3 simulators). We propose a PDES-based tool aimed at reducing the communication overhead between processors. The proposed solution will use light-weight processes to dynamically distribute computation workload while mitigating communication overhead associated with synchronizations. This work is vital to the analytics and validation capabilities of simulation and emulation at Sandia. We have years of experience in Sandia’s simulation and emulation projects (e.g., MINIMEGA and FIREWHEEL). Sandia’s current highly-regarded capabilities in large-scale emulations have focused on wired networks, where two assumptions prevent scalable wireless studies: (a) the connections between objects are mostly static and (b) the nodes have fixed locations.

  16. Identifying large-scale brain networks in fragile X syndrome.

    PubMed

    Hall, Scott S; Jiang, Heidi; Reiss, Allan L; Greicius, Michael D

    2013-11-01

    Fragile X syndrome (FXS) is an X-linked neurogenetic disorder characterized by a cognitive and behavioral phenotype resembling features of autism spectrum disorder. Until now, research has focused largely on identifying regional differences in brain structure and function between individuals with FXS and various control groups. Very little is known about the large-scale brain networks that may underlie the cognitive and behavioral symptoms of FXS. To identify large-scale, resting-state networks in FXS that differ from control individuals matched on age, IQ, and severity of behavioral and cognitive symptoms. Cross-sectional, in vivo neuroimaging study conducted in an academic medical center. Participants (aged 10-23 years) included 17 males and females with FXS and 16 males and females serving as controls. Univariate voxel-based morphometric analyses, fractional amplitude of low-frequency fluctuations (fALFF) analysis, and group-independent component analysis with dual regression. Patients with FXS showed decreased functional connectivity in the salience, precuneus, left executive control, language, and visuospatial networks compared with controls. Decreased fALFF in the bilateral insular, precuneus, and anterior cingulate cortices also was found in patients with FXS compared with control participants. Furthermore, fALFF in the left insular cortex was significantly positively correlated with IQ in patients with FXS. Decreased gray matter density, resting-state connectivity, and fALFF converged in the left insular cortex in patients with FXS. Fragile X syndrome results in widespread reductions in functional connectivity across multiple cognitive and affective brain networks. Converging structural and functional abnormalities in the left insular cortex, a region also implicated in individuals diagnosed with autism spectrum disorder, suggests that insula integrity and connectivity may be compromised in FXS. This method could prove useful in establishing an imaging

  17. Reconfigurable hardware applications on NetFPGA for network monitoring in large area sensor networks

    NASA Astrophysics Data System (ADS)

    Belias, A.; Koutsoumpos, V.; Manolopoulos, K.; Kachris, C.

    2013-10-01

    A valuable functionality for sensor networks, distributed in large volumes is the capability to characterize and analyze the data traffic at wire speed and monitor the data prior to committing to permanent storage. As a demonstrator we use a reconfigurable hardware router for real-time monitoring of data before their transmission to further processing and storage. The reconfigurable hardware router is based on the NetFPGA platform. In this study we report on the hardware implementation to monitor web-based network applications and compare our results with a software based network analyzer.

  18. Autonomous and Decentralized Optimization of Large-Scale Heterogeneous Wireless Networks by Neural Network Dynamics

    NASA Astrophysics Data System (ADS)

    Hasegawa, Mikio; Tran, Ha Nguyen; Miyamoto, Goh; Murata, Yoshitoshi; Harada, Hiroshi; Kato, Shuzo

    We propose a neurodynamical approach to a large-scale optimization problem in Cognitive Wireless Clouds, in which a huge number of mobile terminals with multiple different air interfaces autonomously utilize the most appropriate infrastructure wireless networks, by sensing available wireless networks, selecting the most appropriate one, and reconfiguring themselves with seamless handover to the target networks. To deal with such a cognitive radio network, game theory has been applied in order to analyze the stability of the dynamical systems consisting of the mobile terminals' distributed behaviors, but it is not a tool for globally optimizing the state of the network. As a natural optimization dynamical system model suitable for large-scale complex systems, we introduce the neural network dynamics which converges to an optimal state since its property is to continually decrease its energy function. In this paper, we apply such neurodynamics to the optimization problem of radio access technology selection. We compose a neural network that solves the problem, and we show that it is possible to improve total average throughput simply by using distributed and autonomous neuron updates on the terminal side.

  19. Boolean networks using the chi-square test for inferring large-scale gene regulatory networks.

    PubMed

    Kim, Haseong; Lee, Jae K; Park, Taesung

    2007-02-01

    Boolean network (BN) modeling is a commonly used method for constructing gene regulatory networks from time series microarray data. However, its major drawback is that its computation time is very high or often impractical to construct large-scale gene networks. We propose a variable selection method that are not only reduces BN computation times significantly but also obtains optimal network constructions by using chi-square statistics for testing the independence in contingency tables. Both the computation time and accuracy of the network structures estimated by the proposed method are compared with those of the original BN methods on simulated and real yeast cell cycle microarray gene expression data sets. Our results reveal that the proposed chi-square testing (CST)-based BN method significantly improves the computation time, while its ability to identify all the true network mechanisms was effectively the same as that of full-search BN methods. The proposed BN algorithm is approximately 70.8 and 7.6 times faster than the original BN algorithm when the error sizes of the Best-Fit Extension problem are 0 and 1, respectively. Further, the false positive error rate of the proposed CST-based BN algorithm tends to be less than that of the original BN. The CST-based BN method dramatically improves the computation time of the original BN algorithm. Therefore, it can efficiently infer large-scale gene regulatory network mechanisms.

  20. Weighted social networks for a large scale artificial society

    NASA Astrophysics Data System (ADS)

    Fan, Zong Chen; Duan, Wei; Zhang, Peng; Qiu, Xiao Gang

    2016-12-01

    The method of artificial society has provided a powerful way to study and explain how individual behaviors at micro level give rise to the emergence of global social phenomenon. It also creates the need for an appropriate representation of social structure which usually has a significant influence on human behaviors. It has been widely acknowledged that social networks are the main paradigm to describe social structure and reflect social relationships within a population. To generate social networks for a population of interest, considering physical distance and social distance among people, we propose a generation model of social networks for a large-scale artificial society based on human choice behavior theory under the principle of random utility maximization. As a premise, we first build an artificial society through constructing a synthetic population with a series of attributes in line with the statistical (census) data for Beijing. Then the generation model is applied to assign social relationships to each individual in the synthetic population. Compared with previous empirical findings, the results show that our model can reproduce the general characteristics of social networks, such as high clustering coefficient, significant community structure and small-world property. Our model can also be extended to a larger social micro-simulation as an input initial. It will facilitate to research and predict some social phenomenon or issues, for example, epidemic transition and rumor spreading.

  1. Integration of land-sharing and land-sparing conservation strategies through regional networking: the Mesoamerican Biological Corridor as a lifeline for carnivores in El Salvador.

    PubMed

    Crespin, Silvio J; García-Villalta, Jorge E

    2014-10-01

    Nations with little remaining natural habitat and small extent are challenged when trying to achieve biodiversity targets. We show that the Central American nation of El Salvador cannot viably sustain populations of 87 % of its extant carnivores, especially in the case of large-bodied species with low population densities. Current land-sparing strategies will not suffice; therefore we propose that land-sharing strategies be implemented in tandem with protected areas to expand current conservation efforts via new regional networks. In Central America such a network can be established by linking international protected area systems in a way that implements the existing vision for the Mesoamerican Biological Corridor. Specifically, we propose a re-envisioning of the Mesoamerican Biological Corridor in which land-sharing practices are adopted throughout the agricultural matrix while ensuring formal protection of the remaining natural habitat. Such an integration of land-sparing and land-sharing could result in the creation of an effective network of protected areas, thereby increasing the probability of safeguarding species with populations that overlap national borders.

  2. High Speed Networking and Large-scale Simulation in Geodynamics

    NASA Technical Reports Server (NTRS)

    Kuang, Weijia; Gary, Patrick; Seablom, Michael; Truszkowski, Walt; Odubiyi, Jide; Jiang, Weiyuan; Liu, Dong

    2004-01-01

    Large-scale numerical simulation has been one of the most important approaches for understanding global geodynamical processes. In this approach, peta-scale floating point operations (pflops) are often required to carry out a single physically-meaningful numerical experiment. For example, to model convective flow in the Earth's core and generation of the geomagnetic field (geodynamo), simulation for one magnetic free-decay time (approximately 15000 years) with a modest resolution of 150 in three spatial dimensions would require approximately 0.2 pflops. If such a numerical model is used to predict geomagnetic secular variation over decades and longer, with e.g. an ensemble Kalman filter assimilation approach, approximately 30 (and perhaps more) independent simulations of similar scales would be needed for one data assimilation analysis. Obviously, such a simulation would require an enormous computing resource that exceeds the capacity of a single facility currently available at our disposal. One solution is to utilize a very fast network (e.g. 10Gb optical networks) and available middleware (e.g. Globus Toolkit) to allocate available but often heterogeneous resources for such large-scale computing efforts. At NASA GSFC, we are experimenting with such an approach by networking several clusters for geomagnetic data assimilation research. We shall present our initial testing results in the meeting.

  3. Network Lasso: Clustering and Optimization in Large Graphs

    PubMed Central

    Hallac, David; Leskovec, Jure; Boyd, Stephen

    2016-01-01

    Convex optimization is an essential tool for modern data analysis, as it provides a framework to formulate and solve many problems in machine learning and data mining. However, general convex optimization solvers do not scale well, and scalable solvers are often specialized to only work on a narrow class of problems. Therefore, there is a need for simple, scalable algorithms that can solve many common optimization problems. In this paper, we introduce the network lasso, a generalization of the group lasso to a network setting that allows for simultaneous clustering and optimization on graphs. We develop an algorithm based on the Alternating Direction Method of Multipliers (ADMM) to solve this problem in a distributed and scalable manner, which allows for guaranteed global convergence even on large graphs. We also examine a non-convex extension of this approach. We then demonstrate that many types of problems can be expressed in our framework. We focus on three in particular — binary classification, predicting housing prices, and event detection in time series data — comparing the network lasso to baseline approaches and showing that it is both a fast and accurate method of solving large optimization problems. PMID:27398260

  4. High Speed Networking and Large-scale Simulation in Geodynamics

    NASA Technical Reports Server (NTRS)

    Kuang, Weijia; Gary, Patrick; Seablom, Michael; Truszkowski, Walt; Odubiyi, Jide; Jiang, Weiyuan; Liu, Dong

    2004-01-01

    Large-scale numerical simulation has been one of the most important approaches for understanding global geodynamical processes. In this approach, peta-scale floating point operations (pflops) are often required to carry out a single physically-meaningful numerical experiment. For example, to model convective flow in the Earth's core and generation of the geomagnetic field (geodynamo), simulation for one magnetic free-decay time (approximately 15000 years) with a modest resolution of 150 in three spatial dimensions would require approximately 0.2 pflops. If such a numerical model is used to predict geomagnetic secular variation over decades and longer, with e.g. an ensemble Kalman filter assimilation approach, approximately 30 (and perhaps more) independent simulations of similar scales would be needed for one data assimilation analysis. Obviously, such a simulation would require an enormous computing resource that exceeds the capacity of a single facility currently available at our disposal. One solution is to utilize a very fast network (e.g. 10Gb optical networks) and available middleware (e.g. Globus Toolkit) to allocate available but often heterogeneous resources for such large-scale computing efforts. At NASA GSFC, we are experimenting with such an approach by networking several clusters for geomagnetic data assimilation research. We shall present our initial testing results in the meeting.

  5. Prekindergarten Teachers' Verbal References to Print during Classroom-Based, Large-Group Shared Reading

    ERIC Educational Resources Information Center

    Zucker, Tricia A.; Justice, Laura M.; Piasta, Shayne B.

    2009-01-01

    Purpose: The frequency with which adults reference print when reading with preschool-age children is associated with growth in children's print knowledge (e.g., L.M. Justice & H.K. Ezell, 2000, 2002). This study examined whether prekindergarten (pre-K) teachers naturally reference print during classroom shared reading and if verbal print…

  6. Measuring Large-Scale Social Networks with High Resolution

    PubMed Central

    Stopczynski, Arkadiusz; Sekara, Vedran; Sapiezynski, Piotr; Cuttone, Andrea; Madsen, Mette My; Larsen, Jakob Eg; Lehmann, Sune

    2014-01-01

    This paper describes the deployment of a large-scale study designed to measure human interactions across a variety of communication channels, with high temporal resolution and spanning multiple years—the Copenhagen Networks Study. Specifically, we collect data on face-to-face interactions, telecommunication, social networks, location, and background information (personality, demographics, health, politics) for a densely connected population of 1 000 individuals, using state-of-the-art smartphones as social sensors. Here we provide an overview of the related work and describe the motivation and research agenda driving the study. Additionally, the paper details the data-types measured, and the technical infrastructure in terms of both backend and phone software, as well as an outline of the deployment procedures. We document the participant privacy procedures and their underlying principles. The paper is concluded with early results from data analysis, illustrating the importance of multi-channel high-resolution approach to data collection. PMID:24770359

  7. Atypical Behavior Identification in Large Scale Network Traffic

    SciTech Connect

    Best, Daniel M.; Hafen, Ryan P.; Olsen, Bryan K.; Pike, William A.

    2011-10-23

    Cyber analysts are faced with the daunting challenge of identifying exploits and threats within potentially billions of daily records of network traffic. Enterprise-wide cyber traffic involves hundreds of millions of distinct IP addresses and results in data sets ranging from terabytes to petabytes of raw data. Creating behavioral models and identifying trends based on those models requires data intensive architectures and techniques that can scale as data volume increases. Analysts need scalable visualization methods that foster interactive exploration of data and enable identification of behavioral anomalies. Developers must carefully consider application design, storage, processing, and display to provide usability and interactivity with large-scale data. We present an application that highlights atypical behavior in enterprise network flow records. This is accomplished by utilizing data intensive architectures to store the data, aggregation techniques to optimize data access, statistical techniques to characterize behavior, and a visual analytic environment to render the behavioral trends, highlight atypical activity, and allow for exploration.

  8. Ambulatory Subspecialty Visits in a Large Pediatric Primary Care Network

    PubMed Central

    Vernacchio, Louis; Muto, Jennifer M; Young, Gregory; Risko, Wanessa

    2012-01-01

    Objective To determine patterns of subspecialty utilization within a pediatric primary care network. Data Sources/Study Setting Paid claims from a large not-for-profit health plan for patients of The Pediatric Physicians' Organization at Children's, a network of private pediatric practices affiliated with Children's Hospital Boston. Principal Findings The subspecialty visit rate was 1.01 visits per subject-year. In 2007, 56.8 percent of subjects had no subspecialty visits, whereas 4.2 percent had ≥5 visits; the corresponding figures in 2008 were 54.1 and 4.5 percent, respectively. The most frequently visited subspecialties were Ophthalmology, Orthopedics, Dermatology, Otorhinolaryngology, and Allergy/Immunology. Visit rates varied sevenfold by practice. Conclusions Wide practice variability in pediatric subspecialty utilization suggests an opportunity for reducing unnecessary visits. Better integration between primary care and the most commonly used subspecialties will be needed to meaningfully reduce unnecessary visits and enhance value. PMID:22375886

  9. IR wireless cluster synapses of HYDRA very large neural networks

    NASA Astrophysics Data System (ADS)

    Jannson, Tomasz; Forrester, Thomas

    2008-04-01

    RF/IR wireless (virtual) synapses are critical components of HYDRA (Hyper-Distributed Robotic Autonomy) neural networks, already discussed in two earlier papers. The HYDRA network has the potential to be very large, up to 10 11-neurons and 10 18-synapses, based on already established technologies (cellular RF telephony and IR-wireless LANs). It is organized into almost fully connected IR-wireless clusters. The HYDRA neurons and synapses are very flexible, simple, and low-cost. They can be modified into a broad variety of biologically-inspired brain-like computing capabilities. In this third paper, we focus on neural hardware in general, and on IR-wireless synapses in particular. Such synapses, based on LED/LD-connections, dominate the HYDRA neural cluster.

  10. Foundational perspectives on causality in large-scale brain networks.

    PubMed

    Mannino, Michael; Bressler, Steven L

    2015-12-01

    A profusion of recent work in cognitive neuroscience has been concerned with the endeavor to uncover causal influences in large-scale brain networks. However, despite the fact that many papers give a nod to the important theoretical challenges posed by the concept of causality, this explosion of research has generally not been accompanied by a rigorous conceptual analysis of the nature of causality in the brain. This review provides both a descriptive and prescriptive account of the nature of causality as found within and between large-scale brain networks. In short, it seeks to clarify the concept of causality in large-scale brain networks both philosophically and scientifically. This is accomplished by briefly reviewing the rich philosophical history of work on causality, especially focusing on contributions by David Hume, Immanuel Kant, Bertrand Russell, and Christopher Hitchcock. We go on to discuss the impact that various interpretations of modern physics have had on our understanding of causality. Throughout all this, a central focus is the distinction between theories of deterministic causality (DC), whereby causes uniquely determine their effects, and probabilistic causality (PC), whereby causes change the probability of occurrence of their effects. We argue that, given the topological complexity of its large-scale connectivity, the brain should be considered as a complex system and its causal influences treated as probabilistic in nature. We conclude that PC is well suited for explaining causality in the brain for three reasons: (1) brain causality is often mutual; (2) connectional convergence dictates that only rarely is the activity of one neuronal population uniquely determined by another one; and (3) the causal influences exerted between neuronal populations may not have observable effects. A number of different techniques are currently available to characterize causal influence in the brain. Typically, these techniques quantify the statistical

  11. Foundational perspectives on causality in large-scale brain networks

    NASA Astrophysics Data System (ADS)

    Mannino, Michael; Bressler, Steven L.

    2015-12-01

    A profusion of recent work in cognitive neuroscience has been concerned with the endeavor to uncover causal influences in large-scale brain networks. However, despite the fact that many papers give a nod to the important theoretical challenges posed by the concept of causality, this explosion of research has generally not been accompanied by a rigorous conceptual analysis of the nature of causality in the brain. This review provides both a descriptive and prescriptive account of the nature of causality as found within and between large-scale brain networks. In short, it seeks to clarify the concept of causality in large-scale brain networks both philosophically and scientifically. This is accomplished by briefly reviewing the rich philosophical history of work on causality, especially focusing on contributions by David Hume, Immanuel Kant, Bertrand Russell, and Christopher Hitchcock. We go on to discuss the impact that various interpretations of modern physics have had on our understanding of causality. Throughout all this, a central focus is the distinction between theories of deterministic causality (DC), whereby causes uniquely determine their effects, and probabilistic causality (PC), whereby causes change the probability of occurrence of their effects. We argue that, given the topological complexity of its large-scale connectivity, the brain should be considered as a complex system and its causal influences treated as probabilistic in nature. We conclude that PC is well suited for explaining causality in the brain for three reasons: (1) brain causality is often mutual; (2) connectional convergence dictates that only rarely is the activity of one neuronal population uniquely determined by another one; and (3) the causal influences exerted between neuronal populations may not have observable effects. A number of different techniques are currently available to characterize causal influence in the brain. Typically, these techniques quantify the statistical

  12. Dynamical modeling and analysis of large cellular regulatory networks

    NASA Astrophysics Data System (ADS)

    Bérenguier, D.; Chaouiya, C.; Monteiro, P. T.; Naldi, A.; Remy, E.; Thieffry, D.; Tichit, L.

    2013-06-01

    The dynamical analysis of large biological regulatory networks requires the development of scalable methods for mathematical modeling. Following the approach initially introduced by Thomas, we formalize the interactions between the components of a network in terms of discrete variables, functions, and parameters. Model simulations result in directed graphs, called state transition graphs. We are particularly interested in reachability properties and asymptotic behaviors, which correspond to terminal strongly connected components (or "attractors") in the state transition graph. A well-known problem is the exponential increase of the size of state transition graphs with the number of network components, in particular when using the biologically realistic asynchronous updating assumption. To address this problem, we have developed several complementary methods enabling the analysis of the behavior of large and complex logical models: (i) the definition of transition priority classes to simplify the dynamics; (ii) a model reduction method preserving essential dynamical properties, (iii) a novel algorithm to compact state transition graphs and directly generate compressed representations, emphasizing relevant transient and asymptotic dynamical properties. The power of an approach combining these different methods is demonstrated by applying them to a recent multilevel logical model for the network controlling CD4+ T helper cell response to antigen presentation and to a dozen cytokines. This model accounts for the differentiation of canonical Th1 and Th2 lymphocytes, as well as of inflammatory Th17 and regulatory T cells, along with many hybrid subtypes. All these methods have been implemented into the software GINsim, which enables the definition, the analysis, and the simulation of logical regulatory graphs.

  13. Predicting protein functions from redundancies in large-scale protein interaction networks

    NASA Technical Reports Server (NTRS)

    Samanta, Manoj Pratim; Liang, Shoudan

    2003-01-01

    Interpreting data from large-scale protein interaction experiments has been a challenging task because of the widespread presence of random false positives. Here, we present a network-based statistical algorithm that overcomes this difficulty and allows us to derive functions of unannotated proteins from large-scale interaction data. Our algorithm uses the insight that if two proteins share significantly larger number of common interaction partners than random, they have close functional associations. Analysis of publicly available data from Saccharomyces cerevisiae reveals >2,800 reliable functional associations, 29% of which involve at least one unannotated protein. By further analyzing these associations, we derive tentative functions for 81 unannotated proteins with high certainty. Our method is not overly sensitive to the false positives present in the data. Even after adding 50% randomly generated interactions to the measured data set, we are able to recover almost all (approximately 89%) of the original associations.

