ORAC-DR: Astronomy data reduction pipeline

NASA Astrophysics Data System (ADS)

Jenness, Tim; Economou, Frossie; Cavanagh, Brad; Currie, Malcolm J.; Gibb, Andy

2013-10-01

ORAC-DR is a generic data reduction pipeline infrastructure; it includes specific data processing recipes for a number of instruments. It is used at the James Clerk Maxwell Telescope, United Kingdom Infrared Telescope, AAT, and LCOGT. This pipeline runs at the JCMT Science Archive hosted by CADC to generate near-publication quality data products; the code has been in use since 1998.

Status of the TESS Science Processing Operations Center

NASA Astrophysics Data System (ADS)

Jenkins, Jon Michael; Caldwell, Douglas A.; Davies, Misty; Li, Jie; Morris, Robert L.; Rose, Mark; Smith, Jeffrey C.; Tenenbaum, Peter; Ting, Eric; Twicken, Joseph D.; Wohler, Bill

2018-06-01

The Transiting Exoplanet Survey Satellite (TESS) was selected by NASA’s Explorer Program to conduct a search for Earth’s closest cousins starting in 2018. TESS will conduct an all-sky transit survey of F, G and K dwarf stars between 4 and 12 magnitudes and M dwarf stars within 200 light years. TESS is expected to discover 1,000 small planets less than twice the size of Earth, and to measure the masses of at least 50 of these small worlds. The TESS science pipeline is being developed by the Science Processing Operations Center (SPOC) at NASA Ames Research Center based on the highly successful Kepler science pipeline. Like the Kepler pipeline, the TESS pipeline provides calibrated pixels, simple and systematic error-corrected aperture photometry, and centroid locations for all 200,000+ target stars observed over the 2-year mission, along with associated uncertainties. The pixel and light curve products are modeled on the Kepler archive products and will be archived to the Mikulski Archive for Space Telescopes (MAST). In addition to the nominal science data, the 30-minute Full Frame Images (FFIs) simultaneously collected by TESS will also be calibrated by the SPOC and archived at MAST. The TESS pipeline searches through all light curves for evidence of transits that occur when a planet crosses the disk of its host star. The Data Validation pipeline generates a suite of diagnostic metrics for each transit-like signature, and then extracts planetary parameters by fitting a limb-darkened transit model to each potential planetary signature. The results of the transit search are modeled on the Kepler transit search products (tabulated numerical results, time series products, and pdf reports) all of which will be archived to MAST. Synthetic sample data products are available at https://archive.stsci.edu/tess/ete-6.html.Funding for the TESS Mission has been provided by the NASA Science Mission Directorate.

Integrating the ODI-PPA scientific gateway with the QuickReduce pipeline for on-demand processing

NASA Astrophysics Data System (ADS)

Young, Michael D.; Kotulla, Ralf; Gopu, Arvind; Liu, Wilson

2014-07-01

As imaging systems improve, the size of astronomical data has continued to grow, making the transfer and processing of data a significant burden. To solve this problem for the WIYN Observatory One Degree Imager (ODI), we developed the ODI-Portal, Pipeline, and Archive (ODI-PPA) science gateway, integrating the data archive, data reduction pipelines, and a user portal. In this paper, we discuss the integration of the QuickReduce (QR) pipeline into PPA's Tier 2 processing framework. QR is a set of parallelized, stand-alone Python routines accessible to all users, and operators who can create master calibration products and produce standardized calibrated data, with a short turn-around time. Upon completion, the data are ingested into the archive and portal, and made available to authorized users. Quality metrics and diagnostic plots are generated and presented via the portal for operator approval and user perusal. Additionally, users can tailor the calibration process to their specific science objective(s) by selecting custom datasets, applying preferred master calibrations or generating their own, and selecting pipeline options. Submission of a QuickReduce job initiates data staging, pipeline execution, and ingestion of output data products all while allowing the user to monitor the process status, and to download or further process/analyze the output within the portal. User-generated data products are placed into a private user-space within the portal. ODI-PPA leverages cyberinfrastructure at Indiana University including the Big Red II supercomputer, the Scholarly Data Archive tape system and the Data Capacitor shared file system.

Characterization and Validation of Transiting Planets in the TESS SPOC Pipeline

NASA Astrophysics Data System (ADS)

Twicken, Joseph D.; Caldwell, Douglas A.; Davies, Misty; Jenkins, Jon Michael; Li, Jie; Morris, Robert L.; Rose, Mark; Smith, Jeffrey C.; Tenenbaum, Peter; Ting, Eric; Wohler, Bill

2018-06-01

Light curves for Transiting Exoplanet Survey Satellite (TESS) target stars will be extracted and searched for transiting planet signatures in the Science Processing Operations Center (SPOC) Science Pipeline at NASA Ames Research Center. Targets for which the transiting planet detection threshold is exceeded will be processed in the Data Validation (DV) component of the Pipeline. The primary functions of DV are to (1) characterize planets identified in the transiting planet search, (2) search for additional transiting planet signatures in light curves after modeled transit signatures have been removed, and (3) perform a comprehensive suite of diagnostic tests to aid in discrimination between true transiting planets and false positive detections. DV data products include extensive reports by target, one-page summaries by planet candidate, and tabulated transit model fit and diagnostic test results. DV products may be employed by humans and automated systems to vet planet candidates identified in the Pipeline. TESS will launch in 2018 and survey the full sky for transiting exoplanets over a period of two years. The SPOC pipeline was ported from the Kepler Science Operations Center (SOC) codebase and extended for TESS after the mission was selected for flight in the NASA Astrophysics Explorer program. We describe the Data Validation component of the SPOC Pipeline. The diagnostic tests exploit the flux (i.e., light curve) and pixel time series associated with each target to support the determination of the origin of each purported transiting planet signature. We also highlight the differences between the DV components for Kepler and TESS. Candidate planet detections and data products will be delivered to the Mikulski Archive for Space Telescopes (MAST); the MAST URL is archive.stsci.edu/tess. Funding for the TESS Mission has been provided by the NASA Science Mission Directorate.

A midas plugin to enable construction of reproducible web-based image processing pipelines

PubMed Central

Grauer, Michael; Reynolds, Patrick; Hoogstoel, Marion; Budin, Francois; Styner, Martin A.; Oguz, Ipek

2013-01-01

Image processing is an important quantitative technique for neuroscience researchers, but difficult for those who lack experience in the field. In this paper we present a web-based platform that allows an expert to create a brain image processing pipeline, enabling execution of that pipeline even by those biomedical researchers with limited image processing knowledge. These tools are implemented as a plugin for Midas, an open-source toolkit for creating web based scientific data storage and processing platforms. Using this plugin, an image processing expert can construct a pipeline, create a web-based User Interface, manage jobs, and visualize intermediate results. Pipelines are executed on a grid computing platform using BatchMake and HTCondor. This represents a new capability for biomedical researchers and offers an innovative platform for scientific collaboration. Current tools work well, but can be inaccessible for those lacking image processing expertise. Using this plugin, researchers in collaboration with image processing experts can create workflows with reasonable default settings and streamlined user interfaces, and data can be processed easily from a lab environment without the need for a powerful desktop computer. This platform allows simplified troubleshooting, centralized maintenance, and easy data sharing with collaborators. These capabilities enable reproducible science by sharing datasets and processing pipelines between collaborators. In this paper, we present a description of this innovative Midas plugin, along with results obtained from building and executing several ITK based image processing workflows for diffusion weighted MRI (DW MRI) of rodent brain images, as well as recommendations for building automated image processing pipelines. Although the particular image processing pipelines developed were focused on rodent brain MRI, the presented plugin can be used to support any executable or script-based pipeline. PMID:24416016

A midas plugin to enable construction of reproducible web-based image processing pipelines.

PubMed

Grauer, Michael; Reynolds, Patrick; Hoogstoel, Marion; Budin, Francois; Styner, Martin A; Oguz, Ipek

2013-01-01

Image processing is an important quantitative technique for neuroscience researchers, but difficult for those who lack experience in the field. In this paper we present a web-based platform that allows an expert to create a brain image processing pipeline, enabling execution of that pipeline even by those biomedical researchers with limited image processing knowledge. These tools are implemented as a plugin for Midas, an open-source toolkit for creating web based scientific data storage and processing platforms. Using this plugin, an image processing expert can construct a pipeline, create a web-based User Interface, manage jobs, and visualize intermediate results. Pipelines are executed on a grid computing platform using BatchMake and HTCondor. This represents a new capability for biomedical researchers and offers an innovative platform for scientific collaboration. Current tools work well, but can be inaccessible for those lacking image processing expertise. Using this plugin, researchers in collaboration with image processing experts can create workflows with reasonable default settings and streamlined user interfaces, and data can be processed easily from a lab environment without the need for a powerful desktop computer. This platform allows simplified troubleshooting, centralized maintenance, and easy data sharing with collaborators. These capabilities enable reproducible science by sharing datasets and processing pipelines between collaborators. In this paper, we present a description of this innovative Midas plugin, along with results obtained from building and executing several ITK based image processing workflows for diffusion weighted MRI (DW MRI) of rodent brain images, as well as recommendations for building automated image processing pipelines. Although the particular image processing pipelines developed were focused on rodent brain MRI, the presented plugin can be used to support any executable or script-based pipeline.

Lessons Learned from Developing and Operating the Kepler Science Pipeline and Building the TESS Science Pipeline

NASA Technical Reports Server (NTRS)

Jenkins, Jon M.

2017-01-01

The experience acquired through development, implementation and operation of the KeplerK2 science pipelines can provide lessons learned for the development of science pipelines for other missions such as NASA's Transiting Exoplanet Survey Satellite, and ESA's PLATO mission.

Extending the Fermi-LAT data processing pipeline to the grid

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

Zimmer, S.; Arrabito, L.; Glanzman, T.

2015-05-12

The Data Handling Pipeline ("Pipeline") has been developed for the Fermi Gamma-Ray Space Telescope (Fermi) Large Area Telescope (LAT) which launched in June 2008. Since then it has been in use to completely automate the production of data quality monitoring quantities, reconstruction and routine analysis of all data received from the satellite and to deliver science products to the collaboration and the Fermi Science Support Center. Aside from the reconstruction of raw data from the satellite (Level 1), data reprocessing and various event-level analyses are also reasonably heavy loads on the pipeline and computing resources. These other loads, unlike Levelmore » 1, can run continuously for weeks or months at a time. Additionally, it receives heavy use in performing production Monte Carlo tasks.« less

The Herschel Data Processing System - Hipe And Pipelines - During The Early Mission Phase

NASA Astrophysics Data System (ADS)

Ardila, David R.; Herschel Science Ground Segment Consortium

2010-01-01

The Herschel Space Observatory, the fourth cornerstone mission in the ESA science program, was launched 14th of May 2009. With a 3.5 m telescope, it is the largest space telescope ever launched. Herschel's three instruments (HIFI, PACS, and SPIRE) perform photometry and spectroscopy in the 55 - 672 micron range and will deliver exciting science for the astronomical community during at least three years of routine observations. Here we summarize the state of the Herschel Data Processing System and give an overview about future development milestones and plans. The development of the Herschel Data Processing System started seven years ago to support the data analysis for Instrument Level Tests. Resources were made available to implement a freely distributable Data Processing System capable of interactively and automatically reduce Herschel data at different processing levels. The system combines data retrieval, pipeline execution and scientific analysis in one single environment. The software is coded in Java and Jython to be platform independent and to avoid the need for commercial licenses. The Herschel Interactive Processing Environment (HIPE) is the user-friendly face of Herschel Data Processing. The first PACS preview observation of M51 was processed with HIPE, using basic pipeline scripts to a fantastic image within 30 minutes of data reception. Also the first HIFI observations on DR-21 were successfully reduced to high quality spectra, followed by SPIRE observations on M66 and M74. The Herschel Data Processing System is a joint development by the Herschel Science Ground Segment Consortium, consisting of ESA, the NASA Herschel Science Center, and the HIFI, PACS and SPIRE consortium members.

The Rural Girls in Science Project: from Pipelines to Affirming Science Education

NASA Astrophysics Data System (ADS)

Ginorio, Angela B.; Huston, Michelle; Frevert, Katie; Seibel, Jane Bierman

The Rural Girls in Science (RGS) program was developed to foster the interest in science, engineering, and mathematics among rural high school girls in the state of Washington. Girls served include American Indians, Latinas, and Whites. This article provides an overview of the program and its outcomes not only for the participants (girls, teachers, counselors, and schools) but the researchers. Lessons learned from and about the participants are presented, and lessons learned from the process are discussed to illustrate how RGS moved from a focus on individuals to a focus on the school. The initial guiding concepts (self-esteem and scientific pipeline) were replaced by “possible selves” and our proposed complementary concepts: science-affirming and affirming science education.

