Earth Observations for Early Detection of Agricultural Drought: Contributions of the Famine Early Warning Systems Network (FEWS NET)

NASA Astrophysics Data System (ADS)

Budde, M. E.; Funk, C.; Husak, G. J.; Peterson, P.; Rowland, J.; Senay, G. B.; Verdin, J. P.

2016-12-01

The U.S. Geological Survey (USGS) has a long history of supporting the use of Earth observation data for food security monitoring through its role as an implementing partner of the Famine Early Warning Systems Network (FEWS NET) program. The use of remote sensing and crop modeling to address food security threats in the form of drought, floods, pests, and changing climatic regimes has been a core activity in monitoring FEWS NET countries. In recent years, it has become a requirement that FEWS NET apply monitoring and modeling frameworks at global scales to assess emerging crises in regions that FEWS NET does not traditionally monitor. USGS FEWS NET, in collaboration with the University of California, Santa Barbara, has developed a number of new global applications of satellite observations, derived products, and efficient tools for visualization and analyses to address these requirements. (1) A 35-year quasi-global (+/- 50 degrees latitude) time series of gridded rainfall estimates, the Climate Hazards Infrared Precipitation with Stations (CHIRPS) dataset, based on infrared satellite imagery and station observations. Data are available as 5-day (pentadal) accumulations at 0.05 degree spatial resolution. (2) Global actual evapotranspiration data based on application of the Simplified Surface Energy Balance (SSEB) model using 10-day MODIS Land Surface Temperature composites at 1-km resolution. (3) Production of global expedited MODIS (eMODIS) 10-day NDVI composites updated every 5 days. (4) Development of an updated Early Warning eXplorer (EWX) tool for data visualization, analysis, and sharing. (5) Creation of stand-alone tools for enhancement of gridded rainfall data and trend analyses. (6) Establishment of an agro-climatology analysis tool and knowledge base for more than 90 countries of interest to FEWS NET. In addition to these new products and tools, FEWS NET has partnered with the GEOGLAM community to develop a Crop Monitor for Early Warning (CM4EW) which

TreeNetViz: revealing patterns of networks over tree structures.

PubMed

Gou, Liang; Zhang, Xiaolong Luke

2011-12-01

Network data often contain important attributes from various dimensions such as social affiliations and areas of expertise in a social network. If such attributes exhibit a tree structure, visualizing a compound graph consisting of tree and network structures becomes complicated. How to visually reveal patterns of a network over a tree has not been fully studied. In this paper, we propose a compound graph model, TreeNet, to support visualization and analysis of a network at multiple levels of aggregation over a tree. We also present a visualization design, TreeNetViz, to offer the multiscale and cross-scale exploration and interaction of a TreeNet graph. TreeNetViz uses a Radial, Space-Filling (RSF) visualization to represent the tree structure, a circle layout with novel optimization to show aggregated networks derived from TreeNet, and an edge bundling technique to reduce visual complexity. Our circular layout algorithm reduces both total edge-crossings and edge length and also considers hierarchical structure constraints and edge weight in a TreeNet graph. These experiments illustrate that the algorithm can reduce visual cluttering in TreeNet graphs. Our case study also shows that TreeNetViz has the potential to support the analysis of a compound graph by revealing multiscale and cross-scale network patterns. © 2011 IEEE

EgoNet: identification of human disease ego-network modules

PubMed Central

2014-01-01

Background Mining novel biomarkers from gene expression profiles for accurate disease classification is challenging due to small sample size and high noise in gene expression measurements. Several studies have proposed integrated analyses of microarray data and protein-protein interaction (PPI) networks to find diagnostic subnetwork markers. However, the neighborhood relationship among network member genes has not been fully considered by those methods, leaving many potential gene markers unidentified. The main idea of this study is to take full advantage of the biological observation that genes associated with the same or similar diseases commonly reside in the same neighborhood of molecular networks. Results We present EgoNet, a novel method based on egocentric network-analysis techniques, to exhaustively search and prioritize disease subnetworks and gene markers from a large-scale biological network. When applied to a triple-negative breast cancer (TNBC) microarray dataset, the top selected modules contain both known gene markers in TNBC and novel candidates, such as RAD51 and DOK1, which play a central role in their respective ego-networks by connecting many differentially expressed genes. Conclusions Our results suggest that EgoNet, which is based on the ego network concept, allows the identification of novel biomarkers and provides a deeper understanding of their roles in complex diseases. PMID:24773628

Software-Enabled Distributed Network Governance: The PopMedNet Experience.

PubMed

Davies, Melanie; Erickson, Kyle; Wyner, Zachary; Malenfant, Jessica; Rosen, Rob; Brown, Jeffrey

2016-01-01

The expanded availability of electronic health information has led to increased interest in distributed health data research networks. The distributed research network model leaves data with and under the control of the data holder. Data holders, network coordinating centers, and researchers have distinct needs and challenges within this model. The concerns of network stakeholders are addressed in the design and governance models of the PopMedNet software platform. PopMedNet features include distributed querying, customizable workflows, and auditing and search capabilities. Its flexible role-based access control system enables the enforcement of varying governance policies. Four case studies describe how PopMedNet is used to enforce network governance models. Trust is an essential component of a distributed research network and must be built before data partners may be willing to participate further. The complexity of the PopMedNet system must be managed as networks grow and new data, analytic methods, and querying approaches are developed. The PopMedNet software platform supports a variety of network structures, governance models, and research activities through customizable features designed to meet the needs of network stakeholders.

Marine Vehicle Sensor Network Architecture and Protocol Designs for Ocean Observation

PubMed Central

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

2012-01-01

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

Biochemical Network Stochastic Simulator (BioNetS): software for stochastic modeling of biochemical networks.

PubMed

Adalsteinsson, David; McMillen, David; Elston, Timothy C

2004-03-08

Intrinsic fluctuations due to the stochastic nature of biochemical reactions can have large effects on the response of biochemical networks. This is particularly true for pathways that involve transcriptional regulation, where generally there are two copies of each gene and the number of messenger RNA (mRNA) molecules can be small. Therefore, there is a need for computational tools for developing and investigating stochastic models of biochemical networks. We have developed the software package Biochemical Network Stochastic Simulator (BioNetS) for efficiently and accurately simulating stochastic models of biochemical networks. BioNetS has a graphical user interface that allows models to be entered in a straightforward manner, and allows the user to specify the type of random variable (discrete or continuous) for each chemical species in the network. The discrete variables are simulated using an efficient implementation of the Gillespie algorithm. For the continuous random variables, BioNetS constructs and numerically solves the appropriate chemical Langevin equations. The software package has been developed to scale efficiently with network size, thereby allowing large systems to be studied. BioNetS runs as a BioSpice agent and can be downloaded from http://www.biospice.org. BioNetS also can be run as a stand alone package. All the required files are accessible from http://x.amath.unc.edu/BioNetS. We have developed BioNetS to be a reliable tool for studying the stochastic dynamics of large biochemical networks. Important features of BioNetS are its ability to handle hybrid models that consist of both continuous and discrete random variables and its ability to model cell growth and division. We have verified the accuracy and efficiency of the numerical methods by considering several test systems.

SkyNet: Modular nuclear reaction network library

NASA Astrophysics Data System (ADS)

Lippuner, Jonas; Roberts, Luke F.

2017-10-01

The general-purpose nuclear reaction network SkyNet evolves the abundances of nuclear species under the influence of nuclear reactions. SkyNet can be used to compute the nucleosynthesis evolution in all astrophysical scenarios where nucleosynthesis occurs. Any list of isotopes can be evolved and SkyNet supports various different types of nuclear reactions. SkyNet is modular, permitting new or existing physics, such as nuclear reactions or equations of state, to be easily added or modified.

Mars MetNet Mission - Martian Atmospheric Observational Post Network

NASA Astrophysics Data System (ADS)

Harri, A.-M.; Haukka, H.; Aleksashkin, S.; Arruego, I.; Schmidt, W.; Genzer, M.; Vazquez, L.; Siikonen, T.; Palin, M.

2017-09-01

A new kind of planetary exploration mission for Mars is under development in collaboration between the Finnish Meteorological Institute (FMI), Lavochkin Association (LA), Space Research Institute (IKI) and Institutio Nacional de Tecnica Aerospacial (INTA). The Mars MetNet mission is based on a new semi-hard landing vehicle called MetNet Lander (MNL). The scientific payload of the Mars MetNet Precursor [1] mission is divided into three categories: Atmospheric instruments, Optical devices and Composition and structure devices. Each of the payload instruments will provide significant insights in to the Martian atmospheric behavior. The key technologies of the MetNet Lander have been qualified and the electrical qualification model (EQM) of the payload bay has been built and successfully tested.

Cooperate to Validate: OBSERVAL-NET Experts' Report on Validation of Non-Formal and Informal Learning (VNIL) 2013

ERIC Educational Resources Information Center

Weber Guisan, Saskia; Voit, Janine; Lengauer, Sonja; Proinger, Eva; Duvekot, Ruud; Aagaard, Kirsten

2014-01-01

The present publication is one of the outcomes of the OBSERVAL-NET project (follow-up of the OBSERVAL project). The main aim of OBSERVAL-NET was to set up a stakeholder-centric network of organisations supporting the validation of non-formal and informal learning in Europe based on the formation of national working groups in the 8 participating…

Cooperate to Validate. Observal-Net Experts' Report on Validation of Non-Formal and Informal Learning (VNIL) 2013

ERIC Educational Resources Information Center

Weber Guisan, Saskia; Voit, Janine; Lengauer, Sonja; Proinger, Eva; Duvekot, Ruud; Aagaard, Kirsten

2014-01-01

The present publication is one of the outcomes of the OBSERVAL-NET project (followup of the OBSERVAL project). The main aim of OBSERVAL-NET was to set up a stakeholder centric network of organisations supporting the validation of non-formal and informal learning in Europe based on the formation of national working groups in the 8 participating…

A 3D Active Learning Application for NeMO-Net, the NASA Neural Multi-Modal Observation and Training Network for Global Coral Reef Assessment

NASA Technical Reports Server (NTRS)

van den Bergh, Jarrett; Schutz, Joey; Li, Alan; Chirayath, Ved

2017-01-01

NeMO-Net, the NASA neural multi-modal observation and training network for global coral reef assessment, is an open-source deep convolutional neural network and interactive active learning training software aiming to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology as well as mapping of spatial distribution. We present an interactive video game prototype for tablet and mobile devices where users interactively label morphology classifications over mm-scale 3D coral reef imagery captured using fluid lensing to create a dataset that will be used to train NeMO-Nets convolutional neural network. The application currently allows for users to classify preselected regions of coral in the Pacific and will be expanded to include additional regions captured using our NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as lower-resolution airborne remote sensing data from the ongoing NASA CORAL campaign. Active learning applications present a novel methodology for efficiently training large-scale Neural Networks wherein variances in identification can be rapidly mitigated against control data. NeMO-Net periodically checks users input against pre-classified coral imagery to gauge their accuracy and utilize in-game mechanics to provide classification training. Users actively communicate with a server and are requested to classify areas of coral for which other users had conflicting classifications and contribute their input to a larger database for ranking. In partnering with Mission Blue and IUCN, NeMO-Net leverages an international consortium of subject matter experts to classify areas of confusion identified by NeMO-Net and generate additional labels crucial for identifying decision boundary locations in coral reef assessment.

A 3D Active Learning Application for NeMO-Net, the NASA Neural Multi-Modal Observation and Training Network for Global Coral Reef Assessment

NASA Astrophysics Data System (ADS)

van den Bergh, J.; Schutz, J.; Chirayath, V.; Li, A.

2017-12-01

NeMO-Net, the NASA neural multi-modal observation and training network for global coral reef assessment, is an open-source deep convolutional neural network and interactive active learning training software aiming to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology as well as mapping of spatial distribution. We present an interactive video game prototype for tablet and mobile devices where users interactively label morphology classifications over mm-scale 3D coral reef imagery captured using fluid lensing to create a dataset that will be used to train NeMO-Net's convolutional neural network. The application currently allows for users to classify preselected regions of coral in the Pacific and will be expanded to include additional regions captured using our NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as lower-resolution airborne remote sensing data from the ongoing NASA CORAL campaign.Active learning applications present a novel methodology for efficiently training large-scale Neural Networks wherein variances in identification can be rapidly mitigated against control data. NeMO-Net periodically checks users' input against pre-classified coral imagery to gauge their accuracy and utilizes in-game mechanics to provide classification training. Users actively communicate with a server and are requested to classify areas of coral for which other users had conflicting classifications and contribute their input to a larger database for ranking. In partnering with Mission Blue and IUCN, NeMO-Net leverages an international consortium of subject matter experts to classify areas of confusion identified by NeMO-Net and generate additional labels crucial for identifying decision boundary locations in coral reef assessment.

MotifNet: a web-server for network motif analysis.

PubMed

Smoly, Ilan Y; Lerman, Eugene; Ziv-Ukelson, Michal; Yeger-Lotem, Esti

2017-06-15

Network motifs are small topological patterns that recur in a network significantly more often than expected by chance. Their identification emerged as a powerful approach for uncovering the design principles underlying complex networks. However, available tools for network motif analysis typically require download and execution of computationally intensive software on a local computer. We present MotifNet, the first open-access web-server for network motif analysis. MotifNet allows researchers to analyze integrated networks, where nodes and edges may be labeled, and to search for motifs of up to eight nodes. The output motifs are presented graphically and the user can interactively filter them by their significance, number of instances, node and edge labels, and node identities, and view their instances. MotifNet also allows the user to distinguish between motifs that are centered on specific nodes and motifs that recur in distinct parts of the network. MotifNet is freely available at http://netbio.bgu.ac.il/motifnet . The website was implemented using ReactJs and supports all major browsers. The server interface was implemented in Python with data stored on a MySQL database. estiyl@bgu.ac.il or michaluz@cs.bgu.ac.il. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

S-net project: Construction of large scale seafloor observatory network for tsunamis and earthquakes in Japan

NASA Astrophysics Data System (ADS)

Mochizuki, M.; Kanazawa, T.; Uehira, K.; Shimbo, T.; Shiomi, K.; Kunugi, T.; Aoi, S.; Matsumoto, T.; Sekiguchi, S.; Yamamoto, N.; Takahashi, N.; Shinohara, M.; Yamada, T.

2016-12-01

National Research Institute for Earth Science and Disaster Resilience ( NIED ) has launched the project of constructing an observatory network for tsunamis and earthquakes on the seafloor. The observatory network was named "S-net, Seafloor Observation Network for Earthquakes and Tsunamis along the Japan Trench". The S-net consists of 150 seafloor observatories which are connected in line with submarine optical cables. The total length of submarine optical cable is about 5,700 km. The S-net system extends along Kuril and Japan trenches around Japan islands from north to south covering the area between southeast off island of Hokkaido and off the Boso Peninsula, Chiba Prefecture. The project has been financially supported by MEXT Japan. An observatory package is 34cm in diameter and 226cm long. Each observatory equips two units of a high sensitive water-depth sensor as a tsunami meter and four sets of three-component seismometers. The water-depth sensor has measurement resolution of sub-centimeter level. Combination of multiple seismometers secures wide dynamic range and robustness of the observation that are needed for early earthquake warning. The S-net is composed of six segment networks that consists of about 25 observatories and 800-1,600km length submarine optical cable. Five of six segment networks except the one covering the outer rise area of the Japan Trench has been already installed. The data from the observatories on those five segment networks are being transferred to the data center at NIED on a real-time basis, and then verification of data integrity are being carried out at the present moment. Installation of the last segment network of the S-net, that is, the outer rise one is scheduled to be finished within FY2016. Full-scale operation of the S-net will start at FY2017. We will report construction and operation of the S-net submarine cable system as well as the outline of the obtained data in this presentation.

SkyNet: A Modular Nuclear Reaction Network Library

NASA Astrophysics Data System (ADS)

Lippuner, Jonas; Roberts, Luke F.

2017-12-01

Almost all of the elements heavier than hydrogen that are present in our solar system were produced by nuclear burning processes either in the early universe or at some point in the life cycle of stars. In all of these environments, there are dozens to thousands of nuclear species that interact with each other to produce successively heavier elements. In this paper, we present SkyNet, a new general-purpose nuclear reaction network that evolves the abundances of nuclear species under the influence of nuclear reactions. SkyNet can be used to compute the nucleosynthesis evolution in all astrophysical scenarios where nucleosynthesis occurs. SkyNet is free and open source, and aims to be easy to use and flexible. Any list of isotopes can be evolved, and SkyNet supports different types of nuclear reactions. SkyNet is modular so that new or existing physics, like nuclear reactions or equations of state, can easily be added or modified. Here, we present in detail the physics implemented in SkyNet with a focus on a self-consistent transition to and from nuclear statistical equilibrium to non-equilibrium nuclear burning, our implementation of electron screening, and coupling of the network to an equation of state. We also present comprehensive code tests and comparisons with existing nuclear reaction networks. We find that SkyNet agrees with published results and other codes to an accuracy of a few percent. Discrepancies, where they exist, can be traced to differences in the physics implementations.

Topological analysis of metabolic networks based on petri net theory.

PubMed

Zevedei-Oancea, Ionela; Schuster, Stefan

2011-01-01

Petri net concepts provide additional tools for the modelling of metabolic networks. Here, the similarities between the counterparts in traditional biochemical modelling and Petri net theory are discussed. For example the stoichiometry matrix of a metabolic network corresponds to the incidence matrix of the Petri net. The flux modes and conservation relations have the T-invariants, respectively, P-invariants as counterparts. We reveal the biological meaning of some notions specific to the Petri net framework (traps, siphons, deadlocks, liveness). We focus on the topological analysis rather than on the analysis of the dynamic behaviour. The treatment of external metabolites is discussed. Some simple theoretical examples are presented for illustration. Also the Petri nets corresponding to some biochemical networks are built to support our results. For example, the role of triose phosphate isomerase (TPI) in Trypanosoma brucei metabolism is evaluated by detecting siphons and traps. All Petri net properties treated in this contribution are exemplified on a system extracted from nucleotide metabolism.

Topological analysis of metabolic networks based on Petri net theory.

PubMed

Zevedei-Oancea, Ionela; Schuster, Stefan

2003-01-01

Petri net concepts provide additional tools for the modelling of metabolic networks. Here, the similarities between the counterparts in traditional biochemical modelling and Petri net theory are discussed. For example the stoichiometry matrix of a metabolic network corresponds to the incidence matrix of the Petri net. The flux modes and conservation relations have the T-invariants, respectively, P-invariants as counterparts. We reveal the biological meaning of some notions specific to the Petri net framework (traps, siphons, deadlocks, liveness). We focus on the topological analysis rather than on the analysis of the dynamic behaviour. The treatment of external metabolites is discussed. Some simple theoretical examples are presented for illustration. Also the Petri nets corresponding to some biochemical networks are built to support our results. For example, the role of triose phosphate isomerase (TPI) in Trypanosoma brucei metabolism is evaluated by detecting siphons and traps. All Petri net properties treated in this contribution are exemplified on a system extracted from nucleotide metabolism.

GFD-Net: A novel semantic similarity methodology for the analysis of gene networks.

PubMed

Díaz-Montaña, Juan J; Díaz-Díaz, Norberto; Gómez-Vela, Francisco

2017-04-01

Since the popularization of biological network inference methods, it has become crucial to create methods to validate the resulting models. Here we present GFD-Net, the first methodology that applies the concept of semantic similarity to gene network analysis. GFD-Net combines the concept of semantic similarity with the use of gene network topology to analyze the functional dissimilarity of gene networks based on Gene Ontology (GO). The main innovation of GFD-Net lies in the way that semantic similarity is used to analyze gene networks taking into account the network topology. GFD-Net selects a functionality for each gene (specified by a GO term), weights each edge according to the dissimilarity between the nodes at its ends and calculates a quantitative measure of the network functional dissimilarity, i.e. a quantitative value of the degree of dissimilarity between the connected genes. The robustness of GFD-Net as a gene network validation tool was demonstrated by performing a ROC analysis on several network repositories. Furthermore, a well-known network was analyzed showing that GFD-Net can also be used to infer knowledge. The relevance of GFD-Net becomes more evident in Section "GFD-Net applied to the study of human diseases" where an example of how GFD-Net can be applied to the study of human diseases is presented. GFD-Net is available as an open-source Cytoscape app which offers a user-friendly interface to configure and execute the algorithm as well as the ability to visualize and interact with the results(http://apps.cytoscape.org/apps/gfdnet). Copyright © 2017 Elsevier Inc. All rights reserved.

High-Throughput and Low-Latency Network Communication with NetIO

NASA Astrophysics Data System (ADS)

Schumacher, Jörn; Plessl, Christian; Vandelli, Wainer

2017-10-01

HPC network technologies like Infiniband, TrueScale or OmniPath provide low- latency and high-throughput communication between hosts, which makes them attractive options for data-acquisition systems in large-scale high-energy physics experiments. Like HPC networks, DAQ networks are local and include a well specified number of systems. Unfortunately traditional network communication APIs for HPC clusters like MPI or PGAS exclusively target the HPC community and are not suited well for DAQ applications. It is possible to build distributed DAQ applications using low-level system APIs like Infiniband Verbs, but it requires a non-negligible effort and expert knowledge. At the same time, message services like ZeroMQ have gained popularity in the HEP community. They make it possible to build distributed applications with a high-level approach and provide good performance. Unfortunately, their usage usually limits developers to TCP/IP- based networks. While it is possible to operate a TCP/IP stack on top of Infiniband and OmniPath, this approach may not be very efficient compared to a direct use of native APIs. NetIO is a simple, novel asynchronous message service that can operate on Ethernet, Infiniband and similar network fabrics. In this paper the design and implementation of NetIO is presented and described, and its use is evaluated in comparison to other approaches. NetIO supports different high-level programming models and typical workloads of HEP applications. The ATLAS FELIX project [1] successfully uses NetIO as its central communication platform. The architecture of NetIO is described in this paper, including the user-level API and the internal data-flow design. The paper includes a performance evaluation of NetIO including throughput and latency measurements. The performance is compared against the state-of-the- art ZeroMQ message service. Performance measurements are performed in a lab environment with Ethernet and FDR Infiniband networks.

Snoopy--a unifying Petri net framework to investigate biomolecular networks.

PubMed

Rohr, Christian; Marwan, Wolfgang; Heiner, Monika

2010-04-01

To investigate biomolecular networks, Snoopy provides a unifying Petri net framework comprising a family of related Petri net classes. Models can be hierarchically structured, allowing for the mastering of larger networks. To move easily between the qualitative, stochastic and continuous modelling paradigms, models can be converted into each other. We get models sharing structure, but specialized by their kinetic information. The analysis and iterative reverse engineering of biomolecular networks is supported by the simultaneous use of several Petri net classes, while the graphical user interface adapts dynamically to the active one. Built-in animation and simulation are complemented by exports to various analysis tools. Snoopy facilitates the addition of new Petri net classes thanks to its generic design. Our tool with Petri net samples is available free of charge for non-commercial use at http://www-dssz.informatik.tu-cottbus.de/snoopy.html; supported operating systems: Mac OS X, Windows and Linux (selected distributions).

Need low-cost networking? Consider DeviceNet

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

Moss, W.H.

1996-11-01

The drive to reduce production costs and optimize system performance in manufacturing facilities causes many end users to invest in network solutions. Because of distinct differences between the way tasks are performed and the way data are handled for various applications, it is clear than more than one network will be needed in most facilities. What is not clear is which network is most appropriate for a given application. The information layer is the link between automation and information environments via management information systems (MISs) and manufacturing execution systems (MESs) and manufacturing execution systems (MESs). Here the market has chosenmore » a de facto standard in Ethernet, primarily transmission control protocol/internet protocol (TCP/IP) and secondarily manufacturing messaging system (MMS). There is no single standard at the device layer. However, the DeviceNet communication standard has made strides to reach this goal. This protocol eliminates expensive hardwiring and provides improved communication between devices and important device-level diagnostics not easily accessible or available through hardwired I/O interfaces. DeviceNet is a low-cost communications link connecting industrial devices to a network. Many original equipment manufacturers and end users have chosen the DeviceNet platform for several reasons, but most frequently because of four key features: interchangeability; low cost; advanced diagnostics; insert devices under power.« less

Global Change Network: Combine Nutrient Network and Drought Net in China

NASA Astrophysics Data System (ADS)

Yu, Q.; Wang, C.; Zhu, J.; Xu, X.; Yang, H.; Wei, C.; Cong, N.; Wu, H.; Li, H.; Tian, D.; An, H.; Yu, G.

2017-12-01

Globally, all ecosystems will be impacted to some extent by changes in climate means and more frequent and severe periods of climatic extremes. Although there have been numerous studies examining the effects of changes in climatic means on ecological processes and ecosystems, research on climate extremes is far less common and is only now emerging as a distinct research field in ecology. Furthermore, although we have learned much in the past 20 years about how individual ecosystems are likely to respond to climate change, extending this knowledge to regional and continental scales has been a far greater challenge because of the inconsistent design of experiments and ecological complexity. In order to better forecast how entire regions will respond to eutrophication and extreme drought, two key network has been set up, i.e. Nutrient Network, Drought Net. However, there were few sites in China in the network studies, where locates Eurasian Steppe (the biggest grassland in the world) and Tibetan Plateau grassland (the world's highest and largest plateau grassland). To fill the great gap, we have set up ten sites in China (including 5 sites in Eurasia Steppe and 5 site in Tibetan Plateau), combing Nutrient Network and Drought Net treatments and also increased precipitation, called Global Change Network. There are 16 treatments with 6 repeats, and thus 96 plots in the global change network. The nutrient addition treatments are the same with Nutrient Network, i.e. 10 treatments. Precipitation change treatments include an extreme drought (the same with Drought Net) and a water addition (the amount is the same with drought treatment) treatment. The interactive treatments were only conducted in control N and NPK.

SeaDataNet network services monitoring: Definition and Implementation of Service availability index

NASA Astrophysics Data System (ADS)

Lykiardopoulos, Angelos; Mpalopoulou, Stavroula; Vavilis, Panagiotis; Pantazi, Maria; Iona, Sissy

2014-05-01

SeaDataNet (SDN) is a standardized system for managing large and diverse data sets collected by the oceanographic fleets and the automatic observation systems. The SeaDataNet network is constituted of national oceanographic data centres of 35 countries, active in data collection. SeaDataNetII project's objective is to upgrade the present SeaDataNet infrastructure into an operationally robust and state-of-the-art infrastructure; therefore Network Monitoring is a step to this direction. The term Network Monitoring describes the use of system that constantly monitors a computer network for slow or failing components and that notifies the network administrator in case of outages. Network monitoring is crucial when implementing widely distributed systems over the Internet and in real-time systems as it detects malfunctions that may occur and notifies the system administrator who can immediately respond and correct the problem. In the framework of SeaDataNet II project a monitoring system was developed in order to monitor the SeaDataNet components. The core system is based on Nagios software. Some plug-ins were developed to support SeaDataNet modules. On the top of Nagios Engine a web portal was developed in order to give access to local administrators of SeaDataNet components, to view detailed logs of their own service(s). Currently the system monitors 35 SeaDataNet Download Managers, 9 SeaDataNet Services, 25 GeoSeas Download Managers and 23 UBSS Download Managers . Taking advantage of the continuous monitoring of SeaDataNet system components a total availability index will be implemented. The term availability can be defined as the ability of a functional unit to be in a state to perform a required function under given conditions at a given instant of time or over a given time interval, assuming that the required external resources are provided. Availability measures can be considered as a are very important benefit becauseT - The availability trends that can be

SurvNet: a web server for identifying network-based biomarkers that most correlate with patient survival data.

PubMed

Li, Jun; Roebuck, Paul; Grünewald, Stefan; Liang, Han

2012-07-01

An important task in biomedical research is identifying biomarkers that correlate with patient clinical data, and these biomarkers then provide a critical foundation for the diagnosis and treatment of disease. Conventionally, such an analysis is based on individual genes, but the results are often noisy and difficult to interpret. Using a biological network as the searching platform, network-based biomarkers are expected to be more robust and provide deep insights into the molecular mechanisms of disease. We have developed a novel bioinformatics web server for identifying network-based biomarkers that most correlate with patient survival data, SurvNet. The web server takes three input files: one biological network file, representing a gene regulatory or protein interaction network; one molecular profiling file, containing any type of gene- or protein-centred high-throughput biological data (e.g. microarray expression data or DNA methylation data); and one patient survival data file (e.g. patients' progression-free survival data). Given user-defined parameters, SurvNet will automatically search for subnetworks that most correlate with the observed patient survival data. As the output, SurvNet will generate a list of network biomarkers and display them through a user-friendly interface. SurvNet can be accessed at http://bioinformatics.mdanderson.org/main/SurvNet.

NETS - A NEURAL NETWORK DEVELOPMENT TOOL, VERSION 3.0 (MACINTOSH VERSION)

NASA Technical Reports Server (NTRS)

Phillips, T. A.

1994-01-01

NETS, A Tool for the Development and Evaluation of Neural Networks, provides a simulation of Neural Network algorithms plus an environment for developing such algorithms. Neural Networks are a class of systems modeled after the human brain. Artificial Neural Networks are formed from hundreds or thousands of simulated neurons, connected to each other in a manner similar to brain neurons. Problems which involve pattern matching readily fit the class of problems which NETS is designed to solve. NETS uses the back propagation learning method for all of the networks which it creates. The nodes of a network are usually grouped together into clumps called layers. Generally, a network will have an input layer through which the various environment stimuli are presented to the network, and an output layer for determining the network's response. The number of nodes in these two layers is usually tied to some features of the problem being solved. Other layers, which form intermediate stops between the input and output layers, are called hidden layers. NETS allows the user to customize the patterns of connections between layers of a network. NETS also provides features for saving the weight values of a network during the learning process, which allows for more precise control over the learning process. NETS is an interpreter. Its method of execution is the familiar "read-evaluate-print" loop found in interpreted languages such as BASIC and LISP. The user is presented with a prompt which is the simulator's way of asking for input. After a command is issued, NETS will attempt to evaluate the command, which may produce more prompts requesting specific information or an error if the command is not understood. The typical process involved when using NETS consists of translating the problem into a format which uses input/output pairs, designing a network configuration for the problem, and finally training the network with input/output pairs until an acceptable error is reached. NETS

The net effects of the Project NetWork return-to-work case management experiment on participant earnings, benefit receipt, and other outcomes.

PubMed

Kornfeld, R; Rupp, K

2000-01-01

The Social Security Administration (SSA) initiated Project NetWork in 1991 to test case management as a means of promoting employment among persons with disabilities. The demonstration, which targeted Social Security Disability Insurance (DI) beneficiaries and Supplemental Security Income (SSI) applicants and recipients, offered intensive outreach, work-incentive waivers, and case management/referral services. Participation in Project NetWork was voluntary. Volunteers were randomly assigned to the "treatment" group or the "control" group. Those assigned to the treatment group met individually with a case or referral manager who arranged for rehabilitation and employment services, helped clients develop an individual employment plan, and provided direct employment counseling services. Volunteers assigned to the control group could not receive services from Project NetWork but remained eligible for any employment assistance already available in their communities. For both treatment and control groups, the demonstration waived specific DI and SSI program rules considered to be work disincentives. The experimental impact study thus measures the incremental effects of case and referral management services. The eight demonstration sites were successful in implementing the experimental design roughly as planned. Project NetWork staff were able to recruit large numbers of participants and to provide rehabilitation and employment services on a substantial scale. Most of the sites easily reached their enrollment targets and were able to attract volunteers with demographic characteristics similar to those of the entire SSI and DI caseload and a broad range of moderate and severe disabilities. However, by many measures, volunteers were generally more "work-ready" than project eligible in the demonstration areas who did not volunteer to receive NetWork services. Project NetWork case management increased average annual earnings by $220 per year over the first 2 years following

MPIGeneNet: Parallel Calculation of Gene Co-Expression Networks on Multicore Clusters.

PubMed

Gonzalez-Dominguez, Jorge; Martin, Maria J

2017-10-10

In this work we present MPIGeneNet, a parallel tool that applies Pearson's correlation and Random Matrix Theory to construct gene co-expression networks. It is based on the state-of-the-art sequential tool RMTGeneNet, which provides networks with high robustness and sensitivity at the expenses of relatively long runtimes for large scale input datasets. MPIGeneNet returns the same results as RMTGeneNet but improves the memory management, reduces the I/O cost, and accelerates the two most computationally demanding steps of co-expression network construction by exploiting the compute capabilities of common multicore CPU clusters. Our performance evaluation on two different systems using three typical input datasets shows that MPIGeneNet is significantly faster than RMTGeneNet. As an example, our tool is up to 175.41 times faster on a cluster with eight nodes, each one containing two 12-core Intel Haswell processors. Source code of MPIGeneNet, as well as a reference manual, are available at https://sourceforge.net/projects/mpigenenet/.

Initial Results from the Micro-pulse Lidar Network (MPL-Net)

NASA Technical Reports Server (NTRS)

Welton, Ellsworth J.; Campbell, James R.; Berkoff, Timothy A.; Spinhirne, James D.; Ginoux, Paul; Starr, David OC. (Technical Monitor)

2001-01-01

The micro-pulse lidar system (MPL) was developed in the early 1990s and was the first small, eye-safe, and autonomous lidar built for full time monitoring of cloud and aerosol vertical distributions. In 2000, a new project using MPL systems was started at NASA Goddard Space Flight Center. This new project, the Micro-pulse Lidar Network or MPL-Net, was created to provide long-term observations of aerosol and cloud vertical profiles at key sites around the world. This is accomplished using both NASA operated sites and partnerships with other organizations owning MPL systems. The MPL-Net sites are co-located with NASA AERONET sunphotometers to provide aerosol optical depth data needed for calibration of the MPL. In addition to the long-term sites, MPL-Net provides lidar support for a limited number of field experiments and ocean cruises each year. We will present an overview of the MPL-Net project and show initial results from the first two MPL-Net sites at the South Pole and at Goddard Space Flight Center. Observations of dust layers transported from the Gobi desert, across the Pacific Ocean, to the east coast of the United States will also be shown. MPL-Net affiliated instruments were in place at the desert source region in China, on a research vessel in the Sea of Japan, at ARM sites in Alaska and Oklahoma, and finally at our home site in Maryland (GSFC) during the massive dust storms that occurred in April 2001. The MPL observations of dust layers at each location are shown in comparison to dust layers predicted using the Georgia Tech/Goddard Global Ozone Chemistry Aerosol Radiation and Transport model (GOCART). Finally, the MPL-Net project is the primary ground-validation program for the Geo-Science Laser Altimeter System (GLAS) satellite lidar project (launch date 2002). We will present an overview demonstrating how MPL-Net results are used to help prepare the GLAS data processing algorithms and assist in the calibration/validation of the GLAS data products.

Initial Results From The Micro-pulse Lidar Network (MPL-Net)

NASA Astrophysics Data System (ADS)

Welton, E. J.; Campbell, J. R.; Berkoff, T. A.; Spinhirne, J. D.; Ginoux, P.

2001-12-01

The micro-pulse lidar system (MPL) was developed in the early 1990s and was the first small, eye-safe, and autonomous lidar built for fulltime monitoring of cloud and aerosol vertical distributions. In 2000, a new project using MPL systems was started at NASA Goddard Space Flight Center. This new project, the Micro-pulse Lidar Network or MPL-Net, was created to provide long-term observations of aerosol and cloud vertical profiles at key sites around the world. This is accomplished using both NASA operated sites and partnerships with other organizations owning MPL systems. The MPL-Net sites are co-located with NASA AERONET sunphotometers to provide aerosol optical depth data needed for calibration of the MPL. In addition to the long-term sites, MPL-Net provides lidar support for a limited number of field experiments and ocean cruises each year. We will present an overview of the MPL-Net project and show initial results from the first two MPL-Net sites at the South Pole and at Goddard Space Flight Center. Observations of dust layers transported from the desert regions of China, across the Pacific Ocean, to the east coast of the United States will also be shown. MPL-Net affiliated instruments were in place at the desert source region in China, on a research vessel in the Sea of Japan, at ARM sites in Alaska and Oklahoma, and finally at our home site in Maryland (GSFC) during the massive dust storms that occurred in April 2001. The MPL observations of dust layers at each location are shown in comparison to dust layers predicted using the Georgia Tech/Goddard Global Ozone Chemistry Aerosol Radiation and Transport model (GOCART). Finally, the MPL-Net project is the primary ground-validation program for the Geo-Science Laser Altimeter System (GLAS) satellite lidar project (launch date 2002). We will present an overview demonstrating how MPL-Net results are used to help prepare the GLAS data processing algorithms and assist in the calibration/validation of the GLAS data

Direct observation of macrostructure formation of hierarchically structured meso-macroporous aluminosilicates with 3D interconnectivity by optical microscope.

PubMed

Lemaire, Arnaud; Rooke, Joanna Claire; Chen, Li-Hua; Su, Bao-Lian

2011-03-15

Hierarchically structured spongy meso-macroporous aluminosilicates with high tetrahedral aluminum content were synthesized from a mixture of single molecular alkoxide precursor, (sec-BuO)2-Al-O-Si(OEt)3, already containing Si-O-Al bonds, and a silica coreactant, tetramethoxysilane (TMOS). The spontaneous byproduct templated macroporous structure formation has been directly visualized using in situ high-resolution optical microscopy (OM), allowing the crucial observation of a microbubble dispersion which is directly correlated to the macrostructure observed by electronic microscopies (SEM and TEM). This discovery leads to a comparative study with meso-macroporous pure metal oxide and to a proposal of the formation mechanism of meso-macroporous aluminosilicates with 3D interconnectivity. The aluminosilicate phase/microbubbles emulsion is produced by a phase separation process occurring between the aluminosilicate nanoparticles and the liquid hydrolysis-condensation reaction byproducts (water, methanol, ethanol, and butanol). The use of alkoxysilane improves the heterocondensation rates between the highly reactive aluminum alkoxide part of the single precursor and added silica species but, above all, leads to the spontaneous generation of an unusual meso-macroporosity in alkaline media. The particles obtained at pH = 13.0 featured regular micrometer-sized macrospheres separated by very thin mesoporous walls and connected by submicrometric openings, providing a 3D interconnectivity. The slight increase in pH value to 13.5 induced significant modifications in morphology and textural properties due to the slower gelification process of the aluminosilicate phase, resulting in the formation of an aluminosilicate material constituted of 1-2 µm large independent hollow mesoporous spheres.

PodNet, a protein-protein interaction network of the podocyte.

PubMed

Warsow, Gregor; Endlich, Nicole; Schordan, Eric; Schordan, Sandra; Chilukoti, Ravi K; Homuth, Georg; Moeller, Marcus J; Fuellen, Georg; Endlich, Karlhans

2013-07-01

Interactions between proteins crucially determine cellular structure and function. Differential analysis of the interactome may help elucidate molecular mechanisms during disease development; however, this analysis necessitates mapping of expression data on protein-protein interaction networks. These networks do not exist for the podocyte; therefore, we built PodNet, a literature-based mouse podocyte network in Cytoscape format. Using database protein-protein interactions, we expanded PodNet to XPodNet with enhanced connectivity. In order to test the performance of XPodNet in differential interactome analysis, we examined podocyte developmental differentiation and the effect of cell culture. Transcriptomes of podocytes in 10 different states were mapped on XPodNet and analyzed with the Cytoscape plugin ExprEssence, based on the law of mass action. Interactions between slit diaphragm proteins are most significantly upregulated during podocyte development and most significantly downregulated in culture. On the other hand, our analysis revealed that interactions lost during podocyte differentiation are not regained in culture, suggesting a loss rather than a reversal of differentiation for podocytes in culture. Thus, we have developed PodNet as a valuable tool for differential interactome analysis in podocytes, and we have identified established and unexplored regulated interactions in developing and cultured podocytes.

BioNetCAD: design, simulation and experimental validation of synthetic biochemical networks

PubMed Central

Rialle, Stéphanie; Felicori, Liza; Dias-Lopes, Camila; Pérès, Sabine; El Atia, Sanaâ; Thierry, Alain R.; Amar, Patrick; Molina, Franck

2010-01-01

Motivation: Synthetic biology studies how to design and construct biological systems with functions that do not exist in nature. Biochemical networks, although easier to control, have been used less frequently than genetic networks as a base to build a synthetic system. To date, no clear engineering principles exist to design such cell-free biochemical networks. Results: We describe a methodology for the construction of synthetic biochemical networks based on three main steps: design, simulation and experimental validation. We developed BioNetCAD to help users to go through these steps. BioNetCAD allows designing abstract networks that can be implemented thanks to CompuBioTicDB, a database of parts for synthetic biology. BioNetCAD enables also simulations with the HSim software and the classical Ordinary Differential Equations (ODE). We demonstrate with a case study that BioNetCAD can rationalize and reduce further experimental validation during the construction of a biochemical network. Availability and implementation: BioNetCAD is freely available at http://www.sysdiag.cnrs.fr/BioNetCAD. It is implemented in Java and supported on MS Windows. CompuBioTicDB is freely accessible at http://compubiotic.sysdiag.cnrs.fr/ Contact: stephanie.rialle@sysdiag.cnrs.fr; franck.molina@sysdiag.cnrs.fr Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20628073

NET: a new framework for the vectorization and examination of network data.

PubMed

Lasser, Jana; Katifori, Eleni

2017-01-01

The analysis of complex networks both in general and in particular as pertaining to real biological systems has been the focus of intense scientific attention in the past and present. In this paper we introduce two tools that provide fast and efficient means for the processing and quantification of biological networks like Drosophila tracheoles or leaf venation patterns: the Network Extraction Tool ( NET ) to extract data and the Graph-edit-GUI ( GeGUI ) to visualize and modify networks. NET is especially designed for high-throughput semi-automated analysis of biological datasets containing digital images of networks. The framework starts with the segmentation of the image and then proceeds to vectorization using methodologies from optical character recognition. After a series of steps to clean and improve the quality of the extracted data the framework produces a graph in which the network is represented only by its nodes and neighborhood-relations. The final output contains information about the adjacency matrix of the graph, the width of the edges and the positions of the nodes in space. NET also provides tools for statistical analysis of the network properties, such as the number of nodes or total network length. Other, more complex metrics can be calculated by importing the vectorized network to specialized network analysis packages. GeGUI is designed to facilitate manual correction of non-planar networks as these may contain artifacts or spurious junctions due to branches crossing each other. It is tailored for but not limited to the processing of networks from microscopy images of Drosophila tracheoles. The networks extracted by NET closely approximate the network depicted in the original image. NET is fast, yields reproducible results and is able to capture the full geometry of the network, including curved branches. Additionally GeGUI allows easy handling and visualization of the networks.

MediaNet: a multimedia information network for knowledge representation

NASA Astrophysics Data System (ADS)

Benitez, Ana B.; Smith, John R.; Chang, Shih-Fu

2000-10-01

In this paper, we present MediaNet, which is a knowledge representation framework that uses multimedia content for representing semantic and perceptual information. The main components of MediaNet include conceptual entities, which correspond to real world objects, and relationships among concepts. MediaNet allows the concepts and relationships to be defined or exemplified by multimedia content such as images, video, audio, graphics, and text. MediaNet models the traditional relationship types such as generalization and aggregation but adds additional functionality by modeling perceptual relationships based on feature similarity. For example, MediaNet allows a concept such as car to be defined as a type of a transportation vehicle, but which is further defined and illustrated through example images, videos and sounds of cars. In constructing the MediaNet framework, we have built on the basic principles of semiotics and semantic networks in addition to utilizing the audio-visual content description framework being developed as part of the MPEG-7 multimedia content description standard. By integrating both conceptual and perceptual representations of knowledge, MediaNet has potential to impact a broad range of applications that deal with multimedia content at the semantic and perceptual levels. In particular, we have found that MediaNet can improve the performance of multimedia retrieval applications by using query expansion, refinement and translation across multiple content modalities. In this paper, we report on experiments that use MediaNet in searching for images. We construct the MediaNet knowledge base using both WordNet and an image network built from multiple example images and extracted color and texture descriptors. Initial experimental results demonstrate improved retrieval effectiveness using MediaNet in a content-based retrieval system.