  14. Predicting protein functions from redundancies in large-scale protein interaction networks

    PubMed Central

    Samanta, Manoj Pratim; Liang, Shoudan

    2003-01-01

    Interpreting data from large-scale protein interaction experiments has been a challenging task because of the widespread presence of random false positives. Here, we present a network-based statistical algorithm that overcomes this difficulty and allows us to derive functions of unannotated proteins from large-scale interaction data. Our algorithm uses the insight that if two proteins share significantly larger number of common interaction partners than random, they have close functional associations. Analysis of publicly available data from Saccharomyces cerevisiae reveals >2,800 reliable functional associations, 29% of which involve at least one unannotated protein. By further analyzing these associations, we derive tentative functions for 81 unannotated proteins with high certainty. Our method is not overly sensitive to the false positives present in the data. Even after adding 50% randomly generated interactions to the measured data set, we are able to recover almost all (≈89%) of the original associations. PMID:14566057

  15. Predicting protein functions from redundancies in large-scale protein interaction networks

    NASA Technical Reports Server (NTRS)

    Samanta, Manoj Pratim; Liang, Shoudan

    2003-01-01

    Interpreting data from large-scale protein interaction experiments has been a challenging task because of the widespread presence of random false positives. Here, we present a network-based statistical algorithm that overcomes this difficulty and allows us to derive functions of unannotated proteins from large-scale interaction data. Our algorithm uses the insight that if two proteins share significantly larger number of common interaction partners than random, they have close functional associations. Analysis of publicly available data from Saccharomyces cerevisiae reveals >2,800 reliable functional associations, 29% of which involve at least one unannotated protein. By further analyzing these associations, we derive tentative functions for 81 unannotated proteins with high certainty. Our method is not overly sensitive to the false positives present in the data. Even after adding 50% randomly generated interactions to the measured data set, we are able to recover almost all (approximately 89%) of the original associations.

  16. A Comparison of Users' Personal Information Sharing Awareness, Habits, and Practices in Social Networking Sites and E-Learning Systems

    ERIC Educational Resources Information Center

    Ball, Albert L.

    2012-01-01

    Although reports of identity theft continue to be widely published, users continue to post an increasing amount of personal information online, especially within social networking sites (SNS) and e-learning systems (ELS). Research has suggested that many users lack awareness of the threats that risky online personal information sharing poses to…

  17. A Comparison of Users' Personal Information Sharing Awareness, Habits, and Practices in Social Networking Sites and E-Learning Systems

    ERIC Educational Resources Information Center

    Ball, Albert L.

    2012-01-01

    Although reports of identity theft continue to be widely published, users continue to post an increasing amount of personal information online, especially within social networking sites (SNS) and e-learning systems (ELS). Research has suggested that many users lack awareness of the threats that risky online personal information sharing poses to…

  18. Impacts of a Large Decentralized Telepathology Network in Canada.

    PubMed

    Pare, Guy; Meyer, Julien; Trudel, Marie-Claude; Tetu, Bernard

    2016-03-01

    Telepathology is a fast growing segment of the telemedicine field. As of yet, no prior research has investigated the impacts of large decentralized telepathology projects on patients, clinicians, and healthcare systems. This study aims to fill this gap. We report a benefits evaluation study of a large decentralized telepathology project deployed in Eastern Quebec, Canada whose main objective is to provide continuous coverage of intraoperative consultations in remote hospitals without pathologists on-site. The project involves 18 hospitals, making it one of the largest telepathology networks in the world. We conducted 43 semistructured interviews with several telepathology users and hospital managers. Archival data on the impacts of the telepathology project (e.g., number of service disruptions, average time between initial diagnosis and surgery) were also extracted and analyzed. Our findings show that no service disruptions were recorded in hospitals without pathologists following the deployment of telepathology. Surgeons noted that the use of intraoperative consultations enabled by telepathology helped avoid second surgeries and improved accessibility to care services. Telepathology was also perceived by our respondents as having positive impacts on the remote hospitals' ability to retain and recruit surgeons. The observed benefits should not leave the impression that implementing telepathology is a trivial matter. Indeed, many technical, human, and organizational challenges may be encountered. Telepathology can be highly useful in regional hospitals that do not have a pathologist on-site. More research is needed to investigate the challenges and benefits associated with large decentralized telepathology networks.

  19. Share with thy neighbors

    NASA Astrophysics Data System (ADS)

    Chandra, Surendar; Yu, Xuwen

    2007-01-01

    Peer to peer (P2P) systems are traditionally designed to scale to a large number of nodes. However, we focus on scenarios where the sharing is effected only among neighbors. Localized sharing is particularly attractive in scenarios where wide area network connectivity is undesirable, expensive or unavailable. On the other hand, local neighbors may not offer the wide variety of objects possible in a much larger system. The goal of this paper is to investigate a P2P system that shares contents with its neighbors. We analyze the sharing behavior of Apple iTunes users in an University setting. iTunes restricts the sharing of audio and video objects to peers within the same LAN sub-network. We show that users are already making a significant amount of content available for local sharing. We show that these systems are not appropriate for applications that require access to a specific object. We argue that mechanisms that allow the user to specify classes of interesting objects are better suited for these systems. Mechanisms such as bloom filters can allow each peer to summarize the contents available in the neighborhood, reducing network search overhead. This research can form the basis for future storage systems that utilize the shared storage available in neighbors and build a probabilistic storage for local consumption.

  20. Evolution of an Operating System for Large-Scale Shared-Memory Multiprocessors

    DTIC Science & Technology

    1989-03-01

    ACM Operat- ing Systems Review 19:5. [7] Crowl, L. A., "Shared Memory Multiprocessors and Sequential Programming Languages: A Case Study," Proceedings...Principles, 14-16 December 1981, pp. 64-75. In ACM Operating Systems Review 15:5. [20] Redell, D., "Experience with Topaz TeleDebugging," Proceedings, ACM...34The Interface Between Distributed Operating System and High-Level Programming Language," Proceedings of the 1986 International Conference on Parallel

  1. The application of artificial intelligence techniques to large distributed networks

    NASA Technical Reports Server (NTRS)

    Dubyah, R.; Smith, T. R.; Star, J. L.

    1985-01-01

    Data accessibility and transfer of information, including the land resources information system pilot, are structured as large computer information networks. These pilot efforts include the reduction of the difficulty to find and use data, reducing processing costs, and minimize incompatibility between data sources. Artificial Intelligence (AI) techniques were suggested to achieve these goals. The applicability of certain AI techniques are explored in the context of distributed problem solving systems and the pilot land data system (PLDS). The topics discussed include: PLDS and its data processing requirements, expert systems and PLDS, distributed problem solving systems, AI problem solving paradigms, query processing, and distributed data bases.

  2. Marginalized neural network mixtures for large-scale regression.

    PubMed

    Lazaro-Gredilla, Miguel; Figueiras-Vidal, Aníbal R

    2010-08-01

    For regression tasks, traditional neural networks (NNs) have been superseded by gaussian processes, which provide probabilistic predictions (input-dependent error bars), improved accuracy, and virtually no overfitting. Due to their high computational cost, in scenarios with massive data sets, one has to resort to sparse gaussian processes, which strive to achieve similar performance with much smaller computational effort. In this context, we introduce a mixture of NNs with marginalized output weights that can both provide probabilistic predictions and improve on the performance of sparse gaussian processes, at the same computational cost. The effectiveness of this approach is shown experimentally on some representative large data sets.

  3. A Modular Ring Architecture for Large Scale Neural Network Implementations

    NASA Astrophysics Data System (ADS)

    Jump, Lance B.; Ligomenides, Panos A.

    1989-11-01

    Constructing fully parallel, large scale, neural networks is complicated by the problems of providing for massive interconnectivity and of overcoming fan in/out limitations in area-efficient VLSI/WSI realizations. A modular, bus switched, neural ring architecture employing primitive ring (pRing) processors is proposed, which solves the fan in/out and connectivity problems by a dynamically reconfigurable communication ring that synchronously serves identical, radially connected, processing elements. It also allows cost versus performance trade-offs by the assignment of variable numbers of logical neurons to each physical processing element.

  4. 78 FR 70076 - Large Scale Networking (LSN)-Middleware and Grid Interagency Coordination (MAGIC) Team

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-11-22

    ... Large Scale Networking (LSN)--Middleware and Grid Interagency Coordination (MAGIC) Team AGENCY: The Networking and Information Technology Research and Development (NITRD) National Coordination Office (NCO... Networking (LSN) Coordinating Group (CG). Public Comments: The government seeks individual input; attendees...

  5. Deep Convolutional Neural Networks for large-scale speech tasks.

    PubMed

    Sainath, Tara N; Kingsbury, Brian; Saon, George; Soltau, Hagen; Mohamed, Abdel-rahman; Dahl, George; Ramabhadran, Bhuvana

    2015-04-01

    Convolutional Neural Networks (CNNs) are an alternative type of neural network that can be used to reduce spectral variations and model spectral correlations which exist in signals. Since speech signals exhibit both of these properties, we hypothesize that CNNs are a more effective model for speech compared to Deep Neural Networks (DNNs). In this paper, we explore applying CNNs to large vocabulary continuous speech recognition (LVCSR) tasks. First, we determine the appropriate architecture to make CNNs effective compared to DNNs for LVCSR tasks. Specifically, we focus on how many convolutional layers are needed, what is an appropriate number of hidden units, what is the best pooling strategy. Second, investigate how to incorporate speaker-adapted features, which cannot directly be modeled by CNNs as they do not obey locality in frequency, into the CNN framework. Third, given the importance of sequence training for speech tasks, we introduce a strategy to use ReLU+dropout during Hessian-free sequence training of CNNs. Experiments on 3 LVCSR tasks indicate that a CNN with the proposed speaker-adapted and ReLU+dropout ideas allow for a 12%-14% relative improvement in WER over a strong DNN system, achieving state-of-the art results in these 3 tasks. Copyright © 2014 Elsevier Ltd. All rights reserved.

  6. Large deep neural networks for MS lesion segmentation

    NASA Astrophysics Data System (ADS)

    Prieto, Juan C.; Cavallari, Michele; Palotai, Miklos; Morales Pinzon, Alfredo; Egorova, Svetlana; Styner, Martin; Guttmann, Charles R. G.

    2017-02-01

    Multiple sclerosis (MS) is a multi-factorial autoimmune disorder, characterized by spatial and temporal dissemination of brain lesions that are visible in T2-weighted and Proton Density (PD) MRI. Assessment of lesion burden and is useful for monitoring the course of the disease, and assessing correlates of clinical outcomes. Although there are established semi-automated methods to measure lesion volume, most of them require human interaction and editing, which are time consuming and limits the ability to analyze large sets of data with high accuracy. The primary objective of this work is to improve existing segmentation algorithms and accelerate the time consuming operation of identifying and validating MS lesions. In this paper, a Deep Neural Network for MS Lesion Segmentation is implemented. The MS lesion samples are extracted from the Partners Comprehensive Longitudinal Investigation of Multiple Sclerosis (CLIMB) study. A set of 900 subjects with T2, PD and a manually corrected label map images were used to train a Deep Neural Network and identify MS lesions. Initial tests using this network achieved a 90% accuracy rate. A secondary goal was to enable this data repository for big data analysis by using this algorithm to segment the remaining cases available in the CLIMB repository.

  7. A system for simulating shared memory in heterogeneous distributed-memory networks with specialization for robotics applications

    SciTech Connect

    Jones, J.P.; Bangs, A.L.; Butler, P.L.

    1991-01-01

    Hetero Helix is a programming environment which simulates shared memory on a heterogeneous network of distributed-memory computers. The machines in the network may vary with respect to their native operating systems and internal representation of numbers. Hetero Helix presents a simple programming model to developers, and also considers the needs of designers, system integrators, and maintainers. The key software technology underlying Hetero Helix is the use of a compiler'' which analyzes the data structures in shared memory and automatically generates code which translates data representations from the format native to each machine into a common format, and vice versa. The design of Hetero Helix was motivated in particular by the requirements of robotics applications. Hetero Helix has been used successfully in an integration effort involving 27 CPUs in a heterogeneous network and a body of software totaling roughly 100,00 lines of code. 25 refs., 6 figs.

  8. United Network for Organ Sharing's expanded criteria donors: is stratification useful?

    PubMed

    Baskin-Bey, Edwina S; Kremers, Walter; Stegall, Mark D; Nyberg, Scott L

    2005-06-01

    The United Network for Organ Sharing (UNOS) Expanded Criteria Donor (ECD) system utilizes pre-transplant variables to identify deceased donor kidneys with an increased risk of graft loss. The aim of this study was to compare the ECD system with a quantitative approach, the deceased donor score (DDS), in predicting outcome after kidney transplantation. We retrospectively reviewed 49 111 deceased donor renal transplants from the UNOS database between 1984 and 2002. DDS: 0-39 points; >or=20 points defined as marginal. Recipient outcome variables were analyzed by ANOVA or Kaplan-Meier method. There was a 90% agreement between the DDS and ECD systems as predictors of renal function and graft survival. However, DDS identified ECD- kidneys (10.7%) with a significantly poorer outcome than expected (DDS 20-29 points, n = 5,252). Stratification of ECD+ kidneys identified a group with the poorest outcome (DDS >or=30 points). Predictability of early post-transplant events (i.e. need for hemodialysis, decline of serum creatinine and length of hospital stay) was also improved by DDS. DDS predicted outcome of deceased donor renal transplantation better than the ECD system. Knowledge obtained by stratification of deceased donor kidneys can allow for improved utilization of marginal kidneys which is not achieved by the UNOS ECD definition alone.

  9. Comparative Study of Multicast Protection Algorithms Using Shared Links in 100GET Transport Network

    NASA Astrophysics Data System (ADS)

    Sulaiman, Samer; Haidine, Abdelfattah; Lehnert, Ralf; Tuerk, Stefan

    In recent years new challenges have emerged in the telecommunications market resulting from the increase of network traffic and strong competition. Because of that, service providers feel constrained to replace expensive and complex IP-routers with a cheap and simple solution which guarantees the requested quality of services (QoS) with low cost. One of these solutions is to use the Ethernet technology as a switching layer, which results in using the cheap Ethernet services (E-Line, E-LAN and E-Tree) and to replace the expensive IP-routers. To achieve this migration step, new algorithms that support the available as well as the future services have to be developed. In this paper, we investigate the multicast protection issue. Three multicast protection algorithms based on the shared capacity between primary and backup solutions are proposed and evaluated. The blocking probability is used to evaluate the performance of the proposed algorithms. The sub-path algorithm resulted in a low blocking probability compared with the other algorithms.

  10. The Shared Health Research Information Network (SHRINE): a prototype federated query tool for clinical data repositories.

    PubMed

    Weber, Griffin M; Murphy, Shawn N; McMurry, Andrew J; Macfadden, Douglas; Nigrin, Daniel J; Churchill, Susanne; Kohane, Isaac S

    2009-01-01

    The authors developed a prototype Shared Health Research Information Network (SHRINE) to identify the technical, regulatory, and political challenges of creating a federated query tool for clinical data repositories. Separate Institutional Review Boards (IRBs) at Harvard's three largest affiliated health centers approved use of their data, and the Harvard Medical School IRB approved building a Query Aggregator Interface that can simultaneously send queries to each hospital and display aggregate counts of the number of matching patients. Our experience creating three local repositories using the open source Informatics for Integrating Biology and the Bedside (i2b2) platform can be used as a road map for other institutions. The authors are actively working with the IRBs and regulatory groups to develop procedures that will ultimately allow investigators to obtain identified patient data and biomaterials through SHRINE. This will guide us in creating a future technical architecture that is scalable to a national level, compliant with ethical guidelines, and protective of the interests of the participating hospitals.

  11. Methodology for the Improvement of Large District Heating Networks

    NASA Astrophysics Data System (ADS)

    Volkova, Anna; Mashatin, Vladislav; Hlebnikov, Aleksander; Siirde, Andres

    2012-12-01

    The purpose of this paper is to offer a methodology for the evaluation of large district heating networks. The methodology includes an analysis of heat generation and distribution based on the models created in the TERMIS and EnergyPro software Data from the large-scale Tallinn district heating system was used for the approbation of the proposed methodology as a basis of the case study. The effective operation of the district heating system, both at the stage of heat generation and heat distribution, can reduce the cost of heat supplied to the consumers. It can become an important factor for increasing the number of district heating consumers and demand for the heat load, which in turn will allow installing new cogeneration plants, using renewable energy sources and heat pump technologies

  12. Large Phased Array Radar Using Networked Small Parabolic Reflectors

    NASA Technical Reports Server (NTRS)

    Amoozegar, Farid

    2006-01-01

    Multifunction phased array systems with radar, telecom, and imaging applications have already been established for flat plate phased arrays of dipoles, or waveguides. In this paper the design trades and candidate options for combining the radar and telecom functions of the Deep Space Network (DSN) into a single large transmit array of small parabolic reflectors will be discussed. In particular the effect of combing the radar and telecom functions on the sizes of individual antenna apertures and the corresponding spacing between the antenna elements of the array will be analyzed. A heterogeneous architecture for the DSN large transmit array is proposed to meet the radar and telecom requirements while considering the budget, scheduling, and strategic planning constrains.

  13. Large Phased Array Radar Using Networked Small Parabolic Reflectors

    NASA Technical Reports Server (NTRS)

    Amoozegar, Farid

    2006-01-01

    Multifunction phased array systems with radar, telecom, and imaging applications have already been established for flat plate phased arrays of dipoles, or waveguides. In this paper the design trades and candidate options for combining the radar and telecom functions of the Deep Space Network (DSN) into a single large transmit array of small parabolic reflectors will be discussed. In particular the effect of combing the radar and telecom functions on the sizes of individual antenna apertures and the corresponding spacing between the antenna elements of the array will be analyzed. A heterogeneous architecture for the DSN large transmit array is proposed to meet the radar and telecom requirements while considering the budget, scheduling, and strategic planning constrains.

  14. Brief Mental Training Reorganizes Large-Scale Brain Networks

    PubMed Central

    Tang, Yi-Yuan; Tang, Yan; Tang, Rongxiang; Lewis-Peacock, Jarrod A.

    2017-01-01

    Emerging evidences have shown that one form of mental training—mindfulness meditation, can improve attention, emotion regulation and cognitive performance through changing brain activity and structural connectivity. However, whether and how the short-term mindfulness meditation alters large-scale brain networks are not well understood. Here, we applied a novel data-driven technique, the multivariate pattern analysis (MVPA) to resting-state fMRI (rsfMRI) data to identify changes in brain activity patterns and assess the neural mechanisms induced by a brief mindfulness training—integrative body–mind training (IBMT), which was previously reported in our series of randomized studies. Whole brain rsfMRI was performed on an undergraduate group who received 2 weeks of IBMT with 30 min per session (5 h training in total). Classifiers were trained on measures of functional connectivity in this fMRI data, and they were able to reliably differentiate (with 72% accuracy) patterns of connectivity from before vs. after the IBMT training. After training, an increase in positive functional connections (60 connections) were detected, primarily involving bilateral superior/middle occipital gyrus, bilateral frontale operculum, bilateral superior temporal gyrus, right superior temporal pole, bilateral insula, caudate and cerebellum. These results suggest that brief mental training alters the functional connectivity of large-scale brain networks at rest that may involve a portion of the neural circuitry supporting attention, cognitive and affective processing, awareness and sensory integration and reward processing. PMID:28293180

  15. Brief Mental Training Reorganizes Large-Scale Brain Networks.

    PubMed

    Tang, Yi-Yuan; Tang, Yan; Tang, Rongxiang; Lewis-Peacock, Jarrod A

    2017-01-01

    Emerging evidences have shown that one form of mental training-mindfulness meditation, can improve attention, emotion regulation and cognitive performance through changing brain activity and structural connectivity. However, whether and how the short-term mindfulness meditation alters large-scale brain networks are not well understood. Here, we applied a novel data-driven technique, the multivariate pattern analysis (MVPA) to resting-state fMRI (rsfMRI) data to identify changes in brain activity patterns and assess the neural mechanisms induced by a brief mindfulness training-integrative body-mind training (IBMT), which was previously reported in our series of randomized studies. Whole brain rsfMRI was performed on an undergraduate group who received 2 weeks of IBMT with 30 min per session (5 h training in total). Classifiers were trained on measures of functional connectivity in this fMRI data, and they were able to reliably differentiate (with 72% accuracy) patterns of connectivity from before vs. after the IBMT training. After training, an increase in positive functional connections (60 connections) were detected, primarily involving bilateral superior/middle occipital gyrus, bilateral frontale operculum, bilateral superior temporal gyrus, right superior temporal pole, bilateral insula, caudate and cerebellum. These results suggest that brief mental training alters the functional connectivity of large-scale brain networks at rest that may involve a portion of the neural circuitry supporting attention, cognitive and affective processing, awareness and sensory integration and reward processing.

  16. Automated large-scale control of gene regulatory networks.

    PubMed

    Tan, Mehmet; Alhajj, Reda; Polat, Faruk

    2010-04-01

    Controlling gene regulatory networks (GRNs) is an important and hard problem. As it is the case in all control problems, the curse of dimensionality is the main issue in real applications. It is possible that hundreds of genes may regulate one biological activity in an organism; this implies a huge state space, even in the case of Boolean models. This is also evident in the literature that shows that only models of small portions of the genome could be used in control applications. In this paper, we empower our framework for controlling GRNs by eliminating the need for expert knowledge to specify some crucial threshold that is necessary for producing effective results. Our framework is characterized by applying the factored Markov decision problem (FMDP) method to the control problem of GRNs. The FMDP is a suitable framework for large state spaces as it represents the probability distribution of state transitions using compact models so that more space and time efficient algorithms could be devised for solving control problems. We successfully mapped the GRN control problem to an FMDP and propose a model reduction algorithm that helps find approximate solutions for large networks by using existing FMDP solvers. The test results reported in this paper demonstrate the efficiency and effectiveness of the proposed approach.

  17. Using Swarming Agents for Scalable Security in Large Network Environments

    SciTech Connect

    Crouse, Michael; White, Jacob L.; Fulp, Errin W.; Berenhaut, Kenneth S.; Fink, Glenn A.; Haack, Jereme N.

    2011-09-23

    The difficulty of securing computer infrastructures increases as they grow in size and complexity. Network-based security solutions such as IDS and firewalls cannot scale because of exponentially increasing computational costs inherent in detecting the rapidly growing number of threat signatures. Hostbased solutions like virus scanners and IDS suffer similar issues, and these are compounded when enterprises try to monitor these in a centralized manner. Swarm-based autonomous agent systems like digital ants and artificial immune systems can provide a scalable security solution for large network environments. The digital ants approach offers a biologically inspired design where each ant in the virtual colony can detect atoms of evidence that may help identify a possible threat. By assembling the atomic evidences from different ant types the colony may detect the threat. This decentralized approach can require, on average, fewer computational resources than traditional centralized solutions; however there are limits to its scalability. This paper describes how dividing a large infrastructure into smaller managed enclaves allows the digital ant framework to effectively operate in larger environments. Experimental results will show that using smaller enclaves allows for more consistent distribution of agents and results in faster response times.

  18. Generative models of rich clubs in Hebbian neuronal networks and large-scale human brain networks

    PubMed Central

    Vértes, Petra E.; Alexander-Bloch, Aaron; Bullmore, Edward T.