Nine Years of XMM-Newton Pipeline: Experience and Feedback

NASA Astrophysics Data System (ADS)

Michel, Laurent; Motch, Christian

2009-05-01

The Strasbourg Astronomical Observatory is member of the Survey Science Centre (SSC) of the XMM-Newton satellite. Among other responsibilities, we provide a database access to the 2XMMi catalogue and run the part of the data processing pipeline performing the cross-correlation of EPIC sources with archival catalogs. These tasks were all developed in Strasbourg. Pipeline processing is flawlessly in operation since 1999. We describe here the work load and infrastructure setup in Strasbourg to support SSC activities. Our nine year long SSC experience could be used in the framework of the Simbol-X ground segment.

The Very Large Array Data Processing Pipeline

NASA Astrophysics Data System (ADS)

Kent, Brian R.; Masters, Joseph S.; Chandler, Claire J.; Davis, Lindsey E.; Kern, Jeffrey S.; Ott, Juergen; Schinzel, Frank K.; Medlin, Drew; Muders, Dirk; Williams, Stewart; Geers, Vincent C.; Momjian, Emmanuel; Butler, Bryan J.; Nakazato, Takeshi; Sugimoto, Kanako

2018-01-01

We present the VLA Pipeline, software that is part of the larger pipeline processing framework used for the Karl G. Jansky Very Large Array (VLA), and Atacama Large Millimeter/sub-millimeter Array (ALMA) for both interferometric and single dish observations.Through a collection of base code jointly used by the VLA and ALMA, the pipeline builds a hierarchy of classes to execute individual atomic pipeline tasks within the Common Astronomy Software Applications (CASA) package. Each pipeline task contains heuristics designed by the team to actively decide the best processing path and execution parameters for calibration and imaging. The pipeline code is developed and written in Python and uses a "context" structure for tracking the heuristic decisions and processing results. The pipeline "weblog" acts as the user interface in verifying the quality assurance of each calibration and imaging stage. The majority of VLA scheduling blocks above 1 GHz are now processed with the standard continuum recipe of the pipeline and offer a calibrated measurement set as a basic data product to observatory users. In addition, the pipeline is used for processing data from the VLA Sky Survey (VLASS), a seven year community-driven endeavor started in September 2017 to survey the entire sky down to a declination of -40 degrees at S-band (2-4 GHz). This 5500 hour next-generation large radio survey will explore the time and spectral domains, relying on pipeline processing to generate calibrated measurement sets, polarimetry, and imaging data products that are available to the astronomical community with no proprietary period. Here we present an overview of the pipeline design philosophy, heuristics, and calibration and imaging results produced by the pipeline. Future development will include the testing of spectral line recipes, low signal-to-noise heuristics, and serving as a testing platform for science ready data products.The pipeline is developed as part of the CASA software package by an international consortium of scientists and software developers based at the National Radio Astronomical Observatory (NRAO), the European Southern Observatory (ESO), and the National Astronomical Observatory of Japan (NAOJ).

The LCOGT Observation Portal, Data Pipeline and Science Archive

NASA Astrophysics Data System (ADS)

Lister, Tim; LCOGT Science Archive Team

2014-01-01

Las Cumbres Observatory Global Telescope (LCOGT) is building and deploying a world-wide network of optical telescopes dedicated to time-domain astronomy. During 2012-2013, we successfully deployed and commissioned nine new 1m telescopes at McDonald Observatory (Texas), CTIO (Chile), SAAO (South Africa) and Siding Spring Observatory (Australia). New, improved cameras and additional telescopes will be deployed during 2014. To enable the diverse LCOGT user community of scientific and educational users to request observations on the LCOGT Network and to see their progress and get access to their data, we have developed an Observation Portal system. This Observation Portal integrates proposal submission and observation requests with seamless access to the data products from the data pipelines in near-realtime and long-term products from the Science Archive. We describe the LCOGT Observation Portal and the data pipeline, currently in operation, which makes use of the ORAC-DR automated recipe-based data reduction pipeline and illustrate some of the new data products. We also present the LCOGT Science Archive, which is being developed in partnership with the Infrared Processing and Analysis Center (IPAC) and show some of the new features the Science Archive provides.

Pipeline issues

NASA Technical Reports Server (NTRS)

Eisley, Joe T.

1990-01-01

The declining pool of graduates, the lack of rigorous preparation in science and mathematics, and the declining interest in science and engineering careers at the precollege level promises a shortage of technically educated personnel at the college level for industry, government, and the universities in the next several decades. The educational process, which starts out with a large number of students at the elementary level, but with an ever smaller number preparing for science and engineering at each more advanced educational level, is in a state of crisis. These pipeline issues, so called because the educational process is likened to a series of ever smaller constrictions in a pipe, were examined in a workshop at the Space Grant Conference and a summary of the presentations and the results of the discussion, and the conclusions of the workshop participants are reported.

Performance of Transit Model Fitting in Processing Four Years of Kepler Science Data

NASA Astrophysics Data System (ADS)

Li, Jie; Burke, Christopher J.; Jenkins, Jon Michael; Quintana, Elisa V.; Rowe, Jason; Seader, Shawn; Tenenbaum, Peter; Twicken, Joseph D.

2014-06-01

We present transit model fitting performance of the Kepler Science Operations Center (SOC) Pipeline in processing four years of science data, which were collected by the Kepler spacecraft from May 13, 2009 to May 12, 2013. Threshold Crossing Events (TCEs), which represent transiting planet detections, are generated by the Transiting Planet Search (TPS) component of the pipeline and subsequently processed in the Data Validation (DV) component. The transit model is used in DV to fit TCEs and derive parameters that are used in various diagnostic tests to validate planetary candidates. The standard transit model includes five fit parameters: transit epoch time (i.e. central time of first transit), orbital period, impact parameter, ratio of planet radius to star radius and ratio of semi-major axis to star radius. In the latest Kepler SOC pipeline codebase, the light curve of the target for which a TCE is generated is initially fitted by a trapezoidal model with four parameters: transit epoch time, depth, duration and ingress time. The trapezoidal model fit, implemented with repeated Levenberg-Marquardt minimization, provides a quick and high fidelity assessment of the transit signal. The fit parameters of the trapezoidal model with the minimum chi-square metric are converted to set initial values of the fit parameters of the standard transit model. Additional parameters, such as the equilibrium temperature and effective stellar flux of the planet candidate, are derived from the fit parameters of the standard transit model to characterize pipeline candidates for the search of Earth-size planets in the Habitable Zone. The uncertainties of all derived parameters are updated in the latest codebase to take into account for the propagated errors of the fit parameters as well as the uncertainties in stellar parameters. The results of the transit model fitting of the TCEs identified by the Kepler SOC Pipeline, including fitted and derived parameters, fit goodness metrics and diagnostic figures, are included in the DV report and one-page report summary, which are accessible by the science community at NASA Exoplanet Archive. Funding for the Kepler Mission has been provided by the NASA Science Mission Directorate.

The Dark Energy Survey Image Processing Pipeline

NASA Astrophysics Data System (ADS)

Morganson, E.; Gruendl, R. A.; Menanteau, F.; Carrasco Kind, M.; Chen, Y.-C.; Daues, G.; Drlica-Wagner, A.; Friedel, D. N.; Gower, M.; Johnson, M. W. G.; Johnson, M. D.; Kessler, R.; Paz-Chinchón, F.; Petravick, D.; Pond, C.; Yanny, B.; Allam, S.; Armstrong, R.; Barkhouse, W.; Bechtol, K.; Benoit-Lévy, A.; Bernstein, G. M.; Bertin, E.; Buckley-Geer, E.; Covarrubias, R.; Desai, S.; Diehl, H. T.; Goldstein, D. A.; Gruen, D.; Li, T. S.; Lin, H.; Marriner, J.; Mohr, J. J.; Neilsen, E.; Ngeow, C.-C.; Paech, K.; Rykoff, E. S.; Sako, M.; Sevilla-Noarbe, I.; Sheldon, E.; Sobreira, F.; Tucker, D. L.; Wester, W.; DES Collaboration

2018-07-01

The Dark Energy Survey (DES) is a five-year optical imaging campaign with the goal of understanding the origin of cosmic acceleration. DES performs a ∼5000 deg2 survey of the southern sky in five optical bands (g, r, i, z, Y) to a depth of ∼24th magnitude. Contemporaneously, DES performs a deep, time-domain survey in four optical bands (g, r, i, z) over ∼27 deg2. DES exposures are processed nightly with an evolving data reduction pipeline and evaluated for image quality to determine if they need to be retaken. Difference imaging and transient source detection are also performed in the time domain component nightly. On a bi-annual basis, DES exposures are reprocessed with a refined pipeline and coadded to maximize imaging depth. Here we describe the DES image processing pipeline in support of DES science, as a reference for users of archival DES data, and as a guide for future astronomical surveys.

Presearch data conditioning in the Kepler Science Operations Center pipeline

NASA Astrophysics Data System (ADS)

Twicken, Joseph D.; Chandrasekaran, Hema; Jenkins, Jon M.; Gunter, Jay P.; Girouard, Forrest; Klaus, Todd C.

2010-07-01

We describe the Presearch Data Conditioning (PDC) software component and its context in the Kepler Science Operations Center (SOC) Science Processing Pipeline. The primary tasks of this component are to correct systematic and other errors, remove excess flux due to aperture crowding, and condition the raw flux light curves for over 160,000 long cadence (~thirty minute) and 512 short cadence (~one minute) stellar targets. Long cadence corrected flux light curves are subjected to a transiting planet search in a subsequent pipeline module. We discuss science algorithms for long and short cadence PDC: identification and correction of unexplained (i.e., unrelated to known anomalies) discontinuities; systematic error correction; and removal of excess flux due to aperture crowding. We discuss the propagation of uncertainties from raw to corrected flux. Finally, we present examples from Kepler flight data to illustrate PDC performance. Corrected flux light curves produced by PDC are exported to the Multi-mission Archive at Space Telescope [Science Institute] (MAST) and are made available to the general public in accordance with the NASA/Kepler data release policy.

Middleware Case Study: MeDICi

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

Wynne, Adam S.

2011-05-05

In many application domains in science and engineering, data produced by sensors, instruments and networks is naturally processed by software applications structured as a pipeline . Pipelines comprise a sequence of software components that progressively process discrete units of data to produce a desired outcome. For example, in a Web crawler that is extracting semantics from text on Web sites, the first stage in the pipeline might be to remove all HTML tags to leave only the raw text of the document. The second step may parse the raw text to break it down into its constituent grammatical parts, suchmore » as nouns, verbs and so on. Subsequent steps may look for names of people or places, interesting events or times so documents can be sequenced on a time line. Each of these steps can be written as a specialized program that works in isolation with other steps in the pipeline. In many applications, simple linear software pipelines are sufficient. However, more complex applications require topologies that contain forks and joins, creating pipelines comprising branches where parallel execution is desirable. It is also increasingly common for pipelines to process very large files or high volume data streams which impose end-to-end performance constraints. Additionally, processes in a pipeline may have specific execution requirements and hence need to be distributed as services across a heterogeneous computing and data management infrastructure. From a software engineering perspective, these more complex pipelines become problematic to implement. While simple linear pipelines can be built using minimal infrastructure such as scripting languages, complex topologies and large, high volume data processing requires suitable abstractions, run-time infrastructures and development tools to construct pipelines with the desired qualities-of-service and flexibility to evolve to handle new requirements. The above summarizes the reasons we created the MeDICi Integration Framework (MIF) that is designed for creating high-performance, scalable and modifiable software pipelines. MIF exploits a low friction, robust, open source middleware platform and extends it with component and service-based programmatic interfaces that make implementing complex pipelines simple. The MIF run-time automatically handles queues between pipeline elements in order to handle request bursts, and automatically executes multiple instances of pipeline elements to increase pipeline throughput. Distributed pipeline elements are supported using a range of configurable communications protocols, and the MIF interfaces provide efficient mechanisms for moving data directly between two distributed pipeline elements.« less

IN13B-1660: Analytics and Visualization Pipelines for Big Data on the NASA Earth Exchange (NEX) and OpenNEX

NASA Technical Reports Server (NTRS)

Chaudhary, Aashish; Votava, Petr; Nemani, Ramakrishna R.; Michaelis, Andrew; Kotfila, Chris

2016-01-01

We are developing capabilities for an integrated petabyte-scale Earth science collaborative analysis and visualization environment. The ultimate goal is to deploy this environment within the NASA Earth Exchange (NEX) and OpenNEX in order to enhance existing science data production pipelines in both high-performance computing (HPC) and cloud environments. Bridging of HPC and cloud is a fairly new concept under active research and this system significantly enhances the ability of the scientific community to accelerate analysis and visualization of Earth science data from NASA missions, model outputs and other sources. We have developed a web-based system that seamlessly interfaces with both high-performance computing (HPC) and cloud environments, providing tools that enable science teams to develop and deploy large-scale analysis, visualization and QA pipelines of both the production process and the data products, and enable sharing results with the community. Our project is developed in several stages each addressing separate challenge - workflow integration, parallel execution in either cloud or HPC environments and big-data analytics or visualization. This work benefits a number of existing and upcoming projects supported by NEX, such as the Web Enabled Landsat Data (WELD), where we are developing a new QA pipeline for the 25PB system.