PubNet: a flexible system for visualizing literature derived networks

PubMed Central

Douglas, Shawn M; Montelione, Gaetano T; Gerstein, Mark

2005-01-01

We have developed PubNet, a web-based tool that extracts several types of relationships returned by PubMed queries and maps them into networks, allowing for graphical visualization, textual navigation, and topological analysis. PubNet supports the creation of complex networks derived from the contents of individual citations, such as genes, proteins, Protein Data Bank (PDB) IDs, Medical Subject Headings (MeSH) terms, and authors. This feature allows one to, for example, examine a literature derived network of genes based on functional similarity. PMID:16168087

The MeSO-net (Metropolitan Seismic Observation network) confronts the Pacific Coast of Tohoku Earthquake, Japan (Mw 9.0)

NASA Astrophysics Data System (ADS)

Kasahara, K.; Nakagawa, S.; Sakai, S.; Nanjo, K.; Panayotopoulos, Y.; Morita, Y.; Tsuruoka, H.; Kurashimo, E.; Obara, K.; Hirata, N.; Aketagawa, T.; Kimura, H.

2011-12-01

On April 2007, we have launched the special project for earthquake disaster mitigation in the Tokyo Metropolitan area (Fiscal 2007-2011). As a part of this project, construction of the MeSO-net (Metropolitan Seismic Observation network) has been completed, with about 300 stations deployed at mainly elementary and junior-high schools with an interval of about 5 km in space. This results in a highly dense network that covers the metropolitan area. To achieve stable seismic observation with lower surface ground noise, relative to a measurement on the surface, sensors of all stations were installed in boreholes at a depth of about 20m. The sensors have a wide dynamic range (135dB) and a wide frequency band (DC to 80Hz). Data are digitized with 200Hz sampling and telemetered to the Earthquake Research Institute, University of Tokyo. The MeSO-net that can detect and locate most earthquakes with magnitudes above 2.5 provides a unique baseline in scientific and engineering researches on the Tokyo metropolitan area, as follows. One of the main contributions is to greatly improve the image of the Philippine Sea plate (PSP) (Nakagawa et al., 2010) and provides an accurate estimation of the plate boundaries between the PSP and the Pacific plate, allowing us to possibly discuss clear understanding of the relation between the PSP deformation and M7+ intra-slab earthquake generation. Also, the latest version of the plate model in the metropolitan area, proposed by our project, attracts various researchers, comparing with highly-accurate solutions of fault mechanism, repeating earthquakes, etc. Moreover, long-periods ground motions generated by the 2011 earthquake off the Pacific coast of Tohoku earthquake (Mw 9.0) were observed by the MeSO-net and analyzed to obtain the Array Back-Projection Imaging of this event (Honda et al., 2011). As a result, the overall pattern of the imaged asperities coincides well with the slip distribution determined based on other waveform inversion

NETS - A NEURAL NETWORK DEVELOPMENT TOOL, VERSION 3.0 (MACHINE INDEPENDENT VERSION)

NASA Technical Reports Server (NTRS)

Baffes, P. T.

1994-01-01

NETS, A Tool for the Development and Evaluation of Neural Networks, provides a simulation of Neural Network algorithms plus an environment for developing such algorithms. Neural Networks are a class of systems modeled after the human brain. Artificial Neural Networks are formed from hundreds or thousands of simulated neurons, connected to each other in a manner similar to brain neurons. Problems which involve pattern matching readily fit the class of problems which NETS is designed to solve. NETS uses the back propagation learning method for all of the networks which it creates. The nodes of a network are usually grouped together into clumps called layers. Generally, a network will have an input layer through which the various environment stimuli are presented to the network, and an output layer for determining the network's response. The number of nodes in these two layers is usually tied to some features of the problem being solved. Other layers, which form intermediate stops between the input and output layers, are called hidden layers. NETS allows the user to customize the patterns of connections between layers of a network. NETS also provides features for saving the weight values of a network during the learning process, which allows for more precise control over the learning process. NETS is an interpreter. Its method of execution is the familiar "read-evaluate-print" loop found in interpreted languages such as BASIC and LISP. The user is presented with a prompt which is the simulator's way of asking for input. After a command is issued, NETS will attempt to evaluate the command, which may produce more prompts requesting specific information or an error if the command is not understood. The typical process involved when using NETS consists of translating the problem into a format which uses input/output pairs, designing a network configuration for the problem, and finally training the network with input/output pairs until an acceptable error is reached. NETS

NetDecoder: a network biology platform that decodes context-specific biological networks and gene activities.

PubMed

da Rocha, Edroaldo Lummertz; Ung, Choong Yong; McGehee, Cordelia D; Correia, Cristina; Li, Hu

2016-06-02

The sequential chain of interactions altering the binary state of a biomolecule represents the 'information flow' within a cellular network that determines phenotypic properties. Given the lack of computational tools to dissect context-dependent networks and gene activities, we developed NetDecoder, a network biology platform that models context-dependent information flows using pairwise phenotypic comparative analyses of protein-protein interactions. Using breast cancer, dyslipidemia and Alzheimer's disease as case studies, we demonstrate NetDecoder dissects subnetworks to identify key players significantly impacting cell behaviour specific to a given disease context. We further show genes residing in disease-specific subnetworks are enriched in disease-related signalling pathways and information flow profiles, which drive the resulting disease phenotypes. We also devise a novel scoring scheme to quantify key genes-network routers, which influence many genes, key targets, which are influenced by many genes, and high impact genes, which experience a significant change in regulation. We show the robustness of our results against parameter changes. Our network biology platform includes freely available source code (http://www.NetDecoder.org) for researchers to explore genome-wide context-dependent information flow profiles and key genes, given a set of genes of particular interest and transcriptome data. More importantly, NetDecoder will enable researchers to uncover context-dependent drug targets. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

NetSciEd: Network Science and Education for the Interconnected World

ERIC Educational Resources Information Center

Sayama, Hiroki; Cramer, Catherine; Sheetz, Lori; Uzzo, Stephen

2017-01-01

This short article presents a summary of the NetSciEd (Network Science and Education) initiative that aims to address the need for curricula, resources, accessible materials, and tools for introducing K-12 students and the general public to the concept of networks, a crucial framework in understanding complexity. NetSciEd activities include (1)…

Saver.net lidar network in southern South America

NASA Astrophysics Data System (ADS)

Ristori, Pablo; Otero, Lidia; Jin, Yoshitaka; Barja, Boris; Shimizu, Atsushi; Barbero, Albane; Salvador, Jacobo; Bali, Juan Lucas; Herrera, Milagros; Etala, Paula; Acquesta, Alejandro; Quel, Eduardo; Sugimoto, Nobuo; Mizuno, Akira

2018-04-01

The South American Environmental Risk Management Network (SAVER-Net) is an instrumentation network, mainly composed by lidars, to provide real-time information for atmospheric hazards and risk management purposes in South America. This lidar network have been developed since 2012 and all its sampling points are expected to be fully implemented by 2017. This paper describes the network's status and configuration, the data acquisition and processing scheme (protocols and data levels), as well as some aspects of the scientific networking in Latin American Lidar Network (LALINET). Similarly, the paper lays out future plans on the operation and integration to major international collaborative efforts.

Modeling and performance analysis using extended fuzzy-timing Petri nets for networked virtual environments.

PubMed

Zhou, Y; Murata, T; Defanti, T A

2000-01-01

Despite their attractive properties, networked virtual environments (net-VEs) are notoriously difficult to design, implement, and test due to the concurrency, real-time and networking features in these systems. Net-VEs demand high quality-of-service (QoS) requirements on the network to maintain natural and real-time interactions among users. The current practice for net-VE design is basically trial and error, empirical, and totally lacks formal methods. This paper proposes to apply a Petri net formal modeling technique to a net-VE-NICE (narrative immersive constructionist/collaborative environment), predict the net-VE performance based on simulation, and improve the net-VE performance. NICE is essentially a network of collaborative virtual reality systems called the CAVE-(CAVE automatic virtual environment). First, we introduce extended fuzzy-timing Petri net (EFTN) modeling and analysis techniques. Then, we present EFTN models of the CAVE, NICE, and transport layer protocol used in NICE: transmission control protocol (TCP). We show the possibility analysis based on the EFTN model for the CAVE. Then, by using these models and design/CPN as the simulation tool, we conducted various simulations to study real-time behavior, network effects and performance (latencies and jitters) of NICE. Our simulation results are consistent with experimental data.

Famine Early Warning System Network (FEWS NET)

USGS Publications Warehouse

Verdin, James P.

2006-01-01

The FEWS NET mission is to identify potentially food-insecure conditions early through the provision of timely and analytical hazard and vulnerability information. U.S. Government decision-makers act on this information to authorize mitigation and response activities. The U.S. Geological Survey (USGS) FEWS NET provides tools and data for monitoring and forecasting the incidence of drought and flooding to identify shocks to the food supply system that could lead to famine. Historically focused on Africa, the scope of the network has expanded to be global coverage. FEWS NET implementing partners include the USGS, National Aeronautics and Space Administration (NASA), National Oceanic and Atmospheric Administration (NOAA), United States Agency for International Development (USAID), United States Department of Agriculture (USDA), and Chemonics International.

Functional network in posttranslational modifications: Glyco-Net in Glycoconjugate Data Bank.

PubMed

Miura, Nobuaki; Okada, Takuya; Murayama, Daisuke; Hirose, Kazuko; Sato, Taku; Hashimoto, Ryo; Fukushima, Nobuhiro

2015-01-01

Elucidating pathways related to posttranslational modifications (PTMs) such as glycosylation is of growing importance in post-genome science and technology. Graphical networks describing the relationships among glycan-related molecules, including genes, proteins, lipids, and various biological events, are considered extremely valuable and convenient tools for the systematic investigation of PTMs. Glyco-Net (http://bibi.sci.hokudai.ac.jp/functions/) can dynamically make network figures among various biological molecules and biological events. A certain molecule or event is expressed with a node, and the relationship between the molecule and the event is indicated by arrows in the network figures. In this chapter, we mention the features and current status of the Glyco-Net and a simple example of the search with the Glyco-Net.

Managing cancer care through service delivery networks: The role of professional collaboration in two European cancer networks.

PubMed

Prades, Joan; Morando, Verdiana; Tozzi, Valeria D; Verhoeven, Didier; Germà, Jose R; Borras, Josep M

2017-01-01

Background The study examines two meso-strategic cancer networks, exploring to what extent collaboration can strengthen or hamper network effectiveness. Unlike macro-strategic networks, meso-strategic networks have no hierarchical governance structures nor are they institutionalised within healthcare services' delivery systems. This study aims to analyse the models of professional cooperation and the tools developed for managing clinical practice within two meso-strategic, European cancer networks. Methods Multiple case study design based on the comparative analysis of two cancer networks: Iridium, in Antwerp, Belgium and the Institut Català d'Oncologia in Catalonia, Spain. The case studies applied mixed methods, with qualitative research based on semi-structured interviews ( n = 35) together with case-site observation and material collection. Results The analysis identified four levels of collaborative intensity within medical specialties as well as in multidisciplinary settings, which became both platforms for crosscutting clinical work between hubs' experts and local care teams and the levers for network-based tools development. The organisation of clinical practice relied on professional-based cooperative processes and tiers, lacking vertical integration mechanisms. Conclusions The intensity of professional linkages largely shaped the potential of meso-strategic cancer networks to influence clinical practice organisation. Conversely, the introduction of managerial techniques or network governance structures, without introducing vertical hierarchies, was found to be critical solutions.

Effect of network topology on the evolutionary ultimatum game based on the net-profit decision

NASA Astrophysics Data System (ADS)

Ye, Shun-Qiang; Wang, Lu; Jones, Michael C.; Ye, Ye; Wang, Meng; Xie, Neng-Gang

2016-04-01

The ubiquity of altruist behavior amongst humans has long been a significant puzzle in the social sciences. Ultimatum game has proved to be a useful tool for explaining altruistic behavior among selfish individuals. In an ultimatum game where alternating roles exist, we suppose that players make their decisions based on the net profit of their own. In this paper, we specify a player's strategy with two parameters: offer level α ∈ [ 0,1) and net profit acceptance level β ∈ [ - 1,1). By Monte Carlo simulation, we analyze separately the effect of the size of the neighborhood, the small-world property and the heterogeneity of the degree distributions of the networks. Results show that compared with results observed for homogeneous networks, heterogeneous networks lead to more rational outcomes. Moreover, network structure has no effect on the evolution of kindness level, so moderate kindness is adaptable to any social groups and organizations.

75 FR 65363 - Basic Behavioral and Social Science Opportunity Network (OppNet)

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-22

... public meeting to promote and publicize the Basic Behavioral and Social Science Opportunity Network (Opp... . Background: The Basic Behavioral and Social Science Opportunity Network (OppNet) is a trans-NIH initiative to expand the agency's funding of basic behavioral and social sciences research (b-BSSR). OppNet prioritizes...

Verify MesoNAM Performance

NASA Technical Reports Server (NTRS)

Bauman, William H., III

2010-01-01

The AMU conducted an objective analysis of the MesoNAM forecasts compared to observed values from sensors at specified KSC/CCAFS wind towers by calculating the following statistics to verify the performance of the model: 1) Bias (mean difference), 2) Standard deviation of Bias, 3) Root Mean Square Error (RMSE), and 4) Hypothesis test for Bias = O. The 45 WS LWOs use the MesoNAM to support launch weather operations. However, the actual performance of the model at KSC and CCAFS had not been measured objectively. The analysis compared the MesoNAM forecast winds, temperature and dew point to the observed values from the sensors on wind towers. The data were stratified by tower sensor, month and onshore/offshore wind direction based on the orientation of the coastline to each tower's location. The model's performance statistics were then calculated for each wind tower based on sensor height and model initialization time. The period of record for the data used in this task was based on the operational start of the current MesoNAM in mid-August 2006 and so the task began with the first full month of data, September 2006, through May 2010. The analysis of model performance indicated: a) The accuracy decreased as the forecast valid time from the model initialization increased, b) There was a diurnal signal in T with a cool bias during the late night and a warm bias during the afternoon, c) There was a diurnal signal in Td with a low bias during the afternoon and a high bias during the late night, and d) The model parameters at each vertical level most closely matched the observed parameters at heights closest to those vertical levels. The AMU developed a GUI that consists of a multi-level drop-down menu written in JavaScript embedded within the HTML code. This tool allows the LWO to easily and efficiently navigate among the charts and spreadsheet files containing the model performance statistics. The objective statistics give the LWOs knowledge of the model's strengths and

Petri Nets - A Mathematical Formalism to Analyze Chemical Reaction Networks.

PubMed

Koch, Ina

2010-12-17

In this review we introduce and discuss Petri nets - a mathematical formalism to describe and analyze chemical reaction networks. Petri nets were developed to describe concurrency in general systems. We find most applications to technical and financial systems, but since about twenty years also in systems biology to model biochemical systems. This review aims to give a short informal introduction to the basic formalism illustrated by a chemical example, and to discuss possible applications to the analysis of chemical reaction networks, including cheminformatics. We give a short overview about qualitative as well as quantitative modeling Petri net techniques useful in systems biology, summarizing the state-of-the-art in that field and providing the main literature references. Finally, we discuss advantages and limitations of Petri nets and give an outlook to further development. Copyright © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A meso-network of eddy covariance towers across the Northwest Territories to assess high-latitude carbon and water budgets under increasing pressure

NASA Astrophysics Data System (ADS)

Hurkuck, M.; Marsh, P.; Quinton, W. L.; Humphreys, E.; Lafleur, P.; Helbig, M.; Hould Gosselin, G.; Sonnentag, O.

2017-12-01

Given their large areal coverage, high carbon densities, unique land surface properties, and disturbance regimes, Canada's diverse high-latitude ecosystems across its multiple Arctic, subarctic and boreal ecozones are integral components of the global and regional climate systems. In northwestern Canada, large portions of these ecozones contain permafrost, i.e., perennially cryotic ground. Here, we describe efforts towards a meso-network of nine eddy covariance towers to measure carbon, water and energy fluxes across the Northwest Territories to shed light on high-latitude carbon and water budgets and their rapidly changing biotic and abiotic controls in response to increasing natural and anthropogenic pressures. Distributed across six research sites (Trail Valley Creek, 68.7°N, 133.3°W; Havikpak Creek, 68.3°N, 133.3°W; Daring Lake, 64.8°N, 111.5°W; Smith Creek, 63.1°N, 123.2°W; Scotty Creek, 63.1°N, 123.2°W; Yellowknife, 62.5°N, 114.4°W), the meso-network spans the central portion of the extended ABoVE Study Domain, covering two ecozones (Taiga Plains, Southern Arctic) with differing permafrost regimes (sporadic, discontinuous, continuous), climatic settings (coastal, interior), and seven high-latitude ecosystem types: forested permafrost peat plateau, permafrost-free collapse-scar bog, subarctic woodland, mixed and dwarf-shrub tundra, and sedge fen. With our contribution, we report on the current status of the meso-network development and present results from various synthesis activities examining the role of climatic setting and resulting tundra carbon and water budgets, quantifying the impact of permafrost thaw and associated wetland expansion on boreal forest carbon and water budgets, and determining the relative importance of treeline advance compared to shrub proliferation on tundra carbon and water budgets.

DiffNet: automatic differential functional summarization of dE-MAP networks.

PubMed

Seah, Boon-Siew; Bhowmick, Sourav S; Dewey, C Forbes

2014-10-01

The study of genetic interaction networks that respond to changing conditions is an emerging research problem. Recently, Bandyopadhyay et al. (2010) proposed a technique to construct a differential network (dE-MAPnetwork) from two static gene interaction networks in order to map the interaction differences between them under environment or condition change (e.g., DNA-damaging agent). This differential network is then manually analyzed to conclude that DNA repair is differentially effected by the condition change. Unfortunately, manual construction of differential functional summary from a dE-MAP network that summarizes all pertinent functional responses is time-consuming, laborious and error-prone, impeding large-scale analysis on it. To this end, we propose DiffNet, a novel data-driven algorithm that leverages Gene Ontology (go) annotations to automatically summarize a dE-MAP network to obtain a high-level map of functional responses due to condition change. We tested DiffNet on the dynamic interaction networks following MMS treatment and demonstrated the superiority of our approach in generating differential functional summaries compared to state-of-the-art graph clustering methods. We studied the effects of parameters in DiffNet in controlling the quality of the summary. We also performed a case study that illustrates its utility. Copyright © 2014 Elsevier Inc. All rights reserved.

Radiosonde observational evidence of the influence of extreme SST gradient upon atmospheric meso-scale circulation

NASA Astrophysics Data System (ADS)

Nishikawa, H.; Tachibana, Y.; Udagawa, Y.

2012-12-01

Although the influence of the anomalous midlatitude SST upon atmospheric local circulation has been getting common in particular over the Kuroshio and the Gulf Stream regions, observational studies on the influence of the Okhotsk Sea, which is to the north of the Kuroshio, upon the atmospheric local circulation is much less than those of the Kuroshio. The climate of the Okhotsk SST is very peculiar. Extremely cold SST spots, whose summertime SST is lower than 5 Celsius degrees, are formed around Kuril Islands. Because SSTs are generally determined by local air-sea interaction as well as temperature advection, it is very difficult to isolate only the oceanic influence upon the atmosphere. The SST in this cold spot is, however, dominated by the tidal mixing, which is independent of the atmospheric processes. This unique condition may ease the account for the oceanic influence only. Although the SST environment of the Okhotsk Sea is good for understanding the oceanic influence upon the atmosphere, only a few studies has been executed in this region because of the difficulty of observations by research vessels in this region, where territory problems between Japan and Russia is unsolved. Because of the scant of direct observation, the Okhotsk Sea was still mysterious. In 2006 August, GPS radiosonde observation was carried out by Russian research vessel Khromov in the Sea of Okhotsk by the cooperation between Japan and Russia, and strong SST gradient of about 7 Celsius degrees/10km was observed around the Kuril Islands. The purpose of this study is to demonstrate observational finding of meso-scale atmospheric anticyclonic circulation influenced by the cold oceanic spot around the Kuril Island. The summaries of the observation are as follows. Meso-scale atmospheric ageostrophic anticyclonic circulation in the atmospheric marine-boundary layer is observed in and around the cold spot. A high air pressure area as compared with other surrounding areas is also located at the

Recent developments with the asian dust and aerosol lidar observation network (AD-NET)

NASA Astrophysics Data System (ADS)

Sugimoto, Nobuo; Shimizu, Atsushi; Nishizawa, Tomoaki; Jin, Yoshitaka

2018-04-01

Recent developments of lidars and data analysis methods for AD-Net, and the studies using ADNet are presented. Continuous observation was started in 2001 at three stations using polarizationsensitive Mie-scattering lidars. Currently, lidars, including three multi-wavelength Raman lidars and one high-spectral-resolution lidar, are operated at 20 stations. Recent studies on validation/assimilation of chemical transport models, climatology, and epidemiology of Asian dust are also described.

Petri net modelling of biological networks.

PubMed

Chaouiya, Claudine

2007-07-01

Mathematical modelling is increasingly used to get insights into the functioning of complex biological networks. In this context, Petri nets (PNs) have recently emerged as a promising tool among the various methods employed for the modelling and analysis of molecular networks. PNs come with a series of extensions, which allow different abstraction levels, from purely qualitative to more complex quantitative models. Noteworthily, each of these models preserves the underlying graph, which depicts the interactions between the biological components. This article intends to present the basics of the approach and to foster the potential role PNs could play in the development of the computational systems biology.

The signaling petri net-based simulator: a non-parametric strategy for characterizing the dynamics of cell-specific signaling networks.

PubMed

Ruths, Derek; Muller, Melissa; Tseng, Jen-Te; Nakhleh, Luay; Ram, Prahlad T

2008-02-29

Reconstructing cellular signaling networks and understanding how they work are major endeavors in cell biology. The scale and complexity of these networks, however, render their analysis using experimental biology approaches alone very challenging. As a result, computational methods have been developed and combined with experimental biology approaches, producing powerful tools for the analysis of these networks. These computational methods mostly fall on either end of a spectrum of model parameterization. On one end is a class of structural network analysis methods; these typically use the network connectivity alone to generate hypotheses about global properties. On the other end is a class of dynamic network analysis methods; these use, in addition to the connectivity, kinetic parameters of the biochemical reactions to predict the network's dynamic behavior. These predictions provide detailed insights into the properties that determine aspects of the network's structure and behavior. However, the difficulty of obtaining numerical values of kinetic parameters is widely recognized to limit the applicability of this latter class of methods. Several researchers have observed that the connectivity of a network alone can provide significant insights into its dynamics. Motivated by this fundamental observation, we present the signaling Petri net, a non-parametric model of cellular signaling networks, and the signaling Petri net-based simulator, a Petri net execution strategy for characterizing the dynamics of signal flow through a signaling network using token distribution and sampling. The result is a very fast method, which can analyze large-scale networks, and provide insights into the trends of molecules' activity-levels in response to an external stimulus, based solely on the network's connectivity. We have implemented the signaling Petri net-based simulator in the PathwayOracle toolkit, which is publicly available at http://bioinfo.cs.rice.edu/pathwayoracle. Using

The Signaling Petri Net-Based Simulator: A Non-Parametric Strategy for Characterizing the Dynamics of Cell-Specific Signaling Networks

PubMed Central

Ruths, Derek; Muller, Melissa; Tseng, Jen-Te; Nakhleh, Luay; Ram, Prahlad T.

2008-01-01

Reconstructing cellular signaling networks and understanding how they work are major endeavors in cell biology. The scale and complexity of these networks, however, render their analysis using experimental biology approaches alone very challenging. As a result, computational methods have been developed and combined with experimental biology approaches, producing powerful tools for the analysis of these networks. These computational methods mostly fall on either end of a spectrum of model parameterization. On one end is a class of structural network analysis methods; these typically use the network connectivity alone to generate hypotheses about global properties. On the other end is a class of dynamic network analysis methods; these use, in addition to the connectivity, kinetic parameters of the biochemical reactions to predict the network's dynamic behavior. These predictions provide detailed insights into the properties that determine aspects of the network's structure and behavior. However, the difficulty of obtaining numerical values of kinetic parameters is widely recognized to limit the applicability of this latter class of methods. Several researchers have observed that the connectivity of a network alone can provide significant insights into its dynamics. Motivated by this fundamental observation, we present the signaling Petri net, a non-parametric model of cellular signaling networks, and the signaling Petri net-based simulator, a Petri net execution strategy for characterizing the dynamics of signal flow through a signaling network using token distribution and sampling. The result is a very fast method, which can analyze large-scale networks, and provide insights into the trends of molecules' activity-levels in response to an external stimulus, based solely on the network's connectivity. We have implemented the signaling Petri net-based simulator in the PathwayOracle toolkit, which is publicly available at http://bioinfo.cs.rice.edu/pathwayoracle. Using

SoilNet - A hybrid underground wireless sensor network for near real-time monitoring of hydrological processes

NASA Astrophysics Data System (ADS)

Bogena, H. R.; Huisman, S.; Rosenbaum, U.; Wuethen, A.; Vereecken, H.

2009-04-01

Wireless sensor network technology allows near real-time monitoring of soil properties with a high spatial and temporal resolution for observing hydrological processes in small watersheds. The novel wireless sensor network SoilNet uses the low-cost ZigBee radio network for communication and a hybrid topology with a mixture of underground end devices each wired to several soil sensors and aboveground router devices. The SoilNet sensor network consists of soil water content, salinity and temperature sensors attached to end devices by cables, router devices and a coordinator device. The end devices are buried in the soil and linked wirelessly with nearby aboveground router devices. This ZigBee network design considers channel errors, delays, packet losses, and power and topology constraints. In order to conserve battery power, a reactive routing protocol is used that determines a new route only when it is required. The sensor network is also able to react to external influences, e.g. the occurrence of precipitation. The SoilNet communicator, routing and end devices have been developed by the Forschungszentrum Juelich and will be marketed through external companies. Simultaneously, we have also developed a data management and visualisation system. Recently, a small forest catchment Wüstebach (27 ha) was instrumented with 50 end devices and more than 400 soil sensors in the frame of the TERENO-RUR hydrological observatory. We will present first results of this large sensor network both in terms of spatial-temporal variations in soil water content and the performance of the sensor network (e.g. network stability and power use).

GeoNetGIS: a Geodetic Network Geographical Information System to manage GPS networks in seismic and volcanic areas

NASA Astrophysics Data System (ADS)

Cristofoletti, P.; Esposito, A.; Anzidei, M.

2003-04-01

This paper presents the methodologies and issues involved in the use of GIS techniques to manage geodetic information derived from networks in seismic and volcanic areas. Organization and manipulation of different geodetical, geological and seismic database, give us a new challenge in interpretation of information that has several dimensions, including spatial and temporal variations, also the flexibility and brand range of tools available in GeoNetGIS, make it an attractive platform for earthquake risk assessment. During the last decade the use of geodetic networks based on the Global Positioning System, devoted to geophysical applications, especially for crustal deformation monitoring in seismic and volcanic areas, increased dramatically. The large amount of data provided by these networks, combined with different and independent observations, such as epicentre distribution of recent and historical earthquakes, geological and structural data, photo interpretation of aerial and satellite images, can aid for the detection and parameterization of seismogenic sources. In particular we applied our geodetic oriented GIS to a new GPS network recently set up and surveyed in the Central Apennine region: the CA-GeoNet. GeoNetGIS is designed to analyze in three and four dimensions GPS sources and to improve crustal deformation analysis and interpretation related with tectonic structures and seismicity. It manages many database (DBMS) consisting of different classes, such as Geodesy, Topography, Seismicity, Geology, Geography and Raster Images, administrated according to Thematic Layers. GeoNetGIS represents a powerful research tool allowing to join the analysis of all data layers to integrate the different data base which aid for the identification of the activity of known faults or structures and suggesting the new evidences of active tectonics. A new approach to data integration given by GeoNetGIS capabilities, allow us to create and deliver a wide range of maps, digital

A new concept of the anatomy of the thoracic oesophagus: the meso-oesophagus. Observational study during thoracoscopic esophagectomy.

PubMed

Cuesta, Miguel A; Weijs, Teus J; Bleys, Ronald L A W; van Hillegersberg, Richard; van Berge Henegouwen, Mark I; Gisbertz, Suzanne S; Ruurda, Jelle P; Straatman, Jennifer; Osugi, Harushi; van der Peet, Donald L

2015-09-01

During thoracoscopic oesophageal surgery, we observed not previously described fascia-like structures. Description of similar structures in rectal cancer surgery was of paramount importance in improving the quality of resection. Therefore, we aimed to describe a new comprehensive concept of the surgical anatomy of the thoracic oesophagus with definition of the meso-oesophagus. We retrospectively evaluated 35 consecutive unedited videos of thoracoscopic oesophageal resections for cancer, to determine the surgical anatomy of the oesophageal fascia's vessels and lymphatic drainage. The resulting concept was validated in a prospective study, including 20 patients at three different centres. Additional confirmation was sought by a histologic study of a cadaver's thorax. A thin layer of connective tissue around the infracarinal oesophagus, involving the lymph nodes at the level of the carina, was observed during thoracoscopic esophagectomy in 32 of the 35 patients included in the retrospective study and in 19 of the 20 patients included in the prospective study. A thick fascia-like structure from the upper thoracic aperture to the lower thoracic aperture was visualized in all patients. This fascia is encountered between the descending aorta and left aspect of the infracarinal oesophagus. Above the carina it expands on both sides of the oesophagus to lateral mediastinal structures. This fascia contains oesophageal vessels, lymph vessels and nodes and nerves. The histologic study confirmed these findings. Here we described the concept of the "meso-oesophagus". Applying the description of the meso-oesophagus will create a better understanding of the oesophageal anatomy, leading to more adequate and reproducible surgery.

Qualitatively modelling and analysing genetic regulatory networks: a Petri net approach.

PubMed

Steggles, L Jason; Banks, Richard; Shaw, Oliver; Wipat, Anil

2007-02-01

New developments in post-genomic technology now provide researchers with the data necessary to study regulatory processes in a holistic fashion at multiple levels of biological organization. One of the major challenges for the biologist is to integrate and interpret these vast data resources to gain a greater understanding of the structure and function of the molecular processes that mediate adaptive and cell cycle driven changes in gene expression. In order to achieve this biologists require new tools and techniques to allow pathway related data to be modelled and analysed as network structures, providing valuable insights which can then be validated and investigated in the laboratory. We propose a new technique for constructing and analysing qualitative models of genetic regulatory networks based on the Petri net formalism. We take as our starting point the Boolean network approach of treating genes as binary switches and develop a new Petri net model which uses logic minimization to automate the construction of compact qualitative models. Our approach addresses the shortcomings of Boolean networks by providing access to the wide range of existing Petri net analysis techniques and by using non-determinism to cope with incomplete and inconsistent data. The ideas we present are illustrated by a case study in which the genetic regulatory network controlling sporulation in the bacterium Bacillus subtilis is modelled and analysed. The Petri net model construction tool and the data files for the B. subtilis sporulation case study are available at http://bioinf.ncl.ac.uk/gnapn.

Operational problems of Haniwa net as a form of social capital: interdependence between human networks of physicians and information networks.

PubMed

Maeda, Minoru; Araki, Sanae; Suzuki, Muneou; Umemoto, Katsuhiro; Kai, Yukiko; Araki, Kenji

2012-10-01

In August 2009, Miyazaki Health and Welfare Network (Haniwa Net, hereafter referred to as "the Net"), centrally led by University of Miyazaki Hospital (UMH), adopted a center hospital-based system offering a unilateral linkage that enables the viewing of UMH's medical records through a web-based browser (electronic medical records (EMR)). By the end of December 2010, the network had developed into a system of 79 collaborating physicians from within the prefecture. Beginning in August 2010, physicians in 12 medical institutions were visited and asked to speak freely on the operational issues concerning the Net. Recordings and written accounts were coded using the text analysis software MAXQDA 10 to understand the actual state of operations. Analysis of calculations of Kendall's rank correlation confirmed that the interdependency between human networks and information networks is significant. At the same time, while the negative opinions concerning the functions of the Net were somewhat conspicuous, the results showed a correlation between requests and proposals for operational improvements of the Net, clearly indicating the need for a more user-friendly system and a better viewer.

The “NetBoard”: Network Monitoring Tools Integration for INFN Tier-1 Data Center

NASA Astrophysics Data System (ADS)

De Girolamo, D.; dell'Agnello and, L.; Zani, S.

2012-12-01

The monitoring and alert system is fundamental for the management and the operation of the network in a large data center such as an LHC Tier-1. The network of the INFN Tier-1 at CNAF is a multi-vendor environment: for its management and monitoring several tools have been adopted and different sensors have been developed. In this paper, after an overview on the different aspects to be monitored and the tools used for them (i.e. MRTG, Nagios, Arpwatch, NetFlow, Syslog, etc), we will describe the “NetBoard”, a monitoring toolkit developed at the INFN Tier-1. NetBoard, developed for a multi-vendor network, is able to install and auto-configure all tools needed for its monitoring, either via network devices discovery mechanism or via configuration file or via wizard. In this way, we are also able to activate different types of sensors and Nagios checks according to the equipment vendor specifications. Moreover, when a new device is connected in the LAN, NetBoard can detect where it is plugged. Finally the NetBoard web interface allows to have the overall status of the entire network “at a glance”, both the local and the geographical (including the LHCOPN and the LHCONE) link utilization, health status of network devices (with active alerts) and flow analysis.

Application of deconvolution interferometry with both Hi-net and KiK-net data

NASA Astrophysics Data System (ADS)

Nakata, N.

2013-12-01

Application of deconvolution interferometry to wavefields observed by KiK-net, a strong-motion recording network in Japan, is useful for estimating wave velocities and S-wave splitting in the near surface. Using this technique, for example, Nakata and Snieder (2011, 2012) found changed in velocities caused by Tohoku-Oki earthquake in Japan. At the location of the borehole accelerometer of each KiK-net station, a velocity sensor is also installed as a part of a high-sensitivity seismograph network (Hi-net). I present a technique that uses both Hi-net and KiK-net records for computing deconvolution interferometry. The deconvolved waveform obtained from the combination of Hi-net and KiK-net data is similar to the waveform computed from KiK-net data only, which indicates that one can use Hi-net wavefields for deconvolution interferometry. Because Hi-net records have a high signal-to-noise ratio (S/N) and high dynamic resolution, the S/N and the quality of amplitude and phase of deconvolved waveforms can be improved with Hi-net data. These advantages are especially important for short-time moving-window seismic interferometry and deconvolution interferometry using later coda waves.

Differential C3NET reveals disease networks of direct physical interactions

PubMed Central

2011-01-01

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

Short-Arc Orbit Determination Results and Space Debris Test Observation of the OWL-Net

NASA Astrophysics Data System (ADS)

Choi, J.; Jo, J.; Yim, H.

Korea Astronomy and Space Science Institute had developed the Optical Wide-field patroL-Network (OWL-Net) for maintaining the domestic Low Earth Orbit satellites’ ephemeris and monitoring Geostationary Earth Orbit region. It also can be used to observe space debris. The orbit determination process was planned with batch least square orbit estimator for every week. The optical tracking window is very narrow, several times per week. Sequentialbatch type estimation strategy was attempted for more reliable orbit prediction. We compared the test operation results with Two Line Elements and CPF files to validate the system. This results can be used to estimate the performance of the OWL-Net operations. And also we had observation of the Astro-H debris. We got the dozens of photometric data of the Astro-H debris main part for a few seconds with the chopper system.

The Design and Implementation of Network Teaching Platform Basing on .NET

NASA Astrophysics Data System (ADS)

Yanna, Ren

This paper addresses the problem that students under traditional teaching model have poor operation ability and studies in depth the network teaching platform in domestic colleges and universities, proposing the design concept of network teaching platform of NET + C # + SQL excellent course and designing the overall structure, function module and back-end database of the platform. This paper emphatically expounds the use of MD5 encryption techniques in order to solve data security problems and the assessment of student learning using ADO.NET database access technology as well as the mathematical formula. The example shows that the network teaching platform developed by using WEB application technology has higher safety and availability, and thus improves the students' operation ability.

CHIME-Net, The Connecticut Health Information Network: A Pilot Study

PubMed Central

Reed-Fourquet, LL; Durand, D; Johnson, L; Beaudin, S; Trask, J; DiSilvestro, E; Smith, L; Courtway, P; Pappanikou, J; Bretaigne, R; Pendleton, R; Vogler, E; Lobb, J; Dalal, S; Lynch, JT

1995-01-01

CHIME-Net is a state-wide community health information network project which uses a frame-relay approach to interfacility and internet connectivity. This is a collaborative effort among competitive institutions, which embraces technologies new to the health care industry. The experiences of implementation of the CHIME-Net pilot project are presented as a first milestone for the state-wide effort. PMID:8563347

Development of Network Interface Cards for TRIDAQ systems with the NaNet framework

NASA Astrophysics Data System (ADS)

Ammendola, R.; Biagioni, A.; Cretaro, P.; Di Lorenzo, S.; Fiorini, M.; Frezza, O.; Lamanna, G.; Lo Cicero, F.; Lonardo, A.; Martinelli, M.; Neri, I.; Paolucci, P. S.; Pastorelli, E.; Piandani, R.; Pontisso, L.; Rossetti, D.; Simula, F.; Sozzi, M.; Valente, P.; Vicini, P.

2017-03-01

NaNet is a framework for the development of FPGA-based PCI Express (PCIe) Network Interface Cards (NICs) with real-time data transport architecture that can be effectively employed in TRIDAQ systems. Key features of the architecture are the flexibility in the configuration of the number and kind of the I/O channels, the hardware offloading of the network protocol stack, the stream processing capability, and the zero-copy CPU and GPU Remote Direct Memory Access (RDMA). Three NIC designs have been developed with the NaNet framework: NaNet-1 and NaNet-10 for the CERN NA62 low level trigger and NaNet3 for the KM3NeT-IT underwater neutrino telescope DAQ system. We will focus our description on the NaNet-10 design, as it is the most complete of the three in terms of capabilities and integrated IPs of the framework.

Tool to assess contents of ARM surface meteorology network netCDF files

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

Staudt, A.; Kwan, T.; Tichler, J.

The Atmospheric Radiation Measurement (ARM) Program, supported by the US Department of Energy, is a major program of atmospheric measurement and modeling designed to improve the understanding of processes and properties that affect atmospheric radiation, with a particular focus on the influence of clouds and the role of cloud radiative feedback in the climate system. The ARM Program will use three highly instrumented primary measurement sites. Deployment of instrumentation at the first site, located in the Southern Great Plains of the United States, began in May of 1992. The first phase of deployment at the second site in the Tropicalmore » Western Pacific is scheduled for late in 1995. The third site will be in the North Slope of Alaska and adjacent Arctic Ocean. To meet the scientific objectives of ARM, observations from the ARM sites are combined with data from other sources; these are called external data. Among these external data sets are surface meteorological observations from the Oklahoma Mesonet, a Kansas automated weather network, the Wind Profiler Demonstration Network (WPDN), and the National Weather Service (NWS) surface stations. Before combining these data with the Surface Meteorological Observations Station (SMOS) ARM data, it was necessary to assess the contents and quality of both the ARM and the external data sets. Since these data sets had previously been converted to netCDF format for use by the ARM Science Team, a tool was written to assess the contents of the netCDF files.« less

The development of the Project NetWork administrative records database for policy evaluation.

PubMed

Rupp, K; Driessen, D; Kornfeld, R; Wood, M

1999-01-01

This article describes the development of SSA's administrative records database for the Project NetWork return-to-work experiment targeting persons with disabilities. The article is part of a series of papers on the evaluation of the Project NetWork demonstration. In addition to 8,248 Project NetWork participants randomly assigned to receive case management services and a control group, the simulation identified 138,613 eligible nonparticipants in the demonstration areas. The output data files contain detailed monthly information on Supplemental Security Income (SSI) and Disability Insurance (DI) benefits, annual earnings, and a set of demographic and diagnostic variables. The data allow for the measurement of net outcomes and the analysis of factors affecting participation. The results suggest that it is feasible to simulate complex eligibility rules using administrative records, and create a clean and edited data file for a comprehensive and credible evaluation. The study shows that it is feasible to use administrative records data for selecting control or comparison groups in future demonstration evaluations.

The Design and Realization of Net Testing System on Campus Network

ERIC Educational Resources Information Center

Ren, Zhanying; Liu, Shijie

2005-01-01

According to the requirement of modern teaching theory and technology, based on software engineering, database theory, the technique of net information security and system integration, a net testing system on local network was designed and realized. The system benefits for dividing of testing & teaching and settles the problems of random…

[SOPHO-NET - a research network on psychotherapy for social phobia].

PubMed

Leichsenring, Falk; Salzer, Simone; Beutel, Manfred E; von Consbruch, Katrin; Herpertz, Stephan; Hiller, Wolfgang; Hoyer, Jürgen; Hüsing, Johannes; Irle, Eva; Joraschky, Peter; Konnopka, Alexander; König, Hans-Helmut; de Liz, Therese; Nolting, Björn; Pöhlmann, Karin; Ruhleder, Mirjana; Schauenburg, Henning; Stangier, Ulrich; Strauss, Bernhard; Subic-Wrana, Claudia; Vormfelde, Stefan V; Weniger, Godehard; Willutzki, Ulrike; Wiltink, Jörg; Leibing, Eric

2009-01-01

This paper presents the Social Phobia Psychotherapy Research Network (SOPHO-NET). SOPHO-NET is among the five research networks on psychotherapy funded by "Bundesministerium für Bildung und Forschung". The research program encompasses a coordinated group of studies of social phobia. In the central project (Study A), a multi-center randomized controlled trial, refined models of manualized cognitive-behavioral therapy (CBT) and manualized short-term psychodynamic psychotherapy (STPP) are compared in the treatment of social phobia. A sample of n=512 outpatients will be randomized to either CBT, STPP or wait list. For quality assurance and treatment integrity, a specific project has been established (Project Q). Study A is complemented by four interrelated projects focusing on attachment style (Study B1), cost-effectiveness (Study B2), polymorphisms in the serotonin transporter gene (Study C1) and on structural and functional deviations of hippocampus and amygdala (Study C2). Thus, the SOPHO-NET program allows for a highly interdisciplinary research of psychotherapy in social phobia.

SpecialNet. A National Computer-Based Communications Network.

ERIC Educational Resources Information Center

Morin, Alfred J.

1986-01-01

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

ClueNet: Clustering a temporal network based on topological similarity rather than denseness.

PubMed

Crawford, Joseph; Milenković, Tijana

2018-01-01

Network clustering is a very popular topic in the network science field. Its goal is to divide (partition) the network into groups (clusters or communities) of "topologically related" nodes, where the resulting topology-based clusters are expected to "correlate" well with node label information, i.e., metadata, such as cellular functions of genes/proteins in biological networks, or age or gender of people in social networks. Even for static data, the problem of network clustering is complex. For dynamic data, the problem is even more complex, due to an additional dimension of the data-their temporal (evolving) nature. Since the problem is computationally intractable, heuristic approaches need to be sought. Existing approaches for dynamic network clustering (DNC) have drawbacks. First, they assume that nodes should be in the same cluster if they are densely interconnected within the network. We hypothesize that in some applications, it might be of interest to cluster nodes that are topologically similar to each other instead of or in addition to requiring the nodes to be densely interconnected. Second, they ignore temporal information in their early steps, and when they do consider this information later on, they do so implicitly. We hypothesize that capturing temporal information earlier in the clustering process and doing so explicitly will improve results. We test these two hypotheses via our new approach called ClueNet. We evaluate ClueNet against six existing DNC methods on both social networks capturing evolving interactions between individuals (such as interactions between students in a high school) and biological networks capturing interactions between biomolecules in the cell at different ages. We find that ClueNet is superior in over 83% of all evaluation tests. As more real-world dynamic data are becoming available, DNC and thus ClueNet will only continue to gain importance.