    2014-01-01

    Rich clubs arise when nodes that are ‘rich’ in connections also form an elite, densely connected ‘club’. In brain networks, rich clubs incur high physical connection costs but also appear to be especially valuable to brain function. However, little is known about the selection pressures that drive their formation. Here, we take two complementary approaches to this question: firstly we show, using generative modelling, that the emergence of rich clubs in large-scale human brain networks can be driven by an economic trade-off between connection costs and a second, competing topological term. Secondly we show, using simulated neural networks, that Hebbian learning rules also drive the emergence of rich clubs at the microscopic level, and that the prominence of these features increases with learning time. These results suggest that Hebbian learning may provide a neuronal mechanism for the selection of complex features such as rich clubs. The neural networks that we investigate are explicitly Hebbian, and we argue that the topological term in our model of large-scale brain connectivity may represent an analogous connection rule. This putative link between learning and rich clubs is also consistent with predictions that integrative aspects of brain network organization are especially important for adaptive behaviour. PMID:25180309

  19. Generative models of rich clubs in Hebbian neuronal networks and large-scale human brain networks.

    PubMed

    Vértes, Petra E; Alexander-Bloch, Aaron; Bullmore, Edward T

    2014-10-05

    Rich clubs arise when nodes that are 'rich' in connections also form an elite, densely connected 'club'. In brain networks, rich clubs incur high physical connection costs but also appear to be especially valuable to brain function. However, little is known about the selection pressures that drive their formation. Here, we take two complementary approaches to this question: firstly we show, using generative modelling, that the emergence of rich clubs in large-scale human brain networks can be driven by an economic trade-off between connection costs and a second, competing topological term. Secondly we show, using simulated neural networks, that Hebbian learning rules also drive the emergence of rich clubs at the microscopic level, and that the prominence of these features increases with learning time. These results suggest that Hebbian learning may provide a neuronal mechanism for the selection of complex features such as rich clubs. The neural networks that we investigate are explicitly Hebbian, and we argue that the topological term in our model of large-scale brain connectivity may represent an analogous connection rule. This putative link between learning and rich clubs is also consistent with predictions that integrative aspects of brain network organization are especially important for adaptive behaviour.

  20. 77 FR 58416 - Large Scale Networking (LSN); Middleware and Grid Interagency Coordination (MAGIC) Team

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-09-20

    ... From the Federal Register Online via the Government Publishing Office NATIONAL SCIENCE FOUNDATION Large Scale Networking (LSN); Middleware and Grid Interagency Coordination (MAGIC) Team AGENCY: The... to the Large Scale Networking (LSN) Coordinating Group (CG). Public Comments: The government...

  1. Overview of the gene regulation network and the bacteria biotope tasks in BioNLP'13 shared task.

    PubMed

    Bossy, Robert; Golik, Wiktoria; Ratkovic, Zorana; Valsamou, Dialekti; Bessières, Philippe; Nédellec, Claire

    2015-01-01

    We present the two Bacteria Track tasks of BioNLP 2013 Shared Task (ST): Gene Regulation Network (GRN) and Bacteria Biotope (BB). These tasks were previously introduced in the 2011 BioNLP-ST Bacteria Track as Bacteria Gene Interaction (BI) and Bacteria Biotope (BB). The Bacteria Track was motivated by a need to develop specific BioNLP tools for fine-grained event extraction in bacteria biology. The 2013 tasks expand on the 2011 version by better addressing the biological knowledge modeling needs. New evaluation metrics were designed for the new goals. Moving beyond a list of gene interactions, the goal of the GRN task is to build a gene regulation network from the extracted gene interactions. BB'13 is dedicated to the extraction of bacteria biotopes, i.e. bacterial environmental information, as was BB'11. BB'13 extends the typology of BB'11 to a large diversity of biotopes, as defined by the OntoBiotope ontology. The detection of entities and events is tackled by distinct subtasks in order to measure the progress achieved by the participant systems since 2011. This paper details the corpus preparations and the evaluation metrics, as well as summarizing and discussing the participant results. Five groups participated in each of the two tasks. The high diversity of the participant methods reflects the dynamism of the BioNLP research community. The evaluation results suggest new research directions for the improvement and development of Information Extraction for molecular and environmental biology. The Bacteria Track tasks remain publicly open; the BioNLP-ST website provides an online evaluation service, the reference corpora and the evaluation tools.

  2. Enabling large-scale viscoelastic calculations via neural network acceleration

    NASA Astrophysics Data System (ADS)

    DeVries, Phoebe M. R.; Thompson, T. Ben; Meade, Brendan J.

    2017-03-01

    One of the most significant challenges involved in efforts to understand the effects of repeated earthquake cycle activity is the computational costs of large-scale viscoelastic earthquake cycle models. Computationally intensive viscoelastic codes must be evaluated at thousands of times and locations, and as a result, studies tend to adopt a few fixed rheological structures and model geometries and examine the predicted time-dependent deformation over short (<10 years) time periods at a given depth after a large earthquake. Training a deep neural network to learn a computationally efficient representation of viscoelastic solutions, at any time, location, and for a large range of rheological structures, allows these calculations to be done quickly and reliably, with high spatial and temporal resolutions. We demonstrate that this machine learning approach accelerates viscoelastic calculations by more than 50,000%. This magnitude of acceleration will enable the modeling of geometrically complex faults over thousands of earthquake cycles across wider ranges of model parameters and at larger spatial and temporal scales than have been previously possible.

  3. Natural language acquisition in large scale neural semantic networks

    NASA Astrophysics Data System (ADS)

    Ealey, Douglas

    This thesis puts forward the view that a purely signal- based approach to natural language processing is both plausible and desirable. By questioning the veracity of symbolic representations of meaning, it argues for a unified, non-symbolic model of knowledge representation that is both biologically plausible and, potentially, highly efficient. Processes to generate a grounded, neural form of this model-dubbed the semantic filter-are discussed. The combined effects of local neural organisation, coincident with perceptual maturation, are used to hypothesise its nature. This theoretical model is then validated in light of a number of fundamental neurological constraints and milestones. The mechanisms of semantic and episodic development that the model predicts are then used to explain linguistic properties, such as propositions and verbs, syntax and scripting. To mimic the growth of locally densely connected structures upon an unbounded neural substrate, a system is developed that can grow arbitrarily large, data- dependant structures composed of individual self- organising neural networks. The maturational nature of the data used results in a structure in which the perception of concepts is refined by the networks, but demarcated by subsequent structure. As a consequence, the overall structure shows significant memory and computational benefits, as predicted by the cognitive and neural models. Furthermore, the localised nature of the neural architecture also avoids the increasing error sensitivity and redundancy of traditional systems as the training domain grows. The semantic and episodic filters have been demonstrated to perform as well, or better, than more specialist networks, whilst using significantly larger vocabularies, more complex sentence forms and more natural corpora.

  4. Post-transplant lymphoproliferative disorder after pancreas transplantation: a United Network for Organ Sharing database analysis.

    PubMed

    Jackson, K; Ruppert, K; Shapiro, R

    2013-01-01

    There are not a great deal of data on post-transplant lymphoproliferative disorder (PTLD) following pancreas transplantation. We analyzed the United Network for Organ Sharing national database of pancreas transplants to identify predictors of PTLD development. A univariate Cox model was generated for each potential predictor, and those at least marginally associated (p < 0.15) with PTLD were entered into a multivariable Cox model. PTLD developed in 43 patients (1.0%) of 4205 pancreas transplants. Mean follow-up time was 4.9 ± 2.2 yr. In the multivariable Cox model, recipient EBV seronegativity (HR 5.52, 95% CI: 2.99-10.19, p < 0.001), not having tacrolimus in the immunosuppressive regimen (HR 6.02, 95% CI: 2.74-13.19, p < 0.001), recipient age (HR 0.96, 95% CI: 0.92-0.99, p = 0.02), non-white ethnicity (HR 0.11, 95% CI: 0.02-0.84, p = 0.03), and HLA mismatching (HR 0.80, 95% CI: 0.67-0.97, p = 0.02) were significantly associated with the development of PTLD. Patient survival was significantly decreased in patients with PTLD, with a one-, three-, and five-yr survival of 91%, 76%, and 70%, compared with 97%, 93%, and 88% in patients without PTLD (p < 0.001). PTLD is an uncommon but potentially lethal complication following pancreas transplantation. Patients with the risk factors identified should be monitored closely for the development of PTLD.

  5. Liver transplantation in patients with cystic fibrosis: analysis of United Network for Organ Sharing data.

    PubMed

    Mendizabal, Manuel; Reddy, K Rajender; Cassuto, James; Olthoff, Kim M; Faust, Thomas W; Makar, George A; Rand, Elizabeth B; Shaked, Abraham; Abt, Peter L

    2011-03-01

    The improved life expectancy of patients with cystic fibrosis (CF) has led to a change in the impact of liver disease on the prognosis of this population. Liver transplantation has emerged as the procedure of choice for patients with CF and features of hepatic decompensation and for intractable variceal bleeding as a major manifestation. We retrospectively reviewed the United Network for Organ Sharing database to analyze the outcomes of 55 adults and 148 children with CF who underwent liver transplantation, and we compared them to patients who underwent transplantation for other etiologies. We additionally compared the benefits of liver transplantation among patients who underwent transplantation for cystic fibrosis-related liver disease (CFLD) and those who remained on the waiting list. The 5-year survival rates for children and adults undergoing liver transplantation were 85.8% and 72.7%, respectively (P = 0.016). A multivariate Cox regression analysis comparing pediatric and adult CF patients to patients who underwent transplantation for other etiologies noted lower 5-year survival rates (P < 0.0001). However, compared to those remaining on the waiting list, pediatric transplant recipients with CF (hazard ratio = 0.33, 95% confidence interval = 0.16-0.70, P = 0.004) and adult transplant recipients with CF (hazard ratio = 0.25, 95% confidence interval = 0.11-0.57, P = 0.001) gained a significant survival benefit. In conclusion, long-term outcomes in patients with CFLD are acceptable but are inferior in comparison with the outcomes of those undergoing transplantation for other etiologies. Despite such observations, a survival benefit was noted in transplant patients versus those who remained on the waiting list.

  6. High rate of unemployment after liver transplantation: analysis of the United Network for Organ Sharing database.

    PubMed

    Huda, Amina; Newcomer, Robert; Harrington, Charlene; Blegen, Mary G; Keeffe, Emmet B

    2012-01-01

    The goal of liver transplantation (LT) is to maximize the length and quality of a patient's life and facilitate his or her return to full productivity. The aims of this study were (1) to use the United Network for Organ Sharing (UNOS) data set to determine the proportions of recipients who were employed and unemployed within 24 months after LT between 2002 and 2008 and (2) to examine the factors associated with a return to employment. UNOS data that were collected since the adoption of the Model for End-Stage Liver Disease scoring system on February 27, 2002 were analyzed. There were 21,942 transplant recipients who met the inclusion criteria. The employment status of the recipients was analyzed within a 60-day window at the following times after transplantation: 6, 12, and 24 months. Approximately one-quarter of the LT recipients (5360 or 24.4%) were employed within 24 months after transplantation, and the remaining recipients had not returned to work. The demographic variables that were independently associated with posttransplant employment included an age of 18 to 40 years, male sex, a college degree, Caucasian race, and pretransplant employment. Patients with alcoholic liver disease had a significantly lower rate of employment than patients with other etiologies of liver disease. The recipients who were employed after transplantation had significantly better functional status than those who were not employed. In conclusion, the employment rate after LT is low, with only one-quarter of LT recipients employed. New national and individual transplant program policies are needed to assess the root causes of unemployment in recipients who wish to work after LT. Copyright © 2011 American Association for the Study of Liver Diseases.

  7. Hematocrit distribution and tissue oxygenation in large microcirculatory networks.

    PubMed

    Gould, Ian G; Linninger, Andreas A

    2015-01-01

    Oxygen tension in the brain is controlled by the microcirculatory supply of RBC, but the effect of non-Newtonian blood flow rheology on tissue oxygenation is not well characterized. This study assesses different biphasic blood flow models for predicting tissue oxygen tension as a function of microcirculatory hemodynamics. Two existing plasma-skimming laws are compared against measured RBC distributions in rat and hamster microcirculatory networks. A novel biphasic blood flow model is introduced. The computational models predict tissue oxygenation in the mesentery, cremaster muscle, and the human secondary cortex. This investigation shows deficiencies in prior models, including inconsistent plasma-skimming trends and insufficient oxygen perfusion due to the high prevalence (33%) of RBC-free microvessels. Our novel method yields physiologically sound RBC distributions and tissue oxygen tensions within one standard deviation of experimental measurements. A simple, novel biphasic blood flow model is introduced with equal or better predictive power when applied to historic raw data sets. It can overcome limitations of prior models pertaining to trifurcations, anastomoses, and loops. This new plasma-skimming law eases the computations of bulk blood flow and hematocrit fields in large microcirculatory networks and converges faster than prior procedures. © 2014 John Wiley & Sons Ltd.

  8. Data-Gathering Scheme Using AUVs in Large-Scale Underwater Sensor Networks: A Multihop Approach

    PubMed Central

    Khan, Jawaad Ullah; Cho, Ho-Shin

    2016-01-01

    In this paper, we propose a data-gathering scheme for hierarchical underwater sensor networks, where multiple Autonomous Underwater Vehicles (AUVs) are deployed over large-scale coverage areas. The deployed AUVs constitute an intermittently connected multihop network through inter-AUV synchronization (in this paper, synchronization means an interconnection between nodes for communication) for forwarding data to the designated sink. In such a scenario, the performance of the multihop communication depends upon the synchronization among the vehicles. The mobility parameters of the vehicles vary continuously because of the constantly changing underwater currents. The variations in the AUV mobility parameters reduce the inter-AUV synchronization frequency contributing to delays in the multihop communication. The proposed scheme improves the AUV synchronization frequency by permitting neighboring AUVs to share their status information via a pre-selected node called an agent-node at the static layer of the network. We evaluate the proposed scheme in terms of the AUV synchronization frequency, vertical delay (node→AUV), horizontal delay (AUV→AUV), end-to-end delay, and the packet loss ratio. Simulation results show that the proposed scheme significantly reduces the aforementioned delays without the synchronization time-out process employed in conventional works. PMID:27706042

  9. Data-Gathering Scheme Using AUVs in Large-Scale Underwater Sensor Networks: A Multihop Approach.

    PubMed

    Khan, Jawaad Ullah; Cho, Ho-Shin

    2016-09-30

    In this paper, we propose a data-gathering scheme for hierarchical underwater sensor networks, where multiple Autonomous Underwater Vehicles (AUVs) are deployed over large-scale coverage areas. The deployed AUVs constitute an intermittently connected multihop network through inter-AUV synchronization (in this paper, synchronization means an interconnection between nodes for communication) for forwarding data to the designated sink. In such a scenario, the performance of the multihop communication depends upon the synchronization among the vehicles. The mobility parameters of the vehicles vary continuously because of the constantly changing underwater currents. The variations in the AUV mobility parameters reduce the inter-AUV synchronization frequency contributing to delays in the multihop communication. The proposed scheme improves the AUV synchronization frequency by permitting neighboring AUVs to share their status information via a pre-selected node called an agent-node at the static layer of the network. We evaluate the proposed scheme in terms of the AUV synchronization frequency, vertical delay (node→AUV), horizontal delay (AUV→AUV), end-to-end delay, and the packet loss ratio. Simulation results show that the proposed scheme significantly reduces the aforementioned delays without the synchronization time-out process employed in conventional works.

  10. Just in time connectivity for large spiking networks

    PubMed Central

    Lytton, William W.; Omurtag, Ahmet; Neymotin, Samuel A; Hines, Michael L

    2008-01-01

    The scale of large neuronal network simulations is memory-limited due to the need to store connectivity information: connectivity storage grows as the square of neuron number up to anatomically-relevant limits. Using the NEURON simulator as a discrete-event simulator (no integration), we explored the consequences of avoiding the space costs of connectivity through regenerating connectivity parameters when needed – just-in-time after a presynaptic cell fires. We explored various strategies for automated generation of one or more of the basic static connectivity parameters: delays, postsynaptic cell identities and weights, as well as run-time connectivity state: the event queue. Comparison of the JitCon implementation to NEURON’s standard NetCon connectivity method showed substantial space savings, with associated run-time penalty. Although JitCon saved space by eliminating connectivity parameters, larger simulations were still memory-limited due to growth of the synaptic event queue. We therefore designed a JitEvent algorithm that only added items to the queue when required: instead of alerting multiple postsynaptic cells, a spiking presynaptic cell posted a callback event at the shortest synaptic delay time. At the time of the callback, this same presynaptic cell directly notified the first postsynaptic cell and generated another self-callback for the next delay time. The JitEvent implementation yielded substantial additional time and space savings. We conclude that just-in-time strategies are necessary for very large network simulations but that a variety of alternative strategies should be considered whose optimality will depend on the characteristics of the simulation to be run. PMID:18533821

  11. Just-in-time connectivity for large spiking networks.

    PubMed

    Lytton, William W; Omurtag, Ahmet; Neymotin, Samuel A; Hines, Michael L

    2008-11-01

    The scale of large neuronal network simulations is memory limited due to the need to store connectivity information: connectivity storage grows as the square of neuron number up to anatomically relevant limits. Using the NEURON simulator as a discrete-event simulator (no integration), we explored the consequences of avoiding the space costs of connectivity through regenerating connectivity parameters when needed: just in time after a presynaptic cell fires. We explored various strategies for automated generation of one or more of the basic static connectivity parameters: delays, postsynaptic cell identities, and weights, as well as run-time connectivity state: the event queue. Comparison of the JitCon implementation to NEURON's standard NetCon connectivity method showed substantial space savings, with associated run-time penalty. Although JitCon saved space by eliminating connectivity parameters, larger simulations were still memory limited due to growth of the synaptic event queue. We therefore designed a JitEvent algorithm that added items to the queue only when required: instead of alerting multiple postsynaptic cells, a spiking presynaptic cell posted a callback event at the shortest synaptic delay time. At the time of the callback, this same presynaptic cell directly notified the first postsynaptic cell and generated another self-callback for the next delay time. The JitEvent implementation yielded substantial additional time and space savings. We conclude that just-in-time strategies are necessary for very large network simulations but that a variety of alternative strategies should be considered whose optimality will depend on the characteristics of the simulation to be run.

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

    PubMed Central

    Koren, Hila; Kaminer, Ido

    2016-01-01

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

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

    PubMed

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

    2016-01-01

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

  14. Structural study of GeS2 glass: Reverse Monte Carlo modelling for edge-sharing tetrahedral network

    NASA Astrophysics Data System (ADS)

    Itoh, Keiji

    2017-04-01

    The pulsed neutron diffraction and reverse Monte Carlo (RMC) modelling methods were used to investigate the structure of GeS2 glass. The high-resolution real-space neutron data shows that there is a negligible amount of chemical disorder in the structure of GeS2 glass. The RMC modelling was done by fitting to the neutron total structure factor with constraints for the edge- and corner-sharing tetrahedral configurations as well as the nearest neighbour coordination numbers. Two different structure models (two-dimensional layer network and three-dimensional random network) were examined and both the models reproduced the experimental data.

  15. Applying Social Network Analysis to Understand the Knowledge Sharing Behaviour of Practitioners in a Clinical Online Discussion Forum

    PubMed Central

    Abidi, Syed Sibte Raza

    2012-01-01

    Background Knowledge Translation (KT) plays a vital role in the modern health care community, facilitating the incorporation of new evidence into practice. Web 2.0 tools provide a useful mechanism for establishing an online KT environment in which health practitioners share their practice-related knowledge and experiences with an online community of practice. We have implemented a Web 2.0 based KT environment—an online discussion forum—for pediatric pain practitioners across seven different hospitals in Thailand. The online discussion forum enabled the pediatric pain practitioners to share and translate their experiential knowledge to help improve the management of pediatric pain in hospitals. Objective The goal of this research is to investigate the knowledge sharing dynamics of a community of practice through an online discussion forum. We evaluated the communication patterns of the community members using statistical and social network analysis methods in order to better understand how the online community engages to share experiential knowledge. Methods Statistical analyses and visualizations provide a broad overview of the communication patterns within the discussion forum. Social network analysis provides the tools to delve deeper into the social network, identifying the most active members of the community, reporting the overall health of the social network, isolating the potential core members of the social network, and exploring the inter-group relationships that exist across institutions and professions. Results The statistical analyses revealed a network dominated by a single institution and a single profession, and found a varied relationship between reading and posting content to the discussion forum. The social network analysis discovered a healthy network with strong communication patterns, while identifying which users are at the center of the community in terms of facilitating communication. The group-level analysis suggests that there is

  16. Applying social network analysis to understand the knowledge sharing behaviour of practitioners in a clinical online discussion forum.

    PubMed

    Stewart, Samuel Alan; Abidi, Syed Sibte Raza

    2012-12-04

    Knowledge Translation (KT) plays a vital role in the modern health care community, facilitating the incorporation of new evidence into practice. Web 2.0 tools provide a useful mechanism for establishing an online KT environment in which health practitioners share their practice-related knowledge and experiences with an online community of practice. We have implemented a Web 2.0 based KT environment--an online discussion forum--for pediatric pain practitioners across seven different hospitals in Thailand. The online discussion forum enabled the pediatric pain practitioners to share and translate their experiential knowledge to help improve the management of pediatric pain in hospitals. The goal of this research is to investigate the knowledge sharing dynamics of a community of practice through an online discussion forum. We evaluated the communication patterns of the community members using statistical and social network analysis methods in order to better understand how the online community engages to share experiential knowledge. Statistical analyses and visualizations provide a broad overview of the communication patterns within the discussion forum. Social network analysis provides the tools to delve deeper into the social network, identifying the most active members of the community, reporting the overall health of the social network, isolating the potential core members of the social network, and exploring the inter-group relationships that exist across institutions and professions. The statistical analyses revealed a network dominated by a single institution and a single profession, and found a varied relationship between reading and posting content to the discussion forum. The social network analysis discovered a healthy network with strong communication patterns, while identifying which users are at the center of the community in terms of facilitating communication. The group-level analysis suggests that there is strong interprofessional and interregional

  17. Shared end-to-content backup path protection in k-node (edge) content connected elastic optical datacenter networks.

    PubMed

    Li, Xin; Huang, Shanguo; Yin, Shan; Guo, Bingli; Zhao, Yongli; Zhang, Jie; Zhang, Min; Gu, Wanyi

    2016-05-02

    To quantitatively measure content connectivity and provide protection for different kinds of content, the concept of k-node (edge) content connectivity is proposed recently. Based on k-node (edge) content connectivity, k-node (edge) content connected elastic optical datacenter network (KC-EODN) is proposed to design disaster-resilient and spectrum-efficient optical datacenter networks. In KC-EODN, k independent end-to-content paths are established for each request. However, it will consume too much resource to assign dedicated spectrum for each end-to-content path. Spectrum sharing among multiple end-to-content paths of different requests can greatly improve resource efficiency. In this paper, a novel perfect matching based sharing principle among multiple end-to-content paths of different requests is proposed. Based on the new proposed sharing principle, we present the shared end-to-content backup path protection (SEBPP) scheme for KC-EODN. Integer linear program (ILP) model and heuristic algorithms are designed for SEBPP scheme with the objective of minimizing the total of working and backup spectrum resources. Numerical results show that the proposed SEBPP scheme can greatly reduce spectrum consumption while ensuring the survivability against natural disaster and multi-failures.