Analytics and Visualization Pipelines for Big ­Data on the NASA Earth Exchange (NEX) and OpenNEX

NASA Astrophysics Data System (ADS)

Chaudhary, A.; Votava, P.; Nemani, R. R.; Michaelis, A.; Kotfila, C.

2016-12-01

We are developing capabilities for an integrated petabyte-scale Earth science collaborative analysis and visualization environment. The ultimate goal is to deploy this environment within the NASA Earth Exchange (NEX) and OpenNEX in order to enhance existing science data production pipelines in both high-performance computing (HPC) and cloud environments. Bridging of HPC and cloud is a fairly new concept under active research and this system significantly enhances the ability of the scientific community to accelerate analysis and visualization of Earth science data from NASA missions, model outputs and other sources. We have developed a web-based system that seamlessly interfaces with both high-performance computing (HPC) and cloud environments, providing tools that enable science teams to develop and deploy large-scale analysis, visualization and QA pipelines of both the production process and the data products, and enable sharing results with the community. Our project is developed in several stages each addressing separate challenge - workflow integration, parallel execution in either cloud or HPC environments and big-data analytics or visualization. This work benefits a number of existing and upcoming projects supported by NEX, such as the Web Enabled Landsat Data (WELD), where we are developing a new QA pipeline for the 25PB system.

The TESS Transiting Planet Search Predicted Recovery and Reliability Rates

NASA Astrophysics Data System (ADS)

Smith, Jeffrey C.; Caldwell, Douglas A.; Davies, Misty; Jenkins, Jon Michael; Li, Jie; Morris, Robert L.; Rose, Mark; Tenenbaum, Peter; Ting, Eric; Twicken, Joseph D.; Wohler, Bill

2018-06-01

The Transiting Exoplanet Survey Satellite (TESS) will search for transiting planet signatures via the Science Processing Operations Center (SPOC) Science Pipeline at NASA Ames Research Center. We report on predicted transit recovery and reliability rates for planetary signatures. These estimates are based on simulated runs of the pipeline using realistic stellar models and transiting planet populations along with best estimates for instrumental noise, thermal induced focus changes, instrumental drift and stochastic artifacts in the light curve data. Key sources of false positives are identified and summarized. TESS will launch in 2018 and survey the full sky for transiting exoplanets over a period of two years. The SPOC pipeline was ported from the Kepler Science Operations Center (SOC) codebase and extended for TESS after the mission was selected for flight in the NASA Astrophysics Explorer program. Candidate planet detections and data products will be delivered to the Mikulski Archive for Space Telescopes (MAST); the MAST URL is archive.stsci.edu/tess. Funding for the TESS Mission has been provided by the NASA Science Mission Directorate.

Photometric analysis in the Kepler Science Operations Center pipeline

NASA Astrophysics Data System (ADS)

Twicken, Joseph D.; Clarke, Bruce D.; Bryson, Stephen T.; Tenenbaum, Peter; Wu, Hayley; Jenkins, Jon M.; Girouard, Forrest; Klaus, Todd C.

2010-07-01

We describe the Photometric Analysis (PA) software component and its context in the Kepler Science Operations Center (SOC) Science Processing Pipeline. The primary tasks of this module are to compute the photometric flux and photocenters (centroids) for over 160,000 long cadence (~thirty minute) and 512 short cadence (~one minute) stellar targets from the calibrated pixels in their respective apertures. We discuss science algorithms for long and short cadence PA: cosmic ray cleaning; background estimation and removal; aperture photometry; and flux-weighted centroiding. We discuss the end-to-end propagation of uncertainties for the science algorithms. Finally, we present examples of photometric apertures, raw flux light curves, and centroid time series from Kepler flight data. PA light curves, centroid time series, and barycentric timestamp corrections are exported to the Multi-mission Archive at Space Telescope [Science Institute] (MAST) and are made available to the general public in accordance with the NASA/Kepler data release policy.

Kepler Data Release 4 Notes

NASA Technical Reports Server (NTRS)

Van Cleve, Jeffrey (Editor); Jenkins, Jon; Caldwell, Doug; Allen, Christopher L.; Batalha, Natalie; Bryson, Stephen T.; Chandrasekaran, Hema; Clarke, Bruce D.; Cote, Miles T.; Dotson, Jessie L.;

The Dark Energy Survey Image Processing Pipeline

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

Morganson, E.; et al.

The Dark Energy Survey (DES) is a five-year optical imaging campaign with the goal of understanding the origin of cosmic acceleration. DES performs a 5000 square degree survey of the southern sky in five optical bands (g,r,i,z,Y) to a depth of ~24th magnitude. Contemporaneously, DES performs a deep, time-domain survey in four optical bands (g,r,i,z) over 27 square degrees. DES exposures are processed nightly with an evolving data reduction pipeline and evaluated for image quality to determine if they need to be retaken. Difference imaging and transient source detection are also performed in the time domain component nightly. On amore » bi-annual basis, DES exposures are reprocessed with a refined pipeline and coadded to maximize imaging depth. Here we describe the DES image processing pipeline in support of DES science, as a reference for users of archival DES data, and as a guide for future astronomical surveys.« less

sTools - a data reduction pipeline for the GREGOR Fabry-Pérot Interferometer and the High-resolution Fast Imager at the GREGOR solar telescope

NASA Astrophysics Data System (ADS)

Kuckein, C.; Denker, C.; Verma, M.; Balthasar, H.; González Manrique, S. J.; Louis, R. E.; Diercke, A.

2017-10-01

A huge amount of data has been acquired with the GREGOR Fabry-Pérot Interferometer (GFPI), large-format facility cameras, and since 2016 with the High-resolution Fast Imager (HiFI). These data are processed in standardized procedures with the aim of providing science-ready data for the solar physics community. For this purpose, we have developed a user-friendly data reduction pipeline called ``sTools'' based on the Interactive Data Language (IDL) and licensed under creative commons license. The pipeline delivers reduced and image-reconstructed data with a minimum of user interaction. Furthermore, quick-look data are generated as well as a webpage with an overview of the observations and their statistics. All the processed data are stored online at the GREGOR GFPI and HiFI data archive of the Leibniz Institute for Astrophysics Potsdam (AIP). The principles of the pipeline are presented together with selected high-resolution spectral scans and images processed with sTools.

Kepler Science Operations Center Pipeline Framework

NASA Technical Reports Server (NTRS)

Klaus, Todd C.; McCauliff, Sean; Cote, Miles T.; Girouard, Forrest R.; Wohler, Bill; Allen, Christopher; Middour, Christopher; Caldwell, Douglas A.; Jenkins, Jon M.

2010-01-01

The Kepler mission is designed to continuously monitor up to 170,000 stars at a 30 minute cadence for 3.5 years searching for Earth-size planets. The data are processed at the Science Operations Center (SOC) at NASA Ames Research Center. Because of the large volume of data and the memory and CPU-intensive nature of the analysis, significant computing hardware is required. We have developed generic pipeline framework software that is used to distribute and synchronize the processing across a cluster of CPUs and to manage the resulting products. The framework is written in Java and is therefore platform-independent, and scales from a single, standalone workstation (for development and research on small data sets) to a full cluster of homogeneous or heterogeneous hardware with minimal configuration changes. A plug-in architecture provides customized control of the unit of work without the need to modify the framework itself. Distributed transaction services provide for atomic storage of pipeline products for a unit of work across a relational database and the custom Kepler DB. Generic parameter management and data accountability services are provided to record the parameter values, software versions, and other meta-data used for each pipeline execution. A graphical console allows for the configuration, execution, and monitoring of pipelines. An alert and metrics subsystem is used to monitor the health and performance of the pipeline. The framework was developed for the Kepler project based on Kepler requirements, but the framework itself is generic and could be used for a variety of applications where these features are needed.

The Pan-STARRS PS1 Image Processing Pipeline

NASA Astrophysics Data System (ADS)

Magnier, E.

The Pan-STARRS PS1 Image Processing Pipeline (IPP) performs the image processing and data analysis tasks needed to enable the scientific use of the images obtained by the Pan-STARRS PS1 prototype telescope. The primary goals of the IPP are to process the science images from the Pan-STARRS telescopes and make the results available to other systems within Pan-STARRS. It also is responsible for combining all of the science images in a given filter into a single representation of the non-variable component of the night sky defined as the "Static Sky". To achieve these goals, the IPP also performs other analysis functions to generate the calibrations needed in the science image processing, and to occasionally use the derived data to generate improved astrometric and photometric reference catalogs. It also provides the infrastructure needed to store the incoming data and the resulting data products. The IPP inherits lessons learned, and in some cases code and prototype code, from several other astronomy image analysis systems, including Imcat (Kaiser), the Sloan Digital Sky Survey (REF), the Elixir system (Magnier & Cuillandre), and Vista (Tonry). Imcat and Vista have a large number of robust image processing functions. SDSS has demonstrated a working analysis pipeline and large-scale databasesystem for a dedicated project. The Elixir system has demonstrated an automatic image processing system and an object database system for operational usage. This talk will present an overview of the IPP architecture, functional flow, code development structure, and selected analysis algorithms. Also discussed is the HW highly parallel HW configuration necessary to support PS1 operational requirements. Finally, results are presented of the processing of images collected during PS1 early commissioning tasks utilizing the Pan-STARRS Test Camera #3.

Massive stereo-based DTM production for Mars on cloud computers

NASA Astrophysics Data System (ADS)

Tao, Y.; Muller, J.-P.; Sidiropoulos, P.; Xiong, Si-Ting; Putri, A. R. D.; Walter, S. H. G.; Veitch-Michaelis, J.; Yershov, V.

2018-05-01

Digital Terrain Model (DTM) creation is essential to improving our understanding of the formation processes of the Martian surface. Although there have been previous demonstrations of open-source or commercial planetary 3D reconstruction software, planetary scientists are still struggling with creating good quality DTMs that meet their science needs, especially when there is a requirement to produce a large number of high quality DTMs using "free" software. In this paper, we describe a new open source system to overcome many of these obstacles by demonstrating results in the context of issues found from experience with several planetary DTM pipelines. We introduce a new fully automated multi-resolution DTM processing chain for NASA Mars Reconnaissance Orbiter (MRO) Context Camera (CTX) and High Resolution Imaging Science Experiment (HiRISE) stereo processing, called the Co-registration Ames Stereo Pipeline (ASP) Gotcha Optimised (CASP-GO), based on the open source NASA ASP. CASP-GO employs tie-point based multi-resolution image co-registration, and Gotcha sub-pixel refinement and densification. CASP-GO pipeline is used to produce planet-wide CTX and HiRISE DTMs that guarantee global geo-referencing compliance with respect to High Resolution Stereo Colour imaging (HRSC), and thence to the Mars Orbiter Laser Altimeter (MOLA); providing refined stereo matching completeness and accuracy. All software and good quality products introduced in this paper are being made open-source to the planetary science community through collaboration with NASA Ames, United States Geological Survey (USGS) and the Jet Propulsion Laboratory (JPL), Advanced Multi-Mission Operations System (AMMOS) Planetary Data System (PDS) Pipeline Service (APPS-PDS4), as well as browseable and visualisable through the iMars web based Geographic Information System (webGIS) system.

PDS4 Bundle Creation Governance Using BPMN

NASA Astrophysics Data System (ADS)

Radulescu, C.; Levoe, S. R.; Algermissen, S. S.; Rye, E. D.; Hardman, S. H.

2015-06-01

The AMMOS-PDS Pipeline Service (APPS) provides a Bundle Builder tool, which governs the process of creating, and ultimately generates, PDS4 bundles incrementally, as science products are being generated.

CFHT data processing and calibration ESPaDOnS pipeline: Upena and OPERA (optical spectropolarimetry)

NASA Astrophysics Data System (ADS)

Martioli, Eder; Teeple, D.; Manset, Nadine

2011-03-01

CFHT is ESPaDOnS responsible for processing raw images, removing instrument related artifacts, and delivering science-ready data to the PIs. Here we describe the Upena pipeline, which is the software used to reduce the echelle spectro-polarimetric data obtained with the ESPaDOnS instrument. Upena is an automated pipeline that performs calibration and reduction of raw images. Upena has the capability of both performing real-time image-by-image basis reduction and a post observing night complete reduction. Upena produces polarization and intensity spectra in FITS format. The pipeline is designed to perform parallel computing for improved speed, which assures that the final products are delivered to the PIs before noon HST after each night of observations. We also present the OPERA project, which is an open-source pipeline to reduce ESPaDOnS data that will be developed as a collaborative work between CFHT and the scientific community. OPERA will match the core capabilities of Upena and in addition will be open-source, flexible and extensible.