ClueNet: Clustering a temporal network based on topological similarity rather than denseness

PubMed Central

Milenković, Tijana

2018-01-01

Network clustering is a very popular topic in the network science field. Its goal is to divide (partition) the network into groups (clusters or communities) of “topologically related” nodes, where the resulting topology-based clusters are expected to “correlate” well with node label information, i.e., metadata, such as cellular functions of genes/proteins in biological networks, or age or gender of people in social networks. Even for static data, the problem of network clustering is complex. For dynamic data, the problem is even more complex, due to an additional dimension of the data—their temporal (evolving) nature. Since the problem is computationally intractable, heuristic approaches need to be sought. Existing approaches for dynamic network clustering (DNC) have drawbacks. First, they assume that nodes should be in the same cluster if they are densely interconnected within the network. We hypothesize that in some applications, it might be of interest to cluster nodes that are topologically similar to each other instead of or in addition to requiring the nodes to be densely interconnected. Second, they ignore temporal information in their early steps, and when they do consider this information later on, they do so implicitly. We hypothesize that capturing temporal information earlier in the clustering process and doing so explicitly will improve results. We test these two hypotheses via our new approach called ClueNet. We evaluate ClueNet against six existing DNC methods on both social networks capturing evolving interactions between individuals (such as interactions between students in a high school) and biological networks capturing interactions between biomolecules in the cell at different ages. We find that ClueNet is superior in over 83% of all evaluation tests. As more real-world dynamic data are becoming available, DNC and thus ClueNet will only continue to gain importance. PMID:29738568

netPICOmag: from Design to Network Implementation

NASA Astrophysics Data System (ADS)

Schofield, I.; Connors, M.; Russell, C.

2009-05-01

netPICOmag is the successful conclusion of a design effort involving networking based on Rabbit microcontrollers, PIC microcontrollers, and pulsed magnetometer sensors. GPS timing allows both timestamping of data and the precision counting of the number of pulses produced by the sensor heads in one second. Power over Ethernet, use of DHCP, and broadcast of UDP packets mean a very simple local installation, with one wire leading to a relatively small integrated sensor package which is vertically placed in the ground. Although we continue to make improvements, including through investigating new sensor types, we regard the design as mature and well tested. Here we focus on the need for yet denser magnetometer networks, technological applications which become practical using sensitive yet inexpensive magnetometers, and deployment methods for large numbers of sensors. With careful calibration, netPICOmags overlap with research grade magnetometers. Without it, they still sensitively detect magnetic variations and can be used for an education or outreach program. Due to their low cost, such an application allows many students to be directly involved in gathering data that can be very relevant to them personally when they witness auroras.

ShakeNet: a portable wireless sensor network for instrumenting large civil structures

USGS Publications Warehouse

Kohler, Monica D.; Hao, Shuai; Mishra, Nilesh; Govindan, Ramesh; Nigbor, Robert

2015-08-03

We report our findings from a U.S. Geological Survey (USGS) National Earthquake Hazards Reduction Program-funded project to develop and test a wireless, portable, strong-motion network of up to 40 triaxial accelerometers for structural health monitoring. The overall goal of the project was to record ambient vibrations for several days from USGS-instrumented structures. Structural health monitoring has important applications in fields like civil engineering and the study of earthquakes. The emergence of wireless sensor networks provides a promising means to such applications. However, while most wireless sensor networks are still in the experimentation stage, very few take into consideration the realistic earthquake engineering application requirements. To collect comprehensive data for structural health monitoring for civil engineers, high-resolution vibration sensors and sufficient sampling rates should be adopted, which makes it challenging for current wireless sensor network technology in the following ways: processing capabilities, storage limit, and communication bandwidth. The wireless sensor network has to meet expectations set by wired sensor devices prevalent in the structural health monitoring community. For this project, we built and tested an application-realistic, commercially based, portable, wireless sensor network called ShakeNet for instrumentation of large civil structures, especially for buildings, bridges, or dams after earthquakes. Two to three people can deploy ShakeNet sensors within hours after an earthquake to measure the structural response of the building or bridge during aftershocks. ShakeNet involved the development of a new sensing platform (ShakeBox) running a software suite for networking, data collection, and monitoring. Deployments reported here on a tall building and a large dam were real-world tests of ShakeNet operation, and helped to refine both hardware and software. 

KIKI-net: cross-domain convolutional neural networks for reconstructing undersampled magnetic resonance images.

PubMed

Eo, Taejoon; Jun, Yohan; Kim, Taeseong; Jang, Jinseong; Lee, Ho-Joon; Hwang, Dosik

2018-04-06

To demonstrate accurate MR image reconstruction from undersampled k-space data using cross-domain convolutional neural networks (CNNs) METHODS: Cross-domain CNNs consist of 3 components: (1) a deep CNN operating on the k-space (KCNN), (2) a deep CNN operating on an image domain (ICNN), and (3) an interleaved data consistency operations. These components are alternately applied, and each CNN is trained to minimize the loss between the reconstructed and corresponding fully sampled k-spaces. The final reconstructed image is obtained by forward-propagating the undersampled k-space data through the entire network. Performances of K-net (KCNN with inverse Fourier transform), I-net (ICNN with interleaved data consistency), and various combinations of the 2 different networks were tested. The test results indicated that K-net and I-net have different advantages/disadvantages in terms of tissue-structure restoration. Consequently, the combination of K-net and I-net is superior to single-domain CNNs. Three MR data sets, the T 2 fluid-attenuated inversion recovery (T 2 FLAIR) set from the Alzheimer's Disease Neuroimaging Initiative and 2 data sets acquired at our local institute (T 2 FLAIR and T 1 weighted), were used to evaluate the performance of 7 conventional reconstruction algorithms and the proposed cross-domain CNNs, which hereafter is referred to as KIKI-net. KIKI-net outperforms conventional algorithms with mean improvements of 2.29 dB in peak SNR and 0.031 in structure similarity. KIKI-net exhibits superior performance over state-of-the-art conventional algorithms in terms of restoring tissue structures and removing aliasing artifacts. The results demonstrate that KIKI-net is applicable up to a reduction factor of 3 to 4 based on variable-density Cartesian undersampling. © 2018 International Society for Magnetic Resonance in Medicine.

Space Technology 5 Multi-point Observations of Field-aligned Currents: Temporal Variability of Meso-Scale Structures

NASA Technical Reports Server (NTRS)

Le, Guan; Wang, Yongli; Slavin, James A.; Strangeway, Robert J.

2007-01-01

Space Technology 5 (ST5) is a three micro-satellite constellation deployed into a 300 x 4500 km, dawn-dusk, sun-synchronous polar orbit from March 22 to June 21, 2006, for technology validations. In this paper, we present a study of the temporal variability of field-aligned currents using multi-point magnetic field measurements from ST5. The data demonstrate that meso-scale current structures are commonly embedded within large-scale field-aligned current sheets. The meso-scale current structures are very dynamic with highly variable current density and/or polarity in time scales of - 10 min. They exhibit large temporal variations during both quiet and disturbed times in such time scales. On the other hand, the data also shown that the time scales for the currents to be relatively stable are approx. 1 min for meso-scale currents and approx. 10 min for large scale current sheets. These temporal features are obviously associated with dynamic variations of their particle carriers (mainly electrons) as they respond to the variations of the parallel electric field in auroral acceleration region. The characteristic time scales for the temporal variability of meso-scale field-aligned currents are found to be consistent with those of auroral parallel electric field.

PolNet: A Tool to Quantify Network-Level Cell Polarity and Blood Flow in Vascular Remodeling.

PubMed

Bernabeu, Miguel O; Jones, Martin L; Nash, Rupert W; Pezzarossa, Anna; Coveney, Peter V; Gerhardt, Holger; Franco, Claudio A

2018-05-08

In this article, we present PolNet, an open-source software tool for the study of blood flow and cell-level biological activity during vessel morphogenesis. We provide an image acquisition, segmentation, and analysis protocol to quantify endothelial cell polarity in entire in vivo vascular networks. In combination, we use computational fluid dynamics to characterize the hemodynamics of the vascular networks under study. The tool enables, to our knowledge for the first time, a network-level analysis of polarity and flow for individual endothelial cells. To date, PolNet has proven invaluable for the study of endothelial cell polarization and migration during vascular patterning, as demonstrated by two recent publications. Additionally, the tool can be easily extended to correlate blood flow with other experimental observations at the cellular/molecular level. We release the source code of our tool under the Lesser General Public License. Copyright © 2018 Biophysical Society. Published by Elsevier Inc. All rights reserved.

NetCoDer: A Retransmission Mechanism for WSNs Based on Cooperative Relays and Network Coding

PubMed Central

Valle, Odilson T.; Montez, Carlos; Medeiros de Araujo, Gustavo; Vasques, Francisco; Moraes, Ricardo

2016-01-01

Some of the most difficult problems to deal with when using Wireless Sensor Networks (WSNs) are related to the unreliable nature of communication channels. In this context, the use of cooperative diversity techniques and the application of network coding concepts may be promising solutions to improve the communication reliability. In this paper, we propose the NetCoDer scheme to address this problem. Its design is based on merging cooperative diversity techniques and network coding concepts. We evaluate the effectiveness of the NetCoDer scheme through both an experimental setup with real WSN nodes and a simulation assessment, comparing NetCoDer performance against state-of-the-art TDMA-based (Time Division Multiple Access) retransmission techniques: BlockACK, Master/Slave and Redundant TDMA. The obtained results highlight that the proposed NetCoDer scheme clearly improves the network performance when compared with other retransmission techniques. PMID:27258280

BrainNet Viewer: a network visualization tool for human brain connectomics.

PubMed

Xia, Mingrui; Wang, Jinhui; He, Yong

2013-01-01

The human brain is a complex system whose topological organization can be represented using connectomics. Recent studies have shown that human connectomes can be constructed using various neuroimaging technologies and further characterized using sophisticated analytic strategies, such as graph theory. These methods reveal the intriguing topological architectures of human brain networks in healthy populations and explore the changes throughout normal development and aging and under various pathological conditions. However, given the huge complexity of this methodology, toolboxes for graph-based network visualization are still lacking. Here, using MATLAB with a graphical user interface (GUI), we developed a graph-theoretical network visualization toolbox, called BrainNet Viewer, to illustrate human connectomes as ball-and-stick models. Within this toolbox, several combinations of defined files with connectome information can be loaded to display different combinations of brain surface, nodes and edges. In addition, display properties, such as the color and size of network elements or the layout of the figure, can be adjusted within a comprehensive but easy-to-use settings panel. Moreover, BrainNet Viewer draws the brain surface, nodes and edges in sequence and displays brain networks in multiple views, as required by the user. The figure can be manipulated with certain interaction functions to display more detailed information. Furthermore, the figures can be exported as commonly used image file formats or demonstration video for further use. BrainNet Viewer helps researchers to visualize brain networks in an easy, flexible and quick manner, and this software is freely available on the NITRC website (www.nitrc.org/projects/bnv/).

CrosstalkNet: A Visualization Tool for Differential Co-expression Networks and Communities.

PubMed

Manem, Venkata; Adam, George Alexandru; Gruosso, Tina; Gigoux, Mathieu; Bertos, Nicholas; Park, Morag; Haibe-Kains, Benjamin

2018-04-15

Variations in physiological conditions can rewire molecular interactions between biological compartments, which can yield novel insights into gain or loss of interactions specific to perturbations of interest. Networks are a promising tool to elucidate intercellular interactions, yet exploration of these large-scale networks remains a challenge due to their high dimensionality. To retrieve and mine interactions, we developed CrosstalkNet, a user friendly, web-based network visualization tool that provides a statistical framework to infer condition-specific interactions coupled with a community detection algorithm for bipartite graphs to identify significantly dense subnetworks. As a case study, we used CrosstalkNet to mine a set of 54 and 22 gene-expression profiles from breast tumor and normal samples, respectively, with epithelial and stromal compartments extracted via laser microdissection. We show how CrosstalkNet can be used to explore large-scale co-expression networks and to obtain insights into the biological processes that govern cross-talk between different tumor compartments. Significance: This web application enables researchers to mine complex networks and to decipher novel biological processes in tumor epithelial-stroma cross-talk as well as in other studies of intercompartmental interactions. Cancer Res; 78(8); 2140-3. ©2018 AACR . ©2018 American Association for Cancer Research.

CoryneRegNet 4.0 – A reference database for corynebacterial gene regulatory networks

PubMed Central

Baumbach, Jan

2007-01-01

Background Detailed information on DNA-binding transcription factors (the key players in the regulation of gene expression) and on transcriptional regulatory interactions of microorganisms deduced from literature-derived knowledge, computer predictions and global DNA microarray hybridization experiments, has opened the way for the genome-wide analysis of transcriptional regulatory networks. The large-scale reconstruction of these networks allows the in silico analysis of cell behavior in response to changing environmental conditions. We previously published CoryneRegNet, an ontology-based data warehouse of corynebacterial transcription factors and regulatory networks. Initially, it was designed to provide methods for the analysis and visualization of the gene regulatory network of Corynebacterium glutamicum. Results Now we introduce CoryneRegNet release 4.0, which integrates data on the gene regulatory networks of 4 corynebacteria, 2 mycobacteria and the model organism Escherichia coli K12. As the previous versions, CoryneRegNet provides a web-based user interface to access the database content, to allow various queries, and to support the reconstruction, analysis and visualization of regulatory networks at different hierarchical levels. In this article, we present the further improved database content of CoryneRegNet along with novel analysis features. The network visualization feature GraphVis now allows the inter-species comparisons of reconstructed gene regulatory networks and the projection of gene expression levels onto that networks. Therefore, we added stimulon data directly into the database, but also provide Web Service access to the DNA microarray analysis platform EMMA. Additionally, CoryneRegNet now provides a SOAP based Web Service server, which can easily be consumed by other bioinformatics software systems. Stimulons (imported from the database, or uploaded by the user) can be analyzed in the context of known transcriptional regulatory networks to

NetMOD Version 2.0 Mathematical Framework

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

Merchant, Bion J.; Young, Christopher J.; Chael, Eric P.

2015-08-01

NetMOD ( Net work M onitoring for O ptimal D etection) is a Java-based software package for conducting simulation of seismic, hydroacoustic and infrasonic networks. Network simulations have long been used to study network resilience to station outages and to determine where additional stations are needed to reduce monitoring thresholds. NetMOD makes use of geophysical models to determine the source characteristics, signal attenuation along the path between the source and station, and the performance and noise properties of the station. These geophysical models are combined to simulate the relative amplitudes of signal and noise that are observed at each ofmore » the stations. From these signal-to-noise ratios (SNR), the probabilities of signal detection at each station and event detection across the network of stations can be computed given a detection threshold. The purpose of this document is to clearly and comprehensively present the mathematical framework used by NetMOD, the software package developed by Sandia National Laboratories to assess the monitoring capability of ground-based sensor networks. Many of the NetMOD equations used for simulations are inherited from the NetSim network capability assessment package developed in the late 1980s by SAIC (Sereno et al., 1990).« less

NetMOD version 1.0 user's manual

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

Merchant, Bion John

2014-01-01

NetMOD (Network Monitoring for Optimal Detection) is a Java-based software package for conducting simulation of seismic networks. Specifically, NetMOD simulates the detection capabilities of seismic monitoring networks. Network simulations have long been used to study network resilience to station outages and to determine where additional stations are needed to reduce monitoring thresholds. NetMOD makes use of geophysical models to determine the source characteristics, signal attenuation along the path between the source and station, and the performance and noise properties of the station. These geophysical models are combined to simulate the relative amplitudes of signal and noise that are observed atmore » each of the stations. From these signal-to-noise ratios (SNR), the probability of detection can be computed given a detection threshold. This manual describes how to configure and operate NetMOD to perform seismic detection simulations. In addition, NetMOD is distributed with a simulation dataset for the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) International Monitoring System (IMS) seismic network for the purpose of demonstrating NetMOD's capabilities and providing user training. The tutorial sections of this manual use this dataset when describing how to perform the steps involved when running a simulation.« less

Optical Tracking Data Validation and Orbit Estimation for Sparse Observations of Satellites by the OWL-Net.

PubMed

Choi, Jin; Jo, Jung Hyun; Yim, Hong-Suh; Choi, Eun-Jung; Cho, Sungki; Park, Jang-Hyun

2018-06-07

An Optical Wide-field patroL-Network (OWL-Net) has been developed for maintaining Korean low Earth orbit (LEO) satellites' orbital ephemeris. The OWL-Net consists of five optical tracking stations. Brightness signals of reflected sunlight of the targets were detected by a charged coupled device (CCD). A chopper system was adopted for fast astrometric data sampling, maximum 50 Hz, within a short observation time. The astrometric accuracy of the optical observation data was validated with precise orbital ephemeris such as Consolidated Prediction File (CPF) data and precise orbit determination result with onboard Global Positioning System (GPS) data from the target satellite. In the optical observation simulation of the OWL-Net for 2017, an average observation span for a single arc of 11 LEO observation targets was about 5 min, while an average optical observation separation time was 5 h. We estimated the position and velocity with an atmospheric drag coefficient of LEO observation targets using a sequential-batch orbit estimation technique after multi-arc batch orbit estimation. Post-fit residuals for the multi-arc batch orbit estimation and sequential-batch orbit estimation were analyzed for the optical measurements and reference orbit (CPF and GPS data). The post-fit residuals with reference show few tens-of-meters errors for in-track direction for multi-arc batch and sequential-batch orbit estimation results.

MetNetAPI: A flexible method to access and manipulate biological network data from MetNet

PubMed Central

2010-01-01

Background Convenient programmatic access to different biological databases allows automated integration of scientific knowledge. Many databases support a function to download files or data snapshots, or a webservice that offers "live" data. However, the functionality that a database offers cannot be represented in a static data download file, and webservices may consume considerable computational resources from the host server. Results MetNetAPI is a versatile Application Programming Interface (API) to the MetNetDB database. It abstracts, captures and retains operations away from a biological network repository and website. A range of database functions, previously only available online, can be immediately (and independently from the website) applied to a dataset of interest. Data is available in four layers: molecular entities, localized entities (linked to a specific organelle), interactions, and pathways. Navigation between these layers is intuitive (e.g. one can request the molecular entities in a pathway, as well as request in what pathways a specific entity participates). Data retrieval can be customized: Network objects allow the construction of new and integration of existing pathways and interactions, which can be uploaded back to our server. In contrast to webservices, the computational demand on the host server is limited to processing data-related queries only. Conclusions An API provides several advantages to a systems biology software platform. MetNetAPI illustrates an interface with a central repository of data that represents the complex interrelationships of a metabolic and regulatory network. As an alternative to data-dumps and webservices, it allows access to a current and "live" database and exposes analytical functions to application developers. Yet it only requires limited resources on the server-side (thin server/fat client setup). The API is available for Java, Microsoft.NET and R programming environments and offers flexible query and broad

Scaling of water vapor in the meso-gamma (2-20km) and lower meso-beta (20-50km) scales from tall tower time series

NASA Astrophysics Data System (ADS)

Pressel, K. G.; Collins, W.; Desai, A. R.

2011-12-01

Deficiencies in the parameterization of boundary layer clouds in global climate models (GCMs) remains one of the greatest sources of uncertainty in climate change predictions. Many GCM cloud parameterizations, which seek to include some representation of subgrid-scale cloud variability, do so by making assumptions regarding the subgrid-scale spatial probability density function (PDF) of total water content. Properly specifying the form and parameters of the total water PDF is an essential step in the formulation of PDF based cloud parameterizations. In the cloud free boundary layer, the PDF of total water mixing ratio is equivalent to the PDF of water vapor mixing ratio. Understanding the PDF of water vapor mixing ratio in the cloud free atmosphere is a necessary step towards understanding the PDF of water vapor in the cloudy atmosphere. A primary challenge in empirically constraining the PDF of water vapor mixing ratio is a distinct lack of a spatially distributed observational dataset at or near cloud scale. However, at meso-beta (20-50km) and larger scales, there is a wealth of information on the spatial distribution of water vapor contained in the physically retrieved water vapor profiles from the Atmospheric Infrared Sounder onboard NASA`s Aqua satellite. The scaling (scale-invariance) of the observed water vapor field has been suggested as means of using observations at satellite observed (meso-beta) scales to derive information about cloud scale PDFs. However, doing so requires the derivation of a robust climatology of water vapor scaling from in-situ observations across the meso- gamma (2-20km) and meso-beta scales. In this work, we present the results of the scaling of high frequency (10Hz) time series of water vapor mixing ratio as observed from the 447m WLEF tower located near Park Falls, Wisconsin. Observations from a tall tower offer an ideal set of observations with which to investigate scaling at meso-gamma and meso-beta scales requiring only the

CoryneRegNet: an ontology-based data warehouse of corynebacterial transcription factors and regulatory networks.

PubMed

Baumbach, Jan; Brinkrolf, Karina; Czaja, Lisa F; Rahmann, Sven; Tauch, Andreas

2006-02-14

The application of DNA microarray technology in post-genomic analysis of bacterial genome sequences has allowed the generation of huge amounts of data related to regulatory networks. This data along with literature-derived knowledge on regulation of gene expression has opened the way for genome-wide reconstruction of transcriptional regulatory networks. These large-scale reconstructions can be converted into in silico models of bacterial cells that allow a systematic analysis of network behavior in response to changing environmental conditions. CoryneRegNet was designed to facilitate the genome-wide reconstruction of transcriptional regulatory networks of corynebacteria relevant in biotechnology and human medicine. During the import and integration process of data derived from experimental studies or literature knowledge CoryneRegNet generates links to genome annotations, to identified transcription factors and to the corresponding cis-regulatory elements. CoryneRegNet is based on a multi-layered, hierarchical and modular concept of transcriptional regulation and was implemented by using the relational database management system MySQL and an ontology-based data structure. Reconstructed regulatory networks can be visualized by using the yFiles JAVA graph library. As an application example of CoryneRegNet, we have reconstructed the global transcriptional regulation of a cellular module involved in SOS and stress response of corynebacteria. CoryneRegNet is an ontology-based data warehouse that allows a pertinent data management of regulatory interactions along with the genome-scale reconstruction of transcriptional regulatory networks. These models can further be combined with metabolic networks to build integrated models of cellular function including both metabolism and its transcriptional regulation.

NetWall distributed firewall in the use of campus network

NASA Astrophysics Data System (ADS)

He, Junhua; Zhang, Pengshuai

2011-10-01

Internet provides a modern means of education but also non-mainstream consciousness and poor dissemination of information opens the door, network and moral issues have become prominent, poor dissemination of information and network spread rumors and negative effects of new problems, ideological and political education in schools had a huge impact, poses a severe challenge. This paper presents a distributed firewall will NetWall deployed in a campus network solution. The characteristics of the campus network, using technology to filter out bad information on the means of control, of sensitive information related to the record, establish a complete information security management platform for the campus network.

CellNet: network biology applied to stem cell engineering.

PubMed

Cahan, Patrick; Li, Hu; Morris, Samantha A; Lummertz da Rocha, Edroaldo; Daley, George Q; Collins, James J

2014-08-14

Somatic cell reprogramming, directed differentiation of pluripotent stem cells, and direct conversions between differentiated cell lineages represent powerful approaches to engineer cells for research and regenerative medicine. We have developed CellNet, a network biology platform that more accurately assesses the fidelity of cellular engineering than existing methodologies and generates hypotheses for improving cell derivations. Analyzing expression data from 56 published reports, we found that cells derived via directed differentiation more closely resemble their in vivo counterparts than products of direct conversion, as reflected by the establishment of target cell-type gene regulatory networks (GRNs). Furthermore, we discovered that directly converted cells fail to adequately silence expression programs of the starting population and that the establishment of unintended GRNs is common to virtually every cellular engineering paradigm. CellNet provides a platform for quantifying how closely engineered cell populations resemble their target cell type and a rational strategy to guide enhanced cellular engineering. Copyright © 2014 Elsevier Inc. All rights reserved.

CellNet: Network Biology Applied to Stem Cell Engineering

PubMed Central

Cahan, Patrick; Li, Hu; Morris, Samantha A.; da Rocha, Edroaldo Lummertz; Daley, George Q.; Collins, James J.

2014-01-01

SUMMARY Somatic cell reprogramming, directed differentiation of pluripotent stem cells, and direct conversions between differentiated cell lineages represent powerful approaches to engineer cells for research and regenerative medicine. We have developed CellNet, a network biology platform that more accurately assesses the fidelity of cellular engineering than existing methodologies and generates hypotheses for improving cell derivations. Analyzing expression data from 56 published reports, we found that cells derived via directed differentiation more closely resemble their in vivo counterparts than products of direct conversion, as reflected by the establishment of target cell-type gene regulatory networks (GRNs). Furthermore, we discovered that directly converted cells fail to adequately silence expression programs of the starting population, and that the establishment of unintended GRNs is common to virtually every cellular engineering paradigm. CellNet provides a platform for quantifying how closely engineered cell populations resemble their target cell type and a rational strategy to guide enhanced cellular engineering. PMID:25126793

Statistical Model Applied to NetFlow for Network Intrusion Detection

NASA Astrophysics Data System (ADS)

Proto, André; Alexandre, Leandro A.; Batista, Maira L.; Oliveira, Isabela L.; Cansian, Adriano M.

The computers and network services became presence guaranteed in several places. These characteristics resulted in the growth of illicit events and therefore the computers and networks security has become an essential point in any computing environment. Many methodologies were created to identify these events; however, with increasing of users and services on the Internet, many difficulties are found in trying to monitor a large network environment. This paper proposes a methodology for events detection in large-scale networks. The proposal approaches the anomaly detection using the NetFlow protocol, statistical methods and monitoring the environment in a best time for the application.

Squeeze-SegNet: a new fast deep convolutional neural network for semantic segmentation

NASA Astrophysics Data System (ADS)

Nanfack, Geraldin; Elhassouny, Azeddine; Oulad Haj Thami, Rachid

2018-04-01

The recent researches in Deep Convolutional Neural Network have focused their attention on improving accuracy that provide significant advances. However, if they were limited to classification tasks, nowadays with contributions from Scientific Communities who are embarking in this field, they have become very useful in higher level tasks such as object detection and pixel-wise semantic segmentation. Thus, brilliant ideas in the field of semantic segmentation with deep learning have completed the state of the art of accuracy, however this architectures become very difficult to apply in embedded systems as is the case for autonomous driving. We present a new Deep fully Convolutional Neural Network for pixel-wise semantic segmentation which we call Squeeze-SegNet. The architecture is based on Encoder-Decoder style. We use a SqueezeNet-like encoder and a decoder formed by our proposed squeeze-decoder module and upsample layer using downsample indices like in SegNet and we add a deconvolution layer to provide final multi-channel feature map. On datasets like Camvid or City-states, our net gets SegNet-level accuracy with less than 10 times fewer parameters than SegNet.

SoyNet: a database of co-functional networks for soybean Glycine max.

PubMed

Kim, Eiru; Hwang, Sohyun; Lee, Insuk

2017-01-04

Soybean (Glycine max) is a legume crop with substantial economic value, providing a source of oil and protein for humans and livestock. More than 50% of edible oils consumed globally are derived from this crop. Soybean plants are also important for soil fertility, as they fix atmospheric nitrogen by symbiosis with microorganisms. The latest soybean genome annotation (version 2.0) lists 56 044 coding genes, yet their functional contributions to crop traits remain mostly unknown. Co-functional networks have proven useful for identifying genes that are involved in a particular pathway or phenotype with various network algorithms. Here, we present SoyNet (available at www.inetbio.org/soynet), a database of co-functional networks for G. max and a companion web server for network-based functional predictions. SoyNet maps 1 940 284 co-functional links between 40 812 soybean genes (72.8% of the coding genome), which were inferred from 21 distinct types of genomics data including 734 microarrays and 290 RNA-seq samples from soybean. SoyNet provides a new route to functional investigation of the soybean genome, elucidating genes and pathways of agricultural importance. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

CoryneRegNet: An ontology-based data warehouse of corynebacterial transcription factors and regulatory networks

PubMed Central

Baumbach, Jan; Brinkrolf, Karina; Czaja, Lisa F; Rahmann, Sven; Tauch, Andreas

2006-01-01

Background The application of DNA microarray technology in post-genomic analysis of bacterial genome sequences has allowed the generation of huge amounts of data related to regulatory networks. This data along with literature-derived knowledge on regulation of gene expression has opened the way for genome-wide reconstruction of transcriptional regulatory networks. These large-scale reconstructions can be converted into in silico models of bacterial cells that allow a systematic analysis of network behavior in response to changing environmental conditions. Description CoryneRegNet was designed to facilitate the genome-wide reconstruction of transcriptional regulatory networks of corynebacteria relevant in biotechnology and human medicine. During the import and integration process of data derived from experimental studies or literature knowledge CoryneRegNet generates links to genome annotations, to identified transcription factors and to the corresponding cis-regulatory elements. CoryneRegNet is based on a multi-layered, hierarchical and modular concept of transcriptional regulation and was implemented by using the relational database management system MySQL and an ontology-based data structure. Reconstructed regulatory networks can be visualized by using the yFiles JAVA graph library. As an application example of CoryneRegNet, we have reconstructed the global transcriptional regulation of a cellular module involved in SOS and stress response of corynebacteria. Conclusion CoryneRegNet is an ontology-based data warehouse that allows a pertinent data management of regulatory interactions along with the genome-scale reconstruction of transcriptional regulatory networks. These models can further be combined with metabolic networks to build integrated models of cellular function including both metabolism and its transcriptional regulation. PMID:16478536

Method of preparing meso-haloalkylporphyrins

DOEpatents

Wijesekera, Tilak; Lyons, James E.; Ellis, Jr., Paul E.; Bhinde, Manoj V.

1998-01-01

Transition metal complexes of meso-haloalkylporphyrins, wherein the haloalkyl groups contain 2 to 8 carbon atoms have been found to be highly effective catalysts for oxidation of alkanes and for the decomposition of hydroperoxides. Also disclosed is a process for the preparation of meso-halocarbyl-porphyrins which comprises contacting a halocarbyl dipyrromethane with a halocarbyl-substituted aldehyde in the presence of an acid granular solid catalyst. Also disclosed is a process for the preparation of meso-halocarbyl-porphyrins which comprises contacting a halocarbyl dipyrromethane with a halocarbyl-substituted aldehyde in the presence of an acid granular solic catalyst.

Impact of the 2001 Tohoku-oki earthquake to Tokyo Metropolitan area observed by the Metropolitan Seismic Observation network (MeSO-net)

NASA Astrophysics Data System (ADS)

Hirata, N.; Hayashi, H.; Nakagawa, S.; Sakai, S.; Honda, R.; Kasahara, K.; Obara, K.; Aketagawa, T.; Kimura, H.; Sato, H.; Okaya, D. A.

2011-12-01

The March 11, 2011 Tohoku-oki earthquake brought a great impact to the Tokyo metropolitan area in both seismological aspect and seismic risk management although Tokyo is located 340 km from the epicenter. The event generated very strong ground motion even in the metropolitan area and resulted severe requifaction in many places of Kanto district. National and local governments have started to discuss counter measurement for possible seismic risks in the area taking account for what they learned from the Tohoku-oki event which is much larger than ever experienced in Japan Risk mitigation strategy for the next greater earthquake caused by the Philippine Sea plate (PSP) subducting beneath the Tokyo metropolitan area is of major concern because it caused past mega-thrust earthquakes, such as the 1703 Genroku earthquake (M8.0) and the 1923 Kanto earthquake (M7.9). An M7 or greater (M7+) earthquake in this area at present has high potential to produce devastating loss of life and property with even greater global economic repercussions. The Central Disaster Management Council of Japan estimates that an M7+ earthquake will cause 11,000 fatalities and 112 trillion yen (about 1 trillion US$) economic loss. In order to mitigate disaster for greater Tokyo, the Special Project for Earthquake Disaster Mitigation in the Tokyo Metropolitan Area was launched in collaboration with scientists, engineers, and social-scientists in nationwide institutions. We will discuss the main results that are obtained in the respective fields which have been integrated to improve information on the strategy assessment for seismic risk mitigation in the Tokyo metropolitan area; the project has been much improved after the Tohoku event. In order to image seismic structure beneath the Metropolitan Tokyo area we have developed Metropolitan Seismic Observation network (MeSO-net; Hirata et al., 2009). We have installed 296 seismic stations every few km (Kasahara et al., 2011). We conducted seismic

NeMO-Net & Fluid Lensing: The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment Using Fluid Lensing Augmentation of NASA EOS Data

NASA Technical Reports Server (NTRS)

Chirayath, Ved

2018-01-01

We present preliminary results from NASA NeMO-Net, the first neural multi-modal observation and training network for global coral reef assessment. NeMO-Net is an open-source deep convolutional neural network (CNN) and interactive active learning training software in development which will assess the present and past dynamics of coral reef ecosystems. NeMO-Net exploits active learning and data fusion of mm-scale remotely sensed 3D images of coral reefs captured using fluid lensing with the NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as hyperspectral airborne remote sensing data from the ongoing NASA CORAL mission and lower-resolution satellite data to determine coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. Aquatic ecosystems, particularly coral reefs, remain quantitatively misrepresented by low-resolution remote sensing as a result of refractive distortion from ocean waves, optical attenuation, and remoteness. Machine learning classification of coral reefs using FluidCam mm-scale 3D data show that present satellite and airborne remote sensing techniques poorly characterize coral reef percent living cover, morphology type, and species breakdown at the mm, cm, and meter scales. Indeed, current global assessments of coral reef cover and morphology classification based on km-scale satellite data alone can suffer from segmentation errors greater than 40%, capable of change detection only on yearly temporal scales and decameter spatial scales, significantly hindering our understanding of patterns and processes in marine biodiversity at a time when these ecosystems are experiencing unprecedented anthropogenic pressures, ocean acidification, and sea surface temperature rise. NeMO-Net leverages our augmented machine learning algorithm that demonstrates data fusion of regional FluidCam (mm, cm-scale) airborne remote sensing with

Ω-Net (Omega-Net): Fully automatic, multi-view cardiac MR detection, orientation, and segmentation with deep neural networks.

PubMed

Vigneault, Davis M; Xie, Weidi; Ho, Carolyn Y; Bluemke, David A; Noble, J Alison

2018-05-22

Pixelwise segmentation of the left ventricular (LV) myocardium and the four cardiac chambers in 2-D steady state free precession (SSFP) cine sequences is an essential preprocessing step for a wide range of analyses. Variability in contrast, appearance, orientation, and placement of the heart between patients, clinical views, scanners, and protocols makes fully automatic semantic segmentation a notoriously difficult problem. Here, we present Ω-Net (Omega-Net): A novel convolutional neural network (CNN) architecture for simultaneous localization, transformation into a canonical orientation, and semantic segmentation. First, an initial segmentation is performed on the input image; second, the features learned during this initial segmentation are used to predict the parameters needed to transform the input image into a canonical orientation; and third, a final segmentation is performed on the transformed image. In this work, Ω-Nets of varying depths were trained to detect five foreground classes in any of three clinical views (short axis, SA; four-chamber, 4C; two-chamber, 2C), without prior knowledge of the view being segmented. This constitutes a substantially more challenging problem compared with prior work. The architecture was trained using three-fold cross-validation on a cohort of patients with hypertrophic cardiomyopathy (HCM, N=42) and healthy control subjects (N=21). Network performance, as measured by weighted foreground intersection-over-union (IoU), was substantially improved for the best-performing Ω-Net compared with U-Net segmentation without localization or orientation (0.858 vs 0.834). In addition, to be comparable with other works, Ω-Net was retrained from scratch using five-fold cross-validation on the publicly available 2017 MICCAI Automated Cardiac Diagnosis Challenge (ACDC) dataset. The Ω-Net outperformed the state-of-the-art method in segmentation of the LV and RV bloodpools, and performed slightly worse in segmentation of the LV

NetMOD Version 2.0 Parameters

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

Merchant, Bion J.

2015-08-01

NetMOD ( Net work M onitoring for O ptimal D etection) is a Java-based software package for conducting simulation of seismic, hydroacoustic and infrasonic networks. Network simulations have long been used to study network resilience to station outages and to determine where additional stations are needed to reduce monitoring thresholds. NetMOD makes use of geophysical models to determine the source characteristics, signal attenuation along the path between the source and station, and the performance and noise properties of the station. These geophysical models are combined to simulate the relative amplitudes of signal and noise that are observed at each ofmore » the stations. From these signal-to-noise ratios (SNR), the probability of detection can be computed given a detection threshold. This document describes the parameters that are used to configure the NetMOD tool and the input and output parameters that make up the simulation definitions.« less

Validation and deployment of the first Lidar based weather observation network in New York State: The NYS MesoNet Project

NASA Astrophysics Data System (ADS)

Thobois, L.; Freedman, J.; Royer, P.; Brotzge, J.; Joseph, E.

2018-04-01

The number and quality of atmospheric observations used by meteorologists and operational forecasters are increasing year after year, and yet, consistent improvements in forecast skill remains a challenge. While contributing factors involving these challenges have been identified, including the difficulty in accurately establishing initial conditions, improving the observations at regional and local scales is necessary for accurate depiction of the atmospheric boundary layer (below 2km), particularly the wind profile, in high resolution numerical models. Above the uncertainty of weather forecasts, the goal is also to improve the detection of severe and extreme weather events (severe thunderstorms, tornadoes and other mesoscale phenomena) that can adversely affect life, property and commerce, primarily in densely populated urban centers. This paper will describe the New York State Mesonet that is being deployed in the state of New York, USA. It is composed of 126 stations including 17 profiler sites. These sites will acquire continuous upper air observations through the combination of WINDCUBE Lidars and microwave radiometers. These stations will provide temperature, relative humidity & "3D" wind profile measurements through and above the planetary boundary layer (PBL) and will retrieve derived atmospheric quantities such as the PBL height, cloud base, momentum fluxes, and aerosol & cloud optical properties. The different modes and configurations that will be used for the Lidars are discussed. The performances in terms of data availability and wind accuracy and precision are evaluated. Several profiles with specific wind and aerosol features are presented to illustrate the benefits of the use of Coherent Doppler Lidars to monitor accurately the PBL.

MetaNET--a web-accessible interactive platform for biological metabolic network analysis.

PubMed

Narang, Pankaj; Khan, Shawez; Hemrom, Anmol Jaywant; Lynn, Andrew Michael

2014-01-01

Metabolic reactions have been extensively studied and compiled over the last century. These have provided a theoretical base to implement models, simulations of which are used to identify drug targets and optimize metabolic throughput at a systemic level. While tools for the perturbation of metabolic networks are available, their applications are limited and restricted as they require varied dependencies and often a commercial platform for full functionality. We have developed MetaNET, an open source user-friendly platform-independent and web-accessible resource consisting of several pre-defined workflows for metabolic network analysis. MetaNET is a web-accessible platform that incorporates a range of functions which can be combined to produce different simulations related to metabolic networks. These include (i) optimization of an objective function for wild type strain, gene/catalyst/reaction knock-out/knock-down analysis using flux balance analysis. (ii) flux variability analysis (iii) chemical species participation (iv) cycles and extreme paths identification and (v) choke point reaction analysis to facilitate identification of potential drug targets. The platform is built using custom scripts along with the open-source Galaxy workflow and Systems Biology Research Tool as components. Pre-defined workflows are available for common processes, and an exhaustive list of over 50 functions are provided for user defined workflows. MetaNET, available at http://metanet.osdd.net , provides a user-friendly rich interface allowing the analysis of genome-scale metabolic networks under various genetic and environmental conditions. The framework permits the storage of previous results, the ability to repeat analysis and share results with other users over the internet as well as run different tools simultaneously using pre-defined workflows, and user-created custom workflows.

Bacterial-cellulose-derived interconnected meso-microporous carbon nanofiber networks as binder-free electrodes for high-performance supercapacitors

NASA Astrophysics Data System (ADS)

Hao, Xiaodong; Wang, Jie; Ding, Bing; Wang, Ya; Chang, Zhi; Dou, Hui; Zhang, Xiaogang

2017-06-01

Bacterial cellulose (BC), a typical biomass prepared from the microbial fermentation process, has been proved that it can be an ideal platform for design of three-dimensional (3D) multifunctional nanomaterials in energy storage and conversion field. Here we developed a simple and general silica-assisted strategy for fabrication of interconnected 3D meso-microporous carbon nanofiber networks by confine nanospace pyrolysis of sustainable BC, which can be used as binder-free electrodes for high-performance supercapacitors. The synthesized carbon nanofibers exhibited the features of interconnected 3D networks architecture, large surface area (624 m2 g-1), mesopores-dominated hierarchical porosity, and high graphitization degree. The as-prepared electrode (CN-BC) displayed a maximum specific capacitance of 302 F g-1 at a current density of 0.5 A g-1, high-rate capability and good cyclicity in 6 M KOH electrolyte. This work, together with cost-effective preparation strategy to make high-value utilization of cheap biomass, should have significant implications in the green and mass-producible energy storage.

GeNets: a unified web platform for network-based genomic analyses.

PubMed

Li, Taibo; Kim, April; Rosenbluh, Joseph; Horn, Heiko; Greenfeld, Liraz; An, David; Zimmer, Andrew; Liberzon, Arthur; Bistline, Jon; Natoli, Ted; Li, Yang; Tsherniak, Aviad; Narayan, Rajiv; Subramanian, Aravind; Liefeld, Ted; Wong, Bang; Thompson, Dawn; Calvo, Sarah; Carr, Steve; Boehm, Jesse; Jaffe, Jake; Mesirov, Jill; Hacohen, Nir; Regev, Aviv; Lage, Kasper

2018-06-18

Functional genomics networks are widely used to identify unexpected pathway relationships in large genomic datasets. However, it is challenging to compare the signal-to-noise ratios of different networks and to identify the optimal network with which to interpret a particular genetic dataset. We present GeNets, a platform in which users can train a machine-learning model (Quack) to carry out these comparisons and execute, store, and share analyses of genetic and RNA-sequencing datasets.

Forest-Observation-System.net - towards a global in-situ data repository for biomass datasets validation

NASA Astrophysics Data System (ADS)

Shchepashchenko, D.; Chave, J.; Phillips, O. L.; Davies, S. J.; Lewis, S. L.; Perger, C.; Dresel, C.; Fritz, S.; Scipal, K.

2017-12-01

Forest monitoring is high on the scientific and political agenda. Global measurements of forest height, biomass and how they change with time are urgently needed as essential climate and ecosystem variables. The Forest Observation System - FOS (http://forest-observation-system.net/) is an international cooperation to establish a global in-situ forest biomass database to support earth observation and to encourage investment in relevant field-based observations and science. FOS aims to link the Remote Sensing (RS) community with ecologists who measure forest biomass and estimating biodiversity in the field for a common benefit. The benefit of FOS for the RS community is the partnering of the most established teams and networks that manage permanent forest plots globally; to overcome data sharing issues and introduce a standard biomass data flow from tree level measurement to the plot level aggregation served in the most suitable form for the RS community. Ecologists benefit from the FOS with improved access to global biomass information, data standards, gap identification and potential improved funding opportunities to address the known gaps and deficiencies in the data. FOS closely collaborate with the Center for Tropical Forest Science -CTFS-ForestGEO, the ForestPlots.net (incl. RAINFOR, AfriTRON and T-FORCES), AusCover, Tropical managed Forests Observatory and the IIASA network. FOS is an open initiative with other networks and teams most welcome to join. The online database provides open access for both metadata (e.g. who conducted the measurements, where and which parameters) and actual data for a subset of plots where the authors have granted access. A minimum set of database values include: principal investigator and institution, plot coordinates, number of trees, forest type and tree species composition, wood density, canopy height and above ground biomass of trees. Plot size is 0.25 ha or large. The database will be essential for validating and calibrating

CGBayesNets: Conditional Gaussian Bayesian Network Learning and Inference with Mixed Discrete and Continuous Data

PubMed Central

Weiss, Scott T.

2014-01-01

Bayesian Networks (BN) have been a popular predictive modeling formalism in bioinformatics, but their application in modern genomics has been slowed by an inability to cleanly handle domains with mixed discrete and continuous variables. Existing free BN software packages either discretize continuous variables, which can lead to information loss, or do not include inference routines, which makes prediction with the BN impossible. We present CGBayesNets, a BN package focused around prediction of a clinical phenotype from mixed discrete and continuous variables, which fills these gaps. CGBayesNets implements Bayesian likelihood and inference algorithms for the conditional Gaussian Bayesian network (CGBNs) formalism, one appropriate for predicting an outcome of interest from, e.g., multimodal genomic data. We provide four different network learning algorithms, each making a different tradeoff between computational cost and network likelihood. CGBayesNets provides a full suite of functions for model exploration and verification, including cross validation, bootstrapping, and AUC manipulation. We highlight several results obtained previously with CGBayesNets, including predictive models of wood properties from tree genomics, leukemia subtype classification from mixed genomic data, and robust prediction of intensive care unit mortality outcomes from metabolomic profiles. We also provide detailed example analysis on public metabolomic and gene expression datasets. CGBayesNets is implemented in MATLAB and available as MATLAB source code, under an Open Source license and anonymous download at http://www.cgbayesnets.com. PMID:24922310

CGBayesNets: conditional Gaussian Bayesian network learning and inference with mixed discrete and continuous data.