  18. Managing Information Sharing within an Organizational Setting: A Social Network Perspective

    ERIC Educational Resources Information Center

    Hatala, John-Paul; Lutta, Joseph George

    2009-01-01

    Information sharing is critical to an organization's competitiveness and requires a free flow of information among members if the organization is to remain competitive. A review of the literature on organizational structure and information sharing was conducted to examine the research in this area. A case example illustrates how a social network…

  19. Managing Information Sharing within an Organizational Setting: A Social Network Perspective

    ERIC Educational Resources Information Center

    Hatala, John-Paul; Lutta, Joseph George

    2009-01-01

    Information sharing is critical to an organization's competitiveness and requires a free flow of information among members if the organization is to remain competitive. A review of the literature on organizational structure and information sharing was conducted to examine the research in this area. A case example illustrates how a social network…

  20. Switch: a planning tool for power systems with large shares of intermittent renewable energy.

    PubMed

    Fripp, Matthias

    2012-06-05

    Wind and solar power are highly variable, so it is it unclear how large a role they can play in future power systems. This work introduces a new open-source electricity planning model--Switch--that identifies the least-cost strategy for using renewable and conventional generators and transmission in a large power system over a multidecade period. Switch includes an unprecedented amount of spatial and temporal detail, making it possible to address a new type of question about the optimal design and operation of power systems with large amounts of renewable power. A case study of California for 2012-2027 finds that there is no maximum possible penetration of wind and solar power--these resources could potentially be used to reduce emissions 90% or more below 1990 levels without reducing reliability or severely raising the cost of electricity. This work also finds that policies that encourage customers to shift electricity demand to times when renewable power is most abundant (e.g., well-timed charging of electric vehicles) could make it possible to achieve radical emission reductions at moderate costs.

  1. NDEx: A Community Resource for Sharing and Publishing of Biological Networks.

    PubMed

    Pillich, Rudolf T; Chen, Jing; Rynkov, Vladimir; Welker, David; Pratt, Dexter

    2017-01-01

    Networks are a powerful and flexible paradigm that facilitate communication and computation about interactions of any type, whether social, economic, or biological. NDEx, the Network Data Exchange, is an online commons to enable new modes of collaboration and publication using biological networks. NDEx creates an access point and interface to a broad range of networks, whether they express molecular interactions, curated relationships from literature, or the outputs of systematic analysis of big data. Research organizations can use NDEx as a distribution channel for networks they generate or curate. Developers of bioinformatic applications can store and query NDEx networks via a common programmatic interface. NDEx can also facilitate the integration of networks as data in electronic publications, thus making a step toward an ecosystem in which networks bearing data, hypotheses, and findings flow seamlessly between scientists.

  2. Using Egocentric Networks to Illustrate Information Seeking and Sharing by Alfalfa Farmers in Wyoming

    ERIC Educational Resources Information Center

    Noy, Shiri; Jabbour, Randa

    2017-01-01

    We explored using farmers' egocentric (personal) networks to understand how they seek farming advice and how their advice networks map onto their friendship networks. We examined results from a survey of alfalfa farmers (n = 634) in Wyoming. Farmers reported seeking advice from neighbors and fellow farmers, and most indicated that these people are…

  3. Bionimbus: a cloud for managing, analyzing and sharing large genomics datasets

    PubMed Central

    Heath, Allison P; Greenway, Matthew; Powell, Raymond; Spring, Jonathan; Suarez, Rafael; Hanley, David; Bandlamudi, Chai; McNerney, Megan E; White, Kevin P; Grossman, Robert L

    2014-01-01

    Background As large genomics and phenotypic datasets are becoming more common, it is increasingly difficult for most researchers to access, manage, and analyze them. One possible approach is to provide the research community with several petabyte-scale cloud-based computing platforms containing these data, along with tools and resources to analyze it. Methods Bionimbus is an open source cloud-computing platform that is based primarily upon OpenStack, which manages on-demand virtual machines that provide the required computational resources, and GlusterFS, which is a high-performance clustered file system. Bionimbus also includes Tukey, which is a portal, and associated middleware that provides a single entry point and a single sign on for the various Bionimbus resources; and Yates, which automates the installation, configuration, and maintenance of the software infrastructure required. Results Bionimbus is used by a variety of projects to process genomics and phenotypic data. For example, it is used by an acute myeloid leukemia resequencing project at the University of Chicago. The project requires several computational pipelines, including pipelines for quality control, alignment, variant calling, and annotation. For each sample, the alignment step requires eight CPUs for about 12 h. BAM file sizes ranged from 5 GB to 10 GB for each sample. Conclusions Most members of the research community have difficulty downloading large genomics datasets and obtaining sufficient storage and computer resources to manage and analyze the data. Cloud computing platforms, such as Bionimbus, with data commons that contain large genomics datasets, are one choice for broadening access to research data in genomics. PMID:24464852

  4. Bionimbus: a cloud for managing, analyzing and sharing large genomics datasets.

    PubMed

    Heath, Allison P; Greenway, Matthew; Powell, Raymond; Spring, Jonathan; Suarez, Rafael; Hanley, David; Bandlamudi, Chai; McNerney, Megan E; White, Kevin P; Grossman, Robert L

    2014-01-01

    As large genomics and phenotypic datasets are becoming more common, it is increasingly difficult for most researchers to access, manage, and analyze them. One possible approach is to provide the research community with several petabyte-scale cloud-based computing platforms containing these data, along with tools and resources to analyze it. Bionimbus is an open source cloud-computing platform that is based primarily upon OpenStack, which manages on-demand virtual machines that provide the required computational resources, and GlusterFS, which is a high-performance clustered file system. Bionimbus also includes Tukey, which is a portal, and associated middleware that provides a single entry point and a single sign on for the various Bionimbus resources; and Yates, which automates the installation, configuration, and maintenance of the software infrastructure required. Bionimbus is used by a variety of projects to process genomics and phenotypic data. For example, it is used by an acute myeloid leukemia resequencing project at the University of Chicago. The project requires several computational pipelines, including pipelines for quality control, alignment, variant calling, and annotation. For each sample, the alignment step requires eight CPUs for about 12 h. BAM file sizes ranged from 5 GB to 10 GB for each sample. Most members of the research community have difficulty downloading large genomics datasets and obtaining sufficient storage and computer resources to manage and analyze the data. Cloud computing platforms, such as Bionimbus, with data commons that contain large genomics datasets, are one choice for broadening access to research data in genomics. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  5. Path-protection routing and wavelength assignment in WDM mesh networks under shared-risk-group constraints

    NASA Astrophysics Data System (ADS)

    Zang, Hui; Ou, Canhui; Mukherjee, Biswanath

    2001-10-01

    This study investigates the problem of fault management in a wavelength-division multiplexing (WDM)-based optical mesh network in which failures occur due to fiber cuts. In reality, bundles of fibers often get cut at the same time due to construction or destructive natural events, such as earthquakes. Fibers laid down in the same duct have a significant probability to fail at the same time. If two fibers reside in the same cable (bundle of fibers) or the same duct, we say that these two fibers are in the same Shared Risk Group (SRG). When path protection is employed, we require the primary path and the backup path to be SRG-disjoint, so that the network is survivable under single-SRG failures. Moreover, if two primary paths go through any common SRG, their backup paths cannot share wavelengths on common links. This study addresses the routing and wavelength-assignment problem in a network with path protection under SRG constraints. Off-line algorithms for static traffic is developed to combat single-SRG failures. The objective is to minimize total number of wavelengths used on all the links in the network. Both Integer Linear Programs (ILPs) and heuristic algorithms are presented and their performances are compared through numerical examples.

  6. Multilevel method for modeling large-scale networks.

    SciTech Connect

    Safro, I. M.

    2012-02-24

    Understanding the behavior of real complex networks is of great theoretical and practical significance. It includes developing accurate artificial models whose topological properties are similar to the real networks, generating the artificial networks at different scales under special conditions, investigating a network dynamics, reconstructing missing data, predicting network response, detecting anomalies and other tasks. Network generation, reconstruction, and prediction of its future topology are central issues of this field. In this project, we address the questions related to the understanding of the network modeling, investigating its structure and properties, and generating artificial networks. Most of the modern network generation methods are based either on various random graph models (reinforced by a set of properties such as power law distribution of node degrees, graph diameter, and number of triangles) or on the principle of replicating an existing model with elements of randomization such as R-MAT generator and Kronecker product modeling. Hierarchical models operate at different levels of network hierarchy but with the same finest elements of the network. However, in many cases the methods that include randomization and replication elements on the finest relationships between network nodes and modeling that addresses the problem of preserving a set of simplified properties do not fit accurately enough the real networks. Among the unsatisfactory features are numerically inadequate results, non-stability of algorithms on real (artificial) data, that have been tested on artificial (real) data, and incorrect behavior at different scales. One reason is that randomization and replication of existing structures can create conflicts between fine and coarse scales of the real network geometry. Moreover, the randomization and satisfying of some attribute at the same time can abolish those topological attributes that have been undefined or hidden from

  7. Enabling parallel simulation of large-scale HPC network systems

    DOE PAGES

    Mubarak, Misbah; Carothers, Christopher D.; Ross, Robert B.; ...

    2016-04-07

    Here, with the increasing complexity of today’s high-performance computing (HPC) architectures, simulation has become an indispensable tool for exploring the design space of HPC systems—in particular, networks. In order to make effective design decisions, simulations of these systems must possess the following properties: (1) have high accuracy and fidelity, (2) produce results in a timely manner, and (3) be able to analyze a broad range of network workloads. Most state-of-the-art HPC network simulation frameworks, however, are constrained in one or more of these areas. In this work, we present a simulation framework for modeling two important classes of networks usedmore » in today’s IBM and Cray supercomputers: torus and dragonfly networks. We use the Co-Design of Multi-layer Exascale Storage Architecture (CODES) simulation framework to simulate these network topologies at a flit-level detail using the Rensselaer Optimistic Simulation System (ROSS) for parallel discrete-event simulation. Our simulation framework meets all the requirements of a practical network simulation and can assist network designers in design space exploration. First, it uses validated and detailed flit-level network models to provide an accurate and high-fidelity network simulation. Second, instead of relying on serial time-stepped or traditional conservative discrete-event simulations that limit simulation scalability and efficiency, we use the optimistic event-scheduling capability of ROSS to achieve efficient and scalable HPC network simulations on today’s high-performance cluster systems. Third, our models give network designers a choice in simulating a broad range of network workloads, including HPC application workloads using detailed network traces, an ability that is rarely offered in parallel with high-fidelity network simulations« less

  8. Enabling parallel simulation of large-scale HPC network systems

    SciTech Connect

    Mubarak, Misbah; Carothers, Christopher D.; Ross, Robert B.; Carns, Philip

    2016-04-07

    Here, with the increasing complexity of today’s high-performance computing (HPC) architectures, simulation has become an indispensable tool for exploring the design space of HPC systems—in particular, networks. In order to make effective design decisions, simulations of these systems must possess the following properties: (1) have high accuracy and fidelity, (2) produce results in a timely manner, and (3) be able to analyze a broad range of network workloads. Most state-of-the-art HPC network simulation frameworks, however, are constrained in one or more of these areas. In this work, we present a simulation framework for modeling two important classes of networks used in today’s IBM and Cray supercomputers: torus and dragonfly networks. We use the Co-Design of Multi-layer Exascale Storage Architecture (CODES) simulation framework to simulate these network topologies at a flit-level detail using the Rensselaer Optimistic Simulation System (ROSS) for parallel discrete-event simulation. Our simulation framework meets all the requirements of a practical network simulation and can assist network designers in design space exploration. First, it uses validated and detailed flit-level network models to provide an accurate and high-fidelity network simulation. Second, instead of relying on serial time-stepped or traditional conservative discrete-event simulations that limit simulation scalability and efficiency, we use the optimistic event-scheduling capability of ROSS to achieve efficient and scalable HPC network simulations on today’s high-performance cluster systems. Third, our models give network designers a choice in simulating a broad range of network workloads, including HPC application workloads using detailed network traces, an ability that is rarely offered in parallel with high-fidelity network simulations

  9. Dynamic Spectrum Access to the Combined Resource of Commercial and Public Safety Bands Based on a WCDMA Shared Network

    NASA Astrophysics Data System (ADS)

    Jeon, Hyoungsuk; Im, Sooyeol; Kim, Youmin; Kim, Seunghee; Kim, Jinup; Lee, Hyuckjae

    The public safety spectrum is generally under-utilized due to the unique traffic characteristics of bursty and mission critical. This letter considers the application of dynamic spectrum access (DSA) to the combined spectrum of public safety (PS) and commercial (CMR) users in a common shared network that can provide both PS and CMR services. Our scenario includes the 700MHz Public/Private Partnership which was recently issued by the Federal Communications Commission. We first propose an efficient DSA mechanism to coordinate the combined spectrum, and then establish a call admission control that reflects the proposed DSA in a wideband code division multiple access based network. The essentials of our proposed DSA are opportunistic access to the public safety spectrum and priority access to the commercial spectrum. Simulation results show that these schemes are well harmonized in various network environments.

  10. FluxSuite: a New Scientific Tool for Advanced Network Management and Cross-Sharing of Next-Generation Flux Stations

    NASA Astrophysics Data System (ADS)

    Burba, G. G.; Johnson, D.; Velgersdyk, M.; Beaty, K.; Forgione, A.; Begashaw, I.; Allyn, D.

    2015-12-01

    Significant increases in data generation and computing power in recent years have greatly improved spatial and temporal flux data coverage on multiple scales, from a single station to continental flux networks. At the same time, operating budgets for flux teams and stations infrastructure are getting ever more difficult to acquire and sustain. With more stations and networks, larger data flows from each station, and smaller operating budgets, modern tools are needed to effectively and efficiently handle the entire process. This would help maximize time dedicated to answering research questions, and minimize time and expenses spent on data processing, quality control and station management. Cross-sharing the stations with external institutions may also help leverage available funding, increase scientific collaboration, and promote data analyses and publications. FluxSuite, a new advanced tool combining hardware, software and web-service, was developed to address these specific demands. It automates key stages of flux workflow, minimizes day-to-day site management, and modernizes the handling of data flows: Each next-generation station measures all parameters needed for flux computations Field microcomputer calculates final fully-corrected flux rates in real time, including computation-intensive Fourier transforms, spectra, co-spectra, multiple rotations, stationarity, footprint, etc. Final fluxes, radiation, weather and soil data are merged into a single quality-controlled file Multiple flux stations are linked into an automated time-synchronized network Flux network manager, or PI, can see all stations in real time, including fluxes, supporting data, automated reports, and email alerts PI can assign rights, allow or restrict access to stations and data: selected stations can be shared via rights-managed access internally or with external institutions Researchers without stations could form "virtual networks" for specific projects by collaborating with PIs from

  11. Triple functional shared channel in WDM PON by orthogonal modulation and network coding

    NASA Astrophysics Data System (ADS)

    Lu, Yang; Wei, Yizhen; Hu, Miao; Zhou, Xuefang; Qian, Zhengfeng; Li, Qiliang

    2015-02-01

    A triple functional shared channel in WDM PON is proposed. The channel can be applied for broadcasting, duplex inter-ONU-communication or dynamical bandwidth allocation, increasing the flexibility and the resource utilization of the scheme. The three applications could be achieved by the same hardware, with different software operations. One example scheme is demonstrated. The test results show error free operation is achieved after for the downstream transmission, upstream transmission and the proposed three applications in shared channel after 25 km transmission.

  12. From Social Network (Centralized vs. Decentralized) to Collective Decision-Making (Unshared vs. Shared Consensus)

    PubMed Central

    Sueur, Cédric; Deneubourg, Jean-Louis; Petit, Odile

    2012-01-01

    Relationships we have with our friends, family, or colleagues influence our personal decisions, as well as decisions we make together with others. As in human beings, despotism and egalitarian societies seem to also exist in animals. While studies have shown that social networks constrain many phenomena from amoebae to primates, we still do not know how consensus emerges from the properties of social networks in many biological systems. We created artificial social networks that represent the continuum from centralized to decentralized organization and used an agent-based model to make predictions about the patterns of consensus and collective movements we observed according to the social network. These theoretical results showed that different social networks and especially contrasted ones – star network vs. equal network - led to totally different patterns. Our model showed that, by moving from a centralized network to a decentralized one, the central individual seemed to lose its leadership in the collective movement's decisions. We, therefore, showed a link between the type of social network and the resulting consensus. By comparing our theoretical data with data on five groups of primates, we confirmed that this relationship between social network and consensus also appears to exist in animal societies. PMID:22393416

  13. Overview of the gene regulation network and the bacteria biotope tasks in BioNLP'13 shared task

    PubMed Central

    2015-01-01

    Background We present the two Bacteria Track tasks of BioNLP 2013 Shared Task (ST): Gene Regulation Network (GRN) and Bacteria Biotope (BB). These tasks were previously introduced in the 2011 BioNLP-ST Bacteria Track as Bacteria Gene Interaction (BI) and Bacteria Biotope (BB). The Bacteria Track was motivated by a need to develop specific BioNLP tools for fine-grained event extraction in bacteria biology. The 2013 tasks expand on the 2011 version by better addressing the biological knowledge modeling needs. New evaluation metrics were designed for the new goals. Moving beyond a list of gene interactions, the goal of the GRN task is to build a gene regulation network from the extracted gene interactions. BB'13 is dedicated to the extraction of bacteria biotopes, i.e. bacterial environmental information, as was BB'11. BB'13 extends the typology of BB'11 to a large diversity of biotopes, as defined by the OntoBiotope ontology. The detection of entities and events is tackled by distinct subtasks in order to measure the progress achieved by the participant systems since 2011. Results This paper details the corpus preparations and the evaluation metrics, as well as summarizing and discussing the participant results. Five groups participated in each of the two tasks. The high diversity of the participant methods reflects the dynamism of the BioNLP research community. The highest scores for the GRN and BB'13 tasks are similar to those obtained by the participants in 2011, despite of the increase in difficulty. The high density of events in short text segments (multi-event extraction) was a difficult issue for the participating systems for both tasks. The analysis of the BB'13 results also shows that co-reference resolution and entity boundary detection remain major hindrances. Conclusion The evaluation results suggest new research directions for the improvement and development of Information Extraction for molecular and environmental biology. The Bacteria Track tasks

  14. Mining and state-space modeling and verification of sub-networks from large-scale biomolecular networks.

    PubMed

    Hu, Xiaohua; Wu, Fang-Xiang

    2007-08-31

    Biomolecular networks dynamically respond to stimuli and implement cellular function. Understanding these dynamic changes is the key challenge for cell biologists. As biomolecular networks grow in size and complexity, the model of a biomolecular network must become more rigorous to keep track of all the components and their interactions. In general this presents the need for computer simulation to manipulate and understand the biomolecular network model. In this paper, we present a novel method to model the regulatory system which executes a cellular function and can be represented as a biomolecular network. Our method consists of two steps. First, a novel scale-free network clustering approach is applied to the large-scale biomolecular network to obtain various sub-networks. Second, a state-space model is generated for the sub-networks and simulated to predict their behavior in the cellular context. The modeling results represent hypotheses that are tested against high-throughput data sets (microarrays and/or genetic screens) for both the natural system and perturbations. Notably, the dynamic modeling component of this method depends on the automated network structure generation of the first component and the sub-network clustering, which are both essential to make the solution tractable. Experimental results on time series gene expression data for the human cell cycle indicate our approach is promising for sub-network mining and simulation from large-scale biomolecular network.

  15. Mining and state-space modeling and verification of sub-networks from large-scale biomolecular networks

    PubMed Central

    Hu, Xiaohua; Wu, Fang-Xiang

    2007-01-01

    Background Biomolecular networks dynamically respond to stimuli and implement cellular function. Understanding these dynamic changes is the key challenge for cell biologists. As biomolecular networks grow in size and complexity, the model of a biomolecular network must become more rigorous to keep track of all the components and their interactions. In general this presents the need for computer simulation to manipulate and understand the biomolecular network model. Results In this paper, we present a novel method to model the regulatory system which executes a cellular function and can be represented as a biomolecular network. Our method consists of two steps. First, a novel scale-free network clustering approach is applied to the large-scale biomolecular network to obtain various sub-networks. Second, a state-space model is generated for the sub-networks and simulated to predict their behavior in the cellular context. The modeling results represent hypotheses that are tested against high-throughput data sets (microarrays and/or genetic screens) for both the natural system and perturbations. Notably, the dynamic modeling component of this method depends on the automated network structure generation of the first component and the sub-network clustering, which are both essential to make the solution tractable. Conclusion Experimental results on time series gene expression data for the human cell cycle indicate our approach is promising for sub-network mining and simulation from large-scale biomolecular network. PMID:17764552

  16. The national drug abuse treatment clinical trials network data share project: website design, usage, challenges, and future directions.