Photometer Performance Assessment in Kepler Science Data Processing

NASA Technical Reports Server (NTRS)

Li, Jie; Allen, Christopher; Bryson, Stephen T.; Caldwell, Douglas A.; Chandrasekaran, Hema; Clarke, Bruce D.; Gunter, Jay P.; Jenkins, Jon M.; Klaus, Todd C.; Quintana, Elisa V.;

Inquiry-Driven Field-Based (IDFB) Ocean Science Classes: an Important Role in College Students' Development as Scientists, and Student Retention in the Geo-science Pipeline.

NASA Astrophysics Data System (ADS)

Crane, N. L.

2004-12-01

Experiential learning, engaging students in the process of science, can not only teach students important skills and knowledge, it can also help them become connected with the process on a personal level. This study investigates the role that Inquiry-Driven Field-Based (IDFB) experiences (primarily field classes) in ocean science have on undergraduate science students' development as ocean scientists. Both cognitive (knowledge-based) and affective (motivation and attitude) measures most important to students were used as indicators of development. Major themes will be presented to illustrate how IDFB science experiences can enhance the academic and personal development of students of science. Through their active engagement in the process of science, students gain important skills and knowledge as well as increased confidence, motivation, and ability to plan for their future (in particular their career and educational pathways). This growth is an important part of their development as scientists; the IDFB experience provides them a way to build a relationship with the world of science, and to better understand what science is, what scientists do, and their own future role as scientists. IDFB experiences have a particularly important role in affective measures of development: students develop an important personal connection to science. By doing science, students learn to be scientists and to understand science and science concepts in context. Many underrepresented students do not have the opportunity to take IDFB classes, and addressing this access issue could be an important step towards engaging more underrepresented students in the field. The nature of IDFB experiences and their impact on students makes them a potentially important mechanism for retaining students in the geo-science `pipeline'.

76 FR 72724 - Advisory Committee For Biological Sciences; Notice of Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-25

..., reports about NSF efforts to improve the merit review process, and discussions of fundamental biological... education pipeline. Dated: November 21, 2011. Susanne Bolton, Committee Management Officer. [FR Doc. 2011...

Characterization and Validation of Transiting Planets in the Kepler and TESS Pipelines

NASA Astrophysics Data System (ADS)

Twicken, Joseph; Brownston, Lee; Catanzarite, Joseph; Clarke, Bruce; Cote, Miles; Girouard, Forrest; Li, Jie; McCauliff, Sean; Seader, Shawn; Tenenbaum, Peter; Wohler, Bill; Jenkins, Jon Michael; Batalha, Natalie; Bryson, Steve; Burke, Christopher; Caldwell, Douglas

2015-08-01

Light curves for Kepler targets are searched for transiting planet signatures in the Transiting Planet Search (TPS) component of the Science Operations Center (SOC) Processing Pipeline. Targets for which the detection threshold is exceeded are subsequently processed in the Data Validation (DV) Pipeline component. The primary functions of DV are to (1) characterize planets identified in the transiting planet search, (2) search for additional transiting planet signatures in light curves after modeled transit signatures have been removed, and (3) perform a comprehensive suite of diagnostic tests to aid in discrimination between true transiting planets and false positive detections. DV output products include extensive reports by target, one-page report summaries by planet candidate, and tabulated planet model fit and diagnostic test results. The DV products are employed by humans and automated systems to vet planet candidates identified in the pipeline. The final revision of the Kepler SOC codebase (9.3) was released in March 2015. It will be utilized to reprocess the complete Q1-Q17 data set later this year. At the same time, the SOC Pipeline codebase is being ported to support the Transiting Exoplanet Survey Satellite (TESS) Mission. TESS is expected to launch in 2017 and survey the entire sky for transiting exoplanets over a period of two years. We describe the final revision of the Kepler Data Validation component with emphasis on the diagnostic tests and reports. This revision also serves as the DV baseline for TESS. The diagnostic tests exploit the flux (i.e., light curve), centroid and pixel time series associated with each target to facilitate the determination of the true origin of each purported transiting planet signature. Candidate planet detections and DV products for Kepler are delivered to the Exoplanet Archive at the NASA Exoplanet Science Institute (NExScI). The Exoplanet Archive is located at exoplanetarchive.ipac.caltech.edu. Funding for the Kepler and TESS Missions has been provided by the NASA Science Mission Directorate.

Bifrost: a Modular Python/C++ Framework for Development of High-Throughput Data Analysis Pipelines

NASA Astrophysics Data System (ADS)

Cranmer, Miles; Barsdell, Benjamin R.; Price, Danny C.; Garsden, Hugh; Taylor, Gregory B.; Dowell, Jayce; Schinzel, Frank; Costa, Timothy; Greenhill, Lincoln J.

2017-01-01

Large radio interferometers have data rates that render long-term storage of raw correlator data infeasible, thus motivating development of real-time processing software. For high-throughput applications, processing pipelines are challenging to design and implement. Motivated by science efforts with the Long Wavelength Array, we have developed Bifrost, a novel Python/C++ framework that eases the development of high-throughput data analysis software by packaging algorithms as black box processes in a directed graph. This strategy to modularize code allows astronomers to create parallelism without code adjustment. Bifrost uses CPU/GPU ’circular memory’ data buffers that enable ready introduction of arbitrary functions into the processing path for ’streams’ of data, and allow pipelines to automatically reconfigure in response to astrophysical transient detection or input of new observing settings. We have deployed and tested Bifrost at the latest Long Wavelength Array station, in Sevilleta National Wildlife Refuge, NM, where it handles throughput exceeding 10 Gbps per CPU core.

The Kepler End-to-End Data Pipeline: From Photons to Far Away Worlds

NASA Technical Reports Server (NTRS)

Cooke, Brian; Thompson, Richard; Standley, Shaun

2012-01-01

The Kepler mission is described in overview and the Kepler technique for discovering exoplanets is discussed. The design and implementation of the Kepler spacecraft, tracing the data path from photons entering the telescope aperture through raw observation data transmitted to the ground operations team is described. The technical challenges of operating a large aperture photometer with an unprecedented 95 million pixel detector are addressed as well as the onboard technique for processing and reducing the large volume of data produced by the Kepler photometer. The technique and challenge of day-to-day mission operations that result in a very high percentage of time on target is discussed. This includes the day to day process for monitoring and managing the health of the spacecraft, the annual process for maintaining sun on the solar arrays while still keeping the telescope pointed at the fixed science target, the process for safely but rapidly returning to science operations after a spacecraft initiated safing event and the long term anomaly resolution process.The ground data processing pipeline, from the point that science data is received on the ground to the presentation of preliminary planetary candidates and supporting data to the science team for further evaluation is discussed. Ground management, control, exchange and storage of Kepler's large and growing data set is discussed as well as the process and techniques for removing noise sources and applying calibrations to intermediate data products.

Identifying Evidence-Based Educational Practices: Which Research Designs Provide Findings That Can Influence Social Change?

ERIC Educational Resources Information Center

Schirmer, Barbara R.; Lockman, Alison S.; Schirmer, Todd N.

2016-01-01

We conducted this conceptual study to determine if the Institute of Education Sciences/National Science Foundation pipeline of evidence guidelines could be applied as a protocol that researchers could follow in establishing evidence of effective instructional practices. To do this, we compared these guidelines, new drug development process, and…

SPOKES: An end-to-end simulation facility for spectroscopic cosmological surveys

DOE PAGES

Nord, B.; Amara, A.; Refregier, A.; ...

2016-03-03

The nature of dark matter, dark energy and large-scale gravity pose some of the most pressing questions in cosmology today. These fundamental questions require highly precise measurements, and a number of wide-field spectroscopic survey instruments are being designed to meet this requirement. A key component in these experiments is the development of a simulation tool to forecast science performance, define requirement flow-downs, optimize implementation, demonstrate feasibility, and prepare for exploitation. We present SPOKES (SPectrOscopic KEn Simulation), an end-to-end simulation facility for spectroscopic cosmological surveys designed to address this challenge. SPOKES is based on an integrated infrastructure, modular function organization, coherentmore » data handling and fast data access. These key features allow reproducibility of pipeline runs, enable ease of use and provide flexibility to update functions within the pipeline. The cyclic nature of the pipeline offers the possibility to make the science output an efficient measure for design optimization and feasibility testing. We present the architecture, first science, and computational performance results of the simulation pipeline. The framework is general, but for the benchmark tests, we use the Dark Energy Spectrometer (DESpec), one of the early concepts for the upcoming project, the Dark Energy Spectroscopic Instrument (DESI). As a result, we discuss how the SPOKES framework enables a rigorous process to optimize and exploit spectroscopic survey experiments in order to derive high-precision cosmological measurements optimally.« less

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

Nord, B.; Amara, A.; Refregier, A.

The nature of dark matter, dark energy and large-scale gravity pose some of the most pressing questions in cosmology today. These fundamental questions require highly precise measurements, and a number of wide-field spectroscopic survey instruments are being designed to meet this requirement. A key component in these experiments is the development of a simulation tool to forecast science performance, define requirement flow-downs, optimize implementation, demonstrate feasibility, and prepare for exploitation. We present SPOKES (SPectrOscopic KEn Simulation), an end-to-end simulation facility for spectroscopic cosmological surveys designed to address this challenge. SPOKES is based on an integrated infrastructure, modular function organization, coherentmore » data handling and fast data access. These key features allow reproducibility of pipeline runs, enable ease of use and provide flexibility to update functions within the pipeline. The cyclic nature of the pipeline offers the possibility to make the science output an efficient measure for design optimization and feasibility testing. We present the architecture, first science, and computational performance results of the simulation pipeline. The framework is general, but for the benchmark tests, we use the Dark Energy Spectrometer (DESpec), one of the early concepts for the upcoming project, the Dark Energy Spectroscopic Instrument (DESI). As a result, we discuss how the SPOKES framework enables a rigorous process to optimize and exploit spectroscopic survey experiments in order to derive high-precision cosmological measurements optimally.« less

Understanding decisions Latino students make regarding persistence in the science and math pipeline

NASA Astrophysics Data System (ADS)

Munro, Janet Lynn

This qualitative study focused on the knowledge and perceptions of Latino high school students, as well those of their parents and school personnel, at a southwestern, suburban high school regarding persistence in the math/science pipeline. In the context of the unique school and community setting these students experience, the decision-making process was examined with particular focus on characterizing the relationships that influence the process. While the theoretical framework that informs this study was that of social capital, its primary purpose was to inform the school's processes and policy in support of increased Latino participation in the math and science pipeline. Since course selection may be the most powerful factor affecting school achievement and college-preparedness, and since course selection is influenced by school policy, school personnel, students, parents, and teachers alike, it is important to understand the beliefs and perceptions that characterize the relationships among them. The qualitative research design involved a phenomenological study of nine Latino students, their parents, their teachers and counselors, and certain support personnel from the high school. The school's and community's environment in support of academic intensity served as context for the portrait that developed. Given rapidly changing demographics that bring more and more Latino students to suburban high schools, the persistent achievement gap experienced by Latino students, and the growing dependence of the world economy on a citizenry versed in the math- and science-related fields, a deeper understanding of the decision-making processes Latino 12 students experience can inform school policy as educators struggle to influence those decisions. This study revealed a striking lack of knowledge concerning the college-entrance ramifications of continued course work in math and science beyond that required for graduation, relationships among peers, parents, and school personnel that were markedly lacking in influence over the decision a student makes to continue, or not, course work beyond that required for graduation, and a general dismissal of the value of math- and science-related careers. Also lacking was any evidence of social capital within parental networks that reflected intergenerational closure.

From Description to Explanation: An Empirical Exploration of the African-American Pipeline Problem in STEM

ERIC Educational Resources Information Center

Brown, Bryan A.; Henderson, J. Bryan; Gray, Salina; Donovan, Brian; Sullivan, Shayna; Patterson, Alexis; Waggstaff, William

2016-01-01

We conducted a mixed-methods study of matriculation issues for African-Americans in the STEM pipeline. The project compares the experiences of students currently majoring in science (N?=?304) with the experiences of those who have succeeded in earning science degrees (N?=?307). Participants were surveyed about their pipeline experiences based on…

On-the-fly Data Reprocessing and Analysis Capabilities from the XMM-Newton Archive

NASA Astrophysics Data System (ADS)

Ibarra, A.; Sarmiento, M.; Colomo, E.; Loiseau, N.; Salgado, J.; Gabriel, C.