PubMed

McGeachie, Michael J; Chang, Hsun-Hsien; Weiss, Scott T

2014-06-01

Bayesian Networks (BN) have been a popular predictive modeling formalism in bioinformatics, but their application in modern genomics has been slowed by an inability to cleanly handle domains with mixed discrete and continuous variables. Existing free BN software packages either discretize continuous variables, which can lead to information loss, or do not include inference routines, which makes prediction with the BN impossible. We present CGBayesNets, a BN package focused around prediction of a clinical phenotype from mixed discrete and continuous variables, which fills these gaps. CGBayesNets implements Bayesian likelihood and inference algorithms for the conditional Gaussian Bayesian network (CGBNs) formalism, one appropriate for predicting an outcome of interest from, e.g., multimodal genomic data. We provide four different network learning algorithms, each making a different tradeoff between computational cost and network likelihood. CGBayesNets provides a full suite of functions for model exploration and verification, including cross validation, bootstrapping, and AUC manipulation. We highlight several results obtained previously with CGBayesNets, including predictive models of wood properties from tree genomics, leukemia subtype classification from mixed genomic data, and robust prediction of intensive care unit mortality outcomes from metabolomic profiles. We also provide detailed example analysis on public metabolomic and gene expression datasets. CGBayesNets is implemented in MATLAB and available as MATLAB source code, under an Open Source license and anonymous download at http://www.cgbayesnets.com.

ModObs: Atmospheric modelling for wind energy, climate and environment applications: exploring added value from new observation technique. Work in progress within a FP6 Marie Curie Research Training Network

NASA Astrophysics Data System (ADS)

Sempreviva, A. M.

2009-09-01

The EC FP6 Marie Curie Training Network "ModObs” http://www.modobs.windeng.net addresses the improvement of atmospheric boundary layer (ABL) models to investigate the interplay of processes at different temporal and spatial scales, and to explore the added value from new observation techniques. The overall goal is to bring young scientists to work ogether with experienced researchers in developing a better interaction amongst scientific communities of modelers and experimentalists, using a comprehensive approach to "Climate Change”, "Clean Energy assessment” and "Environmental Policies”, issues. This poster describes the work in progress of ten students, funded by the network, under the supervision of a team of scientists within atmospheric physics, engineering and satellite remote sensing and end-users such as companies in the private sector, all with the appropriate expertise to integrate the most advanced research methods and techniques in the following topics. MODELING: GLOBAL-TO-MESO SCALE: Analytical and process oriented numerical models will be used to study the interaction between the atmosphere and the ocean on a regional scale. Initial results indicate an interaction between the intensity of polar lows and the subsurface warm core often present in the Nordic Seas (11). The presence of waves, mainly swell, influence the MABL fluxes and turbulence structure. The regional and global wave effect on the atmosphere will be also studied and quantified (7) MESO-SCALE: Applicability of the planetary boundary layer (PBL) parametrizations in the meso-scale WRF model to marine atmospheric boundary layer (MABL) over the North Sea is investigated. The most suitable existing PBL parametrization will be additionally improved and used for downscaling North Sea past and future climates (2). Application of the meso-scale model (MM5 and WRF) for the wind energy in off-shore and coastal area. Set-up of the meso-scale model, post-processing and verification of the data

NetMOD Version 2.0 User?s Manual.

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

Merchant, Bion J.

2015-10-01

NetMOD ( Net work M onitoring for O ptimal D etection) is a Java-based software package for conducting simulation of seismic, hydracoustic, and infrasonic networks. Specifically, NetMOD simulates the detection capabilities of monitoring networks. Network simulations have long been used to study network resilience to station outages and to determine where additional stations are needed to reduce monitoring thresholds. NetMOD makes use of geophysical models to determine the source characteristics, signal attenuation along the path between the source and station, and the performance and noise properties of the station. These geophysical models are combined to simulate the relative amplitudes ofmore » signal and noise that are observed at each of the stations. From these signal-to-noise ratios (SNR), the probability of detection can be computed given a detection threshold. This manual describes how to configure and operate NetMOD to perform detection simulations. In addition, NetMOD is distributed with simulation datasets for the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) International Monitoring System (IMS) seismic, hydroacoustic, and infrasonic networks for the purpose of demonstrating NetMOD's capabilities and providing user training. The tutorial sections of this manual use this dataset when describing how to perform the steps involved when running a simulation. ACKNOWLEDGEMENTS We would like to thank the reviewers of this document for their contributions.« less

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

NASA Astrophysics Data System (ADS)

Darroch, Louise; Buck, Justin

2017-04-01

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

[Distribution pattern of meso-micro soil fauna in Eucalyptus grandis plantation].

PubMed

Huang, Yumei; Zhang, Jian; Yang, Wanqin

2006-12-01

In this paper, meso-micro soil fauna were extracted and collected by Baermann's and Tullgren' s method, and their distribution pattern in the Eucalyptus grandis plantation of Hongya County, Sichuan Province was studied. A total of 13 550 specimens were collected, belonging to 6 phyla, 13 classes, and 26 orders. Acarina, Nematoda, Collembola were the dominant groups, and Enchytraeidae was the frequent one. The group and individual numbers of meso-micro soil fauna varied with seasons, being the maximum in autumn or winter, fewer in summer, and the minimum in spring. The density of meso-micro soil fauna in soil profile decreased rapidly with increasing soil depth, but a converse distribution was observed from time to time in 5 - 10 cm and 10 - 15 cm soil layers. The meso-micro soil fauna collected by Baermann's and Tullgren's method had a density of 3. 333 x 10(3) - 2. 533 x 10(5) ind x m(-2) and 1.670 x 10(2) - 2.393 x 10(5) ind x m(-2), respectively, and the decreasing rate of the density with the increase of soil depth was higher for those collected by Tullgren's method. The density-group index of meso-micro soil fauna in the E. grandis plantation was the lowest in spring, but the highest in autumn or summer. There were no significant differences in the density of meso-micro soil fauna and in the density-group index between E. grandis plantation and Quercus acutissima secondary forest.

ChemNet: A Transferable and Generalizable Deep Neural Network for Small-Molecule Property Prediction

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

Goh, Garrett B.; Siegel, Charles M.; Vishnu, Abhinav

With access to large datasets, deep neural networks through representation learning have been able to identify patterns from raw data, achieving human-level accuracy in image and speech recognition tasks. However, in chemistry, availability of large standardized and labelled datasets is scarce, and with a multitude of chemical properties of interest, chemical data is inherently small and fragmented. In this work, we explore transfer learning techniques in conjunction with the existing Chemception CNN model, to create a transferable and generalizable deep neural network for small-molecule property prediction. Our latest model, ChemNet learns in a semi-supervised manner from inexpensive labels computed frommore » the ChEMBL database. When fine-tuned to the Tox21, HIV and FreeSolv dataset, which are 3 separate chemical tasks that ChemNet was not originally trained on, we demonstrate that ChemNet exceeds the performance of existing Chemception models, contemporary MLP models that trains on molecular fingerprints, and it matches the performance of the ConvGraph algorithm, the current state-of-the-art. Furthermore, as ChemNet has been pre-trained on a large diverse chemical database, it can be used as a universal “plug-and-play” deep neural network, which accelerates the deployment of deep neural networks for the prediction of novel small-molecule chemical properties.« less

Meso-macro simulation of the woven fabric local deformation in draping

NASA Astrophysics Data System (ADS)

Iwata, Akira; Inoue, Takuya; Naouar, Naim; Boisse, Philippe; Lomov, Stepan V.

2018-05-01

The paper reports results of such combined meso-macro modelling for a plain weave carbon fabric with spread yarns. The boundary conditions for a local meso-model are taken from the macro draping simulation. The fabric geometry is modelled with WiseTex and transferred to the finite element package. A hyperelastic constitutive model for the yarns (Charmetant - Boisse) is used in the meso-modelling; the model parameters are identified and validated in independent tension, shear, compaction and bending tests of the yarn and the fabric. The simulation reproduces local yarn slippage and buckling, for example, the yarn distortion on the 3D mould corner (see the figure). The simulations are compared with the local fabric distortions observed during draping experiments.

First results of registering ionospheric disturbances obtained with SibNet network of GNSS receivers in active space experiments

NASA Astrophysics Data System (ADS)

Ishin, Artem; Perevalova, Natalia; Voeykov, Sergey; Khakhinov, Vitaliy

2017-12-01

Global and regional networks of GNSS receivers have been successfully used for geophysical research for many years; the number of continuous GNSS stations in the world is steadily growing. The article presents the first results of the use of a new regional network of GNSS stations (SibNet) in active space experiments. The Institute of Solar-Terrestrial Physics of Siberian Branch of Russian Academy of Sciences (ISTP SB RAS) has established this network in the South Baikal region. We describe in detail SibNet, characteristics of receivers in use, parameters of antennas and methods of their installation. We also present the general structure of observation site and the plot of coverage of the receiver operating zone at 50-55° latitudes by radio paths. It is shown that the selected location of receivers allows us to detect ionospheric irregularities of various scales. The purpose of the active space experiments was to reveal and record parameters of the ionospheric irregu larities caused by effects from jet streams of Progress cargo spacecraft. The mapping technique enabled us to identify weak, vertically localized ionospheric irregularities and associate them with the Progress spacecraft engine impact. Thus, it has been shown that SibNet deployed in the Southern Baikal region is an effective instrument for monitoring ionospheric conditions.

atBioNet--an integrated network analysis tool for genomics and biomarker discovery.

PubMed

Ding, Yijun; Chen, Minjun; Liu, Zhichao; Ding, Don; Ye, Yanbin; Zhang, Min; Kelly, Reagan; Guo, Li; Su, Zhenqiang; Harris, Stephen C; Qian, Feng; Ge, Weigong; Fang, Hong; Xu, Xiaowei; Tong, Weida

2012-07-20

Large amounts of mammalian protein-protein interaction (PPI) data have been generated and are available for public use. From a systems biology perspective, Proteins/genes interactions encode the key mechanisms distinguishing disease and health, and such mechanisms can be uncovered through network analysis. An effective network analysis tool should integrate different content-specific PPI databases into a comprehensive network format with a user-friendly platform to identify key functional modules/pathways and the underlying mechanisms of disease and toxicity. atBioNet integrates seven publicly available PPI databases into a network-specific knowledge base. Knowledge expansion is achieved by expanding a user supplied proteins/genes list with interactions from its integrated PPI network. The statistically significant functional modules are determined by applying a fast network-clustering algorithm (SCAN: a Structural Clustering Algorithm for Networks). The functional modules can be visualized either separately or together in the context of the whole network. Integration of pathway information enables enrichment analysis and assessment of the biological function of modules. Three case studies are presented using publicly available disease gene signatures as a basis to discover new biomarkers for acute leukemia, systemic lupus erythematosus, and breast cancer. The results demonstrated that atBioNet can not only identify functional modules and pathways related to the studied diseases, but this information can also be used to hypothesize novel biomarkers for future analysis. atBioNet is a free web-based network analysis tool that provides a systematic insight into proteins/genes interactions through examining significant functional modules. The identified functional modules are useful for determining underlying mechanisms of disease and biomarker discovery. It can be accessed at: http://www.fda.gov/ScienceResearch/BioinformaticsTools/ucm285284.htm.

BoolNet--an R package for generation, reconstruction and analysis of Boolean networks.

PubMed

Müssel, Christoph; Hopfensitz, Martin; Kestler, Hans A

2010-05-15

As the study of information processing in living cells moves from individual pathways to complex regulatory networks, mathematical models and simulation become indispensable tools for analyzing the complex behavior of such networks and can provide deep insights into the functioning of cells. The dynamics of gene expression, for example, can be modeled with Boolean networks (BNs). These are mathematical models of low complexity, but have the advantage of being able to capture essential properties of gene-regulatory networks. However, current implementations of BNs only focus on different sub-aspects of this model and do not allow for a seamless integration into existing preprocessing pipelines. BoolNet efficiently integrates methods for synchronous, asynchronous and probabilistic BNs. This includes reconstructing networks from time series, generating random networks, robustness analysis via perturbation, Markov chain simulations, and identification and visualization of attractors. The package BoolNet is freely available from the R project at http://cran.r-project.org/ or http://www.informatik.uni-ulm.de/ni/mitarbeiter/HKestler/boolnet/ under Artistic License 2.0. hans.kestler@uni-ulm.de Supplementary data are available at Bioinformatics online.

KM3NeT

NASA Astrophysics Data System (ADS)

de Jong, M.

2015-07-01

KM3NeT is a large research infrastructure, that will consist of a network of deep-sea neutrino telescopes in the Mediterranean Sea. The main objective of KM3NeT is the discovery and subsequent observation of high-energy neutrino sources in the Universe. A further physics perspective is the measurement of the mass hierarchy of neutrinos. A corresponding study, ORCA, is ongoing within KM3NeT. A cost effective technology for (very) large water Cherenkov detectors has been developed based on a new generation of low price 3-inch photo-multiplier tubes. Following the successful deployment and operation of two prototypes, the construction of the KM3NeT research infrastructure has started. The prospects of the different phases of the implementation of KM3NeT are summarised.

Effect of densifying the GNSS GBAS network on monitoring the troposphere zenith total delay and precipitable water vapour content during severe weather events

NASA Astrophysics Data System (ADS)

Kapłon, Jan; Stankunavicius, Gintautas

2016-04-01

The dense ground based augmentation networks can provide the important information for monitoring the state of neutral atmosphere. The GNSS&METEO research group at Wroclaw University of Environmental and Life Sciences (WUELS) is operating the self-developed near real-time service estimating the troposphere parameters from GNSS data for the area of Poland. The service is operational since December 2012 and it's results calculated from ASG-EUPOS GBAS network (120 stations) data are supporting the EGVAP (http://egvap.dmi.dk) project. At first the zenith troposphere delays (ZTD) were calculated in hourly intervals, but since September 2015 the service was upgraded to include SmartNet GBAS network (Leica Geosystems Polska - 150 stations). The upgrade included as well: increasing the result interval to 30 minutes, upgrade from Bernese GPS Software v. 5.0 to Bernese GNSS Software v. 5.2 and estimation of the ZTD and it's horizontal gradients. Processing includes nowadays 270 stations. The densification of network from 70 km of mean distance between stations to 40 km created the opportunity to investigate on it's impact on resolution of estimated ZTD and integrated water vapour content (IWV) fields during the weather events of high intensity. Increase in density of ZTD measurements allows to define better the meso-scale features within different synoptic systems (e.g. frontal waves, meso-scale convective systems, squall lines etc). These meso-scale structures, as a rule are short living but fast developing and hardly predictable by numerical models. Even so, such limited size systems can produce very hazardous phenomena - like widespread squalls and thunderstorms, tornadoes, heavy rains, snowfalls, hail etc. because of prevalence of Cb clouds with high concentration of IWV. Study deals with two meteorological events: 2015-09-01 with the devastating squalls and rainfall bringing 2M Euro loss of property in northern Poland and 2015-10-12 with the very active front bringing

Strong motions observed by K-NET and KiK-net during the 2016 Kumamoto earthquake sequence

NASA Astrophysics Data System (ADS)

Suzuki, Wataru; Aoi, Shin; Kunugi, Takashi; Kubo, Hisahiko; Morikawa, Nobuyuki; Nakamura, Hiromitsu; Kimura, Takeshi; Fujiwara, Hiroyuki

2017-01-01

The nationwide strong-motion seismograph network of K-NET and KiK-net in Japan successfully recorded the strong ground motions of the 2016 Kumamoto earthquake sequence, which show the several notable characteristics. For the first large earthquake with a JMA magnitude of 6.5 (21:26, April 14, 2016, JST), the large strong motions are concentrated near the epicenter and the strong-motion attenuations are well predicted by the empirical relation for crustal earthquakes with a moment magnitude of 6.1. For the largest earthquake of the sequence with a JMA magnitude of 7.3 (01:25, April 16, 2016, JST), the large peak ground accelerations and velocities extend from the epicentral area to the northeast direction. The attenuation feature of peak ground accelerations generally follows the empirical relation, whereas that for velocities deviates from the empirical relation for stations with the epicentral distance of greater than 200 km, which can be attributed to the large Love wave having a dominant period around 10 s. The large accelerations were observed at stations even in Oita region, more than 70 km northeast from the epicenter. They are attributed to the local induced earthquake in Oita region, whose moment magnitude is estimated to be 5.5 by matching the amplitudes of the corresponding phases with the empirical attenuation relation. The real-time strong-motion observation has a potential for contributing to the mitigation of the ongoing earthquake disasters. We test a methodology to forecast the regions to be exposed to the large shaking in real time, which has been developed based on the fact that the neighboring stations are already shaken, for the largest event of the Kumamoto earthquakes, and demonstrate that it is simple but effective to quickly make warning. We also shows that the interpolation of the strong motions in real time is feasible, which will be utilized for the real-time forecast of ground motions based on the observed shakings.[Figure not available

Economic Development Network (ED>Net): 1995-96 Report to the Governor and the Legislature.

ERIC Educational Resources Information Center

California Community Colleges, Sacramento. Office of the Chancellor.

The Economic Development Network (ED>Net) of the California Community Colleges was designed to advance the state's economic growth and competitiveness by coordinating and facilitating workforce improvement, technology deployment, and business development initiatives. This report reviews outcomes for ED>Net for 1995-96 based on reports…

QML-AiNet: An immune network approach to learning qualitative differential equation models

PubMed Central

Pang, Wei; Coghill, George M.

2015-01-01

In this paper, we explore the application of Opt-AiNet, an immune network approach for search and optimisation problems, to learning qualitative models in the form of qualitative differential equations. The Opt-AiNet algorithm is adapted to qualitative model learning problems, resulting in the proposed system QML-AiNet. The potential of QML-AiNet to address the scalability and multimodal search space issues of qualitative model learning has been investigated. More importantly, to further improve the efficiency of QML-AiNet, we also modify the mutation operator according to the features of discrete qualitative model space. Experimental results show that the performance of QML-AiNet is comparable to QML-CLONALG, a QML system using the clonal selection algorithm (CLONALG). More importantly, QML-AiNet with the modified mutation operator can significantly improve the scalability of QML and is much more efficient than QML-CLONALG. PMID:25648212

QML-AiNet: An immune network approach to learning qualitative differential equation models.

PubMed

Pang, Wei; Coghill, George M

2015-02-01

In this paper, we explore the application of Opt-AiNet, an immune network approach for search and optimisation problems, to learning qualitative models in the form of qualitative differential equations. The Opt-AiNet algorithm is adapted to qualitative model learning problems, resulting in the proposed system QML-AiNet. The potential of QML-AiNet to address the scalability and multimodal search space issues of qualitative model learning has been investigated. More importantly, to further improve the efficiency of QML-AiNet, we also modify the mutation operator according to the features of discrete qualitative model space. Experimental results show that the performance of QML-AiNet is comparable to QML-CLONALG, a QML system using the clonal selection algorithm (CLONALG). More importantly, QML-AiNet with the modified mutation operator can significantly improve the scalability of QML and is much more efficient than QML-CLONALG.

MoNET: media over net gateway processor for next-generation network

NASA Astrophysics Data System (ADS)

Elabd, Hammam; Sundar, Rangarajan; Dedes, John

2001-12-01

MoNETTM (Media over Net) SX000 product family is designed using a scalable voice, video and packet-processing platform to address applications with channel densities from few voice channels to four OC3 per card. This platform is developed for bridging public circuit-switched network to the next generation packet telephony and data network. The platform consists of a DSP farm, RISC processors and interface modules. DSP farm is required to execute voice compression, image compression and line echo cancellation algorithms for large number of voice, video, fax, and modem or data channels. RISC CPUs are used for performing various packetizations based on RTP, UDP/IP and ATM encapsulations. In addition, RISC CPUs also participate in the DSP farm load management and communication with the host and other MoP devices. The MoNETTM S1000 communications device is designed for voice processing and for bridging TDM to ATM and IP packet networks. The S1000 consists of the DSP farm based on Carmel DSP core and 32-bit RISC CPU, along with Ethernet, Utopia, PCI, and TDM interfaces. In this paper, we will describe the VoIP infrastructure, building blocks of the S500, S1000 and S3000 devices, algorithms executed on these device and associated channel densities, detailed DSP architecture, memory architecture, data flow and scheduling.

Neural networks with fuzzy Petri nets for modeling a machining process

NASA Astrophysics Data System (ADS)

Hanna, Moheb M.

1998-03-01

The paper presents an intelligent architecture based a feedforward neural network with fuzzy Petri nets for modeling product quality in a CNC machining center. It discusses how the proposed architecture can be used for modeling, monitoring and control a product quality specification such as surface roughness. The surface roughness represents the output quality specification manufactured by a CNC machining center as a result of a milling process. The neural network approach employed the selected input parameters which defined by the machine operator via the CNC code. The fuzzy Petri nets approach utilized the exact input milling parameters, such as spindle speed, feed rate, tool diameter and coolant (off/on), which can be obtained via the machine or sensors system. An aim of the proposed architecture is to model the demanded quality of surface roughness as high, medium or low.

tf_unet: Generic convolutional neural network U-Net implementation in Tensorflow

NASA Astrophysics Data System (ADS)

Akeret, Joel; Chang, Chihway; Lucchi, Aurelien; Refregier, Alexandre

2016-11-01

tf_unet mitigates radio frequency interference (RFI) signals in radio data using a special type of Convolutional Neural Network, the U-Net, that enables the classification of clean signal and RFI signatures in 2D time-ordered data acquired from a radio telescope. The code is not tied to a specific segmentation and can be used, for example, to detect radio frequency interference (RFI) in radio astronomy or galaxies and stars in widefield imaging data. This U-Net implementation can outperform classical RFI mitigation algorithms.

Simulation of meso-damage of refractory based on cohesion model and molecular dynamics method

NASA Astrophysics Data System (ADS)

Zhao, Jiuling; Shang, Hehao; Zhu, Zhaojun; Zhang, Guoxing; Duan, Leiguang; Sun, Xinya

2018-06-01

In order to describe the meso-damage of the refractories more accurately, and to study of the relationship between the mesostructured of the refractories and the macro-mechanics, this paper takes the magnesia-carbon refractories as the research object and uses the molecular dynamics method to instead the traditional sequential algorithm to establish the meso-particles filling model including small and large particles. Finally, the finite element software-ABAQUS is used to conducts numerical simulation on the meso-damage evolution process of refractory materials. From the results, the process of initiation and propagation of microscopic interface cracks can be observed intuitively, and the macroscopic stress-strain curve of the refractory material is obtained. The results show that the combination of molecular dynamics modeling and the use of Python in the interface to insert the cohesive element numerical simulation, obtaining of more accurate interface parameters through parameter inversion, can be more accurate to observe the interface of the meso-damage evolution process and effective to consider the effect of the mesostructured of the refractory material on its macroscopic mechanical properties.

SANA NetGO: a combinatorial approach to using Gene Ontology (GO) terms to score network alignments.

PubMed

Hayes, Wayne B; Mamano, Nil

2018-04-15

Gene Ontology (GO) terms are frequently used to score alignments between protein-protein interaction (PPI) networks. Methods exist to measure GO similarity between proteins in isolation, but proteins in a network alignment are not isolated: each pairing is dependent on every other via the alignment itself. Existing measures fail to take into account the frequency of GO terms across networks, instead imposing arbitrary rules on when to allow GO terms. Here we develop NetGO, a new measure that naturally weighs infrequent, informative GO terms more heavily than frequent, less informative GO terms, without arbitrary cutoffs, instead downweighting GO terms according to their frequency in the networks being aligned. This is a global measure applicable only to alignments, independent of pairwise GO measures, in the same sense that the edge-based EC or S3 scores are global measures of topological similarity independent of pairwise topological similarities. We demonstrate the superiority of NetGO in alignments of predetermined quality and show that NetGO correlates with alignment quality better than any existing GO-based alignment measures. We also demonstrate that NetGO provides a measure of taxonomic similarity between species, consistent with existing taxonomic measuresa feature not shared with existing GObased network alignment measures. Finally, we re-score alignments produced by almost a dozen aligners from a previous study and show that NetGO does a better job at separating good alignments from bad ones. Available as part of SANA. whayes@uci.edu. Supplementary data are available at Bioinformatics online.

WaterNet:The NASA Water Cycle Solutions Network

NASA Astrophysics Data System (ADS)

Belvedere, D. R.; Houser, P. R.; Pozzi, W.; Imam, B.; Schiffer, R.; Schlosser, C. A.; Gupta, H.; Martinez, G.; Lopez, V.; Vorosmarty, C.; Fekete, B.; Matthews, D.; Lawford, R.; Welty, C.; Seck, A.

2008-12-01

Water is essential to life and directly impacts and constrains society's welfare, progress, and sustainable growth, and is continuously being transformed by climate change, erosion, pollution, and engineering. Projections of the effects of such factors will remain speculative until more effective global prediction systems and applications are implemented. NASA's unique role is to use its view from space to improve water and energy cycle monitoring and prediction, and has taken steps to collaborate and improve interoperability with existing networks and nodes of research organizations, operational agencies, science communities, and private industry. WaterNet is a Solutions Network, devoted to the identification and recommendation of candidate solutions that propose ways in which water-cycle related NASA research results can be skillfully applied by partner agencies, international organizations, state, and local governments. It is designed to improve and optimize the sustained ability of water cycle researchers, stakeholders, organizations and networks to interact, identify, harness, and extend NASA research results to augment Decision Support Tools that address national needs.

QUAL-NET, a high temporal-resolution eutrophication model for large hydrographic networks

NASA Astrophysics Data System (ADS)

Minaudo, Camille; Curie, Florence; Jullian, Yann; Gassama, Nathalie; Moatar, Florentina

2018-04-01

To allow climate change impact assessment of water quality in river systems, the scientific community lacks efficient deterministic models able to simulate hydrological and biogeochemical processes in drainage networks at the regional scale, with high temporal resolution and water temperature explicitly determined. The model QUALity-NETwork (QUAL-NET) was developed and tested on the Middle Loire River Corridor, a sub-catchment of the Loire River in France, prone to eutrophication. Hourly variations computed efficiently by the model helped disentangle the complex interactions existing between hydrological and biological processes across different timescales. Phosphorus (P) availability was the most constraining factor for phytoplankton development in the Loire River, but simulating bacterial dynamics in QUAL-NET surprisingly evidenced large amounts of organic matter recycled within the water column through the microbial loop, which delivered significant fluxes of available P and enhanced phytoplankton growth. This explained why severe blooms still occur in the Loire River despite large P input reductions since 1990. QUAL-NET could be used to study past evolutions or predict future trajectories under climate change and land use scenarios.

KM3NeT

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

Jong, M. de; Leiden Institute of Physics, Leiden University, Leiden; Collaboration: KM3NeT Collaboration

2015-07-15

KM3NeT is a large research infrastructure, that will consist of a network of deep-sea neutrino telescopes in the Mediterranean Sea. The main objective of KM3NeT is the discovery and subsequent observation of high-energy neutrino sources in the Universe. A further physics perspective is the measurement of the mass hierarchy of neutrinos. A corresponding study, ORCA, is ongoing within KM3NeT. A cost effective technology for (very) large water Cherenkov detectors has been developed based on a new generation of low price 3-inch photo-multiplier tubes. Following the successful deployment and operation of two prototypes, the construction of the KM3NeT research infrastructure hasmore » started. The prospects of the different phases of the implementation of KM3NeT are summarised.« less

SoilNet - A Zigbee based soil moisture sensor network

NASA Astrophysics Data System (ADS)

Bogena, H. R.; Weuthen, A.; Rosenbaum, U.; Huisman, J. A.; Vereecken, H.

2007-12-01

Soil moisture plays a key role in partitioning water and energy fluxes, in providing moisture to the atmosphere for precipitation, and controlling the pattern of groundwater recharge. Large-scale soil moisture variability is driven by variation of precipitation and radiation in space and time. At local scales, land cover, soil conditions, and topography act to redistribute soil moisture. Despite the importance of soil moisture, it is not yet measured in an operational way, e.g. for a better prediction of hydrological and surface energy fluxes (e.g. runoff, latent heat) at larger scales and in the framework of the development of early warning systems (e.g. flood forecasting) and the management of irrigation systems. The SoilNet project aims to develop a sensor network for the near real-time monitoring of soil moisture changes at high spatial and temporal resolution on the basis of the new low-cost ZigBee radio network that operates on top of the IEEE 802.15.4 standard. The sensor network consists of soil moisture sensors attached to end devices by cables, router devices and a coordinator device. The end devices are buried in the soil and linked wirelessly with nearby aboveground router devices. This ZigBee wireless sensor network design considers channel errors, delays, packet losses, and power and topology constraints. In order to conserve battery power, a reactive routing protocol is used that determines a new route only when it is required. The sensor network is also able to react to external influences, e.g. such as rainfall occurrences. The SoilNet communicator, routing and end devices have been developed by the Forschungszentrum Juelich and will be marketed through external companies. We will present first results of experiments to verify network stability and the accuracy of the soil moisture sensors. Simultaneously, we have developed a data management and visualisation system. We tested the wireless network on a 100 by 100 meter forest plot equipped with 25

TexNet seismic network performance and reported seismicity in West Texas

NASA Astrophysics Data System (ADS)

Savvaidis, A.; Lomax, A.; Aiken, C.; Young, B.; Huang, D.; Hennings, P.

2017-12-01

In 2015, the Texas State Legislature began funding the Texas Seismological Network (TexNet). Since then, 22 new permanent broadband three-component seismic stations have been added to 17 existing stations operated by various networks [US, N4, IM]. These stations together with 4 auxiliary stations, i.e. long term deployments of 20 sec portable stations, were deployed to provide a baseline of Texas seismicity. As soon as the deployment of the new permanent stations took place in West Texas, TexNet was able to detect and characterize smaller magnitude events than was possible before, i.e. M < 2.5. As a consequence, additional portable stations were installed in the area in order to better map the current seismicity level. During the different stages of station deployment, we monitored the seismic network performance and its ability to detect earthquake activity. We found that a key limitation to the network performance is industrial noise in West Texas. For example, during daytime, phase picking and event detection rates are much lower than during nighttime at noisy sites. Regarding seismicity, the high density portable station deployment close to the earthquake activity minimizes hypocentral location uncertainties. In addition, we examined the effects of different crustal velocity models in the area of study on hypocentral location using the local network first arrivals. Considerable differences in location were obtained, which shows the importance of local networks and/or reliable crustal velocity models for West Texas. Given the levels of seismicity in West Texas, a plan to continuously monitor the study area is under development.

Modularization of biochemical networks based on classification of Petri net t-invariants.

PubMed

Grafahrend-Belau, Eva; Schreiber, Falk; Heiner, Monika; Sackmann, Andrea; Junker, Björn H; Grunwald, Stefanie; Speer, Astrid; Winder, Katja; Koch, Ina

2008-02-08

Structural analysis of biochemical networks is a growing field in bioinformatics and systems biology. The availability of an increasing amount of biological data from molecular biological networks promises a deeper understanding but confronts researchers with the problem of combinatorial explosion. The amount of qualitative network data is growing much faster than the amount of quantitative data, such as enzyme kinetics. In many cases it is even impossible to measure quantitative data because of limitations of experimental methods, or for ethical reasons. Thus, a huge amount of qualitative data, such as interaction data, is available, but it was not sufficiently used for modeling purposes, until now. New approaches have been developed, but the complexity of data often limits the application of many of the methods. Biochemical Petri nets make it possible to explore static and dynamic qualitative system properties. One Petri net approach is model validation based on the computation of the system's invariant properties, focusing on t-invariants. T-invariants correspond to subnetworks, which describe the basic system behavior.With increasing system complexity, the basic behavior can only be expressed by a huge number of t-invariants. According to our validation criteria for biochemical Petri nets, the necessary verification of the biological meaning, by interpreting each subnetwork (t-invariant) manually, is not possible anymore. Thus, an automated, biologically meaningful classification would be helpful in analyzing t-invariants, and supporting the understanding of the basic behavior of the considered biological system. Here, we introduce a new approach to automatically classify t-invariants to cope with network complexity. We apply clustering techniques such as UPGMA, Complete Linkage, Single Linkage, and Neighbor Joining in combination with different distance measures to get biologically meaningful clusters (t-clusters), which can be interpreted as modules. To find

Modularization of biochemical networks based on classification of Petri net t-invariants

PubMed Central

Grafahrend-Belau, Eva; Schreiber, Falk; Heiner, Monika; Sackmann, Andrea; Junker, Björn H; Grunwald, Stefanie; Speer, Astrid; Winder, Katja; Koch, Ina

2008-01-01

Background Structural analysis of biochemical networks is a growing field in bioinformatics and systems biology. The availability of an increasing amount of biological data from molecular biological networks promises a deeper understanding but confronts researchers with the problem of combinatorial explosion. The amount of qualitative network data is growing much faster than the amount of quantitative data, such as enzyme kinetics. In many cases it is even impossible to measure quantitative data because of limitations of experimental methods, or for ethical reasons. Thus, a huge amount of qualitative data, such as interaction data, is available, but it was not sufficiently used for modeling purposes, until now. New approaches have been developed, but the complexity of data often limits the application of many of the methods. Biochemical Petri nets make it possible to explore static and dynamic qualitative system properties. One Petri net approach is model validation based on the computation of the system's invariant properties, focusing on t-invariants. T-invariants correspond to subnetworks, which describe the basic system behavior. With increasing system complexity, the basic behavior can only be expressed by a huge number of t-invariants. According to our validation criteria for biochemical Petri nets, the necessary verification of the biological meaning, by interpreting each subnetwork (t-invariant) manually, is not possible anymore. Thus, an automated, biologically meaningful classification would be helpful in analyzing t-invariants, and supporting the understanding of the basic behavior of the considered biological system. Methods Here, we introduce a new approach to automatically classify t-invariants to cope with network complexity. We apply clustering techniques such as UPGMA, Complete Linkage, Single Linkage, and Neighbor Joining in combination with different distance measures to get biologically meaningful clusters (t-clusters), which can be interpreted

Net field-aligned currents observed by Triad

NASA Technical Reports Server (NTRS)

Sugiura, M.; Potemra, T. A.

1975-01-01

From the Triad magnetometer observation of a step-like level shift in the east-west component of the magnetic field at 800 km altitude, the existence of a net current flowing into or away from the ionosphere in a current layer was inferred. The current direction is toward the ionosphere on the morning side and away from it on the afternoon side. The field aligned currents observed by Triad are considered as being an important element in the electro-dynamical coupling between the distant magnetosphere and the ionosphere. The current density integrated over the thickness of the layer increases with increasing magnetic activity, but the relation between the current density and Kp in individual cases is not a simple linear relation. An extrapolation of the statistical relation to Kp = 0 indicates existence of a sheet current of order 0.1 amp/m even at extremely quiet times. During periods of higher magnetic activity an integrated current of approximately 1 amp/m and average current density of order 0.000001 amp/sq m are observed. The location and the latitudinal width of the field aligned current layer carrying the net current very roughly agree with those of the region of high electron intensities in the trapping boundary.

[Improving Health Care for Patients with Somatoform and Functional Disorders: A Collaborative Stepped Care Network (Sofu-Net)].

PubMed

Shedden-Mora, Meike; Lau, Katharina; Kuby, Amina; Groß, Beatrice; Gladigau, Maria; Fabisch, Alexandra; Löwe, Bernd

2015-07-01

The management of somatoform disorders in primary care is often limited due to low diagnostic accuracy, delayed referral to psychotherapy and overuse of health care. To address these difficulties, this study aimed to establish a collaborative stepped health care network (Sofu-Net). Sofu-Net was established among 41 primary care physicians, 35 psychotherapists and 8 mental health clinics. Baseline assessment in primary care showed elevated psychopathology and deficits in health care among patients with somatoform symptoms. Network partners provided positive evaluations of Sofu-Net. © Georg Thieme Verlag KG Stuttgart · New York.

Saliency U-Net: A regional saliency map-driven hybrid deep learning network for anomaly segmentation

NASA Astrophysics Data System (ADS)

Karargyros, Alex; Syeda-Mahmood, Tanveer

2018-02-01

Deep learning networks are gaining popularity in many medical image analysis tasks due to their generalized ability to automatically extract relevant features from raw images. However, this can make the learning problem unnecessarily harder requiring network architectures of high complexity. In case of anomaly detection, in particular, there is often sufficient regional difference between the anomaly and the surrounding parenchyma that could be easily highlighted through bottom-up saliency operators. In this paper we propose a new hybrid deep learning network using a combination of raw image and such regional maps to more accurately learn the anomalies using simpler network architectures. Specifically, we modify a deep learning network called U-Net using both the raw and pre-segmented images as input to produce joint encoding (contraction) and expansion paths (decoding) in the U-Net. We present results of successfully delineating subdural and epidural hematomas in brain CT imaging and liver hemangioma in abdominal CT images using such network.

Multi-component quantitation of meso/nanostructural surfaces and its application to local chemical compositions of copper meso/nanostructures self-organized on silica

NASA Astrophysics Data System (ADS)

Huang, Chun-Yi; Chang, Hsin-Wei; Chang, Che-Chen

2018-03-01

Knowledge about the chemical compositions of meso/nanomaterials is fundamental to development of their applications in advanced technologies. Auger electron spectroscopy (AES) is an effective analysis method for the characterization of meso/nanomaterial structures. Although a few studies have reported the use of AES for the analysis of the local composition of these structures, none have explored in detail the validity of the meso/nanoanalysis results generated by the AES instrument. This paper addresses the limitations of AES and the corrections necessary to offset them for this otherwise powerful meso/nanoanalysis tool. The results of corrections made to the AES multi-point analysis of high-density copper-based meso/nanostructures provides major insights into their local chemical compositions and technological prospects, which the primitive composition output of the AES instrument failed to provide.

MMPM - Mission implementation of Mars MetNet Precursor

NASA Astrophysics Data System (ADS)

Harri, A.-M.

2009-04-01

We are developing a new kind of planetary exploration mission for Mars - MetNet in situ observation network based on a new semi-hard landing vehicle called the Met-Net Lander (MNL). The key technical aspects and solutions of the mission will be discussed. The eventual scope of the MetNet Mission is to deploy some 20 MNLs on the Martian surface using inflatable descent system structures, which will be supported by observations from the orbit around Mars. Currently we are working on the MetNet Mars Precursor Mission (MMPM) to deploy one MetNet Lander to Mars in the 2009/2011 launch window as a technology and science demonstration mission. The MNL will have a versatile science payload focused on the atmospheric science of Mars. Detailed characterization of the Martian atmospheric circulation patterns, boundary layer phenomena, and climatology cycles, require simultaneous in-situ measurements by a network of observation posts on the Martian surface. The scientific payload of the MetNet Mission encompasses separate instrument packages for the atmospheric entry and descent phase and for the surface operation phase. The MetNet mission concept and key probe technologies have been developed and the critical subsystems have been qualified to meet the Martian environmental and functional conditions. This development effort has been fulfilled in collaboration between the Finnish Meteorological Institute (FMI), the Russian Lavoschkin Association (LA) and the Russian Space Research Institute (IKI) since August 2001. Currently the INTA (Instituto Nacional de Técnica Aeroespacial) from Spain is also participating in the MetNet payload development.

NetFlow Dynamics

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

Corbet Jr., Thomas F; Beyeler, Walter E; Vanwestrienen, Dirk

NetFlow Dynamics is a web-accessible analysis environment for simulating dynamic flows of materials on model networks. Performing a simulation requires both the NetFlow Dynamics application and a network model which is a description of the structure of the nodes and edges of a network including the flow capacity of each edge and the storage capacity of each node, and the sources and sinks of the material flowing on the network. NetFlow Dynamics consists of databases for storing network models, algorithms to calculate flows on networks, and a GIS-based graphical interface for performing simulations and viewing simulation results. Simulated flows aremore » dynamic in the sense that flows on each edge of the network and inventories at each node change with time and can be out of equilibrium with boundary conditions. Any number of network models could be simulated using Net Flow Dynamics. To date, the models simulated have been models of petroleum infrastructure. The main model has been the National Transportation Fuels Model (NTFM), a network of U.S. oil fields, transmission pipelines, rail lines, refineries, tank farms, and distribution terminals. NetFlow Dynamics supports two different flow algorithms, the Gradient Flow algorithm and the Inventory Control algorithm, that were developed specifically for the NetFlow Dynamics application. The intent is to add additional algorithms in the future as needed. The ability to select from multiple algorithms is desirable because a single algorithm never covers all analysis needs. The current algorithms use a demand-driven capacity-constrained formulation which means that the algorithms strive to use all available capacity and stored inventory to meet desired flows to sinks, subject to the capacity constraints of each network component. The current flow algorithms are best suited for problems in which a material flows on a capacity-constrained network representing a supply chain in which the material supplied can be stored

LiteNet: Lightweight Neural Network for Detecting Arrhythmias at Resource-Constrained Mobile Devices.

PubMed

He, Ziyang; Zhang, Xiaoqing; Cao, Yangjie; Liu, Zhi; Zhang, Bo; Wang, Xiaoyan

2018-04-17

By running applications and services closer to the user, edge processing provides many advantages, such as short response time and reduced network traffic. Deep-learning based algorithms provide significantly better performances than traditional algorithms in many fields but demand more resources, such as higher computational power and more memory. Hence, designing deep learning algorithms that are more suitable for resource-constrained mobile devices is vital. In this paper, we build a lightweight neural network, termed LiteNet which uses a deep learning algorithm design to diagnose arrhythmias, as an example to show how we design deep learning schemes for resource-constrained mobile devices. Compare to other deep learning models with an equivalent accuracy, LiteNet has several advantages. It requires less memory, incurs lower computational cost, and is more feasible for deployment on resource-constrained mobile devices. It can be trained faster than other neural network algorithms and requires less communication across different processing units during distributed training. It uses filters of heterogeneous size in a convolutional layer, which contributes to the generation of various feature maps. The algorithm was tested using the MIT-BIH electrocardiogram (ECG) arrhythmia database; the results showed that LiteNet outperforms comparable schemes in diagnosing arrhythmias, and in its feasibility for use at the mobile devices.

LiteNet: Lightweight Neural Network for Detecting Arrhythmias at Resource-Constrained Mobile Devices

PubMed Central

Zhang, Xiaoqing; Cao, Yangjie; Liu, Zhi; Zhang, Bo; Wang, Xiaoyan

2018-01-01

By running applications and services closer to the user, edge processing provides many advantages, such as short response time and reduced network traffic. Deep-learning based algorithms provide significantly better performances than traditional algorithms in many fields but demand more resources, such as higher computational power and more memory. Hence, designing deep learning algorithms that are more suitable for resource-constrained mobile devices is vital. In this paper, we build a lightweight neural network, termed LiteNet which uses a deep learning algorithm design to diagnose arrhythmias, as an example to show how we design deep learning schemes for resource-constrained mobile devices. Compare to other deep learning models with an equivalent accuracy, LiteNet has several advantages. It requires less memory, incurs lower computational cost, and is more feasible for deployment on resource-constrained mobile devices. It can be trained faster than other neural network algorithms and requires less communication across different processing units during distributed training. It uses filters of heterogeneous size in a convolutional layer, which contributes to the generation of various feature maps. The algorithm was tested using the MIT-BIH electrocardiogram (ECG) arrhythmia database; the results showed that LiteNet outperforms comparable schemes in diagnosing arrhythmias, and in its feasibility for use at the mobile devices. PMID:29673171

Experiences with the ALICE Mesos infrastructure

NASA Astrophysics Data System (ADS)

Berzano, D.; Eulisse, G.; Grigoraş, C.; Napoli, K.

2017-10-01

Apache Mesos is a resource management system for large data centres, initially developed by UC Berkeley, and now maintained under the Apache Foundation umbrella. It is widely used in the industry by companies like Apple, Twitter, and Airbnb and it is known to scale to 10 000s of nodes. Together with other tools of its ecosystem, such as Mesosphere Marathon or Metronome, it provides an end-to-end solution for datacenter operations and a unified way to exploit large distributed systems. We present the experience of the ALICE Experiment Offline & Computing in deploying and using in production the Apache Mesos ecosystem for a variety of tasks on a small 500 cores cluster, using hybrid OpenStack and bare metal resources. We will initially introduce the architecture of our setup and its operation, we will then describe the tasks which are performed by it, including release building and QA, release validation, and simple Monte Carlo production. We will show how we developed Mesos enabled components (called “Mesos Frameworks”) to carry out ALICE specific needs. In particular, we will illustrate our effort to integrate Work Queue, a lightweight batch processing engine developed by University of Notre Dame, which ALICE uses to orchestrate release validation. Finally, we will give an outlook on how to use Mesos as resource manager for DDS, a software deployment system developed by GSI which will be the foundation of the system deployment for ALICE next generation Online-Offline (O2).