    PubMed

    Shmueli-Blumberg, Dikla; Hu, Lian; Allen, Colleen; Frasketi, Michael; Wu, Li-Tzy; Vanveldhuisen, Paul

    2013-01-01

    There are many benefits of data sharing, including the promotion of new research from effective use of existing data, replication of findings through re-analysis of pooled data files, meta-analysis using individual patient data, and reinforcement of open scientific inquiry. A randomized controlled trial is considered as the 'gold standard' for establishing treatment effectiveness, but clinical trial research is very costly, and sharing data is an opportunity to expand the investment of the clinical trial beyond its original goals at minimal costs. We describe the goals, developments, and usage of the Data Share website (http://www.ctndatashare.org) for the National Drug Abuse Treatment Clinical Trials Network (CTN) in the United States, including lessons learned, limitations, and major revisions, and considerations for future directions to improve data sharing. Data management and programming procedures were conducted to produce uniform and Health Insurance Portability and Accountability Act (HIPAA)-compliant de-identified research data files from the completed trials of the CTN for archiving, managing, and sharing on the Data Share website. Since its inception in 2006 and through October 2012, nearly 1700 downloads from 27 clinical trials have been accessed from the Data Share website, with the use increasing over the years. Individuals from 31 countries have downloaded data from the website, and there have been at least 13 publications derived from analyzing data through the public Data Share website. Minimal control over data requests and usage has resulted in little information and lack of control regarding how the data from the website are used. Lack of uniformity in data elements collected across CTN trials has limited cross-study analyses. The Data Share website offers researchers easy access to de-identified data files with the goal to promote additional research and identify new findings from completed CTN studies. To maximize the utility of the website

  17. Distributive Computer Networking: Making It Work on a Regional Basis: Effective sharing through a network requires new management and resource distribution techniques.

    PubMed

    Cornew, R W; Morse, P M

    1975-08-15

    -indicate that such networks are best structured in a hierarchical form. This suggests that national networking should be based in part on the more than 30 existing state and regional networks (15). With the groundwork now laid, we expect to see links among existing regional networks to complement development efforts now occurring at the national level. With Greenberger and others, we believe that one or more networking organizations devoted to the management issues discussed in this article will be required to facilitate resource sharing on a national scale. Because of their experience with these problems and their ability to provide service in many areas of the country through existing facilities, regional networks have a major role to play.

  18. Approximating spectral impact of structural perturbations in large networks.

    PubMed

    Milanese, Attilio; Sun, Jie; Nishikawa, Takashi

    2010-04-01

    Determining the effect of structural perturbations on the eigenvalue spectra of networks is an important problem because the spectra characterize not only their topological structures, but also their dynamical behavior, such as synchronization and cascading processes on networks. Here we develop a theory for estimating the change of the largest eigenvalue of the adjacency matrix or the extreme eigenvalues of the graph Laplacian when small but arbitrary set of links are added or removed from the network. We demonstrate the effectiveness of our approximation schemes using both real and artificial networks, showing in particular that we can accurately obtain the spectral ranking of small subgraphs. We also propose a local iterative scheme which computes the relative ranking of a subgraph using only the connectivity information of its neighbors within a few links. Our results may not only contribute to our theoretical understanding of dynamical processes on networks, but also lead to practical applications in ranking subgraphs of real complex networks.

  19. Challenges to create optical networks for large carriers

    NASA Astrophysics Data System (ADS)

    Nathan, Sri S.; Tarazi, Iyad

    1996-11-01

    All optical network is creating a paradigm shift in the way communication network is designed, comparable to analog to digital transition. This paper focuses on architecture design methods for all optical network. Its primary focus is on the restoration of these networks, as the impact of failure is many magnitudes higher than traditional transmission systems. The paper also has sections related to the key element of all optical network, namely the size of optical cross-connects, as the economics of all optical network heavily depends on the cross-connect size. Capability of multiplexing wavelengths created the ability to transmit high bandwidths and technology leaps in optical amplifier resulted in longer express system. The economic benefits of such architecture are also discussed. Managing wavelengths is another key element in the all optical network. This paper discusses benefits of wavelength switching. Last but not the least, the performance requirement of optical network is discussed. Performance during failure scenarios are discussed. The paper also discusses, at a high level, a typical modeling approach with evaluation criterion for good network design.

  20. Identifying Infection Sources and Regions in Large Networks

    NASA Astrophysics Data System (ADS)

    Luo, Wuqiong; Tay, Wee Peng; Leng, Mei

    2013-06-01

    Identifying the infection sources in a network, including the index cases that introduce a contagious disease into a population network, the servers that inject a computer virus into a computer network, or the individuals who started a rumor in a social network, plays a critical role in limiting the damage caused by the infection through timely quarantine of the sources. We consider the problem of estimating the infection sources and the infection regions (subsets of nodes infected by each source) in a network, based only on knowledge of which nodes are infected and their connections, and when the number of sources is unknown a priori. We derive estimators for the infection sources and their infection regions based on approximations of the infection sequences count. We prove that if there are at most two infection sources in a geometric tree, our estimator identifies the true source or sources with probability going to one as the number of infected nodes increases. When there are more than two infection sources, and when the maximum possible number of infection sources is known, we propose an algorithm with quadratic complexity to estimate the actual number and identities of the infection sources. Simulations on various kinds of networks, including tree networks, small-world networks and real world power grid networks, and tests on two real data sets are provided to verify the performance of our estimators.

  1. Affect-specific activation of shared networks for perception and execution of facial expressions.

    PubMed

    Kircher, Tilo; Pohl, Anna; Krach, Sören; Thimm, Markus; Schulte-Rüther, Martin; Anders, Silke; Mathiak, Klaus

    2013-04-01

    Previous studies have shown overlapping neural activations for observation and execution or imitation of emotional facial expressions. These shared representations have been assumed to provide indirect evidence for a human mirror neuron system, which is suggested to be a prerequisite of action comprehension. We aimed at clarifying whether shared representations in and beyond human mirror areas are specifically activated by affective facial expressions or whether they are activated by facial expressions independent of the emotional meaning. During neuroimaging, participants observed and executed happy and non-emotional facial expressions. Shared representations were revealed for happy facial expressions in the pars opercularis, the precentral gyrus, in the superior temporal gyrus/medial temporal gyrus (MTG), in the pre-supplementary motor area and in the right amygdala. All areas showed less pronounced activation in the non-emotional condition. When directly compared, significant stronger neural responses emerged for happy facial expressions in the pre-supplementary motor area and in the MTG than for non-emotional stimuli. We assume that activation of shared representations depends on the affect and (social) relevance of the facial expression. The pre-supplementary motor area is a core-shared representation-structure supporting observation and execution of affective contagious facial expressions and might have a modulatory role during the preparation of executing happy facial expressions.

  2. Affect-specific activation of shared networks for perception and execution of facial expressions

    PubMed Central

    Kircher, Tilo; Krach, Sören; Thimm, Markus; Schulte-Rüther, Martin; Anders, Silke; Mathiak, Klaus

    2013-01-01

    Previous studies have shown overlapping neural activations for observation and execution or imitation of emotional facial expressions. These shared representations have been assumed to provide indirect evidence for a human mirror neuron system, which is suggested to be a prerequisite of action comprehension. We aimed at clarifying whether shared representations in and beyond human mirror areas are specifically activated by affective facial expressions or whether they are activated by facial expressions independent of the emotional meaning. During neuroimaging, participants observed and executed happy and non-emotional facial expressions. Shared representations were revealed for happy facial expressions in the pars opercularis, the precentral gyrus, in the superior temporal gyrus/medial temporal gyrus (MTG), in the pre-supplementary motor area and in the right amygdala. All areas showed less pronounced activation in the non-emotional condition. When directly compared, significant stronger neural responses emerged for happy facial expressions in the pre-supplementary motor area and in the MTG than for non-emotional stimuli. We assume that activation of shared representations depends on the affect and (social) relevance of the facial expression. The pre-supplementary motor area is a core-shared representation-structure supporting observation and execution of affective contagious facial expressions and might have a modulatory role during the preparation of executing happy facial expressions. PMID:22275167

  3. An e-consent-based shared EHR system architecture for integrated healthcare networks.

    PubMed

    Bergmann, Joachim; Bott, Oliver J; Pretschner, Dietrich P; Haux, Reinhold

    2007-01-01

    Virtual integration of distributed patient data promises advantages over a consolidated health record, but raises questions mainly about practicability and authorization concepts. Our work aims on specification and development of a virtual shared health record architecture using a patient-centred integration and authorization model. A literature survey summarizes considerations of current architectural approaches. Complemented by a methodical analysis in two regional settings, a formal architecture model was specified and implemented. Results presented in this paper are a survey of architectural approaches for shared health records and an architecture model for a virtual shared EHR, which combines a patient-centred integration policy with provider-oriented document management. An electronic consent system assures, that access to the shared record remains under control of the patient. A corresponding system prototype has been developed and is currently being introduced and evaluated in a regional setting. The proposed architecture is capable of partly replacing message-based communications. Operating highly available provider repositories for the virtual shared EHR requires advanced technology and probably means additional costs for care providers. Acceptance of the proposed architecture depends on transparently embedding document validation and digital signature into the work processes. The paradigm shift from paper-based messaging to a "pull model" needs further evaluation.

  4. GeNET: a web application to explore and share Gene Co-expression Network Analysis data.

    PubMed

    Desai, Amit P; Razeghin, Mehdi; Meruvia-Pastor, Oscar; Peña-Castillo, Lourdes

    2017-01-01

    Gene Co-expression Network Analysis (GCNA) is a popular approach to analyze a collection of gene expression profiles. GCNA yields an assignment of genes to gene co-expression modules, a list of gene sets statistically over-represented in these modules, and a gene-to-gene network. There are several computer programs for gene-to-gene network visualization, but these programs have limitations in terms of integrating all the data generated by a GCNA and making these data available online. To facilitate sharing and study of GCNA data, we developed GeNET. For researchers interested in sharing their GCNA data, GeNET provides a convenient interface to upload their data and automatically make it accessible to the public through an online server. For researchers interested in exploring GCNA data published by others, GeNET provides an intuitive online tool to interactively explore GCNA data by genes, gene sets or modules. In addition, GeNET allows users to download all or part of the published data for further computational analysis. To demonstrate the applicability of GeNET, we imported three published GCNA datasets, the largest of which consists of roughly 17,000 genes and 200 conditions. GeNET is available at bengi.cs.mun.ca/genet.

  5. A Scalable QoS-Aware VoD Resource Sharing Scheme for Next Generation Networks

    NASA Astrophysics Data System (ADS)

    Huang, Chenn-Jung; Luo, Yun-Cheng; Chen, Chun-Hua; Hu, Kai-Wen

    In network-aware concept, applications are aware of network conditions and are adaptable to the varying environment to achieve acceptable and predictable performance. In this work, a solution for video on demand service that integrates wireless and wired networks by using the network aware concepts is proposed to reduce the blocking probability and dropping probability of mobile requests. Fuzzy logic inference system is employed to select appropriate cache relay nodes to cache published video streams and distribute them to different peers through service oriented architecture (SOA). SIP-based control protocol and IMS standard are adopted to ensure the possibility of heterogeneous communication and provide a framework for delivering real-time multimedia services over an IP-based network to ensure interoperability, roaming, and end-to-end session management. The experimental results demonstrate that effectiveness and practicability of the proposed work.

  6. A Method of Social Collaboration and Knowledge Sharing Acceleration for e-Learning System: The Distance Learning Network Scenario

    NASA Astrophysics Data System (ADS)

    Różewski, Przemysław

    Nowadays, e-learning systems take the form of the Distance Learning Network (DLN) due to widespread use and accessibility of the Internet and networked e-learning services. The focal point of the DLN performance is efficiency of knowledge processing in asynchronous learning mode and facilitating cooperation between students. In addition, the DLN articulates attention to social aspects of the learning process as well. In this paper, a method for the DLN development is proposed. The main research objectives for the proposed method are the processes of acceleration of social collaboration and knowledge sharing in the DLN. The method introduces knowledge-disposed agents (who represent students in educational scenarios) that form a network of individuals aimed to increase their competence. For every agent the competence expansion process is formulated. Based on that outcome the process of dynamic network formation performed on the social and knowledge levels. The method utilizes formal apparatuses of competence set and network game theories combined with an agent system-based approach.

  7. Explicit integration with GPU acceleration for large kinetic networks

    SciTech Connect

    Brock, Benjamin; Belt, Andrew; Billings, Jay Jay; Guidry, Mike

    2015-12-01

    We demonstrate the first implementation of recently-developed fast explicit kinetic integration algorithms on modern graphics processing unit (GPU) accelerators. Taking as a generic test case a Type Ia supernova explosion with an extremely stiff thermonuclear network having 150 isotopic species and 1604 reactions coupled to hydrodynamics using operator splitting, we demonstrate the capability to solve of order 100 realistic kinetic networks in parallel in the same time that standard implicit methods can solve a single such network on a CPU. This orders-of-magnitude decrease in computation time for solving systems of realistic kinetic networks implies that important coupled, multiphysics problems in various scientific and technical fields that were intractable, or could be simulated only with highly schematic kinetic networks, are now computationally feasible.

  8. Explicit integration with GPU acceleration for large kinetic networks

    DOE PAGES

    Brock, Benjamin; Belt, Andrew; Billings, Jay Jay; ...

    2015-09-15

    In this study, we demonstrate the first implementation of recently-developed fast explicit kinetic integration algorithms on modern graphics processing unit (GPU) accelerators. Taking as a generic test case a Type Ia supernova explosion with an extremely stiff thermonuclear network having 150 isotopic species and 1604 reactions coupled to hydrodynamics using operator splitting, we demonstrate the capability to solve of order 100 realistic kinetic networks in parallel in the same time that standard implicit methods can solve a single such network on a CPU. In addition, this orders-of-magnitude decrease in computation time for solving systems of realistic kinetic networks implies thatmore » important coupled, multiphysics problems in various scientific and technical fields that were intractable, or could be simulated only with highly schematic kinetic networks, are now computationally feasible.« less

  9. Explicit integration with GPU acceleration for large kinetic networks

    SciTech Connect

    Brock, Benjamin; Belt, Andrew; Billings, Jay Jay; Guidry, Mike W.

    2015-09-15

    In this study, we demonstrate the first implementation of recently-developed fast explicit kinetic integration algorithms on modern graphics processing unit (GPU) accelerators. Taking as a generic test case a Type Ia supernova explosion with an extremely stiff thermonuclear network having 150 isotopic species and 1604 reactions coupled to hydrodynamics using operator splitting, we demonstrate the capability to solve of order 100 realistic kinetic networks in parallel in the same time that standard implicit methods can solve a single such network on a CPU. In addition, this orders-of-magnitude decrease in computation time for solving systems of realistic kinetic networks implies that important coupled, multiphysics problems in various scientific and technical fields that were intractable, or could be simulated only with highly schematic kinetic networks, are now computationally feasible.

  10. Knowledge sharing in infection prevention in routine and outbreak situations: a survey of the Society for Healthcare Epidemiology of America Research Network.

    PubMed

    Sommerstein, Rami; Geser, Sonja; Atkinson, Andrew; Tschan, Franziska; Morgan, Daniel J; Marschall, Jonas

    2017-01-01

    In this cross-sectional Society for Healthcare Epidemiology of America Research Network survey on knowledge sharing in infection prevention we identified a rudimentary understanding of how to communicate and share knowledge within healthcare institutions. Our data support the need of further research in this important field.

  11. An Interactive Web Tool for Facilitating Shared Decision-Making in Dementia-Care Networks: A Field Study.

    PubMed

    Span, Marijke; Smits, Carolien; Jukema, Jan; Groen-van de Ven, Leontine; Janssen, Ruud; Vernooij-Dassen, Myrra; Eefsting, Jan; Hettinga, Marike

    2015-01-01

    An interactive web tool has been developed for facilitating shared decision-making in dementia-care networks. The DecideGuide provides a chat function for easier communication between network members, a deciding together function for step-by-step decision-making, and an individual opinion function for eight dementia-related life domains. The aim of this study was to gain insight in the user friendliness of the DecideGuide, user acceptance and satisfaction, and participants' opinion of the DecideGuide for making decisions. A 5-month field study included four dementia-care networks (19 participants in total). The data derived from structured interviews, observations, and information that participants logged in the DecideGuide. Structured interviews took place at the start, middle, and end of the field study with people with dementia, informal caregivers, and case managers. Four observations of case managers' home visits focused on members' responses and use of the tool. (1) The user friendliness of the chat and individual opinion functions was adequate for case managers and most informal caregivers. Older participants, with or without dementia, had some difficulties using a tablet and the DecideGuide. The deciding together function does not yet provide adequate instructions for all. The user interface needs simplification. (2) User acceptance and satisfaction: everybody liked the chat's easy communication, handling difficult issues for discussion, and the option of individual opinions. (3) The DecideGuide helped participants structure their thoughts. They felt more involved and shared more information about daily issues than they had done previously. Participants found the DecideGuide valuable in decision-making. The chat function seems powerful in helping members engage with one another constructively. Such engagement is a prerequisite for making shared decisions. Regardless of participants' use of the tool, they saw the DecideGuide's added value.

  12. Abnormalities in large scale functional networks in unmedicated patients with schizophrenia and effects of risperidone.

    PubMed

    Kraguljac, Nina Vanessa; White, David Matthew; Hadley, Jennifer Ann; Visscher, Kristina; Knight, David; ver Hoef, Lawrence; Falola, Blessing; Lahti, Adrienne Carol

    2016-01-01

    To describe abnormalities in large scale functional networks in unmedicated patients with schizophrenia and to examine effects of risperidone on networks. 34 unmedicated patients with schizophrenia and 34 matched healthy controls were enrolled in this longitudinal study. We collected resting state functional MRI data with a 3T scanner at baseline and six weeks after they were started on risperidone. In addition, a group of 19 healthy controls were scanned twice six weeks apart. Four large scale networks, the dorsal attention network, executive control network, salience network, and default mode network were identified with seed based functional connectivity analyses. Group differences in connectivity, as well as changes in connectivity over time, were assessed on the group's participant level functional connectivity maps. In unmedicated patients with schizophrenia we found resting state connectivity to be increased in the dorsal attention network, executive control network, and salience network relative to control participants, but not the default mode network. Dysconnectivity was attenuated after six weeks of treatment only in the dorsal attention network. Baseline connectivity in this network was also related to clinical response at six weeks of treatment with risperidone. Our results demonstrate abnormalities in large scale functional networks in patients with schizophrenia that are modulated by risperidone only to a certain extent, underscoring the dire need for development of novel antipsychotic medications that have the ability to alleviate symptoms through attenuation of dysconnectivity.

  13. Abnormalities in large scale functional networks in unmedicated patients with schizophrenia and effects of risperidone

    PubMed Central

    Kraguljac, Nina Vanessa; White, David Matthew; Hadley, Jennifer Ann; Visscher, Kristina; Knight, David; ver Hoef, Lawrence; Falola, Blessing; Lahti, Adrienne Carol

    2015-01-01

    Objective To describe abnormalities in large scale functional networks in unmedicated patients with schizophrenia and to examine effects of risperidone on networks. Material and methods 34 unmedicated patients with schizophrenia and 34 matched healthy controls were enrolled in this longitudinal study. We collected resting state functional MRI data with a 3T scanner at baseline and six weeks after they were started on risperidone. In addition, a group of 19 healthy controls were scanned twice six weeks apart. Four large scale networks, the dorsal attention network, executive control network, salience network, and default mode network were identified with seed based functional connectivity analyses. Group differences in connectivity, as well as changes in connectivity over time, were assessed on the group's participant level functional connectivity maps. Results In unmedicated patients with schizophrenia we found resting state connectivity to be increased in the dorsal attention network, executive control network, and salience network relative to control participants, but not the default mode network. Dysconnectivity was attenuated after six weeks of treatment only in the dorsal attention network. Baseline connectivity in this network was also related to clinical response at six weeks of treatment with risperidone. Conclusions Our results demonstrate abnormalities in large scale functional networks in patients with schizophrenia that are modulated by risperidone only to a certain extent, underscoring the dire need for development of novel antipsychotic medications that have the ability to alleviate symptoms through attenuation of dysconnectivity. PMID:26793436

  14. The Shared Bibliographic Input Network (SBIN): A Summary of the Experiment.

    ERIC Educational Resources Information Center

    Cotter, Gladys A.

    As part of its mission to provide centralized services for the acquisition, storage, retrieval, and dissemination of scientific and technical information (STI) to support Department of Defense (DoD) research, development, and engineering studies programs, the Defense Technical Information Center (DTIC) sponsors the Shared Bibliographic Input…

  15. Towards Networked Knowledge: The Learning Registry, an Infrastructure for Sharing Online Learning Resources

    ERIC Educational Resources Information Center

    Lee, Ashley; Hobson, Joe; Bienkowski, Marie; Midgley, Steve; Currier, Sarah; Campbell, Lorna M.; Novoselova, Tatiana

    2012-01-01

    In this article, the authors describe an open-source, open-data digital infrastructure for sharing information about open educational resources (OERs) across disparate systems and platforms. The Learning Registry, which began as a project funded by the U.S. Departments of Education and Defense, currently has an active international community…

  16. Towards Networked Knowledge: The Learning Registry, an Infrastructure for Sharing Online Learning Resources

    ERIC Educational Resources Information Center

    Lee, Ashley; Hobson, Joe; Bienkowski, Marie; Midgley, Steve; Currier, Sarah; Campbell, Lorna M.; Novoselova, Tatiana

    2012-01-01

    In this article, the authors describe an open-source, open-data digital infrastructure for sharing information about open educational resources (OERs) across disparate systems and platforms. The Learning Registry, which began as a project funded by the U.S. Departments of Education and Defense, currently has an active international community…

  17. Has Large-Scale Named-Entity Network Analysis Been Resting on a Flawed Assumption?

    PubMed Central

    Fegley, Brent D.; Torvik, Vetle I.