2017-10-01

The XMM-Newton Science Archive (XSA) includes since last release the possibility to perform on-the-fly data processing with SAS through the Remote Interface for Science Analysis (RISA) server. It enables scientists to analyse data without any download and installation of data and software. The analysis options presently available include extraction of spectra and light curves of user-defined EPIC source regions and full reprocessing of data for which currently archived pipeline products were processed with older SAS versions or calibration files. The current pipeline is fully aligned with the most recent SAS and calibration, while the last full reprocessing of the archive was performed in 2013. The on-the-fly data processing functionality in this release is an experimental version and we invite the community to test and let us know their results. Known issues and workarounds are described in the 'Watchouts' section of the XSA web page. Feedback on how this functionality should evolve will be highly appreciated.

The American Science Pipeline: Sustaining Innovation in a Time of Economic Crisis

ERIC Educational Resources Information Center

Hue, Gillian; Sales, Jessica; Comeau, Dawn; Lynn, David G.; Eisen, Arri

2010-01-01

Significant limitations have emerged in America's science training pipeline, including inaccessibility, inflexibility, financial limitations, and lack of diversity. We present three effective programs that collectively address these challenges. The programs are grounded in rigorous science and integrate through diverse disciplines across…

A Critique of the STEM Pipeline: Young People's Identities in Sweden and Science Education Policy

ERIC Educational Resources Information Center

Mendick, Heather; Berge, Maria; Danielsson, Anna

2017-01-01

In this article, we develop critiques of the pipeline model which dominates Western science education policy, using discourse analysis of interviews with two Swedish young women focused on "identity work". We argue that it is important to unpack the ways that the pipeline model fails to engage with intersections of gender, ethnicity,…

Design and Implementation of Data Reduction Pipelines for the Keck Observatory Archive

NASA Astrophysics Data System (ADS)

Gelino, C. R.; Berriman, G. B.; Kong, M.; Laity, A. C.; Swain, M. A.; Campbell, R.; Goodrich, R. W.; Holt, J.; Lyke, J.; Mader, J. A.; Tran, H. D.; Barlow, T.

2015-09-01

The Keck Observatory Archive (KOA), a collaboration between the NASA Exoplanet Science Institute and the W. M. Keck Observatory, serves science and calibration data for all active and inactive instruments from the twin Keck Telescopes located near the summit of Mauna Kea, Hawaii. In addition to the raw data, we produce and provide quick look reduced data for four instruments (HIRES, LWS, NIRC2, and OSIRIS) so that KOA users can more easily assess the scientific content and the quality of the data, which can often be difficult with raw data. The reduced products derive from both publicly available data reduction packages (when available) and KOA-created reduction scripts. The automation of publicly available data reduction packages has the benefit of providing a good quality product without the additional time and expense of creating a new reduction package, and is easily applied to bulk processing needs. The downside is that the pipeline is not always able to create an ideal product, particularly for spectra, because the processing options for one type of target (eg., point sources) may not be appropriate for other types of targets (eg., extended galaxies and nebulae). In this poster we present the design and implementation for the current pipelines used at KOA and discuss our strategies for handling data for which the nature of the targets and the observers' scientific goals and data taking procedures are unknown. We also discuss our plans for implementing automated pipelines for the remaining six instruments.

Hardware and software facilities for the J-PAS and J-PLUS surveys archiving, processing and data publication

NASA Astrophysics Data System (ADS)

Cristóbal-Hornillos, D.; Varela, J.; Ederoclite, A.; Vázquez Ramió, H.; López-Sainz, A.; Hernández-Fuertes, J.; Civera, T.; Muniesa, D.; Moles, M.; Cenarro, A. J.; Marín-Franch, A.; Yanes-Díaz, A.

2015-05-01

The Observatorio Astrofísico de Javalambre consists of two main telescopes: JST/T250, a 2.5 m telescope with a FoV of 3 deg, and JAST/T80, a 83 cm with a 2 deg FoV. JST/T250 will be devoted to complete the Javalambre-PAU Astronomical Survey (J-PAS). It is a photometric survey with a system of 54 narrow-band plus 3 broad-band filters covering an area of 8500°^2. The JAST/T80 will perform the J-PLUS survey, covering the same area in a system of 12 filters. This contribution presents the software and hardware architecture designed to store and process the data. The processing pipeline runs daily and it is devoted to correct instrumental signature on the science images, to perform astrometric and photometric calibration, and the computation of individual image catalogs. In a second stage, the pipeline performs the combination of the tile mosaics and the computation of final catalogs. The catalogs are ingested in as Scientific database to be provided to the community. The processing software is connected with a management database to store persistent information about the pipeline operations done on each frame. The processing pipeline is executed in a computing cluster under a batch queuing system. Regarding the storage system, it will combine disk and tape technologies. The disk storage system will have capacity to store the data that is accessed by the pipeline. The tape library will store and archive the raw data and earlier data releases with lower access frequency.

The TESS Science Processing Operations Center

NASA Technical Reports Server (NTRS)

Jenkins, Jon; Twicken, Joseph D.; McCauliff, Sean; Campbell, Jennifer; Sanderfer, Dwight; Lung, David; Mansouri-Samani, Masoud; Girouard, Forrest; Tenenbaum, Peter; Klaus, Todd;

The Gemini Recipe System: a dynamic workflow for automated data reduction

NASA Astrophysics Data System (ADS)

Labrie, Kathleen; Allen, Craig; Hirst, Paul; Holt, Jennifer; Allen, River; Dement, Kaniela

2010-07-01

Gemini's next generation data reduction software suite aims to offer greater automation of the data reduction process without compromising the flexibility required by science programs using advanced or unusual observing strategies. The Recipe System is central to our new data reduction software. Developed in Python, it facilitates near-real time processing for data quality assessment, and both on- and off-line science quality processing. The Recipe System can be run as a standalone application or as the data processing core of an automatic pipeline. The data reduction process is defined in a Recipe written in a science (as opposed to computer) oriented language, and consists of a sequence of data reduction steps, called Primitives, which are written in Python and can be launched from the PyRAF user interface by users wishing to use them interactively for more hands-on optimization of the data reduction process. The fact that the same processing Primitives can be run within both the pipeline context and interactively in a PyRAF session is an important strength of the Recipe System. The Recipe System offers dynamic flow control allowing for decisions regarding processing and calibration to be made automatically, based on the pixel and the metadata properties of the dataset at the stage in processing where the decision is being made, and the context in which the processing is being carried out. Processing history and provenance recording are provided by the AstroData middleware, which also offers header abstraction and data type recognition to facilitate the development of instrument-agnostic processing routines.

DALiuGE: A graph execution framework for harnessing the astronomical data deluge

NASA Astrophysics Data System (ADS)

Wu, C.; Tobar, R.; Vinsen, K.; Wicenec, A.; Pallot, D.; Lao, B.; Wang, R.; An, T.; Boulton, M.; Cooper, I.; Dodson, R.; Dolensky, M.; Mei, Y.; Wang, F.

2017-07-01

The Data Activated Liu Graph Engine - DALiuGE- is an execution framework for processing large astronomical datasets at a scale required by the Square Kilometre Array Phase 1 (SKA1). It includes an interface for expressing complex data reduction pipelines consisting of both datasets and algorithmic components and an implementation run-time to execute such pipelines on distributed resources. By mapping the logical view of a pipeline to its physical realisation, DALiuGE separates the concerns of multiple stakeholders, allowing them to collectively optimise large-scale data processing solutions in a coherent manner. The execution in DALiuGE is data-activated, where each individual data item autonomously triggers the processing on itself. Such decentralisation also makes the execution framework very scalable and flexible, supporting pipeline sizes ranging from less than ten tasks running on a laptop to tens of millions of concurrent tasks on the second fastest supercomputer in the world. DALiuGE has been used in production for reducing interferometry datasets from the Karl E. Jansky Very Large Array and the Mingantu Ultrawide Spectral Radioheliograph; and is being developed as the execution framework prototype for the Science Data Processor (SDP) consortium of the Square Kilometre Array (SKA) telescope. This paper presents a technical overview of DALiuGE and discusses case studies from the CHILES and MUSER projects that use DALiuGE to execute production pipelines. In a companion paper, we provide in-depth analysis of DALiuGE's scalability to very large numbers of tasks on two supercomputing facilities.

ODI - Portal, Pipeline, and Archive (ODI-PPA): a web-based astronomical compute archive, visualization, and analysis service

NASA Astrophysics Data System (ADS)

Gopu, Arvind; Hayashi, Soichi; Young, Michael D.; Harbeck, Daniel R.; Boroson, Todd; Liu, Wilson; Kotulla, Ralf; Shaw, Richard; Henschel, Robert; Rajagopal, Jayadev; Stobie, Elizabeth; Knezek, Patricia; Martin, R. Pierre; Archbold, Kevin

2014-07-01

The One Degree Imager-Portal, Pipeline, and Archive (ODI-PPA) is a web science gateway that provides astronomers a modern web interface that acts as a single point of access to their data, and rich computational and visualization capabilities. Its goal is to support scientists in handling complex data sets, and to enhance WIYN Observatory's scientific productivity beyond data acquisition on its 3.5m telescope. ODI-PPA is designed, with periodic user feedback, to be a compute archive that has built-in frameworks including: (1) Collections that allow an astronomer to create logical collations of data products intended for publication, further research, instructional purposes, or to execute data processing tasks (2) Image Explorer and Source Explorer, which together enable real-time interactive visual analysis of massive astronomical data products within an HTML5 capable web browser, and overlaid standard catalog and Source Extractor-generated source markers (3) Workflow framework which enables rapid integration of data processing pipelines on an associated compute cluster and users to request such pipelines to be executed on their data via custom user interfaces. ODI-PPA is made up of several light-weight services connected by a message bus; the web portal built using Twitter/Bootstrap, AngularJS and jQuery JavaScript libraries, and backend services written in PHP (using the Zend framework) and Python; it leverages supercomputing and storage resources at Indiana University. ODI-PPA is designed to be reconfigurable for use in other science domains with large and complex datasets, including an ongoing offshoot project for electron microscopy data.

Outside the pipeline: reimagining science education for nonscientists.

PubMed

Feinstein, Noah Weeth; Allen, Sue; Jenkins, Edgar

2013-04-19

Educational policy increasingly emphasizes knowledge and skills for the preprofessional "science pipeline" rather than helping students use science in daily life. We synthesize research on public engagement with science to develop a research-based plan for cultivating competent outsiders: nonscientists who can access and make sense of science relevant to their lives. Schools should help students access and interpret the science they need in response to specific practical problems, judge the credibility of scientific claims based on both evidence and institutional cues, and cultivate deep amateur involvement in science.

Framework for Integrating Science Data Processing Algorithms Into Process Control Systems

NASA Technical Reports Server (NTRS)

Mattmann, Chris A.; Crichton, Daniel J.; Chang, Albert Y.; Foster, Brian M.; Freeborn, Dana J.; Woollard, David M.; Ramirez, Paul M.

2011-01-01

A software framework called PCS Task Wrapper is responsible for standardizing the setup, process initiation, execution, and file management tasks surrounding the execution of science data algorithms, which are referred to by NASA as Product Generation Executives (PGEs). PGEs codify a scientific algorithm, some step in the overall scientific process involved in a mission science workflow. The PCS Task Wrapper provides a stable operating environment to the underlying PGE during its execution lifecycle. If the PGE requires a file, or metadata regarding the file, the PCS Task Wrapper is responsible for delivering that information to the PGE in a manner that meets its requirements. If the PGE requires knowledge of upstream or downstream PGEs in a sequence of executions, that information is also made available. Finally, if information regarding disk space, or node information such as CPU availability, etc., is required, the PCS Task Wrapper provides this information to the underlying PGE. After this information is collected, the PGE is executed, and its output Product file and Metadata generation is managed via the PCS Task Wrapper framework. The innovation is responsible for marshalling output Products and Metadata back to a PCS File Management component for use in downstream data processing and pedigree. In support of this, the PCS Task Wrapper leverages the PCS Crawler Framework to ingest (during pipeline processing) the output Product files and Metadata produced by the PGE. The architectural components of the PCS Task Wrapper framework include PGE Task Instance, PGE Config File Builder, Config File Property Adder, Science PGE Config File Writer, and PCS Met file Writer. This innovative framework is really the unifying bridge between the execution of a step in the overall processing pipeline, and the available PCS component services as well as the information that they collectively manage.