Onset of meso-scale turbulence in active nematics

NASA Astrophysics Data System (ADS)

Doostmohammadi, Amin; Shendruk, Tyler N.; Thijssen, Kristian; Yeomans, Julia M.

2017-05-01

Meso-scale turbulence is an innate phenomenon, distinct from inertial turbulence, that spontaneously occurs at low Reynolds number in fluidized biological systems. This spatiotemporal disordered flow radically changes nutrient and molecular transport in living fluids and can strongly affect the collective behaviour in prominent biological processes, including biofilm formation, morphogenesis and cancer invasion. Despite its crucial role in such physiological processes, understanding meso-scale turbulence and any relation to classical inertial turbulence remains obscure. Here we show how the motion of active matter along a micro-channel transitions to meso-scale turbulence through the evolution of locally disordered patches (active puffs) from an ordered vortex-lattice flow state. We demonstrate that the stationary critical exponents of this transition to meso-scale turbulence in a channel coincide with the directed percolation universality class. This finding bridges our understanding of the onset of low-Reynolds-number meso-scale turbulence and traditional scale-invariant turbulence in confinement.

NetCooperate: a network-based tool for inferring host-microbe and microbe-microbe cooperation.

PubMed

Levy, Roie; Carr, Rogan; Kreimer, Anat; Freilich, Shiri; Borenstein, Elhanan

2015-05-17

Host-microbe and microbe-microbe interactions are often governed by the complex exchange of metabolites. Such interactions play a key role in determining the way pathogenic and commensal species impact their host and in the assembly of complex microbial communities. Recently, several studies have demonstrated how such interactions are reflected in the organization of the metabolic networks of the interacting species, and introduced various graph theory-based methods to predict host-microbe and microbe-microbe interactions directly from network topology. Using these methods, such studies have revealed evolutionary and ecological processes that shape species interactions and community assembly, highlighting the potential of this reverse-ecology research paradigm. NetCooperate is a web-based tool and a software package for determining host-microbe and microbe-microbe cooperative potential. It specifically calculates two previously developed and validated metrics for species interaction: the Biosynthetic Support Score which quantifies the ability of a host species to supply the nutritional requirements of a parasitic or a commensal species, and the Metabolic Complementarity Index which quantifies the complementarity of a pair of microbial organisms' niches. NetCooperate takes as input a pair of metabolic networks, and returns the pairwise metrics as well as a list of potential syntrophic metabolic compounds. The Biosynthetic Support Score and Metabolic Complementarity Index provide insight into host-microbe and microbe-microbe metabolic interactions. NetCooperate determines these interaction indices from metabolic network topology, and can be used for small- or large-scale analyses. NetCooperate is provided as both a web-based tool and an open-source Python module; both are freely available online at http://elbo.gs.washington.edu/software_netcooperate.html.

Topological Nodal-Net Semimetal in a Graphene Network Structure

NASA Astrophysics Data System (ADS)

Wang, Jian-Tao; Nie, Simin; Weng, Hongming; Kawazoe, Yoshiyuki; Chen, Changfeng

2018-01-01

Topological semimetals are characterized by the nodal points in their electronic structure near the Fermi level, either discrete or forming a continuous line or ring, which are responsible for exotic properties related to the topology of bulk bands. Here we identify by ab initio calculations a distinct topological semimetal that exhibits nodal nets comprising multiple interconnected nodal lines in bulk and have two coupled drumheadlike flat bands around the Fermi level on its surface. This nodal net semimetal state is proposed to be realized in a graphene network structure that can be constructed by inserting a benzene ring into each C- C bond in the bct-C4 lattice or by a crystalline modification of the (5,5) carbon nanotube. These results expand the realm of nodal manifolds in topological semimetals, offering a new platform for exploring novel physics in these fascinating materials.

IntNetDB v1.0: an integrated protein-protein interaction network database generated by a probabilistic model

PubMed Central

Xia, Kai; Dong, Dong; Han, Jing-Dong J

2006-01-01

Background Although protein-protein interaction (PPI) networks have been explored by various experimental methods, the maps so built are still limited in coverage and accuracy. To further expand the PPI network and to extract more accurate information from existing maps, studies have been carried out to integrate various types of functional relationship data. A frequently updated database of computationally analyzed potential PPIs to provide biological researchers with rapid and easy access to analyze original data as a biological network is still lacking. Results By applying a probabilistic model, we integrated 27 heterogeneous genomic, proteomic and functional annotation datasets to predict PPI networks in human. In addition to previously studied data types, we show that phenotypic distances and genetic interactions can also be integrated to predict PPIs. We further built an easy-to-use, updatable integrated PPI database, the Integrated Network Database (IntNetDB) online, to provide automatic prediction and visualization of PPI network among genes of interest. The networks can be visualized in SVG (Scalable Vector Graphics) format for zooming in or out. IntNetDB also provides a tool to extract topologically highly connected network neighborhoods from a specific network for further exploration and research. Using the MCODE (Molecular Complex Detections) algorithm, 190 such neighborhoods were detected among all the predicted interactions. The predicted PPIs can also be mapped to worm, fly and mouse interologs. Conclusion IntNetDB includes 180,010 predicted protein-protein interactions among 9,901 human proteins and represents a useful resource for the research community. Our study has increased prediction coverage by five-fold. IntNetDB also provides easy-to-use network visualization and analysis tools that allow biological researchers unfamiliar with computational biology to access and analyze data over the internet. The web interface of IntNetDB is freely

NETS

NASA Technical Reports Server (NTRS)

Baffes, Paul T.

1993-01-01

NETS development tool provides environment for simulation and development of neural networks - computer programs that "learn" from experience. Written in ANSI standard C, program allows user to generate C code for implementation of neural network.

Safety analysis of urban arterials at the meso level.

PubMed

Li, Jia; Wang, Xuesong

2017-11-01

Urban arterials form the main structure of street networks. They typically have multiple lanes, high traffic volume, and high crash frequency. Classical crash prediction models investigate the relationship between arterial characteristics and traffic safety by treating road segments and intersections as isolated units. This micro-level analysis does not work when examining urban arterial crashes because signal spacing is typically short for urban arterials, and there are interactions between intersections and road segments that classical models do not accommodate. Signal spacing also has safety effects on both intersections and road segments that classical models cannot fully account for because they allocate crashes separately to intersections and road segments. In addition, classical models do not consider the impact on arterial safety of the immediately surrounding street network pattern. This study proposes a new modeling methodology that will offer an integrated treatment of intersections and road segments by combining signalized intersections and their adjacent road segments into a single unit based on road geometric design characteristics and operational conditions. These are called meso-level units because they offer an analytical approach between micro and macro. The safety effects of signal spacing and street network pattern were estimated for this study based on 118 meso-level units obtained from 21 urban arterials in Shanghai, and were examined using CAR (conditional auto regressive) models that corrected for spatial correlation among the units within individual arterials. Results showed shorter arterial signal spacing was associated with higher total and PDO (property damage only) crashes, while arterials with a greater number of parallel roads were associated with lower total, PDO, and injury crashes. The findings from this study can be used in the traffic safety planning, design, and management of urban arterials. Copyright © 2017 Elsevier Ltd. All

The Design of NetSecLab: A Small Competition-Based Network Security Lab

ERIC Educational Resources Information Center

Lee, C. P.; Uluagac, A. S.; Fairbanks, K. D.; Copeland, J. A.

2011-01-01

This paper describes a competition-style of exercise to teach system and network security and to reinforce themes taught in class. The exercise, called NetSecLab, is conducted on a closed network with student-formed teams, each with their own Linux system to defend and from which to launch attacks. Students are expected to learn how to: 1) install…

Current Status and Future Prospect of K-NET and KiK-net

NASA Astrophysics Data System (ADS)

Aoi, S.; Kunugi, T.; Suzuki, W.; Nakamura, H.; Fujiwara, H.

2014-12-01

During 18 years since the deployment of K-NET following the Kobe earthquake, our attention has mainly focused on rapidity of the data collection and an unfailing and reliable observation. In this presentation, we review three generations of the instruments employed by K-NET and KiK-net from these two points of view.At beginning of the 2000's, we newly developed the second generation instruments (K-NET02, K-NET02A, KiK-net06) to replace the first generation instruments (K-NET95, SMAC-MDK) employed when the networks were constructed in the 1990's. These instruments have an automatic dial-out function. It takes typically 2-5 s to establish communication and a few seconds to send the pre-trigger data. After that, data is available typically within a 1.5 s delay. Not only waveform data but also strong motion indexes such as real-time intensity, PGA, PGV, PGD, and response spectra are continuously sent once a second.After the 2011 Tohoku earthquake, we have developed the third generation instruments (K-NET11, KiK-net11) and have replaced almost half of the all stations country wide. Main improvement of this instrument is more unfailing and reliable observation. Because we have often experienced very large ground motions (e.g. 45 records exceeding gravity), the maximum measureable range was expanded from 2000 gal to 4000 gal for the second generation instrument, and to 8000 gal for the third. For the third generation instrument, in case of power failure, observation (including transmission of data) works for seven days thanks to the backup battery, while for the second generation instruments it works only for one day. By adding an oblique component to the three-component accelerometers, we could automatically distinguish shaking data from noise such as electric pulses which may cause a false alarm in EEW. Implementation to guarantee the continuity of observation under severe conditions such as during the Tohoku earthquake is very important, as well as a highly efficient

Community pharmacist participation in a practice-based research network: a report from the Medication Safety Research Network of Indiana (Rx-SafeNet).

PubMed

Patel, Puja; Hemmeger, Heather; Kozak, Mary Ann; Gernant, Stephanie A; Snyder, Margie E

2015-01-01

To describe the experiences and opinions of pharmacists serving as site coordinators for the Medication Safety Research Network of Indiana (Rx-SafeNet). Retail chain, independent, and hospital/health system outpatient community pharmacies throughout Indiana, with a total of 127 pharmacy members represented by 26 site coordinators. Rx-SafeNet, a statewide practice-based research network (PBRN) formed in 2010 and administered by the Purdue University College of Pharmacy. Barriers and facilitators to participation in available research studies, confidence participating in research, and satisfaction with overall network communication. 22 of 26 site coordinators participated, resulting in an 85% response rate. Most (72.2%) of the respondents had received a doctor of pharmacy degree, and 13.6% had postgraduate year (PGY)1 residency training. The highest reported benefits of PBRN membership were an enhanced relationship with the Purdue University College of Pharmacy (81% agreed or strongly agreed) and enhanced professional development (80% agreed or strongly agreed). Time constraints were identified as the greatest potential barrier to network participation, reported by 62% of respondents. In addition, the majority (59%) of survey respondents identified no prior research experience. Last, respondents' confidence in performing research appeared to increase substantially after becoming network members, with 43% reporting a lack of confidence in engaging in research before joining the network compared with 90% reporting confidence after joining the network. In general, Rx-SafeNet site coordinators appeared to experience increased confidence in research engagement after joining the network. While respondents identified a number of benefits associated with network participation, concerns about potential time constraints remained a key barrier to participation. These findings will assist network leadership in identifying opportunities to positively increase member participation

The new WegenerNet climate station network web portal - A gateway to over 10 years of high-resolution precipitation data

NASA Astrophysics Data System (ADS)

Fuchsberger, Jürgen; Kirchengast, Gottfried; Bichler, Christoph; Kabas, Thomas; Lenz, Gunther; Leuprecht, Armin

2017-04-01

The Feldbach region in southeast Austria, characteristic for experiencing a rich variety of weather and climate patterns, has been selected as the focus area for a pioneering weather and climate observation network at very high resolution: The WegenerNet comprises 153 meteorological stations measuring temperature, humidity, precipitation, and other parameters, in a tightly spaced grid within an area of about 20 km × 15 km centered near the city of Feldbach (46.93°N, 15.90°E). With its stations about every 2 km2, each with 5-min time sampling, the network provides regular measurements since January 2007. Detailed information is available in the recent description by Kirchengast et al. (2014) and via www.wegcenter.at/wegenernet. As a smaller "sister network" of the WegenerNet Feldbach region, the WegenerNet Johnsbachtal consists of eleven meteorological stations (complemented by one hydrographic station at the Johnsbach creek), measuring temperature, humidity, precipitation, radiation, wind, and other parameters in an alpine setting at altitudes ranging from below 700 m to over 2100 m. Data are available partly since 2007, partly since more recent dates and have a temporal resolution of 10 minutes. The networks are set to serve as a long-term monitoring and validation facility for weather and climate research and applications. Uses include validation of nonhydrostatic models operated at 1-km-scale resolution and of statistical downscaling techniques (in particular for precipitation), validation of radar and satellite data, study of orography-climate relationships, and many others. Quality-controlled station time series and gridded field data (spacing 200 m × 200 m) are available in near-real time (data latency less than 1-2 h) for visualization and download via a data portal (www.wegenernet.org). This data portal has been undergoing a complete renewal over the last year, and now serves as a modern gateway to the WegenerNet's more than 10 years of high

E3Net: a system for exploring E3-mediated regulatory networks of cellular functions.

PubMed

Han, Youngwoong; Lee, Hodong; Park, Jong C; Yi, Gwan-Su

2012-04-01

Ubiquitin-protein ligase (E3) is a key enzyme targeting specific substrates in diverse cellular processes for ubiquitination and degradation. The existing findings of substrate specificity of E3 are, however, scattered over a number of resources, making it difficult to study them together with an integrative view. Here we present E3Net, a web-based system that provides a comprehensive collection of available E3-substrate specificities and a systematic framework for the analysis of E3-mediated regulatory networks of diverse cellular functions. Currently, E3Net contains 2201 E3s and 4896 substrates in 427 organisms and 1671 E3-substrate specific relations between 493 E3s and 1277 substrates in 42 organisms, extracted mainly from MEDLINE abstracts and UniProt comments with an automatic text mining method and additional manual inspection and partly from high throughput experiment data and public ubiquitination databases. The significant functions and pathways of the extracted E3-specific substrate groups were identified from a functional enrichment analysis with 12 functional category resources for molecular functions, protein families, protein complexes, pathways, cellular processes, cellular localization, and diseases. E3Net includes interactive analysis and navigation tools that make it possible to build an integrative view of E3-substrate networks and their correlated functions with graphical illustrations and summarized descriptions. As a result, E3Net provides a comprehensive resource of E3s, substrates, and their functional implications summarized from the regulatory network structures of E3-specific substrate groups and their correlated functions. This resource will facilitate further in-depth investigation of ubiquitination-dependent regulatory mechanisms. E3Net is freely available online at http://pnet.kaist.ac.kr/e3net.

Borneo vortex and meso-scale convective rainfall

NASA Astrophysics Data System (ADS)

Koseki, S.; Koh, T.-Y.; Teo, C.-K.

2013-08-01

We have investigated how the Borneo vortex develops over the equatorial South China Sea under cold surge conditions in December during the Asian winter monsoon. Composite analysis using reanalysis and satellite datasets has revealed that absolute vorticity and water vapour are transported by strong cold surges from upstream of the South China Sea to around the equator. Rainfall is correspondingly enhanced over the equatorial South China Sea. A semi-idealized experiment reproduced the Borneo vortex over the equatorial South China Sea during a "perpetual" cold surge. The Borneo vortex is manifested as a meso-α cyclone with a comma-shaped rainband in the northeast sector of the cyclone. Vorticity budget analysis showed that the growth of the meso-α cyclone was achieved mainly by vortex stretching. The comma-shaped rainband consists of clusters of meso-β scale rainfall patches. The warm and wet cyclonic southeasterly flow meets with the cold and dry northeasterly surge forming a confluence front in the northeastern sector of the cyclone. Intense upward motion and heavy rainfall result both due to the low-level convergence and the favourable thermodynamic profile at the confluence front. At both meso-α and meso-β scales, the convergence is ultimately caused by the deviatoric strain in the confluence wind pattern but is much enhanced by nonlinear self-enhancement dynamics.

The Transition Region Explorer: Observing the Multi-Scale Dynamics of Geospace

NASA Astrophysics Data System (ADS)

Donovan, E.

2015-12-01

Meso- and global-scale IT remote sensing is accomplished via satellite imagers and ground-based instruments. On the ground, the approach is arrays providing extensive as possible coverage (the "net") and powerful observatories that drill deep to provide detailed information about small-scale processes (the "drill"). Always, there is a trade between cost, spatial resolution, coverage (extent), number of parameters, and more, such that in general the larger the network the sparser the coverage. Where are we now? There are important gaps. With THEMIS-ASI, we see processes that quickly evolve beyond the field of view of one observatory, but involve space/time scales not captured by existing meso- and large-scale arrays. Many forefront questions require observations at heretofore unexplored space and time scales, and comprehensive inter-hemispheric conjugate observations than are presently available. To address this, a new ground-based observing initiative is being developed in Canada. Called TREx, for Transition Region Explorer, this new facility will incorporate dedicated blueline, redline, and Near-Infrared All-Sky Imagers, together with an unprecedented network of ten imaging riometers, with a combined field of view spanning more than three hours of magnetic local time and from equatorward to poleward of typical auroral latitudes (spanning the ionospheric footprint of the "nightside transition region" that separates the highly stretched tail and the inner magnetosphere). The TREx field-of-view is covered by HF radars, and contains a dense network of magnetometers and VLF receivers, as well as other geospace and upper atmospheric remote sensors. Taken together, TREx and these co-located instruments represent a quantum leap forward in terms of imaging, in multiple parameters (precipitation, ionization, convection, and currents), ionospheric dynamics in the above-mentioned scale gap. This represents an exciting new opportunity for studying geospace at the system level

NeMO-Net The Neural Multi-Modal Observation Training Network for Global Coral Reef Assessment

NASA Technical Reports Server (NTRS)

Li, Alan; Chirayath, Ved

2017-01-01

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. Exploiting the fine-scaled features of these datasets, machine learning methods such as MAP, PCA, and SVM can not only accurately classify the living cover and morphology of these reef systems (below 8 error), but are also able to map the spectral space between airborne and satellite imagery, augmenting and improving the classification accuracy of previously low-resolution datasets.We are currently implementing NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive active learning and training software to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. NeMO-Net will be built upon the QGIS platform to ingest UAV, airborne and satellite datasets from various sources and sensor capabilities, and through data-fusion determine the coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. To achieve this, we will exploit virtual data augmentation, the use of semi-supervised learning, and active learning through a tablet platform allowing for users to manually train uncertain or difficult to classify datasets. The project will make use of Pythons extensive libraries for machine learning, as well as extending integration to GPU and

NeMO-Net - The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment

NASA Astrophysics Data System (ADS)

Li, A. S. X.; Chirayath, V.; Segal-Rosenhaimer, M.; Das, K.

2017-12-01

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. Exploiting the fine-scaled features of these datasets, machine learning methods such as MAP, PCA, and SVM can not only accurately classify the living cover and morphology of these reef systems (below 8% error), but are also able to map the spectral space between airborne and satellite imagery, augmenting and improving the classification accuracy of previously low-resolution datasets.We are currently implementing NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive active learning and training software to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. NeMO-Net will be built upon the QGIS platform to ingest UAV, airborne and satellite datasets from various sources and sensor capabilities, and through data-fusion determine the coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. To achieve this, we will exploit virtual data augmentation, the use of semi-supervised learning, and active learning through a tablet platform allowing for users to manually train uncertain or difficult to classify datasets. The project will make use of Python's extensive libraries for machine learning, as well as extending integration to GPU

Correlation Between the "seeing FWHM" of Satellite Optical Observations and Meteorological Data at the OWL-Net Station, Mongolia

NASA Astrophysics Data System (ADS)

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

2016-06-01

The correlation between meteorological data collected at the optical wide-field patrol network (OWL-Net) Station No. 1 and the seeing of satellite optical observation data was analyzed. Meteorological data and satellite optical observation data from June 2014 to November 2015 were analyzed. The analyzed meteorological data were the outdoor air temperature, relative humidity, wind speed, and cloud index data, and the analyzed satellite optical observation data were the seeing full-width at half-maximum (FWHM) data. The annual meteorological pattern for Mongolia was analyzed by collecting meteorological data over four seasons, with data collection beginning after the installation and initial set-up of the OWL-Net Station No. 1 in Mongolia. A comparison of the meteorological data and the seeing of the satellite optical observation data showed that the seeing degrades as the wind strength increases and as the cloud cover decreases. This finding is explained by the bias effect, which is caused by the fact that the number of images taken on the less cloudy days was relatively small. The seeing FWHM showed no clear correlation with either temperature or relative humidity.

Neural network-based estimates of Southern Ocean net community production from in-situ and satellite observation: A methodological study

NASA Astrophysics Data System (ADS)

Chang, C.; Johnson, N. C.; Cassar, N.

2012-12-01

Although the Southern Ocean (SO) net community production (NCP), which is the difference between gross primary production and the community respiration rate, plays an important role in the global carbon cycle, limited in situ measurements prohibit a thorough understanding of the climatology and variability NCP in this region. In order to achieve a more comprehensive characterization of temporal and spatial variability of Southern Ocean NCP, we use a neural network approach based on the self-organizing map (SOM) to reconstruct weekly gridded (1o x 1o) SO NCP maps for the period of 1998-2009. This approach combines in situ measurements of NCP from over 40 research cruises with satellite-derived NCP predictor data, which includes chlorophyll (Chl), particulate organic carbon (POC), photosynthetically available radiation (PAR), sea surface height (SSH), and sea surface temperature (SST), as well as the mixed layer depth (MLD) from a high-resolution ocean general circulation model forced with satellite observed wind. The resulting NCP reconstructions reveal a number of salient features, including low NCP in the subtropics except near land masses, elevated NCP along the subtropical front (STF) around 40oS and especially off the Atlantic coast of the South America between the Río de la Plata and the Falkland Island, and moderate NCP values near Kerguelen Islands and along the Antarctic coast. Peak SO NCP occurs during November - January, as expected, and the climatological NCP field during the growing season closely resembles the climatological POC field. This neural network approach, which reveals complex nonlinear relationships and readily handles missing predictor data, provides a comprehensive view of SO NCP and an opportunity to investigate variability over a period of more than ten years. Convergence of various approaches;

VoxResNet: Deep voxelwise residual networks for brain segmentation from 3D MR images.

PubMed

Chen, Hao; Dou, Qi; Yu, Lequan; Qin, Jing; Heng, Pheng-Ann

2018-04-15

Segmentation of key brain tissues from 3D medical images is of great significance for brain disease diagnosis, progression assessment and monitoring of neurologic conditions. While manual segmentation is time-consuming, laborious, and subjective, automated segmentation is quite challenging due to the complicated anatomical environment of brain and the large variations of brain tissues. We propose a novel voxelwise residual network (VoxResNet) with a set of effective training schemes to cope with this challenging problem. The main merit of residual learning is that it can alleviate the degradation problem when training a deep network so that the performance gains achieved by increasing the network depth can be fully leveraged. With this technique, our VoxResNet is built with 25 layers, and hence can generate more representative features to deal with the large variations of brain tissues than its rivals using hand-crafted features or shallower networks. In order to effectively train such a deep network with limited training data for brain segmentation, we seamlessly integrate multi-modality and multi-level contextual information into our network, so that the complementary information of different modalities can be harnessed and features of different scales can be exploited. Furthermore, an auto-context version of the VoxResNet is proposed by combining the low-level image appearance features, implicit shape information, and high-level context together for further improving the segmentation performance. Extensive experiments on the well-known benchmark (i.e., MRBrainS) of brain segmentation from 3D magnetic resonance (MR) images corroborated the efficacy of the proposed VoxResNet. Our method achieved the first place in the challenge out of 37 competitors including several state-of-the-art brain segmentation methods. Our method is inherently general and can be readily applied as a powerful tool to many brain-related studies, where accurate segmentation of brain

Borneo Vortex and Meso-scale Convective Rainfall

NASA Astrophysics Data System (ADS)

Koh, T. Y.; Koseki, S.; Teo, C. K.

2014-12-01

We have investigated how the Borneo vortex develops over the equatorial South China Sea under cold surge conditions in December during the Asian winter monsoon. Composite analysis using reanalysis and satellite datasets has revealed that absolute vorticity and water vapour are transported by strong cold surges from upstream of the South China Sea to around the equator. Rainfall is correspondingly enhanced over the equatorial South China Sea. A semi-idealized experiment reproduced the Borneo vortex over the equatorial South China Sea during a perpetual cold surge. The Borneo vortex is manifested as a meso-alpha cyclone with a comma-shaped rainband in the northeast sector of the cyclone. Vorticity budget analysis showed that the growth/maintenance of the meso-alpha cyclone was achieved mainly by the vortex stretching. This vortex stretching is due to the upward motion forced by the latent heat release around the cyclone centre. The comma-shaped rainband consists of clusters of meso-beta scale rainfall cells. The intense rainfall in the comma-head (comma-tail) is generated by the confluence of the warmer and wetter cyclonic easterly flow (cyclonic southeasterly flow) and the cooler and drier northeasterly surge in the northwestern (northeastern) sector of the cyclone. Intense upward motion and heavy rainfall resulted due to the low-level convergence and the favourable thermodynamic profile at the confluence zone. In particular, the convergence in the northwestern sector is responsible for maintenance of the meso-alpha cyclone system. At both meso-alpha and meso-beta scales, the convergence is ultimately caused by the deviatoric strain in the confluence wind pattern but is significantly self-enhanced by the nonlinear dynamics. Reference: Koseki, S., T.-Y. Koh and C.-K. Teo (2014), Atmospheric Chemistry and Physics, 14, 4539-4562, doi:10.5194/acp-14-4539-2014, 2014.

S-net : Construction of large scale seafloor observatory network for tsunamis and earthquakes along the Japan Trench

NASA Astrophysics Data System (ADS)

Mochizuki, M.; Uehira, K.; Kanazawa, T.; Shiomi, K.; Kunugi, T.; Aoi, S.; Matsumoto, T.; Sekiguchi, S.; Yamamoto, N.; Takahashi, N.; Nakamura, T.; Shinohara, M.; Yamada, T.

2017-12-01

NIED has launched the project of constructing a seafloor observatory network for tsunamis and earthquakes after the occurrence of the 2011 Tohoku Earthquake to enhance reliability of early warnings of tsunamis and earthquakes. The observatory network was named "S-net". The S-net project has been financially supported by MEXT.The S-net consists of 150 seafloor observatories which are connected in line with submarine optical cables. The total length of submarine optical cable is about 5,500 km. The S-net covers the focal region of the 2011 Tohoku Earthquake and its vicinity regions. Each observatory equips two units of a high sensitive pressure gauges as a tsunami meter and four sets of three-component seismometers. The S-net is composed of six segment networks. Five of six segment networks had been already installed. Installation of the last segment network covering the outer rise area have been finally finished by the end of FY2016. The outer rise segment has special features like no other five segments of the S-net. Those features are deep water and long distance. Most of 25 observatories on the outer rise segment are located at the depth of deeper than 6,000m WD. Especially, three observatories are set on the seafloor of deeper than about 7.000m WD, and then the pressure gauges capable of being used even at 8,000m WD are equipped on those three observatories. Total length of the submarine cables of the outer rise segment is about two times longer than those of the other segments. The longer the cable system is, the higher voltage supply is needed, and thus the observatories on the outer rise segment have high withstanding voltage characteristics. We employ a dispersion management line of a low loss formed by combining a plurality of optical fibers for the outer rise segment cable, in order to achieve long-distance, high-speed and large-capacity data transmission Installation of the outer rise segment was finished and then full-scale operation of S-net has started

ImNet: a fiber optic network with multistar topology for high-speed data transmission

NASA Astrophysics Data System (ADS)

Vossebuerger, F.; Keizers, Andreas; Soederman, N.; Meyer-Ebrecht, Dietrich

1993-10-01

ImNet is a fiber-optic local area network, which has been developed for high speed image communication in Picture Archiving and Communication Systems (PACS). A comprehensive analysis of image communication requirements in hospitals led to the conclusion that there is a need for networks which are optimized for the transmission of large datafiles. ImNet is optimized for this application in contrast to current-state LANs. ImNet consists of two elements: a link module and a switch module. The point-to-point link module can be up to 4 km by using fiber optic cable. For short distances up to 100 m a cheaper module using shielded twisted pair cable is available. The link module works bi-directionally and handles all protocols up to OSI-Level 3. The data rate per link is up to 140 MBit/s (clock rate 175 MHz). The switch module consists of the control unit and the cross-point-switch array. The array has up to fourteen interfaces for link modules. Up to fourteen data transfers each with a maximal transfer rate of 400 MBit/s can be handled at the same time. Thereby the maximal throughput of a switch module is 5.6 GBit/s. Out of these modules a multi-star network can be built i.e., an arbitrary tree structure of stars. This topology allows multiple transmissions at the same time as long as they do not require identical links. Therefore the overall throughput of ImNet can be a multiple of the datarate per link.

Earth Observations for Early Detection of Agricultural Drought in Countries at Risk: Contributions of the Famine Early Warning Systems Network (FEWS NET) (Invited)

NASA Astrophysics Data System (ADS)

Verdin, J. P.; Rowland, J.; Senay, G. B.; Funk, C. C.; Budde, M. E.; Husak, G. J.; Jayanthi, H.

2013-12-01

The Group on Earth Observations' Global Agricultural Monitoring (GEOGLAM) implementation plan emphasizes the information needs of countries at risk of food insecurity emergencies. Countries in this category are often vulnerable to disruption of agricultural production due to drought, while at the same time they lack well developed networks of in-situ observations to support early drought detection. Consequently, it is vital that Earth observations by satellites supplement those available from surface stations. The USGS, in its role as a FEWS NET implementing partner, has recently developed a number of new applications of satellite observations for this purpose. (1) In partnership with the University of California, Santa Barbara, a 30+ year time series of gridded precipitation estimates (CHIRPS) has been developed by blending NOAA GridSat B1 geostationary thermal infrared imagery with station observations using robust geostatistical methods. The core data set consists of pentadal (5-daily) accumulations from 1981-2013 at 0.05 degree spatial resolution between +/- 50 degrees latitude. Validation has been recently completed, and applications for gridded crop water balance calculations and mapping the Standardized Precipitation Index are in development. (2) Actual evapotranspiration (ETa) estimates using MODIS Land Surface Temperature (LST) data at 1-km have been successfully demonstrated using the operational Simplified Surface Energy Balance model with 8-day composites from the LPDAAC. A new, next-day latency implementation using daily LST swath data from the NASA LANCE server is in development for all the crop growing regions of the world. This ETa processing chain follows in the footsteps of (3) the expedited production of MODIS 250-meter NDVI images every five days at USGS EROS, likewise using LANCE daily swath data as input since 2010. Coverage includes Africa, Central Asia, the Middle East, Central America, and the Caribbean. (4) A surface water point monitoring

Net2Align: An Algorithm For Pairwise Global Alignment of Biological Networks

PubMed Central

Wadhwab, Gulshan; Upadhyayaa, K. C.

2016-01-01

The amount of data on molecular interactions is growing at an enormous pace, whereas the progress of methods for analysing this data is still lacking behind. Particularly, in the area of comparative analysis of biological networks, where one wishes to explore the similarity between two biological networks, this holds a potential problem. In consideration that the functionality primarily runs at the network level, it advocates the need for robust comparison methods. In this paper, we describe Net2Align, an algorithm for pairwise global alignment that can perform node-to-node correspondences as well as edge-to-edge correspondences into consideration. The uniqueness of our algorithm is in the fact that it is also able to detect the type of interaction, which is essential in case of directed graphs. The existing algorithm is only able to identify the common nodes but not the common edges. Another striking feature of the algorithm is that it is able to remove duplicate entries in case of variable datasets being aligned. This is achieved through creation of a local database which helps exclude duplicate links. In a pervasive computational study on gene regulatory network, we establish that our algorithm surpasses its counterparts in its results. Net2Align has been implemented in Java 7 and the source code is available as supplementary files. PMID:28356678

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

GeneNetWeaver: in silico benchmark generation and performance profiling of network inference methods.

PubMed

Schaffter, Thomas; Marbach, Daniel; Floreano, Dario

2011-08-15

Over the last decade, numerous methods have been developed for inference of regulatory networks from gene expression data. However, accurate and systematic evaluation of these methods is hampered by the difficulty of constructing adequate benchmarks and the lack of tools for a differentiated analysis of network predictions on such benchmarks. Here, we describe a novel and comprehensive method for in silico benchmark generation and performance profiling of network inference methods available to the community as an open-source software called GeneNetWeaver (GNW). In addition to the generation of detailed dynamical models of gene regulatory networks to be used as benchmarks, GNW provides a network motif analysis that reveals systematic prediction errors, thereby indicating potential ways of improving inference methods. The accuracy of network inference methods is evaluated using standard metrics such as precision-recall and receiver operating characteristic curves. We show how GNW can be used to assess the performance and identify the strengths and weaknesses of six inference methods. Furthermore, we used GNW to provide the international Dialogue for Reverse Engineering Assessments and Methods (DREAM) competition with three network inference challenges (DREAM3, DREAM4 and DREAM5). GNW is available at http://gnw.sourceforge.net along with its Java source code, user manual and supporting data. Supplementary data are available at Bioinformatics online. dario.floreano@epfl.ch.

Changing Community Health Behaviors with a Health Promotion Computer Network: Preliminary Findings from Stanford Health-Net

PubMed Central

Robinson, Thomas N.; Walters, Paul A.

1987-01-01

Computer-based health education has been employed in many settings. However, data on resultant behavior change are lacking. A randomized, controlled, prospective study was performed to test the efficacy of Stanford Health-Net in changing community health behaviors. Graduate and undergraduate students (N=1003) were randomly assigned to treatment and control conditions. The treatment group received access to Health-Net, a health promotion computer network emphasizing specific self-care and preventive strategies. Over a four month intervention period, 26% of the treatment group used Health-Net an average of 6.4 times each (range 1 to 97). Users rated Health-Net favorably. The mean number of ambulatory medical visits decreesed 22.5% more in the treatment group than in the control group (P<.05), while hospitalizations did not differ significantly between groups. In addition, perceived self-efficacy for preventing the acquisition of a STD and herpes increased 577% (P<.05) and 261% (P<.01) more, respectively, in the treatment group than in the control group. These findings suggest that access to Stanford Health-Net can result in significant health behavior change. The advantages of the network approach make it a potential model for other communities.

NetCoffee: a fast and accurate global alignment approach to identify functionally conserved proteins in multiple networks.

PubMed

Hu, Jialu; Kehr, Birte; Reinert, Knut

2014-02-15

Owing to recent advancements in high-throughput technologies, protein-protein interaction networks of more and more species become available in public databases. The question of how to identify functionally conserved proteins across species attracts a lot of attention in computational biology. Network alignments provide a systematic way to solve this problem. However, most existing alignment tools encounter limitations in tackling this problem. Therefore, the demand for faster and more efficient alignment tools is growing. We present a fast and accurate algorithm, NetCoffee, which allows to find a global alignment of multiple protein-protein interaction networks. NetCoffee searches for a global alignment by maximizing a target function using simulated annealing on a set of weighted bipartite graphs that are constructed using a triplet approach similar to T-Coffee. To assess its performance, NetCoffee was applied to four real datasets. Our results suggest that NetCoffee remedies several limitations of previous algorithms, outperforms all existing alignment tools in terms of speed and nevertheless identifies biologically meaningful alignments. The source code and data are freely available for download under the GNU GPL v3 license at https://code.google.com/p/netcoffee/.

Eddy covariance flux measurements of net ecosystem carbon dioxide exchange from a lowland peatland flux tower network in England and Wales

NASA Astrophysics Data System (ADS)

Morrison, Ross; Balzter, Heiko; Burden, Annette; Callaghan, Nathan; Cumming, Alenander; Dixon, Simon; Evans, Jonathan; Kaduk, Joerg; Page, Susan; Pan, Gong; Rayment, Mark; Ridley, Luke; Rylett, Daniel; Worrall, Fred; Evans, Christopher

2016-04-01

Peatlands store disproportionately large amounts of soil carbon relative to other terrestrial ecosystems. Over recent decades, the large amount of carbon stored as peat has proved vulnerable to a range of land use pressures as well as the increasing impacts of climate change. In temperate Europe and elsewhere, large tracts of lowland peatland have been drained and converted to agricultural land use. Such changes have resulted in widespread losses of lowland peatland habitat, land subsidence across extensive areas and the transfer of historically accumulated soil carbon to the atmosphere as carbon dioxide (CO2). More recently, there has been growth in activities aiming to reduce these impacts through improved land management and peatland restoration. Despite a long history of productive land use and management, the magnitude and controls on greenhouse gas emissions from lowland peatland environments remain poorly quantified. Here, results of surface-atmosphere measurements of net ecosystem CO2 exchange (NEE) from a network of seven eddy covariance (EC) flux towers located at a range of lowland peatland ecosystems across the United Kingdom (UK) are presented. This spatially-dense peatland flux tower network forms part of a wider observation programme aiming to quantify carbon, water and greenhouse gas balances for lowland peatlands across the UK. EC measurements totalling over seventeen site years were obtained at sites exhibiting large differences in vegetation cover, hydrological functioning and land management. The sites in the network show remarkable spatial and temporal variability in NEE. Across sites, annual NEE ranged from a net sink of -194 ±38 g CO2-C m-2 yr-1 to a net source of 784±70 g CO2-C m-2 yr-1. The results suggest that semi-natural sites remain net sinks for atmospheric CO2. Sites that are drained for intensive agricultural production range from a small net sink to the largest observed source for atmospheric CO2 within the flux tower network

Reconstructing the regulatory network controlling commitment and sporulation in Physarum polycephalum based on hierarchical Petri Net modelling and simulation.

PubMed

Marwan, Wolfgang; Sujatha, Arumugam; Starostzik, Christine

2005-10-21

We reconstruct the regulatory network controlling commitment and sporulation of Physarum polycephalum from experimental results using a hierarchical Petri Net-based modelling and simulation framework. The stochastic Petri Net consistently describes the structure and simulates the dynamics of the molecular network as analysed by genetic, biochemical and physiological experiments within a single coherent model. The Petri Net then is extended to simulate time-resolved somatic complementation experiments performed by mixing the cytoplasms of mutants altered in the sporulation response, to systematically explore the network structure and to probe its dynamics. This reverse engineering approach presumably can be employed to explore other molecular or genetic signalling systems where the activity of genes or their products can be experimentally controlled in a time-resolved manner.

Ohio SchoolNet Initiatives: The Role of the Ohio Education Computer Network.

ERIC Educational Resources Information Center

Ohio State Legislative Office of Education Oversight, Columbus.

Ohio's Legislative Office of Education Oversight (LOEO) evaluates education-related activities funded wholly or in part by that state. SchoolNet initiatives seek to increase Ohio K-12 schools' access to computers, networks, and other technology, with a particular emphasis on low-wealth districts. This report addresses the gap between the…

OmicsNet: a web-based tool for creation and visual analysis of biological networks in 3D space.

PubMed

Zhou, Guangyan; Xia, Jianguo

2018-06-07

Biological networks play increasingly important roles in omics data integration and systems biology. Over the past decade, many excellent tools have been developed to support creation, analysis and visualization of biological networks. However, important limitations remain: most tools are standalone programs, the majority of them focus on protein-protein interaction (PPI) or metabolic networks, and visualizations often suffer from 'hairball' effects when networks become large. To help address these limitations, we developed OmicsNet - a novel web-based tool that allows users to easily create different types of molecular interaction networks and visually explore them in a three-dimensional (3D) space. Users can upload one or multiple lists of molecules of interest (genes/proteins, microRNAs, transcription factors or metabolites) to create and merge different types of biological networks. The 3D network visualization system was implemented using the powerful Web Graphics Library (WebGL) technology that works natively in most major browsers. OmicsNet supports force-directed layout, multi-layered perspective layout, as well as spherical layout to help visualize and navigate complex networks. A rich set of functions have been implemented to allow users to perform coloring, shading, topology analysis, and enrichment analysis. OmicsNet is freely available at http://www.omicsnet.ca.

BreadNet: An On-Line Community.

ERIC Educational Resources Information Center

Walker, Susan

1987-01-01

Describes BreadNet, a computer network linking Middlebury College English teachers, their associates, and students. Network extends to rural English teachers and their K-8 students. BreadNet used for student pen pal program, teacher teleconferencing, information access. Also describes BreadNet's problems and future possibilities. (TES)

BioNet Digital Communications Framework

NASA Technical Reports Server (NTRS)

Gifford, Kevin; Kuzminsky, Sebastian; Williams, Shea

2010-01-01

BioNet v2 is a peer-to-peer middleware that enables digital communication devices to talk to each other. It provides a software development framework, standardized application, network-transparent device integration services, a flexible messaging model, and network communications for distributed applications. BioNet is an implementation of the Constellation Program Command, Control, Communications and Information (C3I) Interoperability specification, given in CxP 70022-01. The system architecture provides the necessary infrastructure for the integration of heterogeneous wired and wireless sensing and control devices into a unified data system with a standardized application interface, providing plug-and-play operation for hardware and software systems. BioNet v2 features a naming schema for mobility and coarse-grained localization information, data normalization within a network-transparent device driver framework, enabling of network communications to non-IP devices, and fine-grained application control of data subscription band width usage. BioNet directly integrates Disruption Tolerant Networking (DTN) as a communications technology, enabling networked communications with assets that are only intermittently connected including orbiting relay satellites and planetary rover vehicles.

Hierarchical Kohonenen net for anomaly detection in network security.

PubMed

Sarasamma, Suseela T; Zhu, Qiuming A; Huff, Julie

2005-04-01

A novel multilevel hierarchical Kohonen Net (K-Map) for an intrusion detection system is presented. Each level of the hierarchical map is modeled as a simple winner-take-all K-Map. One significant advantage of this multilevel hierarchical K-Map is its computational efficiency. Unlike other statistical anomaly detection methods such as nearest neighbor approach, K-means clustering or probabilistic analysis that employ distance computation in the feature space to identify the outliers, our approach does not involve costly point-to-point computation in organizing the data into clusters. Another advantage is the reduced network size. We use the classification capability of the K-Map on selected dimensions of data set in detecting anomalies. Randomly selected subsets that contain both attacks and normal records from the KDD Cup 1999 benchmark data are used to train the hierarchical net. We use a confidence measure to label the clusters. Then we use the test set from the same KDD Cup 1999 benchmark to test the hierarchical net. We show that a hierarchical K-Map in which each layer operates on a small subset of the feature space is superior to a single-layer K-Map operating on the whole feature space in detecting a variety of attacks in terms of detection rate as well as false positive rate.

First results from comparison of rainfall estimations by GPM IMERG with rainfall measurements from the WegenerNet high density network

NASA Astrophysics Data System (ADS)

Oo, Sungmin; Foelsche, Ulrich; Kirchengast, Gottfried; Fuchsberger, Jürgen

2016-04-01

The research level products of the Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG "Final" run datasets) were compared with rainfall measurements from the WegenerNet high density network as part of ground validation (GV) projects of GPM missions. The WegenerNet network comprises 151 ground level weather stations in an area of 15 km × 20 km in south-eastern Austria (Feldbach region, ˜46.93° N, ˜15.90° E) designed to serve as a long-term monitoring and validation facility for weather and climate research and applications. While the IMERG provides rainfall estimations every half hour at 0.1° resolution, the WegenerNet network measures rainfall every 5 minutes at around 2 km2 resolution and produces 200 m × 200 m gridded datasets. The study was conducted on the domain of the WegenerNet network; eight IMERG grids are overlapped with the network, two of which are entirely covered by the WegenerNet (40 and 39 stations in each grid). We investigated data from April to September of the years 2014 to 2015; the date of first two years after the launch of the GPM Core Observatory. Since the network has a flexibility to work with various spatial and temporal scales, the comparison could be conducted on average-points to pixel basis at both sub-daily and daily timescales. This presentation will summarize the first results of the comparison and future plans to explore the characteristics of errors in the IMERG datasets.