    2013-01-01

    The assumption that a name uniquely identifies an entity introduces two types of errors: splitting treats one entity as two or more (because of name variants); lumping treats multiple entities as if they were one (because of shared names). Here we investigate the extent to which splitting and lumping affect commonly-used measures of large-scale named-entity networks within two disambiguated bibliographic datasets: one for co-author names in biomedicine (PubMed, 2003–2007); the other for co-inventor names in U.S. patents (USPTO, 2003–2007). In both cases, we find that splitting has relatively little effect, whereas lumping has a dramatic effect on network measures. For example, in the biomedical co-authorship network, lumping (based on last name and both initials) drives several measures down: the global clustering coefficient by a factor of 4 (from 0.265 to 0.066); degree assortativity by a factor of ∼13 (from 0.763 to 0.06); and average shortest path by a factor of 1.3 (from 5.9 to 4.5). These results can be explained in part by the fact that lumping artificially creates many intransitive relationships and high-degree vertices. This effect of lumping is much less dramatic but persists with measures that give less weight to high-degree vertices, such as the mean local clustering coefficient and log-based degree assortativity. Furthermore, the log-log distribution of collaborator counts follows a much straighter line (power law) with splitting and lumping errors than without, particularly at the low and the high counts. This suggests that part of the power law often observed for collaborator counts in science and technology reflects an artifact: name ambiguity. PMID:23894639

  18. Clustering in Large Networks Does Not Promote Upstream Reciprocity

    PubMed Central

    Masuda, Naoki

    2011-01-01

    Upstream reciprocity (also called generalized reciprocity) is a putative mechanism for cooperation in social dilemma situations with which players help others when they are helped by somebody else. It is a type of indirect reciprocity. Although upstream reciprocity is often observed in experiments, most theories suggest that it is operative only when players form short cycles such as triangles, implying a small population size, or when it is combined with other mechanisms that promote cooperation on their own. An expectation is that real social networks, which are known to be full of triangles and other short cycles, may accommodate upstream reciprocity. In this study, I extend the upstream reciprocity game proposed for a directed cycle by Boyd and Richerson to the case of general networks. The model is not evolutionary and concerns the conditions under which the unanimity of cooperative players is a Nash equilibrium. I show that an abundance of triangles or other short cycles in a network does little to promote upstream reciprocity. Cooperation is less likely for a larger population size even if triangles are abundant in the network. In addition, in contrast to the results for evolutionary social dilemma games on networks, scale-free networks lead to less cooperation than networks with a homogeneous degree distribution. PMID:21998641

  19. Clustering in large networks does not promote upstream reciprocity.

    PubMed

    Masuda, Naoki

    2011-01-01

    Upstream reciprocity (also called generalized reciprocity) is a putative mechanism for cooperation in social dilemma situations with which players help others when they are helped by somebody else. It is a type of indirect reciprocity. Although upstream reciprocity is often observed in experiments, most theories suggest that it is operative only when players form short cycles such as triangles, implying a small population size, or when it is combined with other mechanisms that promote cooperation on their own. An expectation is that real social networks, which are known to be full of triangles and other short cycles, may accommodate upstream reciprocity. In this study, I extend the upstream reciprocity game proposed for a directed cycle by Boyd and Richerson to the case of general networks. The model is not evolutionary and concerns the conditions under which the unanimity of cooperative players is a Nash equilibrium. I show that an abundance of triangles or other short cycles in a network does little to promote upstream reciprocity. Cooperation is less likely for a larger population size even if triangles are abundant in the network. In addition, in contrast to the results for evolutionary social dilemma games on networks, scale-free networks lead to less cooperation than networks with a homogeneous degree distribution.

  20. Data Sharing: A New Editorial Initiative of the International Committee of Medical Journal Editors. Implications for the Editors’ Network

    PubMed Central

    Alfonso, Fernando; Adamyan, Karlen; Artigou, Jean-Yves; Aschermann, Michael; Boehm, Michael; Buendia, Alfonso; Chu, Pao-Hsien; Cohen, Ariel; Dei Cas, Livio; Dilic, Mirza; Doubell, Anton; Echeverri, Dario; Enç, Nuray; Ferreira-González, Ignacio; J. Filipiak, Krzysztof; Flammer, Andreas; Fleck, Eckart; Gatzov, Plamen; Ginghina, Carmen; Goncalves, Lino; Haouala, Habib; Hassanein, Mahmoud; Heusch, Gerd; Huber, Kurt; Hulín, Ivan; Ivanusa, Mario; Krittayaphong, Rungroj; Lau, Chu-Pak; Marinskis, Germanas; Mach, François; Moreira, Luiz Felipe; Nieminen, Tuomo; Oukerraj, Latifa; Perings, Stefan; Pierard, Luc; Potpara, Tatjana; Reyes-Caorsi, Walter; Rim, Se-Joong; Rødevand, Olaf; Saade, Georges; Sander, Mikael; Shlyakhto, Evgeny; Timuralp, Bilgin; Tousoulis, Dimitris; Ural, Dilek; Piek, J. J.; Varga, Albert; Lüscher, Thomas F.

    2017-01-01

    The International Committee of Medical Journal Editors (ICMJE) provides recommendations to improve the editorial standards and scientific quality of biomedical journals. These recommendations range from uniform technical requirements to more complex and elusive editorial issues including ethical aspects of the scientific process. Recently, registration of clinical trials, conflicts of interest disclosure, and new criteria for authorship- emphasizing the importance of responsibility and accountability-, have been proposed. Last year, a new editorial initiative to foster sharing of clinical trial data was launched. This review discusses this novel initiative with the aim of increasing awareness among readers, investigators, authors and editors belonging to the Editors’ Network of the European Society of Cardiology. PMID:28630534

  1. Large area controlled assembly of transparent conductive networks

    DOEpatents

    Ivanov, Ilia N.; Simpson, John T.

    2015-09-29

    A method of preparing a network comprises disposing a solution comprising particulate materials in a solvent onto a superhydrophobic surface comprising a plurality of superhydrophobic features and interfacial areas between the superhydrophobic features. The plurality of superhydrophobic features has a water contact angle of at least about 150.degree.. The method of preparing the network also comprises removing the solvent from the solution of the particulate materials, and forming a network of the particulate materials in the interfacial areas, the particulate materials receding to the interfacial areas as the solvent is removed.

  2. GPP Webinar: Solar Utilization in Higher Education Networking & Information Sharing Group: Financing Issues Discussion

    EPA Pesticide Factsheets

    This presentation from a Solar Utilization in Higher Education Networking and Information webinar covers financing and project economics issues related to solar project development in the higher education sector.

  3. Combining Flux Balance and Energy Balance Analysis for Large-Scale Metabolic Network: Biochemical Circuit Theory for Analysis of Large-Scale Metabolic Networks

    NASA Technical Reports Server (NTRS)

    Beard, Daniel A.; Liang, Shou-Dan; Qian, Hong; Biegel, Bryan (Technical Monitor)

    2001-01-01

    Predicting behavior of large-scale biochemical metabolic networks represents one of the greatest challenges of bioinformatics and computational biology. Approaches, such as flux balance analysis (FBA), that account for the known stoichiometry of the reaction network while avoiding implementation of detailed reaction kinetics are perhaps the most promising tools for the analysis of large complex networks. As a step towards building a complete theory of biochemical circuit analysis, we introduce energy balance analysis (EBA), which compliments the FBA approach by introducing fundamental constraints based on the first and second laws of thermodynamics. Fluxes obtained with EBA are thermodynamically feasible and provide valuable insight into the activation and suppression of biochemical pathways.

  4. Wi-fi walkman: a wireless handheld that shares and recommends music on peer-to-peer networks

    NASA Astrophysics Data System (ADS)

    Wang, Jun; Reinders, Marcel J.; Pouwelse, Johan; Lagendijk, Reginald L.

    2005-03-01

    The Wi-Fi walkman is a mobile multimedia application that we developed to investigate the technological and usability aspects of human-computer interaction with personalized, intelligent and context-aware wearable devices in peer-to-peer wireless environments such as the future home, office, or university campuses. It is a small handheld device with a wireless link that contains music content. Users carry their own walkman around and listen to music. All this music content is distributed in the peer-to-peer network and is shared using ad-hoc networking. The walkman naturally interacts with the users and users" interest with each other in a peer-to-peer environment. Without annoying interactions, it can learn the users" music interest/taste and consequently provide personalized music recommendation according to the current situated context and user"s interest.

  5. Italian Frontotemporal Dementia Network (FTD Group-SINDEM): sharing clinical and diagnostic procedures in Frontotemporal Dementia in Italy.

    PubMed

    Borroni, B; Turrone, R; Galimberti, D; Nacmias, B; Alberici, A; Benussi, A; Caffarra, P; Caltagirone, C; Cappa, S F; Frisoni, G B; Ghidoni, R; Marra, C; Padovani, A; Rainero, I; Scarpini, E; Silani, V; Sorbi, S; Tagliavini, F; Tremolizzo, L; Bruni, A C

    2015-05-01

    In the prospect of improved disease management and future clinical trials in Frontotemporal Dementia, it is desirable to share common diagnostic procedures. To this aim, the Italian FTD Network, under the aegis of the Italian Neurological Society for Dementia, has been established. Currently, 85 Italian Centers involved in dementia care are part of the network. Each Center completed a questionnaire on the local clinical procedures, focused on (1) clinical assessment, (2) use of neuroimaging and genetics; (3) support for patients and caregivers; (4) an opinion about the prevalence of FTD. The analyses of the results documented a comprehensive clinical and instrumental approach to FTD patients and their caregivers in Italy, with about 1,000 newly diagnosed cases per year and 2,500 patients currently followed by the participating Centers. In analogy to other European FTD consortia, future aims will be devoted to collect data on epidemiology of FTD and its subtypes and to provide harmonization of procedures among Centers.

  6. Director of anesthesiology for liver transplantation: existing practices and recommendations by the United Network for Organ Sharing.

    PubMed

    Mandell, M Susan; Pomfret, Elizabeth A; Steadman, Randall; Hirose, Ryutaro; Reich, David J; Schumann, Roman; Walia, Ann

    2013-04-01

    A new Organ Procurement and Transplantation Network/United Network for Organ Sharing bylaw recommends that all centers appoint a director of liver transplant anesthesia with a uniform set of criteria. We obtained survey data from the Liver Transplant Anesthesia Consortium so that we could compare existing criteria for a director in the United States with the current recommendations. The data set included responses from adult academic liver transplant programs before the new bylaw. The respondent rates were within statistical limits to exclude sampling bias. All centers had a director of liver transplant anesthesia. The criteria varied between institutions, and the data suggest that the availability of resources influenced the choice of criteria. The information suggests that the criteria used in the new bylaw reflect existing practices. The bylaw plays an important role in supporting emerging leadership roles in liver transplant anesthesia and brings greater uniformity to the directorship position.

  7. P2P Watch: Personal Health Information Detection in Peer-to-Peer File-Sharing Networks

    PubMed Central

    El Emam, Khaled; Arbuckle, Luk; Neri, Emilio; Rose, Sean; Jonker, Elizabeth

    2012-01-01

    Background Users of peer-to-peer (P2P) file-sharing networks risk the inadvertent disclosure of personal health information (PHI). In addition to potentially causing harm to the affected individuals, this can heighten the risk of data breaches for health information custodians. Automated PHI detection tools that crawl the P2P networks can identify PHI and alert custodians. While there has been previous work on the detection of personal information in electronic health records, there has been a dearth of research on the automated detection of PHI in heterogeneous user files. Objective To build a system that accurately detects PHI in files sent through P2P file-sharing networks. The system, which we call P2P Watch, uses a pipeline of text processing techniques to automatically detect PHI in files exchanged through P2P networks. P2P Watch processes unstructured texts regardless of the file format, document type, and content. Methods We developed P2P Watch to extract and analyze PHI in text files exchanged on P2P networks. We labeled texts as PHI if they contained identifiable information about a person (eg, name and date of birth) and specifics of the person’s health (eg, diagnosis, prescriptions, and medical procedures). We evaluated the system’s performance through its efficiency and effectiveness on 3924 files gathered from three P2P networks. Results P2P Watch successfully processed 3924 P2P files of unknown content. A manual examination of 1578 randomly selected files marked by the system as non-PHI confirmed that these files indeed did not contain PHI, making the false-negative detection rate equal to zero. Of 57 files marked by the system as PHI, all contained both personally identifiable information and health information: 11 files were PHI disclosures, and 46 files contained organizational materials such as unfilled insurance forms, job applications by medical professionals, and essays. Conclusions PHI can be successfully detected in free-form textual

  8. Brain-machine interface control of a manipulator using small-world neural network and shared control strategy.

    PubMed

    Li, Ting; Hong, Jun; Zhang, Jinhua; Guo, Feng

    2014-03-15

    The improvement of the resolution of brain signal and the ability to control external device has been the most important goal in BMI research field. This paper describes a non-invasive brain-actuated manipulator experiment, which defined a paradigm for the motion control of a serial manipulator based on motor imagery and shared control. The techniques of component selection, spatial filtering and classification of motor imagery were involved. Small-world neural network (SWNN) was used to classify five brain states. To verify the effectiveness of the proposed classifier, we replace the SWNN classifier by a radial basis function (RBF) networks neural network, a standard multi-layered feed-forward backpropagation network (SMN) and a multi-SVM classifier, with the same features for the classification. The results also indicate that the proposed classifier achieves a 3.83% improvement over the best results of other classifiers. We proposed a shared control method consisting of two control patterns to expand the control of BMI from the software angle. The job of path building for reaching the 'end' point was designated as an assessment task. We recorded all paths contributed by subjects and picked up relevant parameters as evaluation coefficients. With the assistance of two control patterns and series of machine learning algorithms, the proposed BMI originally achieved the motion control of a manipulator in the whole workspace. According to experimental results, we confirmed the feasibility of the proposed BMI method for 3D motion control of a manipulator using EEG during motor imagery. Copyright © 2013 Elsevier B.V. All rights reserved.

  9. Stability constraints on large-scale structural brain networks

    PubMed Central

    Gray, Richard T.; Robinson, Peter A.

    2013-01-01

    Stability is an important dynamical property of complex systems and underpins a broad range of coherent self-organized behavior. Based on evidence that some neurological disorders correspond to linear instabilities, we hypothesize that stability constrains the brain's electrical activity and influences its structure and physiology. Using a physiologically-based model of brain electrical activity, we investigated the stability and dispersion solutions of networks of neuronal populations with propagation time delays and dendritic time constants. We find that stability is determined by the spectrum of the network's matrix of connection strengths and is independent of the temporal damping rate of axonal propagation with stability restricting the spectrum to a region in the complex plane. Time delays and dendritic time constants modify the shape of this region but it always contains the unit disk. Instabilities resulting from changes in connection strength initially have frequencies less than a critical frequency. For physiologically plausible parameter values based on the corticothalamic system, this critical frequency is approximately 10 Hz. For excitatory networks and networks with randomly distributed excitatory and inhibitory connections, time delays and non-zero dendritic time constants have no impact on network stability but do effect dispersion frequencies. Random networks with both excitatory and inhibitory connections can have multiple marginally stable modes at low delta frequencies. PMID:23630490

  10. Analysis of a summary network of co-infection in humans reveals that parasites interact most via shared resources.

    PubMed

    Griffiths, Emily C; Pedersen, Amy B; Fenton, Andy; Petchey, Owen L

    2014-05-07

    Simultaneous infection by multiple parasite species (viruses, bacteria, helminths, protozoa or fungi) is commonplace. Most reports show co-infected humans to have worse health than those with single infections. However, we have little understanding of how co-infecting parasites interact within human hosts. We used data from over 300 published studies to construct a network that offers the first broad indications of how groups of co-infecting parasites tend to interact. The network had three levels comprising parasites, the resources they consume and the immune responses they elicit, connected by potential, observed and experimentally proved links. Pairs of parasite species had most potential to interact indirectly through shared resources, rather than through immune responses or other parasites. In addition, the network comprised 10 tightly knit groups, eight of which were associated with particular body parts, and seven of which were dominated by parasite-resource links. Reported co-infection in humans is therefore structured by physical location within the body, with bottom-up, resource-mediated processes most often influencing how, where and which co-infecting parasites interact. The many indirect interactions show how treating an infection could affect other infections in co-infected patients, but the compartmentalized structure of the network will limit how far these indirect effects are likely to spread.

  11. Flash flood prediction in large dams using neural networks

    NASA Astrophysics Data System (ADS)

    Múnera Estrada, J. C.; García Bartual, R.

    2009-04-01

    A flow forecasting methodology is presented as a support tool for flood management in large dams. The practical and efficient use of hydrological real-time measurements is necessary to operate early warning systems for flood disasters prevention, either in natural catchments or in those regulated with reservoirs. In this latter case, the optimal dam operation during flood scenarios should reduce the downstream risks, and at the same time achieve a compromise between different goals: structural security, minimize predictions uncertainty and water resources system management objectives. Downstream constraints depend basically on the geomorphology of the valley, the critical flow thresholds for flooding, the land use and vulnerability associated with human settlements and their economic activities. A dam operation during a flood event thus requires appropriate strategies depending on the flood magnitude and the initial freeboard at the reservoir. The most important difficulty arises from the inherently stochastic character of peak rainfall intensities, their strong spatial and temporal variability, and the highly nonlinear response of semiarid catchments resulting from initial soil moisture condition and the dominant flow mechanisms. The practical integration of a flow prediction model in a real-time system should include combined techniques of pre-processing, data verification and completion, assimilation of information and implementation of real time filters depending on the system characteristics. This work explores the behaviour of real-time flood forecast algorithms based on artificial neural networks (ANN) techniques, in the River Meca catchment (Huelva, Spain), regulated by El Sancho dam. The dam is equipped with three Taintor gates of 12x6 meters. The hydrological data network includes five high-resolution automatic pluviometers (dt=10 min) and three high precision water level sensors in the reservoir. A cross correlation analysis between precipitation data

  12. An efficient approach of attractor calculation for large-scale Boolean gene regulatory networks.

    PubMed

    He, Qinbin; Xia, Zhile; Lin, Bin

    2016-11-07

    Boolean network models provide an efficient way for studying gene regulatory networks. The main dynamics of a Boolean network is determined by its attractors. Attractor calculation plays a key role for analyzing Boolean gene regulatory networks. An approach of attractor calculation was proposed in this study, which improved the predecessor-based approach. Furthermore, the proposed approach combined with the identification of constant nodes and simplified Boolean networks to accelerate attractor calculation. The proposed algorithm is effective to calculate all attractors for large-scale Boolean gene regulatory networks. If the average degree of the network is not too large, the algorithm can get all attractors of a Boolean network with dozens or even hundreds of nodes.

  13. myExperiment: a repository and social network for the sharing of bioinformatics workflows

    PubMed Central

    Goble, Carole A.; Bhagat, Jiten; Aleksejevs, Sergejs; Cruickshank, Don; Michaelides, Danius; Newman, David; Borkum, Mark; Bechhofer, Sean; Roos, Marco; Li, Peter; De Roure, David

    2010-01-01

    myExperiment (http://www.myexperiment.org) is an online research environment that supports the social sharing of bioinformatics workflows. These workflows are procedures consisting of a series of computational tasks using web services, which may be performed on data from its retrieval, integration and analysis, to the visualization of the results. As a public repository of workflows, myExperiment allows anybody to discover those that are relevant to their research, which can then be reused and repurposed to their specific requirements. Conversely, developers can submit their workflows to myExperiment and enable them to be shared in a secure manner. Since its release in 2007, myExperiment currently has over 3500 registered users and contains more than 1000 workflows. The social aspect to the sharing of these workflows is facilitated by registered users forming virtual communities bound together by a common interest or research project. Contributors of workflows can build their reputation within these communities by receiving feedback and credit from individuals who reuse their work. Further documentation about myExperiment including its REST web service is available from http://wiki.myexperiment.org. Feedback and requests for support can be sent to bugs@myexperiment.org. PMID:20501605

  14. myExperiment: a repository and social network for the sharing of bioinformatics workflows.

    PubMed

    Goble, Carole A; Bhagat, Jiten; Aleksejevs, Sergejs; Cruickshank, Don; Michaelides, Danius; Newman, David; Borkum, Mark; Bechhofer, Sean; Roos, Marco; Li, Peter; De Roure, David

    2010-07-01

    myExperiment (http://www.myexperiment.org) is an online research environment that supports the social sharing of bioinformatics workflows. These workflows are procedures consisting of a series of computational tasks using web services, which may be performed on data from its retrieval, integration and analysis, to the visualization of the results. As a public repository of workflows, myExperiment allows anybody to discover those that are relevant to their research, which can then be reused and repurposed to their specific requirements. Conversely, developers can submit their workflows to myExperiment and enable them to be shared in a secure manner. Since its release in 2007, myExperiment currently has over 3500 registered users and contains more than 1000 workflows. The social aspect to the sharing of these workflows is facilitated by registered users forming virtual communities bound together by a common interest or research project. Contributors of workflows can build their reputation within these communities by receiving feedback and credit from individuals who reuse their work. Further documentation about myExperiment including its REST web service is available from http://wiki.myexperiment.org. Feedback and requests for support can be sent to bugs@myexperiment.org.

  15. The Process of Creating a Cross-University Network for Formative and Shared Assessment in Higher Education in Spain and Its Potential Applications

    ERIC Educational Resources Information Center

    Lopez-Pastor, Victor M.; Castejon, Javier; Sicilia-Camacho, Alvaro; Navarro-Adelantado, Vicente; Webb, Graham

    2011-01-01

    During the academic year 2005-2006 a Cross University Network for Formative and Shared Assessment in Higher Education was formed among 48 academics from 16 different universities within Spain and representing a range of academic areas. The Network was formed in response to the determination of a group of individuals who were dissatisfied with, or…

  16. The Process of Creating a Cross-University Network for Formative and Shared Assessment in Higher Education in Spain and Its Potential Applications

    ERIC Educational Resources Information Center

    Lopez-Pastor, Victor M.; Castejon, Javier; Sicilia-Camacho, Alvaro; Navarro-Adelantado, Vicente; Webb, Graham

    2011-01-01

    During the academic year 2005-2006 a Cross University Network for Formative and Shared Assessment in Higher Education was formed among 48 academics from 16 different universities within Spain and representing a range of academic areas. The Network was formed in response to the determination of a group of individuals who were dissatisfied with, or…

  17. Women Saw Large Decrease In Out-Of-Pocket Spending For Contraceptives After ACA Mandate Removed Cost Sharing.

    PubMed

    Becker, Nora V; Polsky, Daniel

    2015-07-01

    The Affordable Care Act mandates that private health insurance plans cover prescription contraceptives with no consumer cost sharing. The positive financial impact of this new provision on consumers who purchase contraceptives could be substantial, but it has not yet been estimated. Using a large administrative claims data set from a national insurer, we estimated out-of-pocket spending before and after the mandate. We found that mean and median per prescription out-of-pocket expenses have decreased for almost all reversible contraceptive methods on the market. The average percentages of out-of-pocket spending for oral contraceptive pill prescriptions and intrauterine device insertions by women using those methods both dropped by 20 percentage points after implementation of the ACA mandate. We estimated average out-of-pocket savings per contraceptive user to be $248 for the intrauterine device and $255 annually for the oral contraceptive pill. Our results suggest that the mandate has led to large reductions in total out-of-pocket spending on contraceptives and that these price changes are likely to be salient for women with private health insurance. Project HOPE—The People-to-People Health Foundation, Inc.