The Chandra Source Catalog: Processing and Infrastructure

NASA Astrophysics Data System (ADS)

Evans, Janet; Evans, Ian N.; Glotfelty, Kenny J.; Hain, Roger; Hall, Diane M.; Miller, Joseph B.; Plummer, David A.; Zografou, Panagoula; Primini, Francis A.; Anderson, Craig S.; Bonaventura, Nina R.; Chen, Judy C.; Davis, John E.; Doe, Stephen M.; Fabbiano, Giuseppina; Galle, Elizabeth C.; Gibbs, Danny G., II; Grier, John D.; Harbo, Peter N.; He, Xiang Qun (Helen); Houck, John C.; Karovska, Margarita; Kashyap, Vinay L.; Lauer, Jennifer; McCollough, Michael L.; McDowell, Jonathan C.; Mitschang, Arik W.; Morgan, Douglas L.; Mossman, Amy E.; Nichols, Joy S.; Nowak, Michael A.; Refsdal, Brian L.; Rots, Arnold H.; Siemiginowska, Aneta L.; Sundheim, Beth A.; Tibbetts, Michael S.; van Stone, David W.; Winkelman, Sherry L.

2009-09-01

Chandra Source Catalog processing recalibrates each observation using the latest available calibration data, and employs a wavelet-based source detection algorithm to identify all the X-ray sources in the field of view. Source properties are then extracted from each detected source that is a candidate for inclusion in the catalog. Catalog processing is completed by matching sources across multiple observations, merging common detections, and applying quality assurance checks. The Chandra Source Catalog processing system shares a common processing infrastructure and utilizes much of the functionality that is built into the Standard Data Processing (SDP) pipeline system that provides calibrated Chandra data to end-users. Other key components of the catalog processing system have been assembled from the portable CIAO data analysis package. Minimal new software tool development has been required to support the science algorithms needed for catalog production. Since processing pipelines must be instantiated for each detected source, the number of pipelines that are run during catalog construction is a factor of order 100 times larger than for SDP. The increased computational load, and inherent parallel nature of the processing, is handled by distributing the workload across a multi-node Beowulf cluster. Modifications to the SDP automated processing application to support catalog processing, and extensions to Chandra Data Archive software to ingest and retrieve catalog products, complete the upgrades to the infrastructure to support catalog processing.

Not letting the perfect be the enemy of the good: steps toward science-ready ALMA images

NASA Astrophysics Data System (ADS)

Kepley, Amanda A.; Donovan Meyer, Jennifer; Brogan, Crystal; Moullet, Arielle; Hibbard, John; Indebetouw, Remy; Mason, Brian

2016-07-01

Historically, radio observatories have placed the onus of calibrating and imaging data on the observer, thus restricting their user base to those already initiated into the mysteries of radio data or those willing to develop these skills. To expand its user base, the Atacama Large Millimeter/submillimeter Array (ALMA) has a high- level directive to calibrate users' data and, ultimately, to deliver scientifically usable images or cubes to principle investigators (PIs). Although an ALMA calibration pipeline is in place, all delivered images continue to be produced for the PI by hand. In this talk, I will describe on-going efforts at the Northern American ALMA Science Center to produce more uniform imaging products that more closely meet the PI science goals and provide better archival value. As a first step, the NAASC imaging group produced a simple imaging template designed to help scientific staff produce uniform imaging products. This script allowed the NAASC to maximize the productivity of data analysts with relatively little guidance by the scientific staff by providing a step-by-step guide to best practices for ALMA imaging. Finally, I will describe the role of the manually produced images in verifying the imaging pipeline and the on-going development of said pipeline. The development of the imaging template, while technically simple, shows how small steps toward unifying processes and sharing knowledge can lead to large gains for science data products.

Extending the Fermi-LAT Data Processing Pipeline to the Grid

NASA Astrophysics Data System (ADS)

Zimmer, S.; Arrabito, L.; Glanzman, T.; Johnson, T.; Lavalley, C.; Tsaregorodtsev, A.

2012-12-01

The Data Handling Pipeline (“Pipeline”) has been developed for the Fermi Gamma-Ray Space Telescope (Fermi) Large Area Telescope (LAT) which launched in June 2008. Since then it has been in use to completely automate the production of data quality monitoring quantities, reconstruction and routine analysis of all data received from the satellite and to deliver science products to the collaboration and the Fermi Science Support Center. Aside from the reconstruction of raw data from the satellite (Level 1), data reprocessing and various event-level analyses are also reasonably heavy loads on the pipeline and computing resources. These other loads, unlike Level 1, can run continuously for weeks or months at a time. In addition it receives heavy use in performing production Monte Carlo tasks. In daily use it receives a new data download every 3 hours and launches about 2000 jobs to process each download, typically completing the processing of the data before the next download arrives. The need for manual intervention has been reduced to less than 0.01% of submitted jobs. The Pipeline software is written almost entirely in Java and comprises several modules. The software comprises web-services that allow online monitoring and provides charts summarizing work flow aspects and performance information. The server supports communication with several batch systems such as LSF and BQS and recently also Sun Grid Engine and Condor. This is accomplished through dedicated job control services that for Fermi are running at SLAC and the other computing site involved in this large scale framework, the Lyon computing center of IN2P3. While being different in the logic of a task, we evaluate a separate interface to the Dirac system in order to communicate with EGI sites to utilize Grid resources, using dedicated Grid optimized systems rather than developing our own. More recently the Pipeline and its associated data catalog have been generalized for use by other experiments, and are currently being used by the Enriched Xenon Observatory (EXO), Cryogenic Dark Matter Search (CDMS) experiments as well as for Monte Carlo simulations for the future Cherenkov Telescope Array (CTA).

The Gemini Recipe System: A Dynamic Workflow for Automated Data Reduction

NASA Astrophysics Data System (ADS)

Labrie, K.; Hirst, P.; Allen, C.

2011-07-01

Gemini's next generation data reduction software suite aims to offer greater automation of the data reduction process without compromising the flexibility required by science programs using advanced or unusual observing strategies. The Recipe System is central to our new data reduction software. Developed in Python, it facilitates near-real time processing for data quality assessment, and both on- and off-line science quality processing. The Recipe System can be run as a standalone application or as the data processing core of an automatic pipeline. Building on concepts that originated in ORAC-DR, a data reduction process is defined in a Recipe written in a science (as opposed to computer) oriented language, and consists of a sequence of data reduction steps called Primitives. The Primitives are written in Python and can be launched from the PyRAF user interface by users wishing for more hands-on optimization of the data reduction process. The fact that the same processing Primitives can be run within both the pipeline context and interactively in a PyRAF session is an important strength of the Recipe System. The Recipe System offers dynamic flow control allowing for decisions regarding processing and calibration to be made automatically, based on the pixel and the metadata properties of the dataset at the stage in processing where the decision is being made, and the context in which the processing is being carried out. Processing history and provenance recording are provided by the AstroData middleware, which also offers header abstraction and data type recognition to facilitate the development of instrument-agnostic processing routines. All observatory or instrument specific definitions are isolated from the core of the AstroData system and distributed in external configuration packages that define a lexicon including classifications, uniform metadata elements, and transformations.

GPU-Based High-performance Imaging for Mingantu Spectral RadioHeliograph

NASA Astrophysics Data System (ADS)

Mei, Ying; Wang, Feng; Wang, Wei; Chen, Linjie; Liu, Yingbo; Deng, Hui; Dai, Wei; Liu, Cuiyin; Yan, Yihua

2018-01-01

As a dedicated solar radio interferometer, the MingantU SpEctral RadioHeliograph (MUSER) generates massive observational data in the frequency range of 400 MHz-15 GHz. High-performance imaging forms a significantly important aspect of MUSER’s massive data processing requirements. In this study, we implement a practical high-performance imaging pipeline for MUSER data processing. At first, the specifications of the MUSER are introduced and its imaging requirements are analyzed. Referring to the most commonly used radio astronomy software such as CASA and MIRIAD, we then implement a high-performance imaging pipeline based on the Graphics Processing Unit technology with respect to the current operational status of the MUSER. A series of critical algorithms and their pseudo codes, i.e., detection of the solar disk and sky brightness, automatic centering of the solar disk and estimation of the number of iterations for clean algorithms, are proposed in detail. The preliminary experimental results indicate that the proposed imaging approach significantly increases the processing performance of MUSER and generates images with high-quality, which can meet the requirements of the MUSER data processing. Supported by the National Key Research and Development Program of China (2016YFE0100300), the Joint Research Fund in Astronomy (No. U1531132, U1631129, U1231205) under cooperative agreement between the National Natural Science Foundation of China (NSFC) and the Chinese Academy of Sciences (CAS), the National Natural Science Foundation of China (Nos. 11403009 and 11463003).

A lightweight, flow-based toolkit for parallel and distributed bioinformatics pipelines

PubMed Central

2011-01-01

Background Bioinformatic analyses typically proceed as chains of data-processing tasks. A pipeline, or 'workflow', is a well-defined protocol, with a specific structure defined by the topology of data-flow interdependencies, and a particular functionality arising from the data transformations applied at each step. In computer science, the dataflow programming (DFP) paradigm defines software systems constructed in this manner, as networks of message-passing components. Thus, bioinformatic workflows can be naturally mapped onto DFP concepts. Results To enable the flexible creation and execution of bioinformatics dataflows, we have written a modular framework for parallel pipelines in Python ('PaPy'). A PaPy workflow is created from re-usable components connected by data-pipes into a directed acyclic graph, which together define nested higher-order map functions. The successive functional transformations of input data are evaluated on flexibly pooled compute resources, either local or remote. Input items are processed in batches of adjustable size, all flowing one to tune the trade-off between parallelism and lazy-evaluation (memory consumption). An add-on module ('NuBio') facilitates the creation of bioinformatics workflows by providing domain specific data-containers (e.g., for biomolecular sequences, alignments, structures) and functionality (e.g., to parse/write standard file formats). Conclusions PaPy offers a modular framework for the creation and deployment of parallel and distributed data-processing workflows. Pipelines derive their functionality from user-written, data-coupled components, so PaPy also can be viewed as a lightweight toolkit for extensible, flow-based bioinformatics data-processing. The simplicity and flexibility of distributed PaPy pipelines may help users bridge the gap between traditional desktop/workstation and grid computing. PaPy is freely distributed as open-source Python code at http://muralab.org/PaPy, and includes extensive documentation and annotated usage examples. PMID:21352538

A lightweight, flow-based toolkit for parallel and distributed bioinformatics pipelines.

PubMed

Cieślik, Marcin; Mura, Cameron

2011-02-25

Bioinformatic analyses typically proceed as chains of data-processing tasks. A pipeline, or 'workflow', is a well-defined protocol, with a specific structure defined by the topology of data-flow interdependencies, and a particular functionality arising from the data transformations applied at each step. In computer science, the dataflow programming (DFP) paradigm defines software systems constructed in this manner, as networks of message-passing components. Thus, bioinformatic workflows can be naturally mapped onto DFP concepts. To enable the flexible creation and execution of bioinformatics dataflows, we have written a modular framework for parallel pipelines in Python ('PaPy'). A PaPy workflow is created from re-usable components connected by data-pipes into a directed acyclic graph, which together define nested higher-order map functions. The successive functional transformations of input data are evaluated on flexibly pooled compute resources, either local or remote. Input items are processed in batches of adjustable size, all flowing one to tune the trade-off between parallelism and lazy-evaluation (memory consumption). An add-on module ('NuBio') facilitates the creation of bioinformatics workflows by providing domain specific data-containers (e.g., for biomolecular sequences, alignments, structures) and functionality (e.g., to parse/write standard file formats). PaPy offers a modular framework for the creation and deployment of parallel and distributed data-processing workflows. Pipelines derive their functionality from user-written, data-coupled components, so PaPy also can be viewed as a lightweight toolkit for extensible, flow-based bioinformatics data-processing. The simplicity and flexibility of distributed PaPy pipelines may help users bridge the gap between traditional desktop/workstation and grid computing. PaPy is freely distributed as open-source Python code at http://muralab.org/PaPy, and includes extensive documentation and annotated usage examples.

EVEREST: Pixel Level Decorrelation of K2 Light Curves

NASA Astrophysics Data System (ADS)

Luger, Rodrigo; Agol, Eric; Kruse, Ethan; Barnes, Rory; Becker, Andrew; Foreman-Mackey, Daniel; Deming, Drake

2016-10-01

We present EPIC Variability Extraction and Removal for Exoplanet Science Targets (EVEREST), an open-source pipeline for removing instrumental noise from K2 light curves. EVEREST employs a variant of pixel level decorrelation to remove systematics introduced by the spacecraft’s pointing error and a Gaussian process to capture astrophysical variability. We apply EVEREST to all K2 targets in campaigns 0-7, yielding light curves with precision comparable to that of the original Kepler mission for stars brighter than {K}p≈ 13, and within a factor of two of the Kepler precision for fainter targets. We perform cross-validation and transit injection and recovery tests to validate the pipeline, and compare our light curves to the other de-trended light curves available for download at the MAST High Level Science Products archive. We find that EVEREST achieves the highest average precision of any of these pipelines for unsaturated K2 stars. The improved precision of these light curves will aid in exoplanet detection and characterization, investigations of stellar variability, asteroseismology, and other photometric studies. The EVEREST pipeline can also easily be applied to future surveys, such as the TESS mission, to correct for instrumental systematics and enable the detection of low signal-to-noise transiting exoplanets. The EVEREST light curves and the source code used to generate them are freely available online.