Defining environmental flows requirements at regional scale by using meso-scale habitat models and catchments classification

NASA Astrophysics Data System (ADS)

Vezza, Paolo; Comoglio, Claudio; Rosso, Maurizio

2010-05-01

The alterations of the natural flow regime and in-stream channel modification due to abstraction from watercourses act on biota through an hydraulic template, which is mediated by channel morphology. Modeling channel hydro-morphology is needed in order to evaluate how much habitat is available for selected fauna under specific environmental conditions, and consequently to assist decision makers in planning options for regulated river management. Meso-scale habitat modeling methods (e.g., MesoHABSIM) offer advantages over the traditional physical habitat evaluation, involving a larger range of habitat variables, allowing longer length of surveyed rivers and enabling understanding of fish behavior at larger spatial scale. In this study we defined a bottom-up method for the ecological discharge evaluation at regional scale, focusing on catchments smaller than 50 km2, most of them located within mountainous areas of Apennines and Alps mountain range in Piedmont (NW Italy). Within the regional study domain we identified 30 representative catchments not affected by water abstractions in order to build up the habitat-flow relationship, to be used as reference when evaluating regulated watercourses or new projects. For each stream we chose a representative reach and obtained fish data by sampling every single functional habitat (i.e. meso-habitat) within the site, keeping separated each area by using nets. The target species were brown trout (Salmo trutta), marble trout (Salmo trutta marmoratus), bullhead (Cottus gobius), chub (Leuciscus cephalus), barbel (Barbus barbus), vairone (Leuciscus souffia) and other rheophilic Cyprinids. The fish habitat suitability criteria was obtained from the observation of habitat use by a selected organism described with a multivariate relationship between habitat characteristics and fish presence. Habitat type, mean slope, cover, biotic choriotop and substrate, stream depth and velocity, water pH, temperature and percentage of dissolved

Spatio-temporal distributions of meso convective systems in NE China and its vicinity

NASA Astrophysics Data System (ADS)

Yuan, Meiying; Li, Zechun; Zhang, Xiaoling; Li, Xun

2008-08-01

Based on the IR cloud imagery from the Chinese FY-2C satellite for June ~ August, 2005 - 2007, statistics is undertaken of meso convective systems (MCS) over NE China and its neighborhood, obtaining the space - time distributions of MCS. MCS include elliptical type( MCC's) , persistent elongated type (PECS's), in shape. Dividing the total MCS into MαMCS, MβMCS and MCC (PECS) . Results show that the number of meso-α MCS (dominantly PECS's) is considerably more than that of meso-β MCS (largely MCCss), which are observed mainly in the NE China plain and Daxing'an Mountains, especially in the entrance to the plain as well as its central ~ northern portion; the MCS occur mainly in June ~ August, particularly in June; the extratropical MCS show two peak phases, one being in 1500-2200 BST the other being 0000-0700 BST as the secondary peaking interval.

Orbit Determination of KOMPSAT-1 and Cryosat-2 Satellites Using Optical Wide-field Patrol Network (OWL-Net) Data with Batch Least Squares Filter

NASA Astrophysics Data System (ADS)

Lee, Eunji; Park, Sang-Young; Shin, Bumjoon; Cho, Sungki; Choi, Eun-Jung; Jo, Junghyun; Park, Jang-Hyun

2017-03-01

The optical wide-field patrol network (OWL-Net) is a Korean optical surveillance system that tracks and monitors domestic satellites. In this study, a batch least squares algorithm was developed for optical measurements and verified by Monte Carlo simulation and covariance analysis. Potential error sources of OWL-Net, such as noise, bias, and clock errors, were analyzed. There is a linear relation between the estimation accuracy and the noise level, and the accuracy significantly depends on the declination bias. In addition, the time-tagging error significantly degrades the observation accuracy, while the time-synchronization offset corresponds to the orbital motion. The Cartesian state vector and measurement bias were determined using the OWL-Net tracking data of the KOMPSAT-1 and Cryosat-2 satellites. The comparison with known orbital information based on two-line elements (TLE) and the consolidated prediction format (CPF) shows that the orbit determination accuracy is similar to that of TLE. Furthermore, the precision and accuracy of OWL-Net observation data were determined to be tens of arcsec and sub-degree level, respectively.

PollyNET - an emerging network of automated raman-polarizarion lidars for continuous aerosolprofiling

NASA Astrophysics Data System (ADS)

Baars, Holger; Althausen, Dietrich; Engelmann, Ronny; Heese, Birgit; Ansmann, Albert; Wandinger, Ulla; Hofer, Julian; Skupin, Annett; Komppula, Mika; Giannakaki, Eleni; Filioglou, Maria; Bortoli, Daniele; Silva, Ana Maria; Pereira, Sergio; Stachlewska, Iwona S.; Kumala, Wojciech; Szczepanik, Dominika; Amiridis, Vassilis; Marinou, Eleni; Kottas, Michail; Mattis, Ina; Müller, Gerhard

2018-04-01

PollyNET is a network of portable, automated, and continuously measuring Ramanpolarization lidars of type Polly operated by several institutes worldwide. The data from permanent and temporary measurements sites are automatically processed in terms of optical aerosol profiles and displayed in near-real time at polly.tropos.de. According to current schedules, the network will grow by 3-4 systems during the upcoming 2-3 years and will then comprise 11 permanent stations and 2 mobile platforms.

EviNet: a web platform for network enrichment analysis with flexible definition of gene sets.

PubMed

Jeggari, Ashwini; Alekseenko, Zhanna; Petrov, Iurii; Dias, José M; Ericson, Johan; Alexeyenko, Andrey

2018-06-09

The new web resource EviNet provides an easily run interface to network enrichment analysis for exploration of novel, experimentally defined gene sets. The major advantages of this analysis are (i) applicability to any genes found in the global network rather than only to those with pathway/ontology term annotations, (ii) ability to connect genes via different molecular mechanisms rather than within one high-throughput platform, and (iii) statistical power sufficient to detect enrichment of very small sets, down to individual genes. The users' gene sets are either defined prior to upload or derived interactively from an uploaded file by differential expression criteria. The pathways and networks used in the analysis can be chosen from the collection menu. The calculation is typically done within seconds or minutes and the stable URL is provided immediately. The results are presented in both visual (network graphs) and tabular formats using jQuery libraries. Uploaded data and analysis results are kept in separated project directories not accessible by other users. EviNet is available at https://www.evinet.org/.

NeMO-Net: The Neural Multi-Modal Observation and Training Network for Global Coral Reef Assessment

NASA Technical Reports Server (NTRS)

Chirayath, Ved

2017-01-01

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. Exploiting the fine-scaled features of these datasets, machine learning methods such as MAP, PCA, and SVM can not only accurately classify the living cover and morphology of these reef systems (below 8 percent error), but are also able to map the spectral space between airborne and satellite imagery, augmenting and improving the classification accuracy of previously low-resolution datasets. We are currently implementing NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive active learning and training software to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. NeMO-Net will be built upon the QGIS platform to ingest UAV, airborne and satellite datasets from various sources and sensor capabilities, and through data-fusion determine the coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. To achieve this, we will exploit virtual data augmentation, the use of semi-supervised learning, and active learning through a tablet platform allowing for users to manually train uncertain or difficult to classify datasets. The project will make use of Pythons extensive libraries for machine learning, as well as extending integration

Towards a Community Environmental Observation Network

NASA Astrophysics Data System (ADS)

Mertl, Stefan; Lettenbichler, Anton

2014-05-01

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

Conversational Scholarship in Cyberspace: The Evolution and Activities of H-Net, the Online Network for the Humanities.

ERIC Educational Resources Information Center

Turnbull, Paul

1996-01-01

The origins and current use of H-Net, an online humanities network on the World Wide Web, are examined. H-Net currently sponsors 73 electronic discussion lists that reach subscribers in 68 countries. Discussion groups have not met expectations for scholarly exchange, possibly because of plagiarism and copyright concerns. New ventures include book…

BASiNET-BiologicAl Sequences NETwork: a case study on coding and non-coding RNAs identification.

PubMed

Ito, Eric Augusto; Katahira, Isaque; Vicente, Fábio Fernandes da Rocha; Pereira, Luiz Filipe Protasio; Lopes, Fabrício Martins

2018-06-05

With the emergence of Next Generation Sequencing (NGS) technologies, a large volume of sequence data in particular de novo sequencing was rapidly produced at relatively low costs. In this context, computational tools are increasingly important to assist in the identification of relevant information to understand the functioning of organisms. This work introduces BASiNET, an alignment-free tool for classifying biological sequences based on the feature extraction from complex network measurements. The method initially transform the sequences and represents them as complex networks. Then it extracts topological measures and constructs a feature vector that is used to classify the sequences. The method was evaluated in the classification of coding and non-coding RNAs of 13 species and compared to the CNCI, PLEK and CPC2 methods. BASiNET outperformed all compared methods in all adopted organisms and datasets. BASiNET have classified sequences in all organisms with high accuracy and low standard deviation, showing that the method is robust and non-biased by the organism. The proposed methodology is implemented in open source in R language and freely available for download at https://cran.r-project.org/package=BASiNET.

An Expanded Study of Net Generation Perceptions on Privacy and Security on Social Networking Sites (SNS)

ERIC Educational Resources Information Center

Lawler, James P.; Molluzzo, John C.; Doshi, Vijal

2012-01-01

Social networking on the Internet continues to be a frequent avenue of communication, especially among Net Generation consumers, giving benefits both personal and professional. The benefits may be eventually hindered by issues in information gathering and sharing on social networking sites. This study evaluates the perceptions of students taking a…

Development and use of the Cytoscape app GFD-Net for measuring semantic dissimilarity of gene networks

PubMed Central

Diaz-Montana, Juan J.; Diaz-Diaz, Norberto

2014-01-01

Gene networks are one of the main computational models used to study the interaction between different elements during biological processes being widely used to represent gene–gene, or protein–protein interaction complexes. We present GFD-Net, a Cytoscape app for visualizing and analyzing the functional dissimilarity of gene networks. PMID:25400907

A Microsoft-Excel-based tool for running and critically appraising network meta-analyses--an overview and application of NetMetaXL.

PubMed

Brown, Stephen; Hutton, Brian; Clifford, Tammy; Coyle, Doug; Grima, Daniel; Wells, George; Cameron, Chris

2014-09-29

The use of network meta-analysis has increased dramatically in recent years. WinBUGS, a freely available Bayesian software package, has been the most widely used software package to conduct network meta-analyses. However, the learning curve for WinBUGS can be daunting, especially for new users. Furthermore, critical appraisal of network meta-analyses conducted in WinBUGS can be challenging given its limited data manipulation capabilities and the fact that generation of graphical output from network meta-analyses often relies on different software packages than the analyses themselves. We developed a freely available Microsoft-Excel-based tool called NetMetaXL, programmed in Visual Basic for Applications, which provides an interface for conducting a Bayesian network meta-analysis using WinBUGS from within Microsoft Excel. . This tool allows the user to easily prepare and enter data, set model assumptions, and run the network meta-analysis, with results being automatically displayed in an Excel spreadsheet. It also contains macros that use NetMetaXL's interface to generate evidence network diagrams, forest plots, league tables of pairwise comparisons, probability plots (rankograms), and inconsistency plots within Microsoft Excel. All figures generated are publication quality, thereby increasing the efficiency of knowledge transfer and manuscript preparation. We demonstrate the application of NetMetaXL using data from a network meta-analysis published previously which compares combined resynchronization and implantable defibrillator therapy in left ventricular dysfunction. We replicate results from the previous publication while demonstrating result summaries generated by the software. Use of the freely available NetMetaXL successfully demonstrated its ability to make running network meta-analyses more accessible to novice WinBUGS users by allowing analyses to be conducted entirely within Microsoft Excel. NetMetaXL also allows for more efficient and transparent

A Microsoft-Excel-based tool for running and critically appraising network meta-analyses—an overview and application of NetMetaXL

PubMed Central

2014-01-01

Background The use of network meta-analysis has increased dramatically in recent years. WinBUGS, a freely available Bayesian software package, has been the most widely used software package to conduct network meta-analyses. However, the learning curve for WinBUGS can be daunting, especially for new users. Furthermore, critical appraisal of network meta-analyses conducted in WinBUGS can be challenging given its limited data manipulation capabilities and the fact that generation of graphical output from network meta-analyses often relies on different software packages than the analyses themselves. Methods We developed a freely available Microsoft-Excel-based tool called NetMetaXL, programmed in Visual Basic for Applications, which provides an interface for conducting a Bayesian network meta-analysis using WinBUGS from within Microsoft Excel. . This tool allows the user to easily prepare and enter data, set model assumptions, and run the network meta-analysis, with results being automatically displayed in an Excel spreadsheet. It also contains macros that use NetMetaXL’s interface to generate evidence network diagrams, forest plots, league tables of pairwise comparisons, probability plots (rankograms), and inconsistency plots within Microsoft Excel. All figures generated are publication quality, thereby increasing the efficiency of knowledge transfer and manuscript preparation. Results We demonstrate the application of NetMetaXL using data from a network meta-analysis published previously which compares combined resynchronization and implantable defibrillator therapy in left ventricular dysfunction. We replicate results from the previous publication while demonstrating result summaries generated by the software. Conclusions Use of the freely available NetMetaXL successfully demonstrated its ability to make running network meta-analyses more accessible to novice WinBUGS users by allowing analyses to be conducted entirely within Microsoft Excel. NetMetaXL also allows

Airflow attenuation and bed net utilization: observations from Africa and Asia.

PubMed

von Seidlein, Lorenz; Ikonomidis, Konstantin; Bruun, Rasmus; Jawara, Musa; Pinder, Margaret; Knols, Bart Gj; Knudsen, Jakob B

2012-06-15

intervention in many areas uptake remains poor. Bed nets reduce airflow, but have no influence on temperature and humidity. The discomfort associated with bed nets is likely to be most intolerable during the hottest and most humid period of the year, which frequently coincides with the peak of malaria vector densities and the force of pathogen transmission. These observations suggest thermal discomfort is a factor limiting bed net use and open a range of architectural possibilities to overcome this limitation.

Network Requirements in Support of Army’s LandWarNet Transformation

DTIC Science & Technology

2011-02-15

To overcome the challenges of future requirements for information dominance , the Army must develop a strategy that ensures its organizations have access to global networks and required services throughout any area of operation. This research project analyzes the Army’s transformation of the LandWarNet in support of an expeditionary Army engaged in persistent conflict. The paper identifies how well

CardioNet: a human metabolic network suited for the study of cardiomyocyte metabolism.

PubMed

Karlstädt, Anja; Fliegner, Daniela; Kararigas, Georgios; Ruderisch, Hugo Sanchez; Regitz-Zagrosek, Vera; Holzhütter, Hermann-Georg

2012-08-29

Availability of oxygen and nutrients in the coronary circulation is a crucial determinant of cardiac performance. Nutrient composition of coronary blood may significantly vary in specific physiological and pathological conditions, for example, administration of special diets, long-term starvation, physical exercise or diabetes. Quantitative analysis of cardiac metabolism from a systems biology perspective may help to a better understanding of the relationship between nutrient supply and efficiency of metabolic processes required for an adequate cardiac output. Here we present CardioNet, the first large-scale reconstruction of the metabolic network of the human cardiomyocyte comprising 1793 metabolic reactions, including 560 transport processes in six compartments. We use flux-balance analysis to demonstrate the capability of the network to accomplish a set of 368 metabolic functions required for maintaining the structural and functional integrity of the cell. Taking the maintenance of ATP, biosynthesis of ceramide, cardiolipin and further important phospholipids as examples, we analyse how a changed supply of glucose, lactate, fatty acids and ketone bodies may influence the efficiency of these essential processes. CardioNet is a functionally validated metabolic network of the human cardiomyocyte that enables theorectical studies of cellular metabolic processes crucial for the accomplishment of an adequate cardiac output.

Isoporphyrin intermediate in heme oxygenase catalysis. Oxidation of alpha-meso-phenylheme.

PubMed

Evans, John P; Niemevz, Fernando; Buldain, Graciela; de Montellano, Paul Ortiz

2008-07-11

Human heme oxygenase-1 (hHO-1) catalyzes the O2- and NADPH-dependent oxidation of heme to biliverdin, CO, and free iron. The first step involves regiospecific insertion of an oxygen atom at the alpha-meso carbon by a ferric hydroperoxide and is predicted to proceed via an isoporphyrin pi-cation intermediate. Here we report spectroscopic detection of a transient intermediate during oxidation by hHO-1 of alpha-meso-phenylheme-IX, alpha-meso-(p-methylphenyl)-mesoheme-III, and alpha-meso-(p-trifluoromethylphenyl)-mesoheme-III. In agreement with previous experiments (Wang, J., Niemevz, F., Lad, L., Huang, L., Alvarez, D. E., Buldain, G., Poulos, T. L., and Ortiz de Montellano, P. R. (2004) J. Biol. Chem. 279, 42593-42604), only the alpha-biliverdin isomer is produced with concomitant formation of the corresponding benzoic acid. The transient intermediate observed in the NADPH-P450 reductase-catalyzed reaction accumulated when the reaction was supported by H2O2 and exhibited the absorption maxima at 435 and 930 nm characteristic of an isoporphyrin. Product analysis by reversed phase high performance liquid chromatography and liquid chromatography electrospray ionization mass spectrometry of the product generated with H2O2 identified it as an isoporphyrin that, on quenching, decayed to benzoylbiliverdin. In the presence of H218O2, one labeled oxygen atom was incorporated into these products. The hHO-1-isoporphyrin complexes were found to have half-lives of 1.7 and 2.4 h for the p-trifluoromethyl- and p-methyl-substituted phenylhemes, respectively. The addition of NADPH-P450 reductase to the H2O2-generated hHO-1-isoporphyrin complex produced alpha-biliverdin, confirming its role as a reaction intermediate. Identification of an isoporphyrin intermediate in the catalytic sequence of hHO-1, the first such intermediate observed in hemoprotein catalysis, completes our understanding of the critical first step of heme oxidation.

NetGen: a novel network-based probabilistic generative model for gene set functional enrichment analysis.

PubMed

Sun, Duanchen; Liu, Yinliang; Zhang, Xiang-Sun; Wu, Ling-Yun

2017-09-21

High-throughput experimental techniques have been dramatically improved and widely applied in the past decades. However, biological interpretation of the high-throughput experimental results, such as differential expression gene sets derived from microarray or RNA-seq experiments, is still a challenging task. Gene Ontology (GO) is commonly used in the functional enrichment studies. The GO terms identified via current functional enrichment analysis tools often contain direct parent or descendant terms in the GO hierarchical structure. Highly redundant terms make users difficult to analyze the underlying biological processes. In this paper, a novel network-based probabilistic generative model, NetGen, was proposed to perform the functional enrichment analysis. An additional protein-protein interaction (PPI) network was explicitly used to assist the identification of significantly enriched GO terms. NetGen achieved a superior performance than the existing methods in the simulation studies. The effectiveness of NetGen was explored further on four real datasets. Notably, several GO terms which were not directly linked with the active gene list for each disease were identified. These terms were closely related to the corresponding diseases when accessed to the curated literatures. NetGen has been implemented in the R package CopTea publicly available at GitHub ( http://github.com/wulingyun/CopTea/ ). Our procedure leads to a more reasonable and interpretable result of the functional enrichment analysis. As a novel term combination-based functional enrichment analysis method, NetGen is complementary to current individual term-based methods, and can help to explore the underlying pathogenesis of complex diseases.

meso-Dihydroguaiaretic acid derivatives with antibacterial and antimycobacterial activity.

PubMed

Reyes-Melo, Karen; García, Abraham; Romo-Mancillas, Antonio; Garza-González, Elvira; Rivas-Galindo, Verónica M; Miranda, Luis D; Vargas-Villarreal, Javier; Favela-Hernández, Juan Manuel J; Camacho-Corona, María Del Rayo

2017-10-15

Thirty-three meso-dihydroguaiaretic acid (meso-DGA) derivatives bearing esters, ethers, and amino-ethers were synthesized. All derivatives were tested against twelve drug-resistant clinical isolates of Gram-positive and Gram-negative bacteria, including sensitive (H37Rv) and multidrug-resistant Mycobacterium tuberculosis strains. Among the tested compounds, four esters (7, 11, 13, and 17), one ether (23), and three amino-ethers (30, 31, and 33) exhibited moderate activity against methicillin-resistant Staphylococcus aureus, whereas 30 and 31 showed better results than levofloxacin against vancomycin-resistant Enterococcus faecium. Additionally, nineteen meso-DGA derivatives displayed moderate to potent activity against M. tuberculosis H37Rv with minimum inhibitory concentration (MIC) values ranging from 3.125 to 50µg/mL. Seven meso-DGA derivatives bearing amino-ethers (26-31 and 33) exhibited the lowest MICs against M. tuberculosis H37Rv and G122 strains, with 31 being as potent as ethambutol (MICs of 3.125 and 6.25µg/mL). The presence of positively charged group precursors possessing steric and hydrophobic features (e.g. N-ethylpiperidine moieties in meso-31) resulted essential to significantly increase the antimycobacterial properties of parent meso-DGA as supported by the R-group pharmacophoric and field-based QSAR analyses. To investigate the safety profile of the antimycobacterial compounds, cytotoxicity on Vero cells was determined. The amino-ether 31 exhibited a selectivity index value of 23, which indicate it was more toxic to M. tuberculosis than to mammalian cells. Therefore, 31 can be considered as a promising antitubercular agent for further studies. Copyright © 2017 Elsevier Ltd. All rights reserved.

Optimizing CMS build infrastructure via Apache Mesos

DOE PAGES

Abdurachmanov, David; Degano, Alessandro; Elmer, Peter; ...

2015-12-23

The Offline Software of the CMS Experiment at the Large Hadron Collider (LHC) at CERN consists of 6M lines of in-house code, developed over a decade by nearly 1000 physicists, as well as a comparable amount of general use open-source code. A critical ingredient to the success of the construction and early operation of the WLCG was the convergence, around the year 2000, on the use of a homogeneous environment of commodity x86-64 processors and Linux.Apache Mesos is a cluster manager that provides efficient resource isolation and sharing across distributed applications, or frameworks. It can run Hadoop, Jenkins, Spark, Aurora,more » and other applications on a dynamically shared pool of nodes. Lastly, we present how we migrated our continuous integration system to schedule jobs on a relatively small Apache Mesos enabled cluster and how this resulted in better resource usage, higher peak performance and lower latency thanks to the dynamic scheduling capabilities of Mesos.« less

Optimizing CMS build infrastructure via Apache Mesos

NASA Astrophysics Data System (ADS)

Abdurachmanov, David; Degano, Alessandro; Elmer, Peter; Eulisse, Giulio; Mendez, David; Muzaffar, Shahzad

2015-12-01

The Offline Software of the CMS Experiment at the Large Hadron Collider (LHC) at CERN consists of 6M lines of in-house code, developed over a decade by nearly 1000 physicists, as well as a comparable amount of general use open-source code. A critical ingredient to the success of the construction and early operation of the WLCG was the convergence, around the year 2000, on the use of a homogeneous environment of commodity x86-64 processors and Linux. Apache Mesos is a cluster manager that provides efficient resource isolation and sharing across distributed applications, or frameworks. It can run Hadoop, Jenkins, Spark, Aurora, and other applications on a dynamically shared pool of nodes. We present how we migrated our continuous integration system to schedule jobs on a relatively small Apache Mesos enabled cluster and how this resulted in better resource usage, higher peak performance and lower latency thanks to the dynamic scheduling capabilities of Mesos.

Optimizing CMS build infrastructure via Apache Mesos

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

Abdurachmanov, David; Degano, Alessandro; Elmer, Peter

The Offline Software of the CMS Experiment at the Large Hadron Collider (LHC) at CERN consists of 6M lines of in-house code, developed over a decade by nearly 1000 physicists, as well as a comparable amount of general use open-source code. A critical ingredient to the success of the construction and early operation of the WLCG was the convergence, around the year 2000, on the use of a homogeneous environment of commodity x86-64 processors and Linux.Apache Mesos is a cluster manager that provides efficient resource isolation and sharing across distributed applications, or frameworks. It can run Hadoop, Jenkins, Spark, Aurora,more » and other applications on a dynamically shared pool of nodes. Lastly, we present how we migrated our continuous integration system to schedule jobs on a relatively small Apache Mesos enabled cluster and how this resulted in better resource usage, higher peak performance and lower latency thanks to the dynamic scheduling capabilities of Mesos.« less

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

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

MercNet: A national monitoring network to assess responses to changing mercury emissions in the United States

USGS Publications Warehouse

Schmeltz, D.; Evers, D.C.; Driscoll, C.T.; Artz, R.; Cohen, M.; Gay, D.; Haeuber, R.; Krabbenhoft, D.P.; Mason, R.; Morris, K.; Wiener, J.G.

2011-01-01

A partnership of federal and state agencies, tribes, industry, and scientists from academic research and environmental organizations is establishing a national, policy-relevant mercury monitoring network, called MercNet, to address key questions concerning changes in anthropogenic mercury emissions and deposition, associated linkages to ecosystem effects, and recovery from mercury contamination. This network would quantify mercury in the atmosphere, land, water, and biota in terrestrial, freshwater, and coastal ecosystems to provide a national scientific capability for evaluating the benefits and effectiveness of emission controls. Program development began with two workshops, convened to establish network goals, to select key indicators for monitoring, to propose a geographic network of monitoring sites, and to design a monitoring plan. MercNet relies strongly on multi-institutional partnerships to secure the capabilities and comprehensive data that are needed to develop, calibrate, and refine predictive mercury models and to guide effective management. Ongoing collaborative efforts include the: (1) development of regional multi-media databases on mercury in the Laurentian Great Lakes, northeastern United States, and eastern Canada; (2) syntheses and reporting of these data for the scientific and policy communities; and (3) evaluation of potential monitoring sites. The MercNet approach could be applied to the development of other monitoring programs, such as emerging efforts to monitor and assess global mercury emission controls. ?? 2011 Springer Science+Business Media, LLC (outside the USA).

TopologyNet: Topology based deep convolutional and multi-task neural networks for biomolecular property predictions

PubMed Central

2017-01-01

Although deep learning approaches have had tremendous success in image, video and audio processing, computer vision, and speech recognition, their applications to three-dimensional (3D) biomolecular structural data sets have been hindered by the geometric and biological complexity. To address this problem we introduce the element-specific persistent homology (ESPH) method. ESPH represents 3D complex geometry by one-dimensional (1D) topological invariants and retains important biological information via a multichannel image-like representation. This representation reveals hidden structure-function relationships in biomolecules. We further integrate ESPH and deep convolutional neural networks to construct a multichannel topological neural network (TopologyNet) for the predictions of protein-ligand binding affinities and protein stability changes upon mutation. To overcome the deep learning limitations from small and noisy training sets, we propose a multi-task multichannel topological convolutional neural network (MM-TCNN). We demonstrate that TopologyNet outperforms the latest methods in the prediction of protein-ligand binding affinities, mutation induced globular protein folding free energy changes, and mutation induced membrane protein folding free energy changes. Availability: weilab.math.msu.edu/TDL/ PMID:28749969

RadNet Air Quality (Fixed Station) Data

EPA Pesticide Factsheets

RadNet is a national network of monitoring stations that regularly collect air for analysis of radioactivity. The RadNet network, which has stations in each State, has been used to track environmental releases of radioactivity from nuclear weapons tests and nuclear accidents. RadNet also documents the status and trends of environmental radioactivity

NET-Works: Linking families, communities and primary care to prevent obesity in preschool-age children.

PubMed

Sherwood, Nancy E; French, Simone A; Veblen-Mortenson, Sara; Crain, A Lauren; Berge, Jerica; Kunin-Batson, Alicia; Mitchell, Nathan; Senso, Meghan

2013-11-01

Obesity prevention in children offers a unique window of opportunity to establish healthful eating and physical activity behaviors to maintain a healthful body weight and avoid the adverse proximal and distal long-term health consequences of obesity. Given that obesity is the result of a complex interaction between biological, behavioral, family-based, and community environmental factors, intervention at multiple levels and across multiple settings is critical for both short- and long-term effectiveness. The Minnesota NET-Works (Now Everybody Together for Amazing and Healthful Kids) study is one of four obesity prevention and/or treatment trials that are part of the Childhood Obesity Prevention and Treatment (COPTR) Consortium. The goal of the NET-Works study is to evaluate an intervention that integrates home, community, primary care and neighborhood strategies to promote healthful eating, activity patterns, and body weight among low income, racially/ethnically diverse preschool-age children. Critical to the success of this intervention is the creation of linkages among the settings to support parents in making home environment and parenting behavior changes to foster healthful child growth. Five hundred racially/ethnically diverse, two-four year old children and their parent or primary caregiver will be randomized to the multi-component intervention or to a usual care comparison group for a three-year period. This paper describes the study design, measurement and intervention protocols, and statistical analysis plan for the NET-Works trial. © 2013 Elsevier Inc. All rights reserved.

Test operation of a real-time tsunami inundation forecast system using actual data observed by S-net

NASA Astrophysics Data System (ADS)

Suzuki, W.; Yamamoto, N.; Miyoshi, T.; Aoi, S.

2017-12-01

If the tsunami inundation information can be rapidly and stably forecast before the large tsunami attacks, the information would have effectively people realize the impeding danger and necessity of evacuation. Toward that goal, we have developed a prototype system to perform the real-time tsunami inundation forecast for Chiba prefecture, eastern Japan, using off-shore ocean bottom pressure data observed by the seafloor observation network for earthquakes and tsunamis along the Japan Trench (S-net) (Aoi et al., 2015, AGU). Because tsunami inundation simulation requires a large computation cost, we employ a database approach searching the pre-calculated tsunami scenarios that reasonably explain the observed S-net pressure data based on the multi-index method (Yamamoto et al., 2016, EPS). The scenario search is regularly repeated, not triggered by the occurrence of the tsunami event, and the forecast information is generated from the selected scenarios that meet the criterion. Test operation of the prototype system using the actual observation data started in April, 2017 and the performance and behavior of the system during non-tsunami event periods have been examined. It is found that the treatment of the noises affecting the observed data is the main issue to be solved toward the improvement of the system. Even if the observed pressure data are filtered to extract the tsunami signals, the noises in ordinary times or unusually large noises like high ocean waves due to storm affect the comparison between the observed and scenario data. Due to the noises, the tsunami scenarios are selected and the tsunami is forecast although any tsunami event does not actually occur. In most cases, the selected scenarios due to the noises have the fault models in the region along the Kurile or Izu-Bonin Trenches, far from the S-net region, or the fault models below the land. Based on the parallel operation of the forecast system with a different scenario search condition and

Optogenetic stimulation of a meso-scale human cortical model

NASA Astrophysics Data System (ADS)

Selvaraj, Prashanth; Szeri, Andrew; Sleigh, Jamie; Kirsch, Heidi

2015-03-01

Neurological phenomena like sleep and seizures depend not only on the activity of individual neurons, but on the dynamics of neuron populations as well. Meso-scale models of cortical activity provide a means to study neural dynamics at the level of neuron populations. Additionally, they offer a safe and economical way to test the effects and efficacy of stimulation techniques on the dynamics of the cortex. Here, we use a physiologically relevant meso-scale model of the cortex to study the hypersynchronous activity of neuron populations during epileptic seizures. The model consists of a set of stochastic, highly non-linear partial differential equations. Next, we use optogenetic stimulation to control seizures in a hyperexcited cortex, and to induce seizures in a normally functioning cortex. The high spatial and temporal resolution this method offers makes a strong case for the use of optogenetics in treating meso scale cortical disorders such as epileptic seizures. We use bifurcation analysis to investigate the effect of optogenetic stimulation in the meso scale model, and its efficacy in suppressing the non-linear dynamics of seizures.

Reconstruction of extended Petri nets from time series data and its application to signal transduction and to gene regulatory networks

PubMed Central

2011-01-01

Background Network inference methods reconstruct mathematical models of molecular or genetic networks directly from experimental data sets. We have previously reported a mathematical method which is exclusively data-driven, does not involve any heuristic decisions within the reconstruction process, and deliveres all possible alternative minimal networks in terms of simple place/transition Petri nets that are consistent with a given discrete time series data set. Results We fundamentally extended the previously published algorithm to consider catalysis and inhibition of the reactions that occur in the underlying network. The results of the reconstruction algorithm are encoded in the form of an extended Petri net involving control arcs. This allows the consideration of processes involving mass flow and/or regulatory interactions. As a non-trivial test case, the phosphate regulatory network of enterobacteria was reconstructed using in silico-generated time-series data sets on wild-type and in silico mutants. Conclusions The new exact algorithm reconstructs extended Petri nets from time series data sets by finding all alternative minimal networks that are consistent with the data. It suggested alternative molecular mechanisms for certain reactions in the network. The algorithm is useful to combine data from wild-type and mutant cells and may potentially integrate physiological, biochemical, pharmacological, and genetic data in the form of a single model. PMID:21762503

Meso-scale Computational Investigation of Polyurea Microstructure and Its Role in Shockwave Attenuation/dispersion

DTIC Science & Technology

2015-07-01

grained simulations of the formation of meso-segregated microstructure and its interaction with the shockwave is analyzed in the present work. It is...help identify these phenomena and processes, meso-scale coarse-grained simulations of the formation of meso-segregated microstructure and its...of shockwave-induced hard-domain densification. Keywords: Polyurea; Meso-scale; Coarse-grained simulations ; Shockwave attenuation; shockwave

HTS-Net: An integrated regulome-interactome approach for establishing network regulation models in high-throughput screenings

PubMed Central

Rioualen, Claire; Da Costa, Quentin; Chetrit, Bernard; Charafe-Jauffret, Emmanuelle; Ginestier, Christophe

2017-01-01

High-throughput RNAi screenings (HTS) allow quantifying the impact of the deletion of each gene in any particular function, from virus-host interactions to cell differentiation. However, there has been less development for functional analysis tools dedicated to RNAi analyses. HTS-Net, a network-based analysis program, was developed to identify gene regulatory modules impacted in high-throughput screenings, by integrating transcription factors-target genes interaction data (regulome) and protein-protein interaction networks (interactome) on top of screening z-scores. HTS-Net produces exhaustive HTML reports for results navigation and exploration. HTS-Net is a new pipeline for RNA interference screening analyses that proves better performance than simple gene rankings by z-scores, by re-prioritizing genes and replacing them in their biological context, as shown by the three studies that we reanalyzed. Formatted input data for the three studied datasets, source code and web site for testing the system are available from the companion web site at http://htsnet.marseille.inserm.fr/. We also compared our program with existing algorithms (CARD and hotnet2). PMID:28949986

BioNetSim: a Petri net-based modeling tool for simulations of biochemical processes.

PubMed

Gao, Junhui; Li, Li; Wu, Xiaolin; Wei, Dong-Qing

2012-03-01

BioNetSim, a Petri net-based software for modeling and simulating biochemistry processes, is developed, whose design and implement are presented in this paper, including logic construction, real-time access to KEGG (Kyoto Encyclopedia of Genes and Genomes), and BioModel database. Furthermore, glycolysis is simulated as an example of its application. BioNetSim is a helpful tool for researchers to download data, model biological network, and simulate complicated biochemistry processes. Gene regulatory networks, metabolic pathways, signaling pathways, and kinetics of cell interaction are all available in BioNetSim, which makes modeling more efficient and effective. Similar to other Petri net-based softwares, BioNetSim does well in graphic application and mathematic construction. Moreover, it shows several powerful predominances. (1) It creates models in database. (2) It realizes the real-time access to KEGG and BioModel and transfers data to Petri net. (3) It provides qualitative analysis, such as computation of constants. (4) It generates graphs for tracing the concentration of every molecule during the simulation processes.

UltraNet Target Parameters. Chapter 1

NASA Technical Reports Server (NTRS)

Kislitzin, Katherine T.; Blaylock, Bruce T. (Technical Monitor)

1992-01-01

The UltraNet is a high speed network capable of rates up to one gigabit per second. It is a hub based network with four optical fiber links connecting each hub. Each link can carry up to 256 megabits of data, and the hub backplane is capable of one gigabit aggregate throughput. Host connections to the hub may be fiber, coax, or channel based. Bus based machines have adapter boards that connect to transceivers in the hub, while channel based machines use a personality module in the hub. One way that the UltraNet achieves its high transfer rates is by off-loading the protocol processing from the hosts to special purpose protocol engines in the UltraNet hubs. In addition, every hub has a PC connected to it by StarLAN for network management purposes. Although there is hub resident and PC resident UltraNet software, this document treats only the host resident UltraNet software.

Prediction of Disease Causing Non-Synonymous SNPs by the Artificial Neural Network Predictor NetDiseaseSNP

PubMed Central

Johansen, Morten Bo; Izarzugaza, Jose M. G.; Brunak, Søren; Petersen, Thomas Nordahl; Gupta, Ramneek

2013-01-01

We have developed a sequence conservation-based artificial neural network predictor called NetDiseaseSNP which classifies nsSNPs as disease-causing or neutral. Our method uses the excellent alignment generation algorithm of SIFT to identify related sequences and a combination of 31 features assessing sequence conservation and the predicted surface accessibility to produce a single score which can be used to rank nsSNPs based on their potential to cause disease. NetDiseaseSNP classifies successfully disease-causing and neutral mutations. In addition, we show that NetDiseaseSNP discriminates cancer driver and passenger mutations satisfactorily. Our method outperforms other state-of-the-art methods on several disease/neutral datasets as well as on cancer driver/passenger mutation datasets and can thus be used to pinpoint and prioritize plausible disease candidates among nsSNPs for further investigation. NetDiseaseSNP is publicly available as an online tool as well as a web service: http://www.cbs.dtu.dk/services/NetDiseaseSNP PMID:23935863

The physical therapy clinical research network (PTClinResNet): methods, efficacy, and benefits of a rehabilitation research network.

PubMed

Winstein, Carolee; Pate, Patricia; Ge, Tingting; Ervin, Carolyn; Baurley, James; Sullivan, Katherine J; Underwood, Samantha J; Fowler, Eileen G; Mulroy, Sara; Brown, David A; Kulig, Kornelia; Gordon, James; Azen, Stanley P

2008-11-01

This article describes the vision, methods, and implementation strategies used in building the infrastructure for PTClinResNet, a clinical research network designed to assess outcomes for health-related mobility associated with evidence-based physical therapy interventions across and within four different disability groups. Specific aims were to (1) create the infrastructure necessary to develop and sustain clinical trials research in rehabilitation, (2) generate evidence to evaluate the efficacy of resistance exercise-based physical interventions designed to improve muscle performance and movement skills, and (3) provide education and training opportunities for present and future clinician-researchers and for the rehabilitation community at-large in its support of evidence-based practice. We present the network's infrastructure, development, and several examples that highlight the benefits of a clinical research network. We suggest that the network structure is ideal for building research capacity and fostering multisite, multiinvestigator clinical research projects designed to generate evidence for the efficacy of rehabilitation interventions.

NetMOD v. 1.0

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

Merchant, Bion J

2015-12-22

NetMOD is a tool to model the performance of global ground-based explosion monitoring systems. The version 2.0 of the software supports the simulation of seismic, hydroacoustic, and infrasonic detection capability. The tool provides a user interface to execute simulations based upon a hypothetical definition of the monitoring system configuration, geophysical properties of the Earth, and detection analysis criteria. NetMOD will be distributed with a project file defining the basic performance characteristics of the International Monitoring System (IMS), a network of sensors operated by the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO). Network modeling is needed to be able to assess and explainmore » the potential effect of changes to the IMS, to prioritize station deployment and repair, and to assess the overall CTBTO monitoring capability currently and in the future. Currently the CTBTO uses version 1.0 of NetMOD, provided to them in early 2014. NetMOD will provide a modern tool that will cover all the simulations currently available and allow for the development of additional simulation capabilities of the IMS in the future. NetMOD simulates the performance of monitoring networks by estimating the relative amplitudes of the signal and noise measured at each of the stations within the network based upon known geophysical principles. From these signal and noise estimates, a probability of detection may be determined for each of the stations. The detection probabilities at each of the stations may then be combined to produce an estimate of the detection probability for the entire monitoring network.« less

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

The NetLander mission: a geophysical network on the surface of Mars

NASA Astrophysics Data System (ADS)

Ferri, F.; Counil, J. L.; Marsal, O.; Rocard, F.; Bonneville, R.; NetLander Team

2001-12-01

The NetLander mission aims at deploying on the surface of Mars a network of four identical landers which will perform simultaneous measurements in order to study the internal structure of Mars, its subsurface, surface, atmosphere and ionosphere. Seismic measurements will evidence the main transitions (lithosphere-mantle-core) as well as mantle discontinuities and crustal structure. The geodetic measurements will allow to determine the state of the core, liquid or not, and to retrieve the density of the core and mantle. The magnetic experiment will retrieve the conductivity profile down to several hundred of kilometers depth, gathering information on temperature gradient and phase transitions. The search for ground water, liquid or solid, will be performed locally by three experiments: seismometers, magnetometers and a ground penetrating radar. Local geology and surface mineralogy will be investigated through a multispectral stereo panoramic camera. A dedicated package will study the thermal properties of the soil at the landing sites. The NetLander will investigate the atmospheric vertical structure at the entry sites, complementing the existing three profiles. The network's ability to measure spatial and seasonal variations of pressure and the near-surface relative humidity will provide an unprecedented opportunity to characterize the H2O cycle. The meteorological package will also provide data relevant to the initiation and evolution of dust processes. Ionospheric investigations, coming along mainly with radio science, radar and electromagnetic sounding, will allow studying ionization processes and monitoring both the large-scale and small-scale plasma variations. The NetLander is a CNES led European mission to be launched in 2007. The nine instruments forming the payload will be provided by space agencies and research laboratories from more than ten European countries and USA.

Surface net solar radiation estimated from satellite measurements - Comparisons with tower observations

NASA Technical Reports Server (NTRS)

Li, Zhanqing; Leighton, H. G.; Cess, Robert D.

1993-01-01

A parameterization that relates the reflected solar flux at the top of the atmosphere to the net solar flux at the surface in terms of only the column water vapor amount and the solar zenith angle was tested against surface observations. Net surface fluxes deduced from coincidental collocated satellite-measured radiances and from measurements from towers in Boulder during summer and near Saskatoon in winter have mean differences of about 2 W/sq m, regardless of whether the sky is clear or cloudy. Furthermore, comparisons between the net fluxes deduced from the parameterization and from surface measurements showed equally good agreement when the data were partitioned into morning and afternoon observations. This is in contrast to results from an empirical clear-sky algorithm that is unable to account adequately for the effects of clouds and that shows, at Boulder, a distinct morning to afternoon variation. It is also demonstrated that the parameterization may be applied to irradiances at the top of the atmosphere that have been temporally averaged. The good agreement between the results of the parameterization and surface measurements suggests that the algorithm is a useful tool for a variety of climate studies.

ModObs: Atmospheric modelling for wind energy, climate and environment applications : exploring added value from new observation technique

NASA Astrophysics Data System (ADS)

Sempreviva, A. M.

2009-04-01

The EC FP6 Marie Curie Training Network "ModObs" http://www.modobs.windeng.net addresses the improvement of atmospheric boundary layer (ABL) models to investigate the interplay of processes at different temporal and spatial scales, and to explore the added value from new observation techniques. The overall goal is to bring young scientists to work together with experienced researchers in developing a better interaction amongst scientific communities of modelers and experimentalists, using a comprehensive approach to "Climate Change", "Clean Energy assessment" and "Environmental Policies", issues. This poster describes the work in progress of ten students, funded by the network, under the supervision of a team of scientists within atmospheric physics, engineering and satellite remote sensing and end-users such as companies in the private sector, all with the appropriate expertise to integrate the most advanced research methods and techniques in the following topics. MODELING: GLOBAL-TO-MESO SCALE: Analytical and process oriented numerical models will be used to study the interaction between the atmosphere and the ocean on a regional scale. Initial results indicate an interaction between the intensity of polar lows and the subsurface warm core often present in the Nordic Seas (11). The presence of waves, mainly swell, influence the MABL fluxes and turbulence structure. The regional and global wave effect on the atmosphere will be also studied and quantified (7) MESO-SCALE: Applicability of the planetary boundary layer (PBL) parametrizations in the meso-scale WRF model to marine atmospheric boundary layer (MABL) over the North Sea is investigated. The most suitable existing PBL parametrization will be additionally improved and used for downscaling North Sea past and future climates (2). Application of the meso-scale model (MM5 and WRF) for the wind energy in off-shore and coastal area. Set-up of the meso-scale model, post-processing and verification of the data from

Multifunctional Mesoscale Observing Networks.