  18. mEducator: A Best Practice Network for Repurposing and Sharing Medical Educational Multi-type Content

    NASA Astrophysics Data System (ADS)

    Bamidis, Panagiotis D.; Kaldoudi, Eleni; Pattichis, Costas

    Although there is an abundance of medical educational content available in individual EU academic institutions, this is not widely available or easy to discover and retrieve, due to lack of standardized content sharing mechanisms. The mEducator EU project will face this lack by implementing and experimenting between two different sharing mechanisms, namely, one based one mashup technologies, and one based on semantic web services. In addition, the mEducator best practice network will critically evaluate existing standards and reference models in the field of e-learning in order to enable specialized state-of-the-art medical educational content to be discovered, retrieved, shared, repurposed and re-used across European higher academic institutions. Educational content included in mEducator covers and represents the whole range of medical educational content, from traditional instructional teaching to active learning and experiential teaching/studying approaches. It spans the whole range of types, from text to exam sheets, algorithms, teaching files, computer programs (simulators or games) and interactive objects (like virtual patients and electronically traced anatomies), while it covers a variety of topics. In this paper, apart from introducing the relevant project concepts and strategies, emphasis is also placed on the notion of (dynamic) user-generated content, its advantages and peculiarities, as well as, gaps in current research and technology practice upon its embedding into existing standards.

  19. Metabolomics integrated elementary flux mode analysis in large metabolic networks.

    PubMed

    Gerstl, Matthias P; Ruckerbauer, David E; Mattanovich, Diethard; Jungreuthmayer, Christian; Zanghellini, Jürgen

    2015-03-10

    Elementary flux modes (EFMs) are non-decomposable steady-state pathways in metabolic networks. They characterize phenotypes, quantify robustness or identify engineering targets. An EFM analysis (EFMA) is currently restricted to medium-scale models, as the number of EFMs explodes with the network's size. However, many topologically feasible EFMs are biologically irrelevant. We present thermodynamic EFMA (tEFMA), which calculates only the small(er) subset of thermodynamically feasible EFMs. We integrate network embedded thermodynamics into EFMA and show that we can use the metabolome to identify and remove thermodynamically infeasible EFMs during an EFMA without losing biologically relevant EFMs. Calculating only the thermodynamically feasible EFMs strongly reduces memory consumption and program runtime, allowing the analysis of larger networks. We apply tEFMA to study the central carbon metabolism of E. coli and find that up to 80% of its EFMs are thermodynamically infeasible. Moreover, we identify glutamate dehydrogenase as a bottleneck, when E. coli is grown on glucose and explain its inactivity as a consequence of network embedded thermodynamics. We implemented tEFMA as a Java package which is available for download at https://github.com/mpgerstl/tEFMA.

  20. The large-scale organization of the hadron decay network

    NASA Astrophysics Data System (ADS)

    Xu, Xinping; Liu, Feng

    2008-01-01

    The standard model of particle physics predicts a complex structure of decay modes for hadrons, which opens up an avenue for observing the internal forces governing the decay dynamics. In this paper, we present the decay modes of hadrons as a network in which the nodes are particles and directed links are pointing from the mother particles to daughter particles. Using the database of decay modes collected from the Particle Data Group, we try to unveil the topological structure and possible intrinsic nature of hadron decays in the light of recent investigations of complex networks. We study distributions of the numbers of daughter and mother particles, and explore scaling laws that may govern the underlying decay structure of the system. We find that it is a small-world network with symmetrical structure. We also study the influence of constraints arising from conservation laws on the network structure, and our analysis suggests that the constraints of conservations of momentum energy, charge, lepton number and baryon number play important roles in the topology of the decay network. Finally, we classify the hadrons into communities according to their quark component, and uncover the relationship between the particle roles and connection patterns in the communities.

  1. Remote facility sharing with ATM networks [PC based ATM Link Delay Simulator (LDS)]. Final report

    SciTech Connect

    Kung, H. T.

    2001-06-01

    The ATM Link Delay Simulator (LDS) adds propagation delay to the ATM link on which it is installed, to allow control of link propagation delay in network protocol experiments simulating an adjustable piece of optical fiber. Our LDS simulates a delay of between 1.5 and 500 milliseconds and is built with commodity PC hardware, only the ATM network interface card is not generally available. Our implementation is special in that it preserves the exact spacing of ATM data cells a feature that requires sustained high performance. Our implementation shows that applications demanding sustained high performance are possible on commodity PC hardware. This illustrates the promise that PC hardware has for adaptability to demanding specialized testing of high speed network.

  2. The online Managed Knowledge Network that shares knowledge for eHealth in NHS Scotland.

    PubMed

    Dallest, Kathy; Strachan, Heather; Flett, Gillian

    2009-01-01

    The Managed Knowledge Network (MKN) for Nurses, Midwives and the Allied Health Professions (NMAHPs) in NHS Scotland was launched in November 2007. The online portal supports the NMAHP network to manage its knowledge and information sources that facilitate engagement with the national eHealth programme and realisation of benefits that eHealth offers to improve healthcare and service delivery. It is an integrated change management and knowledge management initiative. Web2 technologies support the social networking side of knowledge management and learning, allowing people to contact each other and collaborate. MKN resources are managed within the e-Library also giving access to over 5,000 online journals and over 500 bibliographic databases.

  3. Large-Scale High School Reform through School Improvement Networks: Exploring Possibilities for "Developmental Evaluation"

    ERIC Educational Resources Information Center

    Peurach, Donald J.; Lenhoff, Sarah Winchell; Glazer, Joshua L.

    2016-01-01

    Recognizing school improvement networks as a leading strategy for large-scale high school reform, this analysis examines developmental evaluation as an approach to examining school improvement networks as "learning systems" able to produce, use, and refine practical knowledge in large numbers of schools. Through a case study of one…

  4. Large-Scale High School Reform through School Improvement Networks: Exploring Possibilities for "Developmental Evaluation"

    ERIC Educational Resources Information Center

    Peurach, Donald J.; Lenhoff, Sarah Winchell; Glazer, Joshua L.

    2016-01-01

    Recognizing school improvement networks as a leading strategy for large-scale high school reform, this analysis examines developmental evaluation as an approach to examining school improvement networks as "learning systems" able to produce, use, and refine practical knowledge in large numbers of schools. Through a case study of one…

  5. Analysis of Community Detection Algorithms for Large Scale Cyber Networks

    SciTech Connect

    Mane, Prachita; Shanbhag, Sunanda; Kamath, Tanmayee; Mackey, Patrick S.; Springer, John

    2016-09-30

    The aim of this project is to use existing community detection algorithms on an IP network dataset to create supernodes within the network. This study compares the performance of different algorithms on the network in terms of running time. The paper begins with an introduction to the concept of clustering and community detection followed by the research question that the team aimed to address. Further the paper describes the graph metrics that were considered in order to shortlist algorithms followed by a brief explanation of each algorithm with respect to the graph metric on which it is based. The next section in the paper describes the methodology used by the team in order to run the algorithms and determine which algorithm is most efficient with respect to running time. Finally, the last section of the paper includes the results obtained by the team and a conclusion based on those results as well as future work.

  6. Wide-area ATM networking for large-scale MPPs

    SciTech Connect

    Papadopoulos, P.M.; Geist, G.A. II

    1997-04-01

    This paper presents early experiences with using high-speed ATM interfaces to connect multiple Intel Paragons on both local and wide area networks. The testbed includes the 1024 and 512 node Paragons running the OSF operating system at Oak Ridge National Laboratory and the 1840 node Paragon running the Puma operating system at Sandia National Laboratories. The experimental OC-12 (622 Mbits/sec) interfaces are built by GigaNet and provide a proprietary API for sending AAL-5 encapsulated packets. PVM is used as the massaging infrastructure and significant modifications have been made to use the GigaNet API, operate in the Puma environment, and attain acceptable performance over local networks. These modifications are described along with a discussion of roadblocks to networking MPPs with high-performance interfaces. Our early prototype utilizes approximately 25 percent of an OC-12 circuit and 80 percent of an OC-3 circuit in send plus acknowledgment ping-pong tests.

  7. The U.S. Culture Collection Network Responding to the Requirements of the Nagoya Protocol on Access and Benefit Sharing.

    PubMed

    McCluskey, Kevin; Barker, Katharine B; Barton, Hazel A; Boundy-Mills, Kyria; Brown, Daniel R; Coddington, Jonathan A; Cook, Kevin; Desmeth, Philippe; Geiser, David; Glaeser, Jessie A; Greene, Stephanie; Kang, Seogchan; Lomas, Michael W; Melcher, Ulrich; Miller, Scott E; Nobles, David R; Owens, Kristina J; Reichman, Jerome H; da Silva, Manuela; Wertz, John; Whitworth, Cale; Smith, David

    2017-08-15

    The U.S. Culture Collection Network held a meeting to share information about how culture collections are responding to the requirements of the recently enacted Nagoya Protocol on Access to Genetic Resources and the Fair and Equitable Sharing of Benefits Arising from their Utilization to the Convention on Biological Diversity (CBD). The meeting included representatives of many culture collections and other biological collections, the U.S. Department of State, U.S. Department of Agriculture, Secretariat of the CBD, interested scientific societies, and collection groups, including Scientific Collections International and the Global Genome Biodiversity Network. The participants learned about the policies of the United States and other countries regarding access to genetic resources, the definition of genetic resources, and the status of historical materials and genetic sequence information. Key topics included what constitutes access and how the CBD Access and Benefit-Sharing Clearing-House can help guide researchers through the process of obtaining Prior Informed Consent on Mutually Agreed Terms. U.S. scientists and their international collaborators are required to follow the regulations of other countries when working with microbes originally isolated outside the United States, and the local regulations required by the Nagoya Protocol vary by the country of origin of the genetic resource. Managers of diverse living collections in the United States described their holdings and their efforts to provide access to genetic resources. This meeting laid the foundation for cooperation in establishing a set of standard operating procedures for U.S. and international culture collections in response to the Nagoya Protocol.

  8. The U.S. Culture Collection Network Responding to the Requirements of the Nagoya Protocol on Access and Benefit Sharing

    PubMed Central

    Barker, Katharine B.; Barton, Hazel A.; Boundy-Mills, Kyria; Brown, Daniel R.; Coddington, Jonathan A.; Cook, Kevin; Desmeth, Philippe; Geiser, David; Glaeser, Jessie A.; Greene, Stephanie; Kang, Seogchan; Lomas, Michael W.; Melcher, Ulrich; Miller, Scott E.; Nobles, David R.; Owens, Kristina J.; Reichman, Jerome H.; da Silva, Manuela; Wertz, John; Whitworth, Cale; Smith, David

    2017-01-01

    ABSTRACT The U.S. Culture Collection Network held a meeting to share information about how culture collections are responding to the requirements of the recently enacted Nagoya Protocol on Access to Genetic Resources and the Fair and Equitable Sharing of Benefits Arising from their Utilization to the Convention on Biological Diversity (CBD). The meeting included representatives of many culture collections and other biological collections, the U.S. Department of State, U.S. Department of Agriculture, Secretariat of the CBD, interested scientific societies, and collection groups, including Scientific Collections International and the Global Genome Biodiversity Network. The participants learned about the policies of the United States and other countries regarding access to genetic resources, the definition of genetic resources, and the status of historical materials and genetic sequence information. Key topics included what constitutes access and how the CBD Access and Benefit-Sharing Clearing-House can help guide researchers through the process of obtaining Prior Informed Consent on Mutually Agreed Terms. U.S. scientists and their international collaborators are required to follow the regulations of other countries when working with microbes originally isolated outside the United States, and the local regulations required by the Nagoya Protocol vary by the country of origin of the genetic resource. Managers of diverse living collections in the United States described their holdings and their efforts to provide access to genetic resources. This meeting laid the foundation for cooperation in establishing a set of standard operating procedures for U.S. and international culture collections in response to the Nagoya Protocol. PMID:28811341

  9. A Topology Visualization Early Warning Distribution Algorithm for Large-Scale Network Security Incidents

    PubMed Central

    He, Hui; Fan, Guotao; Ye, Jianwei; Zhang, Weizhe

    2013-01-01

    It is of great significance to research the early warning system for large-scale network security incidents. It can improve the network system's emergency response capabilities, alleviate the cyber attacks' damage, and strengthen the system's counterattack ability. A comprehensive early warning system is presented in this paper, which combines active measurement and anomaly detection. The key visualization algorithm and technology of the system are mainly discussed. The large-scale network system's plane visualization is realized based on the divide and conquer thought. First, the topology of the large-scale network is divided into some small-scale networks by the MLkP/CR algorithm. Second, the sub graph plane visualization algorithm is applied to each small-scale network. Finally, the small-scale networks' topologies are combined into a topology based on the automatic distribution algorithm of force analysis. As the algorithm transforms the large-scale network topology plane visualization problem into a series of small-scale network topology plane visualization and distribution problems, it has higher parallelism and is able to handle the display of ultra-large-scale network topology. PMID:24191145

  10. A topology visualization early warning distribution algorithm for large-scale network security incidents.

    PubMed

    He, Hui; Fan, Guotao; Ye, Jianwei; Zhang, Weizhe

    2013-01-01

    It is of great significance to research the early warning system for large-scale network security incidents. It can improve the network system's emergency response capabilities, alleviate the cyber attacks' damage, and strengthen the system's counterattack ability. A comprehensive early warning system is presented in this paper, which combines active measurement and anomaly detection. The key visualization algorithm and technology of the system are mainly discussed. The large-scale network system's plane visualization is realized based on the divide and conquer thought. First, the topology of the large-scale network is divided into some small-scale networks by the MLkP/CR algorithm. Second, the sub graph plane visualization algorithm is applied to each small-scale network. Finally, the small-scale networks' topologies are combined into a topology based on the automatic distribution algorithm of force analysis. As the algorithm transforms the large-scale network topology plane visualization problem into a series of small-scale network topology plane visualization and distribution problems, it has higher parallelism and is able to handle the display of ultra-large-scale network topology.

  11. Large-Scale Functional Brain Network Reorganization During Taoist Meditation.

    PubMed

    Jao, Tun; Li, Chia-Wei; Vértes, Petra E; Wu, Changwei Wesley; Achard, Sophie; Hsieh, Chao-Hsien; Liou, Chien-Hui; Chen, Jyh-Horng; Bullmore, Edward T

    2016-02-01

    Meditation induces a distinct and reversible mental state that provides insights into brain correlates of consciousness. We explored brain network changes related to meditation by graph theoretical analysis of resting-state functional magnetic resonance imaging data. Eighteen Taoist meditators with varying levels of expertise were scanned using a within-subjects counterbalanced design during resting and meditation states. State-related differences in network topology were measured globally and at the level of individual nodes and edges. Although measures of global network topology, such as small-worldness, were unchanged, meditation was characterized by an extensive and expertise-dependent reorganization of the hubs (highly connected nodes) and edges (functional connections). Areas of sensory cortex, especially the bilateral primary visual and auditory cortices, and the bilateral temporopolar areas, which had the highest degree (or connectivity) during the resting state, showed the biggest decrease during meditation. Conversely, bilateral thalamus and components of the default mode network, mainly the bilateral precuneus and posterior cingulate cortex, had low degree in the resting state but increased degree during meditation. Additionally, these changes in nodal degree were accompanied by reorganization of anatomical orientation of the edges. During meditation, long-distance longitudinal (antero-posterior) edges increased proportionally, whereas orthogonal long-distance transverse (right-left) edges connecting bilaterally homologous cortices decreased. Our findings suggest that transient changes in consciousness associated with meditation introduce convergent changes in the topological and spatial properties of brain functional networks, and the anatomical pattern of integration might be as important as the global level of integration when considering the network basis for human consciousness.

  12. Reconfigurable middleware architectures for large scale sensor networks

    SciTech Connect

    Brennan, Sean M.

    2010-03-01

    Wireless sensor networks, in an e ffort to be energy efficient, typically lack the high-level abstractions of advanced programming languages. Though strong, the dichotomy between these two paradigms can be overcome. The SENSIX software framework, described in this dissertation, uniquely integrates constraint-dominated wireless sensor networks with the flexibility of object-oriented programming models, without violating the principles of either. Though these two computing paradigms are contradictory in many ways, SENSIX bridges them to yield a dynamic middleware abstraction unifying low-level resource-aware task recon figuration and high-level object recomposition.

  13. Encoding, Rehearsal, and Recall in Signers and Speakers: Shared Network but Differential Engagement

    PubMed Central

    Newman, A. J.; Mukherjee, M.; Hauser, P.; Kemeny, S.; Braun, A.; Boutla, M.

    2008-01-01

    Short-term memory (STM), or the ability to hold verbal information in mind for a few seconds, is known to rely on the integrity of a frontoparietal network of areas. Here, we used functional magnetic resonance imaging to ask whether a similar network is engaged when verbal information is conveyed through a visuospatial language, American Sign Language, rather than speech. Deaf native signers and hearing native English speakers performed a verbal recall task, where they had to first encode a list of letters in memory, maintain it for a few seconds, and finally recall it in the order presented. The frontoparietal network described to mediate STM in speakers was also observed in signers, with its recruitment appearing independent of the modality of the language. This finding supports the view that signed and spoken STM rely on similar mechanisms. However, deaf signers and hearing speakers differentially engaged key structures of the frontoparietal network as the stages of STM unfold. In particular, deaf signers relied to a greater extent than hearing speakers on passive memory storage areas during encoding and maintenance, but on executive process areas during recall. This work opens new avenues for understanding similarities and differences in STM performance in signers and speakers. PMID:18245041

  14. Library Technology Grants Awarded To Support Networking and Resource-Sharing Activities, Fiscal Year 1992.

    ERIC Educational Resources Information Center

    Office of Educational Research and Improvement (ED), Washington, DC. Office of Library Programs.

    This report provides an annotated listing of 30 institutions receiving grants from the U.S. Department of Education under the College Library Technology and Cooperation Grants Program during 1992 in the following four categories: (1) networking grants; (2) combinations grants; (3) services to institutions; and (4) research and demonstration. These…

  15. Complementing Security Breach of Authentication by Using Shared Authentication Information in Mobile WiMAX Networks

    NASA Astrophysics Data System (ADS)

    Kim, Youngwook; Lim, Hyoung-Kyu; Bahk, Saewoong

    The signalling protocol vulnerability opens DDoS problem in Mobile WiMAX networks. This letter proposes an authentication method that uses the unrevealed upper 64bits of Cipher-based MAC as a solution. It runs for MSs in idle mode and reduces the calculation complexity by 59% under DDoS attack while incurring 1% overhead under normal condition.

  16. Collaborative Learning in Networked Environments: Interaction through Shared Workspaces and Communication Tools

    ERIC Educational Resources Information Center

    Hakkinen, Paivi

    2003-01-01

    Today, a variety of web-based learning environments have been developed for educational purposes, especially in higher education and continuing education courses. At the same time many studies have reported how networked interaction in many learning projects results in superficial and experience-based discussion, and does not reach the level of…

  17. Algorithms for Data Sharing, Coordination, and Communication in Dynamic Network Settings

    DTIC Science & Technology

    2007-12-03

    Chakraborty, and Nancy Lynch. Clock Synchronization for Wireless Networks. In Teruo Higashino , editor, Principles of Distributed Systems: OPODIS 2004: 8th...Teruo Higashino , editor, Principles of Distributed Systems: OPODIS 2004: 8th International Conference on Principles of Distributed 4 Systems, Grenoble

  18. Generic patterns in the evolution of urban water networks: Evidence from a large Asian city

    NASA Astrophysics Data System (ADS)

    Krueger, Elisabeth; Klinkhamer, Christopher; Urich, Christian; Zhan, Xianyuan; Rao, P. Suresh C.

    2017-03-01

    We examine high-resolution urban infrastructure data using every pipe for the water distribution network (WDN) and sanitary sewer network (SSN) in a large Asian city (≈4 million residents) to explore the structure as well as the spatial and temporal evolution of these infrastructure networks. Network data were spatially disaggregated into multiple subnets to examine intracity topological differences for functional zones of the WDN and SSN, and time-stamped SSN data were examined to understand network evolution over several decades as the city expanded. Graphs were generated using a dual-mapping technique (Hierarchical Intersection Continuity Negotiation), which emphasizes the functional attributes of these networks. Network graphs for WDNs and SSNs are characterized by several network topological metrics, and a double Pareto (power-law) model approximates the node-degree distributions of both water infrastructure networks (WDN and SSN), across spatial and hierarchical scales relevant to urban settings, and throughout their temporal evolution over several decades. These results indicate that generic mechanisms govern the networks' evolution, similar to those of scale-free networks found in nature. Deviations from the general topological patterns are indicative of (1) incomplete establishment of network hierarchies and functional network evolution, (2) capacity for growth (expansion) or densification (e.g., in-fill), and (3) likely network vulnerabilities. We discuss the implications of our findings for the (re-)design of urban infrastructure networks to enhance their resilience to external and internal threats.

  19. HydroShare for iUTAH: Collaborative Publication, Interoperability, and Reuse of Hydrologic Data and Models for a Large, Interdisciplinary Water Research Project

    NASA Astrophysics Data System (ADS)

    Horsburgh, J. S.; Jones, A. S.

    2016-12-01

    Data and models used within the hydrologic science community are diverse. New research data and model repositories have succeeded in making data and models more accessible, but have been, in most cases, limited to particular types or classes of data or models and also lack the type of collaborative, and iterative functionality needed to enable shared data collection and modeling workflows. File sharing systems currently used within many scientific communities for private sharing of preliminary and intermediate data and modeling products do not support collaborative data capture, description, visualization, and annotation. More recently, hydrologic datasets and models have been cast as "social objects" that can be published, collaborated around, annotated, discovered, and accessed. Yet it can be difficult using existing software tools to achieve the kind of collaborative workflows and data/model reuse that many envision. HydroShare is a new, web-based system for sharing hydrologic data and models with specific functionality aimed at making collaboration easier and achieving new levels of interactive functionality and interoperability. Within HydroShare, we have developed new functionality for creating datasets, describing them with metadata, and sharing them with collaborators. HydroShare is enabled by a generic data model and content packaging scheme that supports describing and sharing diverse hydrologic datasets and models. Interoperability among the diverse types of data and models used by hydrologic scientists is achieved through the use of consistent storage, management, sharing, publication, and annotation within HydroShare. In this presentation, we highlight and demonstrate how the flexibility of HydroShare's data model and packaging scheme, HydroShare's access control and sharing functionality, and versioning and publication capabilities have enabled the sharing and publication of research datasets for a large, interdisciplinary water research project

  20. Large-Scale Neural Network for Sentence Processing

    ERIC Educational Resources Information Center

    Cooke, Ayanna; Grossman, Murray; DeVita, Christian; Gonzalez-Atavales, Julio; Moore, Peachie; Chen, Willis; Gee, James; Detre, John

    2006-01-01

    Our model of sentence comprehension includes at least grammatical processes important for structure-building, and executive resources such as working memory that support these grammatical processes. We hypothesized that a core network of brain regions supports grammatical processes, and that additional brain regions are activated depending on the…

  1. Large-scale brain network dynamics supporting adolescent cognitive control.

    PubMed

    Dwyer, Dominic B; Harrison, Ben J; Yücel, Murat; Whittle, Sarah; Zalesky, Andrew; Pantelis, Christos; Allen, Nicholas B; Fornito, Alex

    2014-10-15

    Adolescence is a time when the ability to engage cognitive control is linked to crucial life outcomes. Despite a historical focus on prefrontal cortex functioning, recent evidence suggests that differences between individuals may relate to interactions between distributed brain regions that collectively form a cognitive control network (CCN). Other research points to a spatially distinct and functionally antagonistic system--the default-mode network (DMN)--which typically deactivates during performance of control tasks. This literature implies that individual differences in cognitive control are determined either by activation or functional connectivity of CCN regions, deactivation or functional connectivity of DMN regions, or some combination of both. We tested between these possibilities using a multilevel fMRI characterization of CCN and DMN dynamics, measured during performance of a cognitive control task and during a task-free resting state, in 73 human adolescents. Better cognitive control performance was associated with (1) reduced activation of CCN regions, but not deactivation of the DMN; (2) variations in task-related, but not resting-state, functional connectivity within a distributed network involving both the CCN and DMN; (3) functional segregation of core elements of these two systems; and (4) task-dependent functional integration of a set of peripheral nodes into either one network or the other in response to prevailing stimulus conditions. These results indicate that individual differences in adolescent cognitive control are not solely attributable to the functioning of any single region or network, but are instead dependent on a dynamic and context-dependent interplay between the CCN and DMN. Copyright © 2014 the authors 0270-6474/14/3414096-13$15.00/0.