ML-o-Scope: A Diagnostic Visualization System for Deep Machine Learning Pipelines

DTIC Science & Technology

2014-05-16

ML-o-scope: a diagnostic visualization system for deep machine learning pipelines Daniel Bruckner Electrical Engineering and Computer Sciences... machine learning pipelines 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f...the system as a support for tuning large scale object-classification pipelines. 1 Introduction A new generation of pipelined machine learning models

Investigating interoperability of the LSST data management software stack with Astropy

NASA Astrophysics Data System (ADS)

Jenness, Tim; Bosch, James; Owen, Russell; Parejko, John; Sick, Jonathan; Swinbank, John; de Val-Borro, Miguel; Dubois-Felsmann, Gregory; Lim, K.-T.; Lupton, Robert H.; Schellart, Pim; Krughoff, K. S.; Tollerud, Erik J.

2016-07-01

The Large Synoptic Survey Telescope (LSST) will be an 8.4m optical survey telescope sited in Chile and capable of imaging the entire sky twice a week. The data rate of approximately 15TB per night and the requirements to both issue alerts on transient sources within 60 seconds of observing and create annual data releases means that automated data management systems and data processing pipelines are a key deliverable of the LSST construction project. The LSST data management software has been in development since 2004 and is based on a C++ core with a Python control layer. The software consists of nearly a quarter of a million lines of code covering the system from fundamental WCS and table libraries to pipeline environments and distributed process execution. The Astropy project began in 2011 as an attempt to bring together disparate open source Python projects and build a core standard infrastructure that can be used and built upon by the astronomy community. This project has been phenomenally successful in the years since it has begun and has grown to be the de facto standard for Python software in astronomy. Astropy brings with it considerable expectations from the community on how astronomy Python software should be developed and it is clear that by the time LSST is fully operational in the 2020s many of the prospective users of the LSST software stack will expect it to be fully interoperable with Astropy. In this paper we describe the overlap between the LSST science pipeline software and Astropy software and investigate areas where the LSST software provides new functionality. We also discuss the possibilities of re-engineering the LSST science pipeline software to build upon Astropy, including the option of contributing affliated packages.

Problematizing the STEM Pipeline Metaphor: Is the STEM Pipeline Metaphor Serving Our Students and the STEM Workforce?

ERIC Educational Resources Information Center

Cannady, Matthew A.; Greenwald, Eric; Harris, Kimberly N.

2014-01-01

Researchers and policy makers often use the metaphor of an ever-narrowing pipeline to describe the trajectory to a science, technology, engineering or mathematics (STEM) degree or career. This study interrogates the appropriateness of the STEM pipeline as the dominant frame for understanding and making policies related to STEM career trajectories.…

The TESS science processing operations center

NASA Astrophysics Data System (ADS)

Jenkins, Jon M.; Twicken, Joseph D.; McCauliff, Sean; Campbell, Jennifer; Sanderfer, Dwight; Lung, David; Mansouri-Samani, Masoud; Girouard, Forrest; Tenenbaum, Peter; Klaus, Todd; Smith, Jeffrey C.; Caldwell, Douglas A.; Chacon, A. D.; Henze, Christopher; Heiges, Cory; Latham, David W.; Morgan, Edward; Swade, Daryl; Rinehart, Stephen; Vanderspek, Roland

2016-08-01

The Transiting Exoplanet Survey Satellite (TESS) will conduct a search for Earth's closest cousins starting in early 2018 and is expected to discover 1,000 small planets with Rp < 4 R⊕ and measure the masses of at least 50 of these small worlds. The Science Processing Operations Center (SPOC) is being developed at NASA Ames Research Center based on the Kepler science pipeline and will generate calibrated pixels and light curves on the NASA Advanced Supercomputing Division's Pleiades supercomputer. The SPOC will also search for periodic transit events and generate validation products for the transit-like features in the light curves. All TESS SPOC data products will be archived to the Mikulski Archive for Space Telescopes (MAST).

Attributions, Influences and Outcomes for Underrepresented and Disadvantaged Participants of a Medical Sciences Enrichment Pipeline Program

ERIC Educational Resources Information Center

Pinckney, Charlyene Carol

2014-01-01

The current study was undertaken to examine the effectiveness of the Rowan University-School of Osteopathic Medicine - Summer Pre-Medical Research and Education Program (Summer PREP), a postsecondary medical sciences enrichment pipeline program for under-represented and disadvantaged students. Thirty-four former program participants were surveyed…

New Software for Ensemble Creation in the Spitzer-Space-Telescope Operations Database

NASA Technical Reports Server (NTRS)

Laher, Russ; Rector, John

2004-01-01

Some of the computer pipelines used to process digital astronomical images from NASA's Spitzer Space Telescope require multiple input images, in order to generate high-level science and calibration products. The images are grouped into ensembles according to well documented ensemble-creation rules by making explicit associations in the operations Informix database at the Spitzer Science Center (SSC). The advantage of this approach is that a simple database query can retrieve the required ensemble of pipeline input images. New and improved software for ensemble creation has been developed. The new software is much faster than the existing software because it uses pre-compiled database stored-procedures written in Informix SPL (SQL programming language). The new software is also more flexible because the ensemble creation rules are now stored in and read from newly defined database tables. This table-driven approach was implemented so that ensemble rules can be inserted, updated, or deleted without modifying software.

The Milky Way Project: Mapping star formation in our home Galaxy, one click at a time

NASA Astrophysics Data System (ADS)

Jayasinghe, Tharindu K.; Povich, Matthew S.; Dixon, Don; Velasco, Jose; Milky Way Project Team

2017-01-01

In the recent years, citizen science has helped astronomers comb through large data sets to identify patterns and objects that are not easily found through automated processes. The Milky Way Project (MWP), a popular citizen science initiative, presents internet users with images from the GLIMPSE, MIPSGAL, SMOG and CYGNUS-X surveys of the Galactic plane using the Spitzer Space Telescope. These citizen scientists are directed to make "classification" drawings on the images to identify targeted classes of astronomical objects. We present an updated data reduction pipeline for the MWP. Written from the ground up in Python, this data reduction pipeline allows for the aggregation of classifications made by MWP users into catalogs of infrared (IR) bubbles, IR bow shocks and “yellowballs” (which may be the early precursors of IR bubbles). Coupled with the more accurate bubble classification tool used in the latest iterations of the MWP, this pipeline enables for better accuracy in the shapes and sizes of the bubbles when compared with those listed in the first MWP data release (DR1). We obtain an initial catalog of over 4000 bubbles using 2 million user classifications made between 2012 and 2015. Combined with the classifications from the latest MWP iteration (2016-2017), we will use a database of over 4 million classifications to produce a MWP DR2 bubble catalog. We will also create the first catalog of candidate IR bow shocks identified through citizen science and an updated “yellowball” catalog. This work is supported by the National Science Foundation under grants CAREER-1454334 and AST-1411851.

ESO science data product standard for 1D spectral products

NASA Astrophysics Data System (ADS)

Micol, Alberto; Arnaboldi, Magda; Delmotte, Nausicaa A. R.; Mascetti, Laura; Retzlaff, Joerg

2016-07-01

The ESO Phase 3 process allows the upload, validation, storage, and publication of reduced data through the ESO Science Archive Facility. Since its introduction, 2 million data products have been archived and published; 80% of them are one-dimensional extracted and calibrated spectra. Central to Phase3 is the ESO science data product standard that defines metadata and data format of any product. This contribution describes the ESO data standard for 1d-spectra, its adoption by the reduction pipelines of selected instrument modes for in-house generation of reduced spectra, the enhanced archive legacy value. Archive usage statistics are provided.

Prime the Pipeline Project (P[cube]): Putting Knowledge to Work

ERIC Educational Resources Information Center

Greenes, Carole; Wolfe, Susan; Weight, Stephanie; Cavanagh, Mary; Zehring, Julie

2011-01-01

With funding from NSF, the Prime the Pipeline Project (P[cube]) is responding to the need to strengthen the science, technology, engineering, and mathematics (STEM) pipeline from high school to college by developing and evaluating the scientific village strategy and the culture it creates. The scientific village, a community of high school…

The TESS Science Processing Operations Center

NASA Technical Reports Server (NTRS)

Jenkins, Jon M.; Twicken, Joseph D.; McCauliff, Sean; Campbell, Jennifer; Sanderfer, Dwight; Lung, David; Mansouri-Samani, Masoud; Girouard, Forrest; Tenenbaum, Peter; Klaus, Todd;

JWST science data products

NASA Astrophysics Data System (ADS)

Swade, Daryl; Bushouse, Howard; Greene, Gretchen; Swam, Michael

2014-07-01

Science data products for James Webb Space Telescope (JWST) ©observations will be generated by the Data Management Subsystem (DMS) within the JWST Science and Operations Center (S&OC) at the Space Telescope Science Institute (STScI). Data processing pipelines within the DMS will produce uncalibrated and calibrated exposure files, as well as higher level data products that result from combined exposures, such as mosaic images. Information to support the science observations, for example data from engineering telemetry, proposer inputs, and observation planning will be captured and incorporated into the science data products. All files will be generated in Flexible Image Transport System (FITS) format. The data products will be made available through the Mikulski Archive for Space Telescopes (MAST) and adhere to International Virtual Observatory Alliance (IVOA) standard data protocols.

Traveling the Road to Success: A Discourse on Persistence throughout the Science Pipeline with African American Students at a Predominantly White Institution

ERIC Educational Resources Information Center

Russell, Melody L.; Atwater, Mary M.

2005-01-01

This study focuses on 11 African American undergraduate seniors in a biology degree program at a predominantly white research institution in the southeastern United States. These 11 respondents shared their journeys throughout the high school and college science pipeline. Participants described similar precollege factors and experiences that…

Building Effective Pipelines to Increase Diversity in the Geosciences

NASA Astrophysics Data System (ADS)

Snow, E.; Robinson, C. R.; Neal-Mujahid, R.

2017-12-01

The U.S. Geological Survey (USGS) recognizes and understands the importance of a diverse workforce in advancing our science. Valuing Differences is one of the guiding principles of the USGS, and is the critical basis of the collaboration among the Youth and Education in Science (YES) program in the USGS Office of Science, Quality, and Integrity (OSQI), the Office of Diversity and Equal Opportunity (ODEO), and USGS science centers to build pipeline programs targeting diverse young scientists. Pipeline programs are robust, sustained relationships between two entities that provide a pathway from one to the other, in this case, from minority serving institutions to the USGS. The USGS has benefited from pipeline programs for many years. Our longest running program, with University of Puerto Rico Mayaguez (UPR), is a targeted outreach and internship program that has been managed by USGS scientists in Florida since the mid-1980's Originally begun as the Minority Participation in the Earth Sciences (MPES ) Program, it has evolved over the years, and in its several forms has brought dozens of interns to the USGS. Based in part on that success, in 2006 USGS scientists in Woods Hole MA worked with their Florida counterparts to build a pipeline program with City College of New York (CCNY). In this program, USGS scientists visit CCNY monthly, giving a symposium and meeting with students and faculty. The talks are so successful that the college created a course around them. In 2017, the CCNY and UPR programs brought 12 students to the USGS for summer internships. The CCNY model has been so successful that USGS is exploring creating similar pipeline programs. The YES office is coordinating with ODEO and USGS science centers to identify partner universities and build relationships that will lead to robust partnership where USGS scientists will visit regularly to engage with faculty and students and recruit students for USGS internships. The ideal partner universities will have a high population of underserved students, strong support for minority and first-generation students, proximity to a USGS office, and faculty and/or majors in several of the fields most important to USGS science: geology, geochemistry, energy, biology, ecology, environmental health, hydrology, climate science, GIS, high-capacity computing, and remote sensing.

A Bridge to the Stars: A Model High School-to-College Pipeline to Improve Diversity in STEM

NASA Astrophysics Data System (ADS)

McIntosh, Daniel H.; Jennings, Derrick H.