NASA Astrophysics Data System (ADS)

Dabberdt, Walter F.; Schlatter, Thomas W.; Carr, Frederick H.; Friday, Elbert W. Joe; Jorgensen, David; Koch, Steven; Pirone, Maria; Ralph, F. Martin; Sun, Juanzhen; Welsh, Patrick; Wilson, James W.; Zou, Xiaolei

2005-07-01

More than 120 scientists, engineers, administrators, and users met on 8 10 December 2003 in a workshop format to discuss the needs for enhanced three-dimensional mesoscale observing networks. Improved networks are seen as being critical to advancing numerical and empirical modeling for a variety of mesoscale applications, including severe weather warnings and forecasts, hydrology, air-quality forecasting, chemical emergency response, transportation safety, energy management, and others. The participants shared a clear and common vision for the observing requirements: existing two-dimensional mesoscale measurement networks do not provide observations of the type, frequency, and density that are required to optimize mesoscale prediction and nowcasts. To be viable, mesoscale observing networks must serve multiple applications, and the public, private, and academic sectors must all actively participate in their design and implementation, as well as in the creation and delivery of value-added products. The mesoscale measurement challenge can best be met by an integrated approach that considers all elements of an end-to-end solution—identifying end users and their needs, designing an optimal mix of observations, defining the balance between static and dynamic (targeted or adaptive) sampling strategies, establishing long-term test beds, and developing effective implementation strategies. Detailed recommendations are provided pertaining to nowcasting, numerical prediction and data assimilation, test beds, and implementation strategies.

DeepID-Net: Deformable Deep Convolutional Neural Networks for Object Detection.

PubMed

Ouyang, Wanli; Zeng, Xingyu; Wang, Xiaogang; Qiu, Shi; Luo, Ping; Tian, Yonglong; Li, Hongsheng; Yang, Shuo; Wang, Zhe; Li, Hongyang; Loy, Chen Change; Wang, Kun; Yan, Junjie; Tang, Xiaoou

2016-07-07

In this paper, we propose deformable deep convolutional neural networks for generic object detection. This new deep learning object detection framework has innovations in multiple aspects. In the proposed new deep architecture, a new deformation constrained pooling (def-pooling) layer models the deformation of object parts with geometric constraint and penalty. A new pre-training strategy is proposed to learn feature representations more suitable for the object detection task and with good generalization capability. By changing the net structures, training strategies, adding and removing some key components in the detection pipeline, a set of models with large diversity are obtained, which significantly improves the effectiveness of model averaging. The proposed approach improves the mean averaged precision obtained by RCNN [16], which was the state-of-the-art, from 31% to 50.3% on the ILSVRC2014 detection test set. It also outperforms the winner of ILSVRC2014, GoogLeNet, by 6.1%. Detailed component-wise analysis is also provided through extensive experimental evaluation, which provides a global view for people to understand the deep learning object detection pipeline.

Topology of the European Network of Earth Observation Networks and the need for an European Network of Networks

NASA Astrophysics Data System (ADS)

Masó, Joan; Serral, Ivette; McCallum, Ian; Blonda, Palma; Plag, Hans-Peter

2016-04-01

ConnectinGEO (Coordinating an Observation Network of Networks EnCompassing saTellite and IN-situ to fill the Gaps in European Observations" is an H2020 Coordination and Support Action with the primary goal of linking existing Earth Observation networks with science and technology (S&T) communities, the industry sector, the Group on Earth Observations (GEO), and Copernicus. The project will end in February 2017. ConnectinGEO will initiate a European Network of Earth Observation Networks (ENEON) that will encompass space-based, airborne and in-situ observations networks. ENEON will be composed of project partners representing thematic observation networks along with the GEOSS Science and Technology Stakeholder Network, GEO Communities of Practices, Copernicus services, Sentinel missions and in-situ support data representatives, representatives of the European space-based, airborne and in-situ observations networks. This communication presents the complex panorama of Earth Observations Networks in Europe. The list of networks is classified by discipline, variables, geospatial scope, etc. We also capture the membership and relations with other networks and umbrella organizations like GEO. The result is a complex interrelation between networks that can not be clearly expressed in a flat list. Technically the networks can be represented as nodes with relations between them as lines connecting the nodes in a graph. We have chosen RDF as a language and an AllegroGraph 3.3 triple store that is visualized in several ways using for example Gruff 5.7. Our final aim is to identify gaps in the EO Networks and justify the need for a more structured coordination between them.

ENERGY-NET (Energy, Environment and Society Learning Network): Enhancing opportunities for learning using an Earth systems science framework

NASA Astrophysics Data System (ADS)

Elliott, E. M.; Bain, D. J.; Divers, M. T.; Crowley, K. J.; Povis, K.; Scardina, A.; Steiner, M.

2012-12-01

We describe a newly funded collaborative NSF initiative, ENERGY-NET (Energy, Environment and Society Learning Network), that brings together the Carnegie Museum of Natural History (CMNH) with the Learning Science and Geoscience research strengths at the University of Pittsburgh. ENERGY-NET aims to create rich opportunities for participatory learning and public education in the arena of energy, the environment, and society using an Earth systems science framework. We build upon a long-established teen docent program at CMNH and to form Geoscience Squads comprised of underserved teens. Together, the ENERGY-NET team, including museum staff, experts in informal learning sciences, and geoscientists spanning career stage (undergraduates, graduate students, faculty) provides inquiry-based learning experiences guided by Earth systems science principles. Together, the team works with Geoscience Squads to design "Exploration Stations" for use with CMNH visitors that employ an Earth systems science framework to explore the intersecting lenses of energy, the environment, and society. The goals of ENERGY-NET are to: 1) Develop a rich set of experiential learning activities to enhance public knowledge about the complex dynamics between Energy, Environment, and Society for demonstration at CMNH; 2) Expand diversity in the geosciences workforce by mentoring underrepresented teens, providing authentic learning experiences in earth systems science and life skills, and providing networking opportunities with geoscientists; and 3) Institutionalize ENERGY-NET collaborations among geosciences expert, learning researchers, and museum staff to yield long-term improvements in public geoscience education and geoscience workforce recruiting.

Dissecting engineered cell types and enhancing cell fate conversion via CellNet

PubMed Central

Morris, Samantha A.; Cahan, Patrick; Li, Hu; Zhao, Anna M.; San Roman, Adrianna K.; Shivdasani, Ramesh A.; Collins, James J.; Daley, George Q.

2014-01-01

SUMMARY Engineering clinically relevant cells in vitro holds promise for regenerative medicine, but most protocols fail to faithfully recapitulate target cell properties. To address this, we developed CellNet, a network biology platform that determines whether engineered cells are equivalent to their target tissues, diagnoses aberrant gene regulatory networks, and prioritizes candidate transcriptional regulators to enhance engineered conversions. Using CellNet, we improved B cell to macrophage conversion, transcriptionally and functionally, by knocking down predicted B cell regulators. Analyzing conversion of fibroblasts to induced hepatocytes (iHeps), CellNet revealed an unexpected intestinal program regulated by the master regulator Cdx2. We observed long-term functional engraftment of mouse colon by iHeps, thereby establishing their broader potential as endoderm progenitors and demonstrating direct conversion of fibroblasts into intestinal epithelium. Our studies illustrate how CellNet can be employed to improve direct conversion and to uncover unappreciated properties of engineered cells. PMID:25126792

Rich-Cores in Networks

PubMed Central

Ma, Athen; Mondragón, Raúl J.

2015-01-01

A core comprises of a group of central and densely connected nodes which governs the overall behaviour of a network. It is recognised as one of the key meso-scale structures in complex networks. Profiling this meso-scale structure currently relies on a limited number of methods which are often complex and parameter dependent or require a null model. As a result, scalability issues are likely to arise when dealing with very large networks together with the need for subjective adjustment of parameters. The notion of a rich-club describes nodes which are essentially the hub of a network, as they play a dominating role in structural and functional properties. The definition of a rich-club naturally emphasises high degree nodes and divides a network into two subgroups. Here, we develop a method to characterise a rich-core in networks by theoretically coupling the underlying principle of a rich-club with the escape time of a random walker. The method is fast, scalable to large networks and completely parameter free. In particular, we show that the evolution of the core in World Trade and C. elegans networks correspond to responses to historical events and key stages in their physical development, respectively. PMID:25799585

Rich-cores in networks.

PubMed

Ma, Athen; Mondragón, Raúl J

2015-01-01

A core comprises of a group of central and densely connected nodes which governs the overall behaviour of a network. It is recognised as one of the key meso-scale structures in complex networks. Profiling this meso-scale structure currently relies on a limited number of methods which are often complex and parameter dependent or require a null model. As a result, scalability issues are likely to arise when dealing with very large networks together with the need for subjective adjustment of parameters. The notion of a rich-club describes nodes which are essentially the hub of a network, as they play a dominating role in structural and functional properties. The definition of a rich-club naturally emphasises high degree nodes and divides a network into two subgroups. Here, we develop a method to characterise a rich-core in networks by theoretically coupling the underlying principle of a rich-club with the escape time of a random walker. The method is fast, scalable to large networks and completely parameter free. In particular, we show that the evolution of the core in World Trade and C. elegans networks correspond to responses to historical events and key stages in their physical development, respectively.

Strong-motion observations of the M 7.8 Gorkha, Nepal, earthquake sequence and development of the N-shake strong-motion network

USGS Publications Warehouse

Dixit, Amod; Ringler, Adam; Sumy, Danielle F.; Cochran, Elizabeth S.; Hough, Susan E.; Martin, Stacey; Gibbons, Steven; Luetgert, James H.; Galetzka, John; Shrestha, Surya; Rajaure, Sudhir; McNamara, Daniel E.

2015-01-01

We present and describe strong-motion data observations from the 2015 M 7.8 Gorkha, Nepal, earthquake sequence collected using existing and new Quake-Catcher Network (QCN) and U.S. Geological Survey NetQuakes sensors located in the Kathmandu Valley. A comparison of QCN data with waveforms recorded by a conventional strong-motion (NetQuakes) instrument validates the QCN data. We present preliminary analysis of spectral accelerations, and peak ground acceleration and velocity for earthquakes up to M 7.3 from the QCN stations, as well as preliminary analysis of the mainshock recording from the NetQuakes station. We show that mainshock peak accelerations were lower than expected and conclude the Kathmandu Valley experienced a pervasively nonlinear response during the mainshock. Phase picks from the QCN and NetQuakes data are also used to improve aftershock locations. This study confirms the utility of QCN instruments to contribute to ground-motion investigations and aftershock response in regions where conventional instrumentation and open-access seismic data are limited. Initial pilot installations of QCN instruments in 2014 are now being expanded to create the Nepal–Shaking Hazard Assessment for Kathmandu and its Environment (N-SHAKE) network.

CoryneRegNet 3.0--an interactive systems biology platform for the analysis of gene regulatory networks in corynebacteria and Escherichia coli.

PubMed

Baumbach, Jan; Wittkop, Tobias; Rademacher, Katrin; Rahmann, Sven; Brinkrolf, Karina; Tauch, Andreas

2007-04-30

CoryneRegNet is an ontology-based data warehouse for the reconstruction and visualization of transcriptional regulatory interactions in prokaryotes. To extend the biological content of CoryneRegNet, we added comprehensive data on transcriptional regulations in the model organism Escherichia coli K-12, originally deposited in the international reference database RegulonDB. The enhanced web interface of CoryneRegNet offers several types of search options. The results of a search are displayed in a table-based style and include a visualization of the genetic organization of the respective gene region. Information on DNA binding sites of transcriptional regulators is depicted by sequence logos. The results can also be displayed by several layouters implemented in the graphical user interface GraphVis, allowing, for instance, the visualization of genome-wide network reconstructions and the homology-based inter-species comparison of reconstructed gene regulatory networks. In an application example, we compare the composition of the gene regulatory networks involved in the SOS response of E. coli and Corynebacterium glutamicum. CoryneRegNet is available at the following URL: http://www.cebitec.uni-bielefeld.de/groups/gi/software/coryneregnet/.

Network of Women in Higher Education in the Pacific (NetWHEP). Report of Meeting of September 28-October 1, 1996.

ERIC Educational Resources Information Center

Network of Women in Higher Education in the Pacific, Suva (Fiji).

This report of a meeting of the Network of Women in Higher Education in the Pacific (NetWHEP) contains transcripts of major addresses, a copy of the program, statistics and summary information relating to the status of women in higher education for nine countries, and general information about the NetWHEP organization. Included are: a transcript…

AuRu/meso-Mn2O3: A Highly Active and Stable Catalyst for Methane Combustion

NASA Astrophysics Data System (ADS)

Han, Z.; Fang, J. Y.; Xie, S. H.; Deng, J. G.; Liu, Y. X.; Dai, H. X.

2018-05-01

Three-dimensionally ordered mesoporous Mn2O3 (meso-Mn2O3) and its supported Au, Ru, and AuRu alloy (0.49 wt% Au/meso-Mn2O3, 0.48 wt% Ru/meso-Mn2O3, and 0.97 wt% AuRu/meso-Mn2O3 (Au/Ru molar ratio = 0.98)) nanocatalysts were prepared using the KIT-6-templating and polyvinyl alcohol-protected reduction methods, respectively. Physicochemical properties of the samples were characterized by means of numerous techniques, and their catalytic activities were evaluated for the combustion of methane. It is found that among all of the samples, 0.48 wt% Ru/meso-Mn 2O3 and 0.97 wt% AuRu/meso-Mn2O3 performed the best (the reaction temperature (T90% ) at 90% methane conversion was 530-540°C), but the latter showed a better thermal stability than the former. The partial deactivation of 0.97 wt% AuRu/meso-Mn2O3 due to H2O or CO2 introduction was reversible. It is concluded that the good catalytic activity and thermal stability of 0.97 wt% AuRu/meso-Mn2O3 was associated with the high dispersion of AuRu alloy NPs (2-5 nm) on the surface of meso-Mn2O3 and good low-temperature reducibility.

Atmospheric CO2 Observations Reveal Strong Correlation Between Regional Net Biospheric Carbon Uptake and Solar-Induced Chlorophyll Fluorescence

NASA Astrophysics Data System (ADS)

Shiga, Yoichi P.; Tadić, Jovan M.; Qiu, Xuemei; Yadav, Vineet; Andrews, Arlyn E.; Berry, Joseph A.; Michalak, Anna M.

2018-01-01

Recent studies have shown the promise of remotely sensed solar-induced chlorophyll fluorescence (SIF) in informing terrestrial carbon exchange, but analyses have been limited to either plot level ( 1 km2) or hemispheric/global ( 108 km2) scales due to the lack of a direct measure of carbon exchange at intermediate scales. Here we use a network of atmospheric CO2 observations over North America to explore the value of SIF for informing net ecosystem exchange (NEE) at regional scales. We find that SIF explains space-time NEE patterns at regional ( 100 km2) scales better than a variety of other vegetation and climate indicators. We further show that incorporating SIF into an atmospheric inversion leads to a spatial redistribution of NEE estimates over North America, with more uptake attributed to agricultural regions and less to needleleaf forests. Our results highlight the synergy of ground-based and spaceborne carbon cycle observations.

Extending Value of Information Methods to Include the Co-Net Benefits of Earth Observations

NASA Astrophysics Data System (ADS)

Macauley, M.

2015-12-01

The widening relevance of Earth observations information across the spectrum of natural and environmental resources markedly enhances the value of these observations. An example is observations of forest extent, species composition, health, and change; this information can help in assessing carbon sequestration, biodiversity and habitat, watershed management, fuelwood potential, and other ecosystem services as well as inform the opportunity cost of forest removal for alternative land use such as agriculture, pasture, or development. These "stacked" indicators or co- net benefits add significant value to Earth observations. In part because of reliance on case studies, much previous research about the value of information from Earth observations has assessed individual applications rather than aggregate across applications, thus tending to undervalue the observations. Aggregating across applications is difficult, however, because it requires common units of measurement: controlling for spatial, spectral, and temporal attributes of the observations; and consistent application of value of information techniques. This paper will discuss general principles of co-net benefit aggregation and illustrate its application to attributing value to Earth observations.

Implementing neural nets with programmable logic

NASA Technical Reports Server (NTRS)

Vidal, Jacques J.

1988-01-01

Networks of Boolean programmable logic modules are presented as one purely digital class of artificial neural nets. The approach contrasts with the continuous analog framework usually suggested. Programmable logic networks are capable of handling many neural-net applications. They avoid some of the limitations of threshold logic networks and present distinct opportunities. The network nodes are called dynamically programmable logic modules. They can be implemented with digitally controlled demultiplexers. Each node performs a Boolean function of its inputs which can be dynamically assigned. The overall network is therefore a combinational circuit and its outputs are Boolean global functions of the network's input variables. The approach offers definite advantages for VLSI implementation, namely, a regular architecture with limited connectivity, simplicity of the control machinery, natural modularity, and the support of a mature technology.

Limitations of shallow nets approximation.

PubMed

Lin, Shao-Bo

2017-10-01

In this paper, we aim at analyzing the approximation abilities of shallow networks in reproducing kernel Hilbert spaces (RKHSs). We prove that there is a probability measure such that the achievable lower bound for approximating by shallow nets can be realized for all functions in balls of reproducing kernel Hilbert space with high probability, which is different with the classical minimax approximation error estimates. This result together with the existing approximation results for deep nets shows the limitations for shallow nets and provides a theoretical explanation on why deep nets perform better than shallow nets. Copyright © 2017 Elsevier Ltd. All rights reserved.

Validation and correction of rainfall data from the WegenerNet high density network in southeast Austria

NASA Astrophysics Data System (ADS)

O, Sungmin; Foelsche, U.; Kirchengast, G.; Fuchsberger, J.

2018-01-01

Eight years of daily rainfall data from WegenerNet were analyzed by comparison with data from Austrian national weather stations. WegenerNet includes 153 ground level weather stations in an area of about 15 km × 20 km in the Feldbach region in southeast Austria. Rainfall has been measured by tipping bucket gauges at 150 stations of the network since the beginning of 2007. Since rain gauge measurements are considered close to true rainfall, there are increasing needs for WegenerNet data for the validation of rainfall data products such as remote sensing based estimates or model outputs. Serving these needs, this paper aims at providing a clearer interpretation on WegenerNet rainfall data for users in hydro-meteorological communities. Five clusters - a cluster consists of one national weather station and its four closest WegenerNet stations - allowed us close comparison of datasets between the stations. Linear regression analysis and error estimation with statistical indices were conducted to quantitatively evaluate the WegenerNet daily rainfall data. It was found that rainfall data between the stations show good linear relationships with an average correlation coefficient (r) of 0.97 , while WegenerNet sensors tend to underestimate rainfall according to the regression slope (0.87). For the five clusters investigated, the bias and relative bias were - 0.97 mm d-1 and - 11.5 % on average (except data from new sensors). The average of bias and relative bias, however, could be reduced by about 80 % through a simple linear regression-slope correction, with the assumption that the underestimation in WegenerNet data was caused by systematic errors. The results from the study have been employed to improve WegenerNet data for user applications so that a new version of the data (v5) is now available at the WegenerNet data portal (www.wegenernet.org).

Site Assessment of a New State-Wide Seismic Network in Texas (TexNet)

NASA Astrophysics Data System (ADS)

Savvaidis, A.; Young, B.; Mukherjee, T.; Hennings, P.; Rathje, E.; Zalachoris, G.; Young, M.; Walter, J. I.; DeShon, H. R.; Frohlich, C.

2016-12-01

Earthquake activity has recently increased in the southern mid-continent of the U.S., including Texas. To monitor seismicity activity in the state of Texas, a new seismicity monitoring program known as TexNet, was funded by the Texas State Legislature in 2015. TexNet consists of 22 new permanent broadband (120s post-hole) seismic stations that will complement the 17 stations currently operating in the State. These permanent stations will provide the baseline seismicity of the state. In addition, 36 portable stations (incorporating both a 20s post-hole seismometer and a post-hole accelerometer) will be used to densify the network in specific areas, of the State, depending on measured seismicity level, proximity to infrastructure, or other scientific investigations. One goal for TexNet is to provide authenticated data needed to evaluate the location, and frequency of earthquakes. To minimize the uncertainties in earthquake locations and increase detectability of the network, an extensive site assessment survey was conducted. The initial station positions were chosen based on Earthscope, Transportable Array (TA) site positions, while ensuring that the stations were relatively evenly-spaced across the State. We then analyzed the noise and earthquake data from the TA seismometers, and added new locations based on geology, topography, and absence of nearby human activities. A 30-min noise test was conducted at each site to identify the site amplification using HVSR information. A 24-hr survey then followed, where the noise level during day and night was identified, analyzed using power spectral density and compared to the NHNM and NLNM (Peterson, 1993; USGS Open File Report, 322). Based on these survey results nearby alternative sites were evaluated to improve final site position. Full deployment and data streaming is expected by December 2016, and will be discussed during this presentation.

Aerosol observation using multi-wavelength Mie-Raman lidars of the Ad-Net and aerosol component analysis

NASA Astrophysics Data System (ADS)

Nishizawa, Tomoaki; Sugimoto, Nobuo; Shimizu, Atsushi; Uno, Itsushi; Hara, Yukari; Kudo, Rei

2018-04-01

We deployed multi-wavelength Mie-Raman lidars (MMRL) at three sites of the AD-Net and have conducted continuous measurements using them since 2013. To analyze the MMRL data and better understand the externally mixing state of main aerosol components (e.g., dust, sea-salt, and black carbon) in the atmosphere, we developed an integrated package of aerosol component retrieval algorithms, which have already been developed or are being developed, to estimate vertical profiles of the aerosol components. This package applies to the other ground-based lidar network data (e.g., EARLINET) and satellite-borne lidar data (e.g., CALIOP/CALIPSO and ATLID/EarthCARE) as well as the other lidar data of the AD-Net.

Utilizing semantic networks to database and retrieve generalized stochastic colored Petri nets

NASA Technical Reports Server (NTRS)

Farah, Jeffrey J.; Kelley, Robert B.

1992-01-01

Previous work has introduced the Planning Coordinator (PCOORD), a coordinator functioning within the hierarchy of the Intelligent Machine Mode. Within the structure of the Planning Coordinator resides the Primitive Structure Database (PSDB) functioning to provide the primitive structures utilized by the Planning Coordinator in the establishing of error recovery or on-line path plans. This report further explores the Primitive Structure Database and establishes the potential of utilizing semantic networks as a means of efficiently storing and retrieving the Generalized Stochastic Colored Petri Nets from which the error recovery plans are derived.

CellNetVis: a web tool for visualization of biological networks using force-directed layout constrained by cellular components.

PubMed

Heberle, Henry; Carazzolle, Marcelo Falsarella; Telles, Guilherme P; Meirelles, Gabriela Vaz; Minghim, Rosane

2017-09-13

The advent of "omics" science has brought new perspectives in contemporary biology through the high-throughput analyses of molecular interactions, providing new clues in protein/gene function and in the organization of biological pathways. Biomolecular interaction networks, or graphs, are simple abstract representations where the components of a cell (e.g. proteins, metabolites etc.) are represented by nodes and their interactions are represented by edges. An appropriate visualization of data is crucial for understanding such networks, since pathways are related to functions that occur in specific regions of the cell. The force-directed layout is an important and widely used technique to draw networks according to their topologies. Placing the networks into cellular compartments helps to quickly identify where network elements are located and, more specifically, concentrated. Currently, only a few tools provide the capability of visually organizing networks by cellular compartments. Most of them cannot handle large and dense networks. Even for small networks with hundreds of nodes the available tools are not able to reposition the network while the user is interacting, limiting the visual exploration capability. Here we propose CellNetVis, a web tool to easily display biological networks in a cell diagram employing a constrained force-directed layout algorithm. The tool is freely available and open-source. It was originally designed for networks generated by the Integrated Interactome System and can be used with networks from others databases, like InnateDB. CellNetVis has demonstrated to be applicable for dynamic investigation of complex networks over a consistent representation of a cell on the Web, with capabilities not matched elsewhere.

Review of FEWS NET Biophysical Monitoring Requirements

NASA Technical Reports Server (NTRS)

Ross, K. W.; Brown, Molly E.; Verdin, J.; Underwood, L. W.

2009-01-01

The Famine Early Warning System Network (FEWS NET) provides monitoring and early warning support to decision makers responsible for responding to famine and food insecurity. FEWS NET transforms satellite remote sensing data into rainfall and vegetation information that can be used by these decision makers. The National Aeronautics and Space Administration has recently funded activities to enhance remote sensing inputs to FEWS NET. To elicit Earth observation requirements, a professional review questionnaire was disseminated to FEWS NET expert end-users: it focused upon operational requirements to determine additional useful remote sensing data and; subsequently, beneficial FEWS NET biophysical supplementary inputs. The review was completed by over 40 experts from around the world, enabling a robust set of professional perspectives to be gathered and analyzed rapidly. Reviewers were asked to evaluate the relative importance of environmental variables and spatio-temporal requirements for Earth science data products, in particular for rainfall and vegetation products. The results showed that spatio-temporal resolution requirements are complex and need to vary according to place, time, and hazard: that high resolution remote sensing products continue to be in demand, and that rainfall and vegetation products were valued as data that provide actionable food security information.

Surface Net Solar Radiation Estimated from Satellite Measurements: Comparisons with Tower Observations

NASA Technical Reports Server (NTRS)

Li, Zhanqing; Leighton, H. G.; Cess, Robert D.

1993-01-01

A parameterization that relates the reflected solar flux at the top of the atmosphere to the net solar flux at the surface in terms of only the column water vapor amount and the solar zenith angle was tested against surface observations. Net surface fluxes deduced from coincidental collocated satellite-measured radiances and from measurements from towers in Boulder during summer and near Saskatoon in winter have mean differences of about 2 W/sq m, regardless of whether the sky is clear or cloudy. Furthermore, comparisons between the net fluxes deduced from the parameterization and from surface measurements showed equally good agreement when the data were partitioned into morning and afternoon observations. This is in contrast to results from an empirical clear-sky algorithm that is unable to account adequately for the effects of clouds and that shows, at Boulder, a distinct morning to afternoon variation, which is presumably due to the predominance of different cloud types throughout the day. It is also demonstrated that the parameterization may be applied to irradiances at the top of the atmosphere that have been temporally averaged by using the temporally averaged column water vapor amount and the temporally averaged cosine of the solar zenith angle. The good agreement between the results of the parameterization and surface measurements suggests that the algorithm is a useful tool for a variety of climate studies.

STEPP--Search Tool for Exploration of Petri net Paths: a new tool for Petri net-based path analysis in biochemical networks.

PubMed

Koch, Ina; Schueler, Markus; Heiner, Monika

2005-01-01

To understand biochemical processes caused by, e. g., mutations or deletions in the genome, the knowledge of possible alternative paths between two arbitrary chemical compounds is of increasing interest for biotechnology, pharmacology, medicine, and drug design. With the steadily increasing amount of data from high-throughput experiments new biochemical networks can be constructed and existing ones can be extended, which results in many large metabolic, signal transduction, and gene regulatory networks. The search for alternative paths within these complex and large networks can provide a huge amount of solutions, which can not be handled manually. Moreover, not all of the alternative paths are generally of interest. Therefore, we have developed and implemented a method, which allows us to define constraints to reduce the set of all structurally possible paths to the truly interesting path set. The paper describes the search algorithm and the constraints definition language. We give examples for path searches using this dedicated special language for a Petri net model of the sucrose-to-starch breakdown in the potato tuber.

STEPP - Search Tool for Exploration of Petri net Paths: A New Tool for Petri Net-Based Path Analysis in Biochemical Networks.

PubMed

Koch, Ina; Schüler, Markus; Heiner, Monika

2011-01-01

To understand biochemical processes caused by, e.g., mutations or deletions in the genome, the knowledge of possible alternative paths between two arbitrary chemical compounds is of increasing interest for biotechnology, pharmacology, medicine, and drug design. With the steadily increasing amount of data from high-throughput experiments new biochemical networks can be constructed and existing ones can be extended, which results in many large metabolic, signal transduction, and gene regulatory networks. The search for alternative paths within these complex and large networks can provide a huge amount of solutions, which can not be handled manually. Moreover, not all of the alternative paths are generally of interest. Therefore, we have developed and implemented a method, which allows us to define constraints to reduce the set of all structurally possible paths to the truly interesting path set. The paper describes the search algorithm and the constraints definition language. We give examples for path searches using this dedicated special language for a Petri net model of the sucrose-to-starch breakdown in the potato tuber. http://sanaga.tfh-berlin.de/~stepp/

MPL-net at ARM Sites

NASA Technical Reports Server (NTRS)

Spinhirne, J. D.; Welton, E. J.; Campbell, J. R.; Berkoff, T. A.; Starr, David OC. (Technical Monitor)

2002-01-01

The NASA MPL-net project goal is consistent data products of the vertical distribution of clouds and aerosol from globally distributed lidar observation sites. The four ARM micro pulse lidars are a basis of the network to consist of over twelve sites. The science objective is ground truth for global satellite retrievals and accurate vertical distribution information in combination with surface radiation measurements for aerosol and cloud models. The project involves improvement in instruments and data processing and cooperation with ARM and other partners.

PetriScape - A plugin for discrete Petri net simulations in Cytoscape.

PubMed

Almeida, Diogo; Azevedo, Vasco; Silva, Artur; Baumbach, Jan

2016-06-04

Systems biology plays a central role for biological network analysis in the post-genomic era. Cytoscape is the standard bioinformatics tool offering the community an extensible platform for computational analysis of the emerging cellular network together with experimental omics data sets. However, only few apps/plugins/tools are available for simulating network dynamics in Cytoscape 3. Many approaches of varying complexity exist but none of them have been integrated into Cytoscape as app/plugin yet. Here, we introduce PetriScape, the first Petri net simulator for Cytoscape. Although discrete Petri nets are quite simplistic models, they are capable of modeling global network properties and simulating their behaviour. In addition, they are easily understood and well visualizable. PetriScape comes with the following main functionalities: (1) import of biological networks in SBML format, (2) conversion into a Petri net, (3) visualization as Petri net, and (4) simulation and visualization of the token flow in Cytoscape. PetriScape is the first Cytoscape plugin for Petri nets. It allows a straightforward Petri net model creation, simulation and visualization with Cytoscape, providing clues about the activity of key components in biological networks.

PetriScape - A plugin for discrete Petri net simulations in Cytoscape.

PubMed

Almeida, Diogo; Azevedo, Vasco; Silva, Artur; Baumbach, Jan

2016-03-01

Systems biology plays a central role for biological network analysis in the post-genomic era. Cytoscape is the standard bioinformatics tool offering the community an extensible platform for computational analysis of the emerging cellular network together with experimental omics data sets. However, only few apps/plugins/tools are available for simulating network dynamics in Cytoscape 3. Many approaches of varying complexity exist but none of them have been integrated into Cytoscape as app/plugin yet. Here, we introduce PetriScape, the first Petri net simulator for Cytoscape. Although discrete Petri nets are quite simplistic models, they are capable of modeling global network properties and simulating their behaviour. In addition, they are easily understood and well visualizable. PetriScape comes with the following main functionalities: (1) import of biological networks in SBML format, (2) conversion into a Petri net, (3) visualization as Petri net, and (4) simulation and visualization of the token flow in Cytoscape. PetriScape is the first Cytoscape plugin for Petri nets. It allows a straightforward Petri net model creation, simulation and visualization with Cytoscape, providing clues about the activity of key components in biological networks.

Markets, voucher subsidies and free nets combine to achieve high bed net coverage in rural Tanzania.

PubMed

Khatib, Rashid A; Killeen, Gerry F; Abdulla, Salim M K; Kahigwa, Elizeus; McElroy, Peter D; Gerrets, Rene P M; Mshinda, Hassan; Mwita, Alex; Kachur, S Patrick

2008-06-02

Tanzania has a well-developed network of commercial ITN retailers. In 2004, the government introduced a voucher subsidy for pregnant women and, in mid 2005, helped distribute free nets to under-fives in small number of districts, including Rufiji on the southern coast, during a child health campaign. Contributions of these multiple insecticide-treated net delivery strategies existing at the same time and place to coverage in a poor rural community were assessed. Cross-sectional household survey in 6,331 members of randomly selected 1,752 households of 31 rural villages of Demographic Surveillance System in Rufiji district, Southern Tanzania was conducted in 2006. A questionnaire was administered to every consenting respondent about net use, treatment status and delivery mechanism. Net use was 62.7% overall, 87.2% amongst infants (0 to 1 year), 81.8% amongst young children (>1 to 5 years), 54.5% amongst older children (6 to 15 years) and 59.6% amongst adults (>15 years). 30.2% of all nets had been treated six months prior to interview. The biggest source of nets used by infants was purchase from the private sector with a voucher subsidy (41.8%). Half of nets used by young children (50.0%) and over a third of those used by older children (37.2%) were obtained free of charge through the vaccination campaign. The largest source of nets amongst the population overall was commercial purchase (45.1% use) and was the primary means for protecting adults (60.2% use). All delivery mechanisms, especially sale of nets at full market price, under-served the poorest but no difference in equity was observed between voucher-subsidized and freely distributed nets. All three delivery strategies enabled a poor rural community to achieve net coverage high enough to yield both personal and community level protection for the entire population. Each of them reached their relevant target group and free nets only temporarily suppressed the net market, illustrating that in this setting that

Spreading paths in partially observed social networks

NASA Astrophysics Data System (ADS)

Onnela, Jukka-Pekka; Christakis, Nicholas A.

2012-03-01

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

Spreading paths in partially observed social networks.

PubMed

Onnela, Jukka-Pekka; Christakis, Nicholas A

2012-03-01

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

Neural network-based estimates of Southern Ocean net community production from in-situ O2 / Ar and satellite observation: a methodological study

NASA Astrophysics Data System (ADS)

Chang, C.-H.; Johnson, N. C.; Cassar, N.

2013-10-01

Southern Ocean organic carbon export plays an important role in the global carbon cycle, yet its basin-scale climatology and variability are uncertain due to limited coverage of in situ observations. In this study, a neural network approach based on the self-organizing map (SOM) is adopted to construct weekly gridded (1° × 1°) maps of organic carbon export for the Southern Ocean from 1998 to 2009. The SOM is trained with in situ measurements of O2 / Ar-derived net community production (NCP) that are tightly linked to the carbon export in the mixed layer on timescales of 1-2 weeks, and six potential NCP predictors: photosynthetically available radiation (PAR), particulate organic carbon (POC), chlorophyll (Chl), sea surface temperature (SST), sea surface height (SSH), and mixed layer depth (MLD). This non-parametric approach is based entirely on the observed statistical relationships between NCP and the predictors, and therefore is strongly constrained by observations. A thorough cross-validation yields three retained NCP predictors, Chl, PAR, and MLD. Our constructed NCP is further validated by good agreement with previously published independent in situ derived NCP of weekly or longer temporal resolution through real-time and climatological comparisons at various sampling sites. The resulting November-March NCP climatology reveals a pronounced zonal band of high NCP roughly following the subtropical front in the Atlantic, Indian and western Pacific sectors, and turns southeastward shortly after the dateline. Other regions of elevated NCP include the upwelling zones off Chile and Namibia, Patagonian Shelf, Antarctic coast, and areas surrounding the Islands of Kerguelen, South Georgia, and Crozet. This basin-scale NCP climatology closely resembles that of the satellite POC field and observed air-sea CO2 flux. The long-term mean area-integrated NCP south of 50° S from our dataset, 14 mmol C m-2 d-1, falls within the range of 8.3-24 mmol C m-2 d-1 from other model

GhostNet marine debris survey in the Gulf of Alaska--satellite guidance and aircraft observations.

PubMed

Pichel, William G; Veenstra, Timothy S; Churnside, James H; Arabini, Elena; Friedman, Karen S; Foley, David G; Brainard, Russell E; Kiefer, Dale; Ogle, Simeon; Clemente-Colón, Pablo; Li, Xiaofeng

2012-01-01

Marine debris, particularly debris that is composed of lost or abandoned fishing gear, is recognized as a serious threat to marine life, vessels, and coral reefs. The goal of the GhostNet project is the detection of derelict nets at sea through the use of weather and ocean models, drifting buoys and satellite imagery to locate convergent areas where nets are likely to collect, followed by airborne surveys with trained observers and remote sensing instruments to spot individual derelict nets. These components of GhostNet were first tested together in the field during a 14-day marine debris survey of the Gulf of Alaska in July and August 2003. Model, buoy, and satellite data were used in flight planning. A manned aircraft survey with visible and IR cameras and a LIDAR instrument located debris in the targeted locations, including 102 individual pieces of debris of anthropogenic or terrestrial origin. Published by Elsevier Ltd.

AdaNET research project

NASA Technical Reports Server (NTRS)

Digman, R. Michael

1988-01-01

The components necessary for the success of the commercialization of an Ada Technology Transition Network are reported in detail. The organizational plan presents the planned structure for services development and technical transition of AdaNET services to potential user communities. The Business Plan is the operational plan for the AdaNET service as a commercial venture. The Technical Plan is the plan from which the AdaNET can be designed including detailed requirements analysis. Also contained is an analysis of user fees and charges, and a proposed user fee schedule.

A Science Cloud: OneSpaceNet

NASA Astrophysics Data System (ADS)

Morikawa, Y.; Murata, K. T.; Watari, S.; Kato, H.; Yamamoto, K.; Inoue, S.; Tsubouchi, K.; Fukazawa, K.; Kimura, E.; Tatebe, O.; Shimojo, S.

2010-12-01

Main methodologies of Solar-Terrestrial Physics (STP) so far are theoretical, experimental and observational, and computer simulation approaches. Recently "informatics" is expected as a new (fourth) approach to the STP studies. Informatics is a methodology to analyze large-scale data (observation data and computer simulation data) to obtain new findings using a variety of data processing techniques. At NICT (National Institute of Information and Communications Technology, Japan) we are now developing a new research environment named "OneSpaceNet". The OneSpaceNet is a cloud-computing environment specialized for science works, which connects many researchers with high-speed network (JGN: Japan Gigabit Network). The JGN is a wide-area back-born network operated by NICT; it provides 10G network and many access points (AP) over Japan. The OneSpaceNet also provides with rich computer resources for research studies, such as super-computers, large-scale data storage area, licensed applications, visualization devices (like tiled display wall: TDW), database/DBMS, cluster computers (4-8 nodes) for data processing and communication devices. What is amazing in use of the science cloud is that a user simply prepares a terminal (low-cost PC). Once connecting the PC to JGN2plus, the user can make full use of the rich resources of the science cloud. Using communication devices, such as video-conference system, streaming and reflector servers, and media-players, the users on the OneSpaceNet can make research communications as if they belong to a same (one) laboratory: they are members of a virtual laboratory. The specification of the computer resources on the OneSpaceNet is as follows: The size of data storage we have developed so far is almost 1PB. The number of the data files managed on the cloud storage is getting larger and now more than 40,000,000. What is notable is that the disks forming the large-scale storage are distributed to 5 data centers over Japan (but the storage

Observing Arctic Ecology using Networked Infomechanical Systems

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

Serving Real-Time Point Observation Data in netCDF using Climate and Forecasting Discrete Sampling Geometry Conventions

NASA Astrophysics Data System (ADS)

Ward-Garrison, C.; May, R.; Davis, E.; Arms, S. C.

2016-12-01

NetCDF is a set of software libraries and self-describing, machine-independent data formats that support the creation, access, and sharing of array-oriented scientific data. The Climate and Forecasting (CF) metadata conventions for netCDF foster the ability to work with netCDF files in general and useful ways. These conventions include metadata attributes for physical units, standard names, and spatial coordinate systems. While these conventions have been successful in easing the use of working with netCDF-formatted output from climate and forecast models, their use for point-based observation data has been less so. Unidata has prototyped using the discrete sampling geometry (DSG) CF conventions to serve, using the THREDDS Data Server, the real-time point observation data flowing across the Internet Data Distribution (IDD). These data originate in text format reports for individual stations (e.g. METAR surface data or TEMP upper air data) and are converted and stored in netCDF files in real-time. This work discusses the experiences and challenges of using the current CF DSG conventions for storing such real-time data. We also test how parts of netCDF's extended data model can address these challenges, in order to inform decisions for a future version of CF (CF 2.0) that would take advantage of features of the netCDF enhanced data model.

Percolation of a general network of networks.

PubMed

Gao, Jianxi; Buldyrev, Sergey V; Stanley, H Eugene; Xu, Xiaoming; Havlin, Shlomo

2013-12-01

Percolation theory is an approach to study the vulnerability of a system. We develop an analytical framework and analyze the percolation properties of a network composed of interdependent networks (NetONet). Typically, percolation of a single network shows that the damage in the network due to a failure is a continuous function of the size of the failure, i.e., the fraction of failed nodes. In sharp contrast, in NetONet, due to the cascading failures, the percolation transition may be discontinuous and even a single node failure may lead to an abrupt collapse of the system. We demonstrate our general framework for a NetONet composed of n classic Erdős-Rényi (ER) networks, where each network depends on the same number m of other networks, i.e., for a random regular network (RR) formed of interdependent ER networks. The dependency between nodes of different networks is taken as one-to-one correspondence, i.e., a node in one network can depend only on one node in the other network (no-feedback condition). In contrast to a treelike NetONet in which the size of the largest connected cluster (mutual component) depends on n, the loops in the RR NetONet cause the largest connected cluster to depend only on m and the topology of each network but not on n. We also analyzed the extremely vulnerable feedback condition of coupling, where the coupling between nodes of different networks is not one-to-one correspondence. In the case of NetONet formed of ER networks, percolation only exhibits two phases, a second order phase transition and collapse, and no first order percolation transition regime is found in the case of the no-feedback condition. In the case of NetONet composed of RR networks, there exists a first order phase transition when the coupling strength q (fraction of interdependency links) is large and a second order phase transition when q is small. Our insight on the resilience of coupled networks might help in designing robust interdependent systems.

Statistical adjustment of culture-independent diagnostic tests for trend analysis in the Foodborne Diseases Active Surveillance Network (FoodNet), USA.

PubMed

Gu, Weidong; Dutta, Vikrant; Patrick, Mary; Bruce, Beau B; Geissler, Aimee; Huang, Jennifer; Fitzgerald, Collette; Henao, Olga

2018-03-19

Culture-independent diagnostic tests (CIDTs) are increasingly used to diagnose Campylobacter infection in the Foodborne Diseases Active Surveillance Network (FoodNet). Because CIDTs have different performance characteristics compared with culture, which has been used historically and is still used to diagnose campylobacteriosis, adjustment of cases diagnosed by CIDT is needed to compare with culture-confirmed cases for monitoring incidence trends. We identified the necessary parameters for CIDT adjustment using culture as the gold standard, and derived formulas to calculate positive predictive values (PPVs). We conducted a literature review and meta-analysis to examine the variability in CIDT performance and Campylobacter prevalence applicable to FoodNet sites. We then developed a Monte Carlo method to estimate test-type and site-specific PPVs with their associated uncertainties. The uncertainty in our estimated PPVs was largely derived from uncertainty about the specificity of CIDTs and low prevalence of Campylobacter in tested samples. Stable CIDT-adjusted incidences of Campylobacter cases from 2012 to 2015 were observed compared with a decline in culture-confirmed incidence. We highlight the lack of data on the total numbers of tested samples as one of main limitations for CIDT adjustment. Our results demonstrate the importance of adjusting CIDTs for understanding trends in Campylobacter incidence in FoodNet.

Controlled release of ibuprofen by meso-macroporous silica

NASA Astrophysics Data System (ADS)

Santamaría, E.; Maestro, A.; Porras, M.; Gutiérrez, J. M.; González, C.