  2. Large-Scale Recurrent Neural Network Based Modelling of Gene Regulatory Network Using Cuckoo Search-Flower Pollination Algorithm.

    PubMed

    Mandal, Sudip; Khan, Abhinandan; Saha, Goutam; Pal, Rajat K

    2016-01-01

    The accurate prediction of genetic networks using computational tools is one of the greatest challenges in the postgenomic era. Recurrent Neural Network is one of the most popular but simple approaches to model the network dynamics from time-series microarray data. To date, it has been successfully applied to computationally derive small-scale artificial and real-world genetic networks with high accuracy. However, they underperformed for large-scale genetic networks. Here, a new methodology has been proposed where a hybrid Cuckoo Search-Flower Pollination Algorithm has been implemented with Recurrent Neural Network. Cuckoo Search is used to search the best combination of regulators. Moreover, Flower Pollination Algorithm is applied to optimize the model parameters of the Recurrent Neural Network formalism. Initially, the proposed method is tested on a benchmark large-scale artificial network for both noiseless and noisy data. The results obtained show that the proposed methodology is capable of increasing the inference of correct regulations and decreasing false regulations to a high degree. Secondly, the proposed methodology has been validated against the real-world dataset of the DNA SOS repair network of Escherichia coli. However, the proposed method sacrifices computational time complexity in both cases due to the hybrid optimization process.

  3. Large-Scale Recurrent Neural Network Based Modelling of Gene Regulatory Network Using Cuckoo Search-Flower Pollination Algorithm

    PubMed Central

    Mandal, Sudip; Khan, Abhinandan; Saha, Goutam; Pal, Rajat K.

    2016-01-01

    The accurate prediction of genetic networks using computational tools is one of the greatest challenges in the postgenomic era. Recurrent Neural Network is one of the most popular but simple approaches to model the network dynamics from time-series microarray data. To date, it has been successfully applied to computationally derive small-scale artificial and real-world genetic networks with high accuracy. However, they underperformed for large-scale genetic networks. Here, a new methodology has been proposed where a hybrid Cuckoo Search-Flower Pollination Algorithm has been implemented with Recurrent Neural Network. Cuckoo Search is used to search the best combination of regulators. Moreover, Flower Pollination Algorithm is applied to optimize the model parameters of the Recurrent Neural Network formalism. Initially, the proposed method is tested on a benchmark large-scale artificial network for both noiseless and noisy data. The results obtained show that the proposed methodology is capable of increasing the inference of correct regulations and decreasing false regulations to a high degree. Secondly, the proposed methodology has been validated against the real-world dataset of the DNA SOS repair network of Escherichia coli. However, the proposed method sacrifices computational time complexity in both cases due to the hybrid optimization process. PMID:26989410

  4. Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction.

    PubMed

    Ma, Xiaolei; Dai, Zhuang; He, Zhengbing; Ma, Jihui; Wang, Yong; Wang, Yunpeng

    2017-04-10

    This paper proposes a convolutional neural network (CNN)-based method that learns traffic as images and predicts large-scale, network-wide traffic speed with a high accuracy. Spatiotemporal traffic dynamics are converted to images describing the time and space relations of traffic flow via a two-dimensional time-space matrix. A CNN is applied to the image following two consecutive steps: abstract traffic feature extraction and network-wide traffic speed prediction. The effectiveness of the proposed method is evaluated by taking two real-world transportation networks, the second ring road and north-east transportation network in Beijing, as examples, and comparing the method with four prevailing algorithms, namely, ordinary least squares, k-nearest neighbors, artificial neural network, and random forest, and three deep learning architectures, namely, stacked autoencoder, recurrent neural network, and long-short-term memory network. The results show that the proposed method outperforms other algorithms by an average accuracy improvement of 42.91% within an acceptable execution time. The CNN can train the model in a reasonable time and, thus, is suitable for large-scale transportation networks.

  5. Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction

    PubMed Central

    Ma, Xiaolei; Dai, Zhuang; He, Zhengbing; Ma, Jihui; Wang, Yong; Wang, Yunpeng

    2017-01-01

    This paper proposes a convolutional neural network (CNN)-based method that learns traffic as images and predicts large-scale, network-wide traffic speed with a high accuracy. Spatiotemporal traffic dynamics are converted to images describing the time and space relations of traffic flow via a two-dimensional time-space matrix. A CNN is applied to the image following two consecutive steps: abstract traffic feature extraction and network-wide traffic speed prediction. The effectiveness of the proposed method is evaluated by taking two real-world transportation networks, the second ring road and north-east transportation network in Beijing, as examples, and comparing the method with four prevailing algorithms, namely, ordinary least squares, k-nearest neighbors, artificial neural network, and random forest, and three deep learning architectures, namely, stacked autoencoder, recurrent neural network, and long-short-term memory network. The results show that the proposed method outperforms other algorithms by an average accuracy improvement of 42.91% within an acceptable execution time. The CNN can train the model in a reasonable time and, thus, is suitable for large-scale transportation networks. PMID:28394270

  6. Think Locally, Act Locally: The Detection of Small, Medium-Sized, and Large Communities in Large Networks

    PubMed Central

    Jeub, Lucas G. S.; Balachandran, Prakash; Porter, Mason A.; Mucha, Peter J.; Mahoney, Michael W.

    2016-01-01

    It is common in the study of networks to investigate intermediate-sized (or “meso-scale”) features to try to gain an understanding of network structure and function. For example, numerous algorithms have been developed to try to identify “communities,” which are typically construed as sets of nodes with denser connections internally than with the remainder of a network. In this paper, we adopt a complementary perspective that “communities” are associated with bottlenecks of locally-biased dynamical processes that begin at seed sets of nodes, and we employ several different community-identification procedures (using diffusion-based and geodesic-based dynamics) to investigate community quality as a function of community size. Using several empirical and synthetic networks, we identify several distinct scenarios for “size-resolved community structure” that can arise in real (and realistic) networks: (i) the best small groups of nodes can be better than the best large groups (for a given formulation of the idea of a good community); (ii) the best small groups can have a quality that is comparable to the best medium-sized and large groups; and (iii) the best small groups of nodes can be worse than the best large groups. As we discuss in detail, which of these three cases holds for a given network can make an enormous difference when investigating and making claims about network community structure, and it is important to take this into account to obtain reliable downstream conclusions. Depending on which scenario holds, one may or may not be able to successfully identify “good” communities in a given network (and good communities might not even exist for a given community quality measure), the manner in which different small communities fit together to form meso-scale network structures can be very different, and processes such as viral propagation and information diffusion can exhibit very different dynamics. In addition, our results suggest that

  7. Visual analysis of large heterogeneous social networks by semantic and structural abstraction.

    PubMed

    Shen, Zeqian; Ma, Kwan-Liu; Eliassi-Rad, Tina

    2006-01-01

    Social network analysis is an active area of study beyond sociology. It uncovers the invisible relationships between actors in a network and provides understanding of social processes and behaviors. It has become an important technique in a variety of application areas such as the Web, organizational studies, and homeland security. This paper presents a visual analytics tool, OntoVis, for understanding large, heterogeneous social networks, in which nodes and links could represent different concepts and relations, respectively. These concepts and relations are related through an ontology (also known as a schema). OntoVis is named such because it uses information in the ontology associated with a social network to semantically prune a large, heterogeneous network. In addition to semantic abstraction, OntoVis also allows users to do structural abstraction and importance filtering to make large networks manageable and to facilitate analytic reasoning. All these unique capabilities of OntoVis are illustrated with several case studies.

  8. Autonomous management of a recursive area hierarchy for large scale wireless sensor networks using multiple parents

    SciTech Connect

    Cree, Johnathan Vee; Delgado-Frias, Jose

    2016-03-01

    Large scale wireless sensor networks have been proposed for applications ranging from anomaly detection in an environment to vehicle tracking. Many of these applications require the networks to be distributed across a large geographic area while supporting three to five year network lifetimes. In order to support these requirements large scale wireless sensor networks of duty-cycled devices need a method of efficient and effective autonomous configuration/maintenance. This method should gracefully handle the synchronization tasks duty-cycled networks. Further, an effective configuration solution needs to recognize that in-network data aggregation and analysis presents significant benefits to wireless sensor network and should configure the network in a way such that said higher level functions benefit from the logically imposed structure. NOA, the proposed configuration and maintenance protocol, provides a multi-parent hierarchical logical structure for the network that reduces the synchronization workload. It also provides higher level functions with significant inherent benefits such as but not limited to: removing network divisions that are created by single-parent hierarchies, guarantees for when data will be compared in the hierarchy, and redundancies for communication as well as in-network data aggregation/analysis/storage.

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

    SciTech Connect

    Yoon, Hong-Jun; Tourassi, Georgia

    2014-01-01

    Analyzing the contents of online social networks is an effective process for monitoring and understanding peoples behaviors. Since the nature of conversation and information propagation is similar to traditional conversation and learning, one of the popular socio-cognitive methods, social cognitive theory was applied to online social networks to. Two major news topics about colon cancer were chosen to monitor traffic of Twitter messages. The activity of leaders on the issue (i.e., news companies or people will prior Twitter activity on topics related to colon cancer) was monitored. In addition, the activity of followers , people who never discussed the topics before, but replied to the discussions was also monitored. Topics that produce tangible benefits such as positive outcomes from appropriate preventive actions received dramatically more attention and online social media traffic. Such characteristics can be explained with social cognitive theory and thus present opportunities for effective health campaigns.

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

    PubMed Central

    Yoon, Hong-Jun; Tourassi, Georgia

    2015-01-01

    Analyzing the contents of online social networks is an effective process for monitoring and understanding peoples’ behaviors. Since the nature of conversation and information propagation is similar to traditional conversation and learning, one of the popular socio-cognitive methods, social cognitive theory was applied to online social networks to. Two major news topics about colon cancer were chosen to monitor traffic of Twitter messages. The activity of “leaders” on the issue (i.e., news companies or people will prior Twitter activity on topics related to colon cancer) was monitored. In addition, the activity of “followers”, people who never discussed the topics before, but replied to the discussions was also monitored. Topics that produce tangible benefits such as positive outcomes from appropriate preventive actions received dramatically more attention and online social media traffic. Such characteristics can be explained with social cognitive theory and thus present opportunities for effective health campaigns. PMID:25973446

  11. A Novel Distributed Privacy Paradigm for Visual Sensor Networks Based on Sharing Dynamical Systems

    NASA Astrophysics Data System (ADS)

    Luh, William; Kundur, Deepa; Zourntos, Takis

    2006-12-01

    Visual sensor networks (VSNs) provide surveillance images/video which must be protected from eavesdropping and tampering en route to the base station. In the spirit of sensor networks, we propose a novel paradigm for securing privacy and confidentiality in a distributed manner. Our paradigm is based on the control of dynamical systems, which we show is well suited for VSNs due to its low complexity in terms of processing and communication, while achieving robustness to both unintentional noise and intentional attacks as long as a small subset of nodes are affected. We also present a low complexity algorithm called TANGRAM to demonstrate the feasibility of applying our novel paradigm to VSNs. We present and discuss simulation results of TANGRAM.

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

    PubMed

    Yoon, Hong-Jun; Tourassi, Georgia

    2014-05-01

    Analyzing the contents of online social networks is an effective process for monitoring and understanding peoples' behaviors. Since the nature of conversation and information propagation is similar to traditional conversation and learning, one of the popular socio-cognitive methods, social cognitive theory was applied to online social networks to. Two major news topics about colon cancer were chosen to monitor traffic of Twitter messages. The activity of "leaders" on the issue (i.e., news companies or people will prior Twitter activity on topics related to colon cancer) was monitored. In addition, the activity of "followers", people who never discussed the topics before, but replied to the discussions was also monitored. Topics that produce tangible benefits such as positive outcomes from appropriate preventive actions received dramatically more attention and online social media traffic. Such characteristics can be explained with social cognitive theory and thus present opportunities for effective health campaigns.

  13. Data transfer over the wide area network with a large round trip time

    NASA Astrophysics Data System (ADS)

    Matsunaga, H.; Isobe, T.; Mashimo, T.; Sakamoto, H.; Ueda, I.

    2010-04-01

    A Tier-2 regional center is running at the University of Tokyo in Japan. This center receives a large amount of data of the ATLAS experiment from the Tier-1 center in France. Although the link between the two centers has 10Gbps bandwidth, it is not a dedicated link but is shared with other traffic, and the round trip time is 290ms. It is not easy to exploit the available bandwidth for such a link, so-called long fat network. We performed data transfer tests by using GridFTP in various combinations of the parameters, such as the number of parallel streams and the TCP window size. In addition, we have gained experience of the actual data transfer in our production system where the Disk Pool Manager (DPM) is used as the Storage Element and the data transfer is controlled by the File Transfer Service (FTS). We report results of the tests and the daily activity, and discuss the improvement of the data transfer throughput.

  14. Large-scale sparse functional networks from resting state fMRI.

    PubMed

    Li, Hongming; Satterthwaite, Theodore D; Fan, Yong

    2017-08-01

    Delineation of large-scale functional networks (FNs) from resting state functional MRI data has become a standard tool to explore the functional brain organization in neuroscience. However, existing methods sacrifice subject specific variation in order to maintain the across-subject correspondence necessary for group-level analyses. In order to obtain subject specific FNs that are comparable across subjects, existing brain decomposition techniques typically adopt heuristic strategies or assume a specific statistical distribution for the FNs across subjects, and therefore might yield biased results. Here we present a novel data-driven method for detecting subject specific FNs while establishing group level correspondence. Our method simultaneously computes subject specific FNs for a group of subjects regularized by group sparsity, to generate subject specific FNs that are spatially sparse and share common spatial patterns across subjects. Our method is built upon non-negative matrix decomposition techniques, enhanced by a data locality regularization term that makes the decomposition robust to imaging noise and improves spatial smoothness and functional coherences of the subject specific FNs. Our method also adopts automatic relevance determination techniques to eliminate redundant FNs in order to generate a compact set of informative sparse FNs. We have validated our method based on simulated, task fMRI, and resting state fMRI datasets. The experimental results have demonstrated our method could obtain subject specific, sparse, non-negative FNs with improved functional coherence, providing enhanced ability for characterizing the functional brain of individual subjects. Copyright © 2017 Elsevier Inc. All rights reserved.

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

    DTIC Science & Technology

    2016-04-10

    transmitted over-the- air with GCN, Simplified Multicast Forwarding (SMF) [6], Optimized Link State Routing ( OLSR ) [7], and the Babel routing...protocol [8]. As can be seen from Figure 6, GCN delivered the most packets successfully (close to 75%) and significantly more than OLSR and Babel. The...maximum delivery success in this test was capacity limited. SMF floods the entire network with data resulting in higher delivery success than OLSR and Babel

  16. Peer Network Drinking Predicts Increased Alcohol Use From Adolescence to Early Adulthood After Controlling for Genetic and Shared Environmental Selection

    PubMed Central

    Cruz, Jennifer E.; Emery, Robert E.; Turkheimer, Eric

    2013-01-01

    Research consistently links adolescents' and young adults' drinking with their peers' alcohol intake. In interpreting this correlation, 2 essential questions are often overlooked. First, which peers are more important, best friends or broader social networks? Second, do peers cause increased drinking, or do young people select friends whose drinking habits match their own? The present study combines social network analyses with family (twin and sibling) designs to answer these questions via data from the National Longitudinal Study of Adolescent Health. Analysis of peer nomination data from 134 schools (n = 82,629) and 1,846 twin and sibling pairs shows that peer network substance use predicts changes in drinking from adolescence into young adult life even after controlling for genetic and shared environmental selection, as well as best friend substance use. This effect was particularly strong for high-intensity friendships. Although the peer-adolescent drinking correlation is partially explained by selection, the present finding offers powerful evidence that peers also cause increased drinking. PMID:22390657

  17. scMRI Reveals Large-Scale Brain Network Abnormalities in Autism

    PubMed Central

    Zielinski, Brandon A.; Anderson, Jeffrey S.; Froehlich, Alyson L.; Prigge, Molly B. D.; Nielsen, Jared A.; Cooperrider, Jason R.; Cariello, Annahir N.; Fletcher, P. Thomas; Alexander, Andrew L.; Lange, Nicholas; Bigler, Erin D.; Lainhart, Janet E.

    2012-01-01

    Autism is a complex neurological condition characterized by childhood onset of dysfunction in multiple cognitive domains including socio-emotional function, speech and language, and processing of internally versus externally directed stimuli. Although gross brain anatomic differences in autism are well established, recent studies investigating regional differences in brain structure and function have yielded divergent and seemingly contradictory results. How regional abnormalities relate to the autistic phenotype remains unclear. We hypothesized that autism exhibits distinct perturbations in network-level brain architecture, and that cognitive dysfunction may be reflected by abnormal network structure. Network-level anatomic abnormalities in autism have not been previously described. We used structural covariance MRI to investigate network-level differences in gray matter structure within two large-scale networks strongly implicated in autism, the salience network and the default mode network, in autistic subjects and age-, gender-, and IQ-matched controls. We report specific perturbations in brain network architecture in the salience and default-mode networks consistent with clinical manifestations of autism. Extent and distribution of the salience network, involved in social-emotional regulation of environmental stimuli, is restricted in autism. In contrast, posterior elements of the default mode network have increased spatial distribution, suggesting a ‘posteriorization’ of this network. These findings are consistent with a network-based model of autism, and suggest a unifying interpretation of previous work. Moreover, we provide evidence of specific abnormalities in brain network architecture underlying autism that are quantifiable using standard clinical MRI. PMID:23185305

  18. Critical dynamics on a large human Open Connectome network

    NASA Astrophysics Data System (ADS)

    Ódor, Géza

    2016-12-01

    Extended numerical simulations of threshold models have been performed on a human brain network with N =836 733 connected nodes available from the Open Connectome Project. While in the case of simple threshold models a sharp discontinuous phase transition without any critical dynamics arises, variable threshold models exhibit extended power-law scaling regions. This is attributed to fact that Griffiths effects, stemming from the topological or interaction heterogeneity of the network, can become relevant if the input sensitivity of nodes is equalized. I have studied the effects of link directness, as well as the consequence of inhibitory connections. Nonuniversal power-law avalanche size and time distributions have been found with exponents agreeing with the values obtained in electrode experiments of the human brain. The dynamical critical region occurs in an extended control parameter space without the assumption of self-organized criticality.

  19. Critical dynamics on a large human Open Connectome network.

    PubMed

    Ódor, Géza

    2016-12-01

    Extended numerical simulations of threshold models have been performed on a human brain network with N=836733 connected nodes available from the Open Connectome Project. While in the case of simple threshold models a sharp discontinuous phase transition without any critical dynamics arises, variable threshold models exhibit extended power-law scaling regions. This is attributed to fact that Griffiths effects, stemming from the topological or interaction heterogeneity of the network, can become relevant if the input sensitivity of nodes is equalized. I have studied the effects of link directness, as well as the consequence of inhibitory connections. Nonuniversal power-law avalanche size and time distributions have been found with exponents agreeing with the values obtained in electrode experiments of the human brain. The dynamical critical region occurs in an extended control parameter space without the assumption of self-organized criticality.

  20. TF-Cluster: A pipeline for identifying functionally coordinated transcription factors via network decomposition of the shared coexpression connectivity matrix (SCCM)

    PubMed Central

    2011-01-01

    Background Identifying the key transcription factors (TFs) controlling a biological process is the first step toward a better understanding of underpinning regulatory mechanisms. However, due to the involvement of a large number of genes and complex interactions in gene regulatory networks, identifying TFs involved in a biological process remains particularly difficult. The challenges include: (1) Most eukaryotic genomes encode thousands of TFs, which are organized in gene families of various sizes and in many cases with poor sequence conservation, making it difficult to recognize TFs for a biological process; (2) Transcription usually involves several hundred genes that generate a combination of intrinsic noise from upstream signaling networks and lead to fluctuations in transcription; (3) A TF can function in different cell types or developmental stages. Currently, the methods available for identifying TFs involved in biological processes are still very scarce, and the development of novel, more powerful methods is desperately needed. Results We developed a computational pipeline called TF-Cluster for identifying functionally coordinated TFs in two steps: (1) Construction of a shared coexpression connectivity matrix (SCCM), in which each entry represents the number of shared coexpressed genes between two TFs. This sparse and symmetric matrix embodies a new concept of coexpression networks in which genes are associated in the context of other shared coexpressed genes; (2) Decomposition of the SCCM using a novel heuristic algorithm termed "Triple-Link", which searches the highest connectivity in the SCCM, and then uses two connected TF as a primer for growing a TF cluster with a number of linking criteria. We applied TF-Cluster to microarray data from human stem cells and Arabidopsis roots, and then demonstrated that many of the resulting TF clusters contain functionally coordinated TFs that, based on existing literature, accurately represent a biological process