2014-02-01

Structured meso-macroporous silica was successfully synthesized from an O/W emulsion using decane as a dispersed phase. Sodium silicate solution, which acts as a silica source and a poly(ethylene oxide)-poly(propylene oxide)-poly(ethylene oxide) (EO19PO39EO19) denoted as P84 was used in order to stabilize the emulsion and as a mesopore template. The materials obtained were characterized through transmission electron microscopy (TEM), scanning electron microscopy (SEM), small-angle X-ray diffraction scattering (SAXS) and nitrogen adsorption-desorption isotherms. Ibuprofen (IBU) was selected as the model drug and loaded into ordered meso-macroporous materials. The effect of the materials’ properties on IBU drug loading and release was studied. The results showed that the loading of IBU increases as the macropore presence in the material is increased. The IBU adsorption process followed the Langmuir adsorption isotherm. A two-step release process, consisting of an initial fast release and then a slower release was observed. Macropores enhanced the adsorption capacity of the material; this was probably due to the fact that they allowed the drug to access internal pores. When only mesopores were present, ibuprofen was probably adsorbed on the mesopores close to the surface. Moreover, the more macropore present in the material, the slower the release behaviour observed, as the ibuprofen adsorbed in the internal pores had to diffuse along the macropore channels up to the surface of the material. The material obtained from a highly concentrated emulsion was functionalized with amino groups using two methods, the post-grafting mechanism and the co-condensation mechanism. Both routes improve IBU adsorption in the material and show good behaviour as a controlled drug delivery system.

ConvNetQuake: Convolutional Neural Network for Earthquake Detection and Location

NASA Astrophysics Data System (ADS)

Denolle, M.; Perol, T.; Gharbi, M.

2017-12-01

Over the last decades, the volume of seismic data has increased exponentially, creating a need for efficient algorithms to reliably detect and locate earthquakes. Today's most elaborate methods scan through the plethora of continuous seismic records, searching for repeating seismic signals. In this work, we leverage the recent advances in artificial intelligence and present ConvNetQuake, a highly scalable convolutional neural network for probabilistic earthquake detection and location from single stations. We apply our technique to study two years of induced seismicity in Oklahoma (USA). We detect 20 times more earthquakes than previously cataloged by the Oklahoma Geological Survey. Our algorithm detection performances are at least one order of magnitude faster than other established methods.

The multilocus sequence typing network: mlst.net.

PubMed

Aanensen, David M; Spratt, Brian G

2005-07-01

The unambiguous characterization of strains of a pathogen is crucial for addressing questions relating to its epidemiology, population and evolutionary biology. Multilocus sequence typing (MLST), which defines strains from the sequences at seven house-keeping loci, has become the method of choice for molecular typing of many bacterial and fungal pathogens (and non-pathogens), and MLST schemes and strain databases are available for a growing number of prokaryotic and eukaryotic organisms. Sequence data are ideal for strain characterization as they are unambiguous, meaning strains can readily be compared between laboratories via the Internet. Laboratories undertaking MLST can quickly progress from sequencing the seven gene fragments to characterizing their strains and relating them to those submitted by others and to the population as a whole. We provide the gateway to a number of MLST schemes, each of which contain a set of tools for the initial characterization of strains, and methods for relating query strains to other strains of the species, including clustering based on differences in allelic profiles, phylogenetic trees based on concatenated sequences, and a recently developed method (eBURST) for identifying clonal complexes within a species and displaying the overall structure of the population. This network of MLST websites is available at http://www.mlst.net.

SpectralNET--an application for spectral graph analysis and visualization.

PubMed

Forman, Joshua J; Clemons, Paul A; Schreiber, Stuart L; Haggarty, Stephen J

2005-10-19

Graph theory provides a computational framework for modeling a variety of datasets including those emerging from genomics, proteomics, and chemical genetics. Networks of genes, proteins, small molecules, or other objects of study can be represented as graphs of nodes (vertices) and interactions (edges) that can carry different weights. SpectralNET is a flexible application for analyzing and visualizing these biological and chemical networks. Available both as a standalone .NET executable and as an ASP.NET web application, SpectralNET was designed specifically with the analysis of graph-theoretic metrics in mind, a computational task not easily accessible using currently available applications. Users can choose either to upload a network for analysis using a variety of input formats, or to have SpectralNET generate an idealized random network for comparison to a real-world dataset. Whichever graph-generation method is used, SpectralNET displays detailed information about each connected component of the graph, including graphs of degree distribution, clustering coefficient by degree, and average distance by degree. In addition, extensive information about the selected vertex is shown, including degree, clustering coefficient, various distance metrics, and the corresponding components of the adjacency, Laplacian, and normalized Laplacian eigenvectors. SpectralNET also displays several graph visualizations, including a linear dimensionality reduction for uploaded datasets (Principal Components Analysis) and a non-linear dimensionality reduction that provides an elegant view of global graph structure (Laplacian eigenvectors). SpectralNET provides an easily accessible means of analyzing graph-theoretic metrics for data modeling and dimensionality reduction. SpectralNET is publicly available as both a .NET application and an ASP.NET web application from http://chembank.broad.harvard.edu/resources/. Source code is available upon request.

Autism BrainNet: A network of postmortem brain banks established to facilitate autism research.

PubMed

Amaral, David G; Anderson, Matthew P; Ansorge, Olaf; Chance, Steven; Hare, Carolyn; Hof, Patrick R; Miller, Melissa; Nagakura, Ikue; Pickett, Jane; Schumann, Cynthia; Tamminga, Carol

2018-01-01

Autism spectrum disorder (ASD or autism) is a neurodevelopmental condition that affects over 1% of the population worldwide. Developing effective preventions and treatments for autism will depend on understanding the genetic perturbations and underlying neuropathology of the disorder. While evidence from magnetic resonance imaging and other noninvasive techniques points to altered development and organization of the autistic brain, these tools lack the resolution for identifying the cellular and molecular underpinnings of the disorder. Postmortem studies of high-quality human brain tissue currently represent the only viable option to pursuing these types of studies. However, the availability of high-quality ASD brain tissue has been extremely limited. Here we describe the establishment of a privately funded tissue bank, Autism BrainNet, a network of brain collection sites that work in a coordinated fashion to develop an adequate library of human postmortem brain tissues. Autism BrainNet was initiated as a collaboration between the Simons Foundation and Autism Speaks, and is currently funded by the Simons Foundation Autism Research Initiative. Autism BrainNet has collection sites (nodes) in California, Texas, New York, and Massachusetts; an affiliated, international node is located in Oxford, England. All donations to this network become part of a consolidated pool of tissue that is distributed to qualified investigators worldwide to carry out autism research. An essential component of this program is a widespread outreach program that highlights the need for postmortem brain donations to families affected by autism, led by the Autism Science Foundation. Challenges include an outreach campaign that deals with a disorder beginning in early childhood, collecting an adequate number of donations to deal with the high level of biologic heterogeneity of autism, and preparing this limited resource for optimal distribution to the greatest number of investigators. Copyright

Site Assessment of a New State-Wide Seismic Network in Texas (TexNet), USA.

NASA Astrophysics Data System (ADS)

Savvaidis, Alexandros; Young, Bissett; Hennings, Peter; Rathje, Ellen; Zalachoris, George; Young, Michael H.; Walter, Jacob I.; DeShon, Heather R.; Frohlich, Cliff

2017-04-01

Earthquake activity has recently increased in the southern mid-continent of the U.S., including Texas. To monitor seismicity activity in the state of Texas, a new seismicity monitoring program known as TexNet, was funded by the Texas State Legislature in 2015. TexNet consists of 22 new permanent broadband (120s post-hole) seismic stations that will complement the 17 stations currently operating in the State. These permanent stations will provide the baseline seismicity of the state. In addition, 36 portable stations (incorporating both a 20s post-hole seismometer and a post-hole accelerometer) will be used to densify the network in specific areas, of the State, depending on measured seismicity level, proximity to infrastructure, or other scientific investigations. One goal for TexNet is to provide authenticated data needed to evaluate the location, and frequency of earthquakes. To minimize the uncertainties in earthquake locations and increase detectability of the network, an extensive site assessment survey was conducted. The initial station positions were chosen based on Earthscope, Transportable Array (TA) site positions, while ensuring that the stations were relatively evenly-spaced across the State. We then analyzed the noise and earthquake data from the TA seismometers, and added new locations based on geology, topography, and absence of nearby human activities. A 30-min noise test was conducted at each site to identify the site amplification using HVSR information. A 24-hr survey then followed, where the noise level during day and night was identified, analyzed using power spectral density and compared to the NHNM and NLNM (Peterson, 1993; USGS Open File Report, 322). Based on these survey results nearby alternative sites were evaluated to improve final site position. Deployment and data streaming started on September 2016, and will be discussed during this presentation.

Suppressing epidemics on networks by exploiting observer nodes.

PubMed

Takaguchi, Taro; Hasegawa, Takehisa; Yoshida, Yuichi

2014-07-01

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

Suppressing epidemics on networks by exploiting observer nodes

NASA Astrophysics Data System (ADS)

Takaguchi, Taro; Hasegawa, Takehisa; Yoshida, Yuichi

2014-07-01

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

In-beam experience with a highly granular DAQ and control network: TrbNet

NASA Astrophysics Data System (ADS)

Michel, J.; Korcyl, G.; Maier, L.; Traxler, M.

2013-02-01

Virtually all Data Acquisition Systems (DAQ) for nuclear and particle physics experiments use a large number of Field Programmable Gate Arrays (FPGAs) for data transport and more complex tasks as pattern recognition and data reduction. All these FPGAs in a large system have to share a common state like a trigger number or an epoch counter to keep the system synchronized for a consistent event/epoch building. Additionally, the collected data has to be transported with high bandwidth, optionally via the ubiquitous Ethernet protocol. Furthermore, the FPGAs' internal states and configuration memories have to be accessed for control and monitoring purposes. Another requirement for a modern DAQ-network is the fault-tolerance for intermittent data errors in the form of automatic retransmission of faulty data. As FPGAs suffer from Single Event Effects when exposed to ionizing particles, the system has to deal with failing FPGAs. The TrbNet protocol was developed taking all these requirements into account. Three virtual channels are merged on one physical medium: The trigger/epoch information is transported with the highest priority. The data channel is second in the priority order, while the control channel is the last. Combined with a small frame size of 80 bit this guarantees a low latency data transport: A system with 100 front-ends can be built with a one-way latency of 2.2 us. The TrbNet-protocol was implemented in each of the 550 FPGAs of the HADES upgrade project and has been successfully used during the Au+Au campaign in April 2012. With 2ṡ106/s Au-ions and 3% interaction ratio the accepted trigger rate is 10 kHz while data is written to storage with 150 MBytes/s. Errors are reliably mitigated via the implemented retransmission of packets and auto-shut-down of individual links. TrbNet was also used for full monitoring of the FEE status. The network stack is written in VHDL and was successfully deployed on various Lattice and Xilinx devices. The TrbNet is also

Potential of hybrid functionalized meso-porous materials for the separation and immobilization of radionuclides

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

Luca, V.

2013-07-01

Functionalized meso-porous materials are a class of hybrid organic-inorganic material in which a meso-porous metal oxide framework is functionalized with multifunctional organic molecules. These molecules may contain one or more anchor groups that form strong bonds to the pore surfaces of the metal oxide framework and free functional groups that can impart and or modify the functionality of the material such as for binding metal ions in solution. Such materials have been extensively studied over the past decade and are of particular interest in absorption applications because of the tremendous versatility in choosing the composition and architecture of the metalmore » oxide framework and the nature of the functional organic molecule as well as the efficient mass transfer that can occur through a well-designed hierarchically porous network. A sorbent for nuclear applications would have to be highly selective for particular radio nuclides, it would need to be hydrolytically and radiolytically stable, and it would have to possess reasonable capacity and fast kinetics. The sorbent would also have to be available in a form suitable for use in a column. Finally, it would also be desirable if once saturated with radio nuclides, the sorbent could be recycled or converted directly into a ceramic or glass waste form suitable for direct repository disposal or even converted directly into a material that could be used as a transmutation target. Such a cradle-to- grave strategy could have many benefits in so far as process efficiency and the generation of secondary wastes are concerned.This paper will provide an overview of work done on all of the above mentioned aspects of the development of functionalized meso-porous adsorbent materials for the selective separation of lanthanides and actinides and discuss the prospects for future implementation of a cradle-to-grave strategy with such materials. (author)« less

Neural nets on the MPP

NASA Technical Reports Server (NTRS)

Hastings, Harold M.; Waner, Stefan

1987-01-01

The Massively Parallel Processor (MPP) is an ideal machine for computer experiments with simulated neural nets as well as more general cellular automata. Experiments using the MPP with a formal model neural network are described. The results on problem mapping and computational efficiency apply equally well to the neural nets of Hopfield, Hinton et al., and Geman and Geman.

NetMiner-an ensemble pipeline for building genome-wide and high-quality gene co-expression network using massive-scale RNA-seq samples.

PubMed

Yu, Hua; Jiao, Bingke; Lu, Lu; Wang, Pengfei; Chen, Shuangcheng; Liang, Chengzhi; Liu, Wei

2018-01-01

Accurately reconstructing gene co-expression network is of great importance for uncovering the genetic architecture underlying complex and various phenotypes. The recent availability of high-throughput RNA-seq sequencing has made genome-wide detecting and quantifying of the novel, rare and low-abundance transcripts practical. However, its potential merits in reconstructing gene co-expression network have still not been well explored. Using massive-scale RNA-seq samples, we have designed an ensemble pipeline, called NetMiner, for building genome-scale and high-quality Gene Co-expression Network (GCN) by integrating three frequently used inference algorithms. We constructed a RNA-seq-based GCN in one species of monocot rice. The quality of network obtained by our method was verified and evaluated by the curated gene functional association data sets, which obviously outperformed each single method. In addition, the powerful capability of network for associating genes with functions and agronomic traits was shown by enrichment analysis and case studies. In particular, we demonstrated the potential value of our proposed method to predict the biological roles of unknown protein-coding genes, long non-coding RNA (lncRNA) genes and circular RNA (circRNA) genes. Our results provided a valuable and highly reliable data source to select key candidate genes for subsequent experimental validation. To facilitate identification of novel genes regulating important biological processes and phenotypes in other plants or animals, we have published the source code of NetMiner, making it freely available at https://github.com/czllab/NetMiner.

MicroRadarNet: A network of weather micro radars for the identification of local high resolution precipitation patterns

NASA Astrophysics Data System (ADS)

Turso, S.; Paolella, S.; Gabella, M.; Perona, G.

2013-01-01

In this paper, MicroRadarNet, a novel micro radar network for continuous, unattended meteorological monitoring is presented. Key aspects and constraints are introduced. Specific design strategies are highlighted, leading to the technological implementations of this wireless, low-cost, low power consumption sensor network. Raw spatial and temporal datasets are processed on-board in real-time, featuring a consistent evaluation of the signals from the sensors and optimizing the data loads to be transmitted. Network servers perform the final post-elaboration steps on the data streams coming from each unit. Final network products are meteorological mappings of weather events, monitored with high spatial and temporal resolution, and lastly served to the end user through any Web browser. This networked approach is shown to imply a sensible reduction of the overall operational costs, including management and maintenance aspects, if compared to the traditional long range monitoring strategy. Adoption of the TITAN storm identification and nowcasting engine is also here evaluated for in-loop integration within the MicroRadarNet data processing chain. A brief description of the engine workflow is provided, to present preliminary feasibility results and performance estimates. The outcomes were not so predictable, taking into account relevant operational differences between a Western Alps micro radar scenario and the long range radar context in the Denver region of Colorado. Finally, positive results from a set of case studies are discussed, motivating further refinements and integration activities.

Famine Early Warning Systems Network (FEWS NET) Contributions to Strengthening Resilience and Sustainability for the East African Community

NASA Astrophysics Data System (ADS)

Budde, M. E.; Galu, G.; Funk, C. C.; Verdin, J. P.; Rowland, J.

2014-12-01

The Planning for Resilience in East Africa through Policy, Adaptation, Research, and Economic Development (PREPARED) is a multi-organizational project aimed at mainstreaming climate-resilient development planning and program implementation into the East African Community (EAC). The Famine Early Warning Systems Network (FEWS NET) has partnered with the PREPARED project to address three key development challenges for the EAC; 1) increasing resiliency to climate change, 2) managing trans-boundary freshwater biodiversity and conservation and 3) improving access to drinking water supply and sanitation services. USGS FEWS NET has been instrumental in the development of gridded climate data sets that are the fundamental building blocks for climate change adaptation studies in the region. Tools such as the Geospatial Climate Tool (GeoCLIM) have been developed to interpolate time-series grids of precipitation and temperature values from station observations and associated satellite imagery, elevation data, and other spatially continuous fields. The GeoCLIM tool also allows the identification of anomalies and assessments of both their frequency of occurrence and directional trends. A major effort has been put forth to build the capacities of local and regional institutions to use GeoCLIM to integrate their station data (which is not typically available to the public) into improved national and regional gridded climate data sets. In addition to the improvements and capacity building activities related to geospatial analysis tools, FEWS NET will assist in two other areas; 1) downscaling of climate change scenarios and 2) vulnerability impact assessments. FEWS NET will provide expertise in statistical downscaling of Global Climate Model output fields and work with regional institutions to assess results of other downscaling methods. Completion of a vulnerability impact assessment (VIA) involves the examination of sectoral consequences in identified climate "hot spots". FEWS NET

IntNetLncSim: an integrative network analysis method to infer human lncRNA functional similarity

PubMed Central

Hu, Yang; Yang, Haixiu; Zhou, Chen; Sun, Jie; Zhou, Meng

2016-01-01

Increasing evidence indicated that long non-coding RNAs (lncRNAs) were involved in various biological processes and complex diseases by communicating with mRNAs/miRNAs each other. Exploiting interactions between lncRNAs and mRNA/miRNAs to lncRNA functional similarity (LFS) is an effective method to explore function of lncRNAs and predict novel lncRNA-disease associations. In this article, we proposed an integrative framework, IntNetLncSim, to infer LFS by modeling the information flow in an integrated network that comprises both lncRNA-related transcriptional and post-transcriptional information. The performance of IntNetLncSim was evaluated by investigating the relationship of LFS with the similarity of lncRNA-related mRNA sets (LmRSets) and miRNA sets (LmiRSets). As a result, LFS by IntNetLncSim was significant positively correlated with the LmRSet (Pearson correlation γ2=0.8424) and LmiRSet (Pearson correlation γ2=0.2601). Particularly, the performance of IntNetLncSim is superior to several previous methods. In the case of applying the LFS to identify novel lncRNA-disease relationships, we achieved an area under the ROC curve (0.7300) in experimentally verified lncRNA-disease associations based on leave-one-out cross-validation. Furthermore, highly-ranked lncRNA-disease associations confirmed by literature mining demonstrated the excellent performance of IntNetLncSim. Finally, a web-accessible system was provided for querying LFS and potential lncRNA-disease relationships: http://www.bio-bigdata.com/IntNetLncSim. PMID:27323856

IntNetLncSim: an integrative network analysis method to infer human lncRNA functional similarity.

PubMed

Cheng, Liang; Shi, Hongbo; Wang, Zhenzhen; Hu, Yang; Yang, Haixiu; Zhou, Chen; Sun, Jie; Zhou, Meng

2016-07-26

Increasing evidence indicated that long non-coding RNAs (lncRNAs) were involved in various biological processes and complex diseases by communicating with mRNAs/miRNAs each other. Exploiting interactions between lncRNAs and mRNA/miRNAs to lncRNA functional similarity (LFS) is an effective method to explore function of lncRNAs and predict novel lncRNA-disease associations. In this article, we proposed an integrative framework, IntNetLncSim, to infer LFS by modeling the information flow in an integrated network that comprises both lncRNA-related transcriptional and post-transcriptional information. The performance of IntNetLncSim was evaluated by investigating the relationship of LFS with the similarity of lncRNA-related mRNA sets (LmRSets) and miRNA sets (LmiRSets). As a result, LFS by IntNetLncSim was significant positively correlated with the LmRSet (Pearson correlation γ2=0.8424) and LmiRSet (Pearson correlation γ2=0.2601). Particularly, the performance of IntNetLncSim is superior to several previous methods. In the case of applying the LFS to identify novel lncRNA-disease relationships, we achieved an area under the ROC curve (0.7300) in experimentally verified lncRNA-disease associations based on leave-one-out cross-validation. Furthermore, highly-ranked lncRNA-disease associations confirmed by literature mining demonstrated the excellent performance of IntNetLncSim. Finally, a web-accessible system was provided for querying LFS and potential lncRNA-disease relationships: http://www.bio-bigdata.com/IntNetLncSim.

WhaleNet/environet

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

Williamson, J.M.

1994-12-31

WhaleNet has established a network where students, educators, and scientists can interact and share data for use in interdisciplinary curricular and student research activities in classrooms around the world by utilizing telecommunication. This program enables students to participate in marine/whale research programs in real-time with WhaleNet data and supplementary curriculum materials regardless of their geographic location. Systems have been established with research organizations and whale watch companies whereby research data is posted by scientists and students participating in whale watches on the WhaleNet bulletin board and shared with participating classrooms. WhaleNet presently has contacts with classrooms across the nation, andmore » with research groups, whale watch organizations, science museums, and universities from Alaska to North Carolina, Hawaii to Maine, and Belize to Norway. WhaleNet has plans to make existing whale and fisheries research databases available for classroom use and to have research data from satellite tagging programs on various species of whales available for classroom access in real-time.« less

RadNet Air Data From Honolulu, HI

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RadNet Air Data From Birmingham, AL

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RadNet Air Data From Dallas, TX

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RadNet Air Data From Omaha, NE

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RadNet Air Data From Montgomery, AL

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RadNet Air Data From Burlington, VT

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RadNet Air Data From Washington, DC

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RadNet Air Data From Rochester, NY

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RadNet Air Data From Tampa, FL

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RadNet Air Data From Cincinnati, OH

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RadNet Air Data From Fairbanks, AK

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RadNet Air Data From Yuma, AZ

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RadNet Air Data From Kalispell, MT

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RadNet Air Data From Kearney, NE

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RadNet Air Data From Phoenix, AZ

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RadNet Air Data From Pierre, SD

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RadNet Air Data From Augusta, GA

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RadNet Air Data From Syracuse, NY

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RadNet Air Data From Albany, NY

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RadNet Air Data From Anchorage, AK

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RadNet Air Data From Philadelphia, PA

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RadNet Air Data From Houston, TX

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RadNet Air Data From Duluth, MN

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RadNet Air Data From Raleigh, NC

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RadNet Air Data From Louisville, KY

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RadNet Air Data From Cleveland, OH

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RadNet Air Data From Carlsbad, NM

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RadNet Air Data From Corvallis, OR

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RadNet Air Data From Orono, ME

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RadNet Air Data From Reno, NV

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RadNet Air Data From Nashville, TN

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RadNet Air Data From Concord, NH

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RadNet Air Data From Paducah, KY

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RadNet Air Data From Edison, NJ

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RadNet Air Data From Wilmington, NC

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RadNet Air Data From Boise, ID

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RadNet Air Data From Albuquerque, NM

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RadNet Air Data From Fresno, CA

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RadNet Air Data From Amarillo, TX

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RadNet Air Data From Portland, OR

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RadNet Air Data From Jacksonville, FL

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RadNet Air Data From Dover, DE

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RadNet Air Data From Baltimore, MD

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RadNet Air Data From Miami, FL

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RadNet Air Data From Billings, MT

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RadNet Air Data From Providence, RI

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RadNet Air Data From Knoxville, TN

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RadNet Air Data From Columbus, OH

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RadNet Air Data From Bloomsburg, PA

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RadNet Air Data From Shreveport, LA

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RadNet Air Data From Laredo, TX

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RadNet Air Data From Bakersfield, CA

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RadNet Air Data From Portland, ME

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RadNet Air Data From Champaign, IL

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RadNet Air Data From Tucson, AZ

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RadNet Air Data From Juneau, AK

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RadNet Air Data From Toledo, OH

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RadNet Air Data From Boston, MA

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RadNet Air Data From Indianapolis, IN

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RadNet Air Data From Yaphank, NY

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RadNet Air Data From Anaheim, CA

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RadNet Air Data From Riverside, CA

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RadNet Air Data From Detroit, MI

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RadNet Air Data From Wichita, KS

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RadNet Air Data From Columbia, SC

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RadNet Air Data From Milwaukee, WI

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RadNet Air Data From Richmond, VA

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RadNet Air Data From Tulsa, OK

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RadNet Air Data From Aurora, IL

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RadNet Air Data From Hartford, CT

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Hartford. CT from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Charleston, WV

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Charleston, WV from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Shawano, WI

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Shawano, WI from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Harlingen, TX

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Harlingen, TX from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation

RadNet Air Data From Springfield, MO

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Springfield, MO from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Olympia, WA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Olympia, WA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Memphis, TN

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Memphis, TN from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Lubbock, TX

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Lubbock, TX from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Sacramento, CA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Sacramento, CA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Lockport, NY

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Lockport, NY from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Jackson, MS

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Jackson, MS from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Seattle, WA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Seattle, WA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Pittsburgh, PA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Pittsburgh, PA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Madison, WI

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Madison, WI from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Ellensburg, WA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Ellensburg, WA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Harrisonburg, VA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Harrisonburg, VA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Bismarck, ND

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Bismarck, ND from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Denver, CO

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Denver, CO from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Charlotte, NC

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Charlotte, NC from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Lexington, KY

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Lexington, KY from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Casper, WY

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Casper, WY from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Eureka, CA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Eureka, CA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Lincoln, NE

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Lincoln, NE from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Orlando, FL

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Orlando, FL from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Mobile, AL

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Mobile, AL from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Spokane, WA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Spokane, WA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Atlanta, GA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Atlanta, GA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Greensboro, NC

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Greensboro, NC from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Chicago, IL

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Chicago, IL from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Worcester, MA

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Worcester, MA from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

RadNet Air Data From Austin, TX

EPA Pesticide Factsheets

This page presents radiation air monitoring and air filter analysis data for Austin, TX from EPA's RadNet system. RadNet is a nationwide network of monitoring stations that measure radiation in air, drinking water and precipitation.

North American Meso Model Forecast Meteograms

Science.gov Websites

BUFR unpacking is also available. New RUC FORECAST METEOGRAMS are now available. Forecasts of surface variables and vertical profiles of cloud and wind are available for over 1300 stations within the North American Meso model domain. A complete list of the available stations can be found here . Select a region

Surface daytime net radiation estimation using artificial neural networks

DOE PAGES

Jiang, Bo; Zhang, Yi; Liang, Shunlin; ...

2014-11-11

Net all-wave surface radiation (R n) is one of the most important fundamental parameters in various applications. However, conventional R n measurements are difficult to collect because of the high cost and ongoing maintenance of recording instruments. Therefore, various empirical R n estimation models have been developed. This study presents the results of two artificial neural network (ANN) models (general regression neural networks (GRNN) and Neuroet) to estimate R n globally from multi-source data, including remotely sensed products, surface measurements, and meteorological reanalysis products. R n estimates provided by the two ANNs were tested against in-situ radiation measurements obtained frommore » 251 global sites between 1991–2010 both in global mode (all data were used to fit the models) and in conditional mode (the data were divided into four subsets and the models were fitted separately). Based on the results obtained from extensive experiments, it has been proved that the two ANNs were superior to linear-based empirical models in both global and conditional modes and that the GRNN performed better and was more stable than Neuroet. The GRNN estimates had a determination coefficient (R 2) of 0.92, a root mean square error (RMSE) of 34.27 W·m –2 , and a bias of –0.61 W·m –2 in global mode based on the validation dataset. In conclusion, ANN methods are a potentially powerful tool for global R n estimation.« less

Comparison of 37 months global net radiation flux derived from PICARD-BOS over the same period observations of CERES and ARGO

NASA Astrophysics Data System (ADS)

Zhu, Ping; Wild, Martin

2016-04-01

The absolute level of the global net radiation flux (NRF) is fixed at the level of [0.5-1.0] Wm-2 based on the ocean heat content measurements [1]. The space derived global NRF is at the same order of magnitude than the ocean [2]. Considering the atmosphere has a negligible effects on the global NRF determination, the surface global NRF is consistent with the values determined from space [3]. Instead of studying the absolute level of the global NRF, we focus on the interannual variation of global net radiation flux, which were derived from the PICARD-BOS experiment and its comparison with values over the same period but obtained from the NASA-CERES system and inferred from the ocean heat content survey by ARGO network. [1] Allan, Richard P., Chunlei Liu, Norman G. Loeb, Matthew D. Palmer, Malcolm Roberts, Doug Smith, and Pier-Luigi Vidale (2014), Changes in global net radiative imbalance 1985-2012, Geophysical Research Letters, 41 (no.15), 5588-5597. [2] Loeb, Norman G., John M. Lyman, Gregory C. Johnson, Richard P. Allan, David R. Doelling, Takmeng Wong, Brian J. Soden, and Graeme L. Stephens (2012), Observed changes in top-of-the-atmosphere radiation and upper-ocean heating consistent within uncertainty, Nature Geoscience, 5 (no.2), 110-113. [3] Wild, Martin, Doris Folini, Maria Z. Hakuba, Christoph Schar, Sonia I. Seneviratne, Seiji Kato, David Rutan, Christof Ammann, Eric F. Wood, and Gert Konig-Langlo (2015), the energy balance over land and oceans: an assessment based on direct observations and CMIP5 climate models, Climate Dynamics, 44 (no.11-12), 3393-3429.

The ANTARES observation network

NASA Astrophysics Data System (ADS)

Dogliotti, Ana I.; Ulloa, Osvaldo; Muller-Karger, Frank; Hu, Chuanmin; Murch, Brock; Taylor, Charles; Yuras, Gabriel; Kampel, Milton; Lutz, Vivian; Gaeta, Salvador; Gagliardini, Domingo A.; Garcia, Carlos A. E.; Klein, Eduardo; Helbling, Walter; Varela, Ramon; Barbieri, Elena; Negri, Ruben; Frouin, Robert; Sathyendranath, Shubha; Platt, Trevor

2005-08-01

The ANTARES network seeks to understand the variability of the coastal environment on a continental scale and the local, regional, and global factors and processes that effect this change. The focus are coastal zones of South America and the Caribbean Sea. The initial approach includes developing time series of in situ and satellite-based environmental observations in coastal and oceanic regions. The network is constituted by experts that seek to exchange ideas, develop an infrastructure for mutual logistical and knowledge support, and link in situ time series of observations located around the Americas with real-time and historical satellite-derived time series of relevant products. A major objective is to generate information that will be distributed publicly and openly in the service of coastal ocean research, resource management, science-based policy making and education in the Americas. As a first stage, the network has linked oceanographic time series located in Argentina, Brazil, Chile and Venezuela. The group has also developed an online tool to examine satellite data collected with sensors such as NASA's MODIS. Specifically, continental-scale high-resolution (1 km) maps of chlorophyll and of sea surface temperature are generated and served daily over the web according to specifications of users within the ANTARES network. Other satellite-derived variables will be added as support for the network is solidified. ANTARES serves data and offers simple analysis tools that anyone can use with the ultimate goal of improving coastal assessments, management and policies.

Neural network-based estimates of Southern Ocean net community production from in situ O2 / Ar and satellite observation: a methodological study

NASA Astrophysics Data System (ADS)

Chang, C.-H.; Johnson, N. C.; Cassar, N.

2014-06-01

Southern Ocean organic carbon export plays an important role in the global carbon cycle, yet its basin-scale climatology and variability are uncertain due to limited coverage of in situ observations. In this study, a neural network approach based on the self-organizing map (SOM) is adopted to construct weekly gridded (1° × 1°) maps of organic carbon export for the Southern Ocean from 1998 to 2009. The SOM is trained with in situ measurements of O2 / Ar-derived net community production (NCP) that are tightly linked to the carbon export in the mixed layer on timescales of one to two weeks and with six potential NCP predictors: photosynthetically available radiation (PAR), particulate organic carbon (POC), chlorophyll (Chl), sea surface temperature (SST), sea surface height (SSH), and mixed layer depth (MLD). This nonparametric approach is based entirely on the observed statistical relationships between NCP and the predictors and, therefore, is strongly constrained by observations. A thorough cross-validation yields three retained NCP predictors, Chl, PAR, and MLD. Our constructed NCP is further validated by good agreement with previously published, independent in situ derived NCP of weekly or longer temporal resolution through real-time and climatological comparisons at various sampling sites. The resulting November-March NCP climatology reveals a pronounced zonal band of high NCP roughly following the Subtropical Front in the Atlantic, Indian, and western Pacific sectors, and turns southeastward shortly after the dateline. Other regions of elevated NCP include the upwelling zones off Chile and Namibia, the Patagonian Shelf, the Antarctic coast, and areas surrounding the Islands of Kerguelen, South Georgia, and Crozet. This basin-scale NCP climatology closely resembles that of the satellite POC field and observed air-sea CO2 flux. The long-term mean area-integrated NCP south of 50° S from our dataset, 17.9 mmol C m-2 d-1, falls within the range of 8.3 to 24 mmol

The EuroNet paediatric hodgkin network - modern imaging data management for real time central review in multicentre trials.

PubMed

Kurch, L; Mauz-Körholz, C; Bertling, S; Wallinder, M; Kaminska, M; Marwede, D; Tchavdarova, L; Georgi, T W; Elsner, A; Barthel, A; Stoevesandt, D; Hasenclever, D; Sattler, B; Sabri, O; Körholz, D; Kluge, R

2013-11-01

Since 2007, children and adolescents with Hodgkin lymphomas are treated in the Europe-wide EuroNet-PHL trials. A real time central review process for stratification of the patients enhances quality control and efficient therapy management. This process includes reading of all cross-sectional-images. Since reference evaluation is time critical, a fast, easy to handle and safe data transfer is important. In addition, immediate and constant access to all the data has to be guaranteed in case of queries and for regulatory reasons. To meet the mentioned requirements the EuroNet Paediatric Hodgkin Data Network (funded by the European Union - Project Number: 2007108) was established between 2008 and 2011. A respective tailored data protection plan was formulated. The aim of this article is to describe the networks' mode of operation and the advantages for multi-centre trials that include centralized image review. © Georg Thieme Verlag KG Stuttgart · New York.

Synthetic route to meso-tetra hydrocarbyl or substituted hydrocarbyl porphyrins and derivatives

DOEpatents

Wijesekera, T.P.; Wagner, R.W.

1993-08-31

The hydroxyl group in a pyrrolic compound having in the 2-position thereof a group having the formula R(OH)CH-R is hydrocarbyl or substituted hydrocarbyl, is replaced by a group, for example a p-nitrobenzoate group, having better leaving properties than those of hydroxyl for a subsequent self-condensation and cyclization of the pyrrolic compound to form a meso-hydrocarbyl or meso-substituted hydrocarbyl porphyrin.

Synthetic route to meso-tetra hydrocarbyl or substituted hydrocarbyl porphyrins and derivatives

DOEpatents

Wijesekera, Tilak P.; Wagner, Richard W.

1993-01-01

The hydroxyl group in a pyrrolic compound having in the 2-position thereof a group having the formula R(OH)CH--R is hydrocarbyl or substituted hydrocarbyl, is replaced by a group, for example a p-nitrobenzoate group, having better leaving properties than those of hydroxyl for a subsequent self-condensation and cyclization of the pyrrolic compound to form a meso-hydrocarbyl or meso-substituted hydrocarbyl porphyrin.

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

NASA Astrophysics Data System (ADS)

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

2016-02-01

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

SpectralNET – an application for spectral graph analysis and visualization

PubMed Central

Forman, Joshua J; Clemons, Paul A; Schreiber, Stuart L; Haggarty, Stephen J

2005-01-01

Background Graph theory provides a computational framework for modeling a variety of datasets including those emerging from genomics, proteomics, and chemical genetics. Networks of genes, proteins, small molecules, or other objects of study can be represented as graphs of nodes (vertices) and interactions (edges) that can carry different weights. SpectralNET is a flexible application for analyzing and visualizing these biological and chemical networks. Results Available both as a standalone .NET executable and as an ASP.NET web application, SpectralNET was designed specifically with the analysis of graph-theoretic metrics in mind, a computational task not easily accessible using currently available applications. Users can choose either to upload a network for analysis using a variety of input formats, or to have SpectralNET generate an idealized random network for comparison to a real-world dataset. Whichever graph-generation method is used, SpectralNET displays detailed information about each connected component of the graph, including graphs of degree distribution, clustering coefficient by degree, and average distance by degree. In addition, extensive information about the selected vertex is shown, including degree, clustering coefficient, various distance metrics, and the corresponding components of the adjacency, Laplacian, and normalized Laplacian eigenvectors. SpectralNET also displays several graph visualizations, including a linear dimensionality reduction for uploaded datasets (Principal Components Analysis) and a non-linear dimensionality reduction that provides an elegant view of global graph structure (Laplacian eigenvectors). Conclusion SpectralNET provides an easily accessible means of analyzing graph-theoretic metrics for data modeling and dimensionality reduction. SpectralNET is publicly available as both a .NET application and an ASP.NET web application from . Source code is available upon request. PMID:16236170

The ClaudicatioNet concept: design of a national integrated care network providing active and healthy aging for patients with intermittent claudication.

PubMed

Lauret, Gert-Jan; Gijsbers, Harm J H; Hendriks, Erik J M; Bartelink, Marie-Louise; de Bie, Rob A; Teijink, Joep A W

2012-01-01

Intermittent claudication (IC) is a manifestation of peripheral arterial occlusive disease (PAOD). Besides cardiovascular risk management, supervised exercise therapy (SET) should be offered to all patients with IC. Outdated guidelines, an insufficient number of specialized physiotherapists (PTs), lack of awareness of the importance of SET by referring physicians, and misguided financial incentives all seriously impede the availability of a structured SET program in The Netherlands. By initiating regional care networks, ClaudicatioNet aims to improve the quality of care for patients with IC. Based on the chronic care model as a conceptual framework, these networks should enhance the access, continuity, and (cost) efficiency of the health care system. With the aid of a national database, health care professionals will be able to benchmark patient results while ClaudicatioNet will be able to monitor quality of care by way of functional and patient reported outcome measures. The success of ClaudicatioNet is dependent on several factors. Vascular surgeons, general practitioners and coordinating central caregivers will need to team up and work in close collaboration with specialized PTs. A substantial task in the upcoming years will be to monitor the quality, volume, and distribution of ClaudicatioNet PTs. Finally, misguided financial incentives within the Dutch health care system need to be tackled. With ClaudicatioNet, integrated care pathways are likely to improve in the upcoming years. This should result in the achievement of optimal quality of care for all patients with IC.

NASA's Software Bank (NETS)

NASA Technical Reports Server (NTRS)

1992-01-01

NETS (A Neural Network Development Tool) is a software system for mimicking the human brain. It is used in a University of Arkansas project in pattern matching of chemical systems. If successful, chemists would be able to identify mixtures of compounds without long and costly separation procedures. Using NETS, the group has trained the computer to recognize pattern relationships in a known compound and associate the results to an unknown compound. The research appears to be promising.

A kinetic energy study of the meso beta-scale storm environment during AVE-SESAME 5 (20-21 May 1979)

NASA Technical Reports Server (NTRS)

Printy, M. F.; Fuelberg, H. E.

1984-01-01

Kinetic energy of the near storm environment was analyzed by meso beta scale data. It was found that horizontal winds in the 400 to 150 mb layer strengthen rapidly north of the developing convection. Peak values then decrease such that the maximum disappears 6 h later. Southeast of the storms, wind speeds above 300 mb decrease nearly 50% during the 3 h period of most intense thunderstorm activity. When the convection dissipates, wind patterns return to prestorm conditions. The mesoscale storm environment of AVE-SESAME 5 is characterized by large values of cross contour generation of kinetic energy, transfers of energy to nonresolvable scales of motion, and horizontal flux divergence. These processes are maximized within the upper troposphere and are greatest during times of strongest convection. It is shown that patterns agree with observed weather features. The southeast area of the network is examined to determine causes for vertical wind variations.

A Petri net approach to the study of persistence in chemical reaction networks.

PubMed

Angeli, David; De Leenheer, Patrick; Sontag, Eduardo D

2007-12-01

Persistence is the property, for differential equations in R(n), that solutions starting in the positive orthant do not approach the boundary of the orthant. For chemical reactions and population models, this translates into the non-extinction property: provided that every species is present at the start of the reaction, no species will tend to be eliminated in the course of the reaction. This paper provides checkable conditions for persistence of chemical species in reaction networks, using concepts and tools from Petri net theory, and verifies these conditions on various systems which arise in the modeling of cell signaling pathways.

The PluriNetWork: An Electronic Representation of the Network Underlying Pluripotency in Mouse, and Its Applications

PubMed Central

Greber, Boris; Siatkowski, Marcin; Paudel, Yogesh; Warsow, Gregor; Cap, Clemens; Schöler, Hans; Fuellen, Georg

2010-01-01

Background Analysis of the mechanisms underlying pluripotency and reprogramming would benefit substantially from easy access to an electronic network of genes, proteins and mechanisms. Moreover, interpreting gene expression data needs to move beyond just the identification of the up-/downregulation of key genes and of overrepresented processes and pathways, towards clarifying the essential effects of the experiment in molecular terms. Methodology/Principal Findings We have assembled a network of 574 molecular interactions, stimulations and inhibitions, based on a collection of research data from 177 publications until June 2010, involving 274 mouse genes/proteins, all in a standard electronic format, enabling analyses by readily available software such as Cytoscape and its plugins. The network includes the core circuit of Oct4 (Pou5f1), Sox2 and Nanog, its periphery (such as Stat3, Klf4, Esrrb, and c-Myc), connections to upstream signaling pathways (such as Activin, WNT, FGF, BMP, Insulin, Notch and LIF), and epigenetic regulators as well as some other relevant genes/proteins, such as proteins involved in nuclear import/export. We describe the general properties of the network, as well as a Gene Ontology analysis of the genes included. We use several expression data sets to condense the network to a set of network links that are affected in the course of an experiment, yielding hypotheses about the underlying mechanisms. Conclusions/Significance We have initiated an electronic data repository that will be useful to understand pluripotency and to facilitate the interpretation of high-throughput data. To keep up with the growth of knowledge on the fundamental processes of pluripotency and reprogramming, we suggest to combine Wiki and social networking software towards a community curation system that is easy to use and flexible, and tailored to provide a benefit for the scientist, and to improve communication and exchange of research results. A PluriNetWork tutorial

The Net Neutrality Debate: The Basics

ERIC Educational Resources Information Center

Greenfield, Rich

2006-01-01

Rich Greenfield examines the basics of today's net neutrality debate that is likely to be an ongoing issue for society. Greenfield states the problems inherent in the definition of "net neutrality" used by Common Cause: "Network neutrality is the principle that Internet users should be able to access any web content they choose and…

Imaging of glutathione localization in brain with technetium-99M meso-hexamethyl propyleneamine oxime

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

Sasaki, T.; Toyama, H.; Oda, K.

1995-05-01

Previous studies have shown decreasing [Tc-99m] meso-HM-PAO uptake in accordance with glutathione (GSH) content in diethyl, maleate (DEM) treated mice brain. In order to elucidate the retention mechanism of [Tc-99m] HM-PAO in brain and to visualize the regional localization of GSH in the brain with [Tc-99m] meso-HM-PAO, the relationship between the tissue GSH content and uptake of [Tc-99m] meso-HM-PAO was studied in rats and rabbits. Increasing pre-load of DEM (550 mg/kg body weight), an agent to reduce GSH content by glutathione transferase, led to a decrease in GSH (control 1.972{plus_minus}0.017 vs DEM 1.138{plus_minus}0.106 mM) and uptake of [Tc-99m] meso-HM-PAO tomore » half of the control in the rat brain (control 0.281{plus_minus}0.024 vs DEM 0.153 {plus_minus} 0.009 % dose/g). On the other hand, the DEM did not decrease GSH or the uptake of [Tc-99m] meso-HM-PAO in the rabbit brain, in which glutathione transferase activity is very low. These results were also demonstrated by images with pin-hole collimated gamma camera. The uptake of [Tc-99m] meso showed variations in the regional distribution, but the d,l-isomer was uniform. [Tc-99m] meso-HM-PAO uptake was well correlated with GSH content in mice brain regions (r=0.800, p<0.02), whereas [Tc-99m]d,l-HM-PAO was not (r=0.017, p>0.5). Both [Tc-99m] mesa HM-PAO uptake and GSH content were especially high at cerebellum (Uptake: 2.598{plus_minus}0.256 % dose/g. GSH: 2.372{plus_minus}0.107 mM) as compared to other areas (Uptake;cerebral cortex 1.797{plus_minus}0.100 brain stem 1.607 {plus_minus}0.112 % dose/g. GSH: cerebral cortex 1.635{plus_minus}0.142 brain stem 1.478{plus_minus}0.141 mM).« less