2017-01-01

Increasing participation by historically underrepresented Americans in the STEM workforce remains a national priority. Existing strategies have failed to increase diversity especially in the physical sciences despite federal mandates. To meet this urgent challenge, it is imperative to immediately identify and support the expansion of effective high school-to-college STEM pipelines. A Bridge to the Stars (ABttS) is a creative and tested pipeline designed to steadily increase the numbers of disadvantaged 15-21 year-olds pursuing and completing 4-year STEM degrees. This unique program offers extended engagement in astronomy, arguably the most accessible window to science, through a 3-tier STEM immersion program of innovative learning (in a freshman science course), authentic research training (in a freshman science lab), and supportive near-peer mentoring at U.Missouri-Kansas City, an urban research university. Each tier of the ABttS pipeline by itself has the potential to broaden student aspirations for careers as technological innovators or STEM educators. Students who elect to transition through multiple tiers will substantially reinforce their successes with STEM activities, and significantly bolster their self-esteem necessary to personally manifest STEM aspirations. We will summarize the impact of this program after 5 years, and share our latest improvements. The long-term mission of ABttS is to see urban educational institutions across the U.S. adopt similar pipelines in all STEM disciplines built on the ABttS model.

Optimizing the TESS Planet Finding Pipeline

NASA Astrophysics Data System (ADS)

Chitamitara, Aerbwong; Smith, Jeffrey C.; Tenenbaum, Peter; TESS Science Processing Operations Center

2017-10-01

The Transiting Exoplanet Survey Satellite (TESS) is a new NASA planet finding all-sky survey that will observe stars within 200 light years and 10-100 times brighter than that of the highly successful Kepler mission. TESS is expected to detect ~1000 planets smaller than Neptune and dozens of Earth size planets. As in the Kepler mission, the Science Processing Operations Center (SPOC) processing pipeline at NASA Ames Research center is tasked with calibrating the raw pixel data, generating systematic error corrected light curves and then detecting and validating transit signals. The Transiting Planet Search (TPS) component of the pipeline must be modified and tuned for the new data characteristics in TESS. For example, due to each sector being viewed for as little as 28 days, the pipeline will be identifying transiting planets based on a minimum of two transit signals rather than three, as in the Kepler mission. This may result in a significantly higher false positive rate. The study presented here is to measure the detection efficiency of the TESS pipeline using simulated data. Transiting planets identified by TPS are compared to transiting planets from the simulated transit model using the measured epochs, periods, transit durations and the expected detection statistic of injected transit signals (expected MES). From the comparisons, the recovery and false positive rates of TPS is measured. Measurements of recovery in TPS are then used to adjust TPS configuration parameters to maximize the planet recovery rate and minimize false detections. The improvements in recovery rate between initial TPS conditions and after various adjustments will be presented and discussed.

Data Mining Citizen Science Results

NASA Astrophysics Data System (ADS)

Borne, K. D.

2012-12-01

Scientific discovery from big data is enabled through multiple channels, including data mining (through the application of machine learning algorithms) and human computation (commonly implemented through citizen science tasks). We will describe the results of new data mining experiments on the results from citizen science activities. Discovering patterns, trends, and anomalies in data are among the powerful contributions of citizen science. Establishing scientific algorithms that can subsequently re-discover the same types of patterns, trends, and anomalies in automatic data processing pipelines will ultimately result from the transformation of those human algorithms into computer algorithms, which can then be applied to much larger data collections. Scientific discovery from big data is thus greatly amplified through the marriage of data mining with citizen science.

HEP Computing Tools, Grid and Supercomputers for Genome Sequencing Studies

NASA Astrophysics Data System (ADS)

De, K.; Klimentov, A.; Maeno, T.; Mashinistov, R.; Novikov, A.; Poyda, A.; Tertychnyy, I.; Wenaus, T.

2017-10-01

PanDA - Production and Distributed Analysis Workload Management System has been developed to address ATLAS experiment at LHC data processing and analysis challenges. Recently PanDA has been extended to run HEP scientific applications on Leadership Class Facilities and supercomputers. The success of the projects to use PanDA beyond HEP and Grid has drawn attention from other compute intensive sciences such as bioinformatics. Recent advances of Next Generation Genome Sequencing (NGS) technology led to increasing streams of sequencing data that need to be processed, analysed and made available for bioinformaticians worldwide. Analysis of genomes sequencing data using popular software pipeline PALEOMIX can take a month even running it on the powerful computer resource. In this paper we will describe the adaptation the PALEOMIX pipeline to run it on a distributed computing environment powered by PanDA. To run pipeline we split input files into chunks which are run separately on different nodes as separate inputs for PALEOMIX and finally merge output file, it is very similar to what it done by ATLAS to process and to simulate data. We dramatically decreased the total walltime because of jobs (re)submission automation and brokering within PanDA. Using software tools developed initially for HEP and Grid can reduce payload execution time for Mammoths DNA samples from weeks to days.

Discrete pre-processing step effects in registration-based pipelines, a preliminary volumetric study on T1-weighted images.

PubMed

Muncy, Nathan M; Hedges-Muncy, Ariana M; Kirwan, C Brock

2017-01-01

Pre-processing MRI scans prior to performing volumetric analyses is common practice in MRI studies. As pre-processing steps adjust the voxel intensities, the space in which the scan exists, and the amount of data in the scan, it is possible that the steps have an effect on the volumetric output. To date, studies have compared between and not within pipelines, and so the impact of each step is unknown. This study aims to quantify the effects of pre-processing steps on volumetric measures in T1-weighted scans within a single pipeline. It was our hypothesis that pre-processing steps would significantly impact ROI volume estimations. One hundred fifteen participants from the OASIS dataset were used, where each participant contributed three scans. All scans were then pre-processed using a step-wise pipeline. Bilateral hippocampus, putamen, and middle temporal gyrus volume estimations were assessed following each successive step, and all data were processed by the same pipeline 5 times. Repeated-measures analyses tested for a main effects of pipeline step, scan-rescan (for MRI scanner consistency) and repeated pipeline runs (for algorithmic consistency). A main effect of pipeline step was detected, and interestingly an interaction between pipeline step and ROI exists. No effect for either scan-rescan or repeated pipeline run was detected. We then supply a correction for noise in the data resulting from pre-processing.

From maturity to value-added innovation: lessons from the pharmaceutical and agro-biotechnology industries.

PubMed

Mittra, James; Tait, Joyce; Wield, David

2011-03-01

The pharmaceutical and agro-biotechnology industries have been confronted by dwindling product pipelines and rapid developments in life sciences, thus demanding a strategic rethink of conventional research and development. Despite offering both industries a solution to the pipeline problem, the life sciences have also brought complex regulatory challenges for firms. In this paper, we comment on the response of these industries to the life science trajectory, in the context of maturing conventional small-molecule product pipelines and routes to market. The challenges of managing transition from maturity to new high-value-added innovation models are addressed. Furthermore, we argue that regulation plays a crucial role in shaping the innovation systems of both industries, and as such, we suggest potentially useful changes to the current regulatory system. Copyright © 2010 Elsevier Ltd. All rights reserved.

Barriers to the Preclinical Development of Therapeutics that Target Aging Mechanisms

PubMed Central

Burd, Christin E.; Gill, Matthew S.; Niedernhofer, Laura J.; Robbins, Paul D.; Austad, Steven N.; Barzilai, Nir

2016-01-01

Through the progress of basic science research, fundamental mechanisms that contribute to age-related decline are being described with increasing depth and detail. Although these efforts have identified new drug targets and compounds that extend life span in model organisms, clinical trials of therapeutics that target aging processes remain scarce. Progress in aging research is hindered by barriers associated with the translation of basic science discoveries into the clinic. This report summarizes discussions held at a 2014 Geroscience Network retreat focused on identifying hurdles that currently impede the preclinical development of drugs targeting fundamental aging processes. From these discussions, it was evident that aging researchers have varied perceptions of the ideal preclinical pipeline. To forge a clear and cohesive path forward, several areas of controversy must first be resolved and new tools developed. Here, we focus on five key issues in preclinical drug development (drug discovery, lead compound development, translational preclinical biomarkers, funding, and integration between researchers and clinicians), expanding upon discussions held at the Geroscience Retreat and suggesting areas for further research. By bringing these findings to the attention of the aging research community, we hope to lay the foundation for a concerted preclinical drug development pipeline. PMID:27535964

Synergy Between Archives, VO, and the Grid at ESAC

NASA Astrophysics Data System (ADS)

Arviset, C.; Alvarez, R.; Gabriel, C.; Osuna, P.; Ott, S.

2011-07-01

Over the years, in support to the Science Operations Centers at ESAC, we have set up two Grid infrastructures. These have been built: 1) to facilitate daily research for scientists at ESAC, 2) to provide high computing capabilities for project data processing pipelines (e.g., Herschel), 3) to support science operations activities (e.g., calibration monitoring). Furthermore, closer collaboration between the science archives, the Virtual Observatory (VO) and data processing activities has led to an other Grid use case: the Remote Interface to XMM-Newton SAS Analysis (RISA). This web service-based system allows users to launch SAS tasks transparently to the GRID, save results on http-based storage and visualize them through VO tools. This paper presents real and operational use cases of Grid usages in these contexts

The Gemini NICI Planet-Finding Campaign: The Companion Detection Pipeline

NASA Astrophysics Data System (ADS)

Wahhaj, Zahed; Liu, Michael C.; Biller, Beth A.; Nielsen, Eric L.; Close, Laird M.; Hayward, Thomas L.; Hartung, Markus; Chun, Mark; Ftaclas, Christ; Toomey, Douglas W.

2013-12-01

We present high-contrast image processing techniques used by the Gemini NICI Planet-Finding Campaign to detect faint companions to bright stars. The Near-Infrared Coronographic Imager (NICI) is an adaptive optics instrument installed on the 8 m Gemini South telescope, capable of angular and spectral difference imaging and specifically designed to image exoplanets. The Campaign data pipeline achieves median contrasts of 12.6 mag at 0.''5 and 14.4 mag at 1'' separation, for a sample of 45 stars (V = 4.3-13.9 mag) from the early phase of the campaign. We also present a novel approach to calculating contrast curves for companion detection based on 95% completeness in the recovery of artificial companions injected into the raw data, while accounting for the false-positive rate. We use this technique to select the image processing algorithms that are more successful at recovering faint simulated point sources. We compare our pipeline to the performance of the Locally Optimized Combination of Images (LOCI) algorithm for NICI data and do not find significant improvement with LOCI. Based on observations obtained at the Gemini Observatory, which is operated by the Association of Universities for Research in Astronomy, Inc., under a cooperative agreement with the NSF on behalf of the Gemini partnership: the National Science Foundation (United States), the Science and Technology Facilities Council (United Kingdom), the National Research Council (Canada), CONICYT (Chile), the Australian Research Council (Australia), Ministério da Ciência e Tecnologia (Brazil) and Ministerio de Ciencia, Tecnología e Innovación Productiva (Argentina).

Pipeline Processing for VISTA

NASA Astrophysics Data System (ADS)

Lewis, J. R.; Irwin, M.; Bunclark, P.

2010-12-01

The VISTA telescope is a 4 metre instrument which has recently been commissioned at Paranal, Chile. Equipped with an infrared camera, 16 2Kx2K Raytheon detectors and a 1.7 square degree field of view, VISTA represents a huge leap in infrared survey capability in the southern hemisphere. Pipeline processing of IR data is far more technically challenging than for optical data. IR detectors are inherently more unstable, while the sky emission is over 100 times brighter than most objects of interest, and varies in a complex spatial and temporal manner. To compensate for this, exposure times are kept short, leading to high nightly data rates. VISTA is expected to generate an average of 250 GB of data per night over the next 5-10 years, which far exceeds the current total data rate of all 8m-class telescopes. In this presentation we discuss the pipelines that have been developed to deal with IR imaging data from VISTA and discuss the primary issues involved in an end-to-end system capable of: robustly removing instrument and night sky signatures; monitoring data quality and system integrity; providing astrometric and photometric calibration; and generating photon noise-limited images and science-ready astronomical catalogues.

PipeCraft: Flexible open-source toolkit for bioinformatics analysis of custom high-throughput amplicon sequencing data.

PubMed

Anslan, Sten; Bahram, Mohammad; Hiiesalu, Indrek; Tedersoo, Leho

2017-11-01

High-throughput sequencing methods have become a routine analysis tool in environmental sciences as well as in public and private sector. These methods provide vast amount of data, which need to be analysed in several steps. Although the bioinformatics may be applied using several public tools, many analytical pipelines allow too few options for the optimal analysis for more complicated or customized designs. Here, we introduce PipeCraft, a flexible and handy bioinformatics pipeline with a user-friendly graphical interface that links several public tools for analysing amplicon sequencing data. Users are able to customize the pipeline by selecting the most suitable tools and options to process raw sequences from Illumina, Pacific Biosciences, Ion Torrent and Roche 454 sequencing platforms. We described the design and options of PipeCraft and evaluated its performance by analysing the data sets from three different sequencing platforms. We demonstrated that PipeCraft is able to process large data sets within 24 hr. The graphical user interface and the automated links between various bioinformatics tools enable easy customization of the workflow. All analytical steps and options are recorded in log files and are easily traceable. © 2017 John Wiley & Sons Ltd.

Dynamic Black-Level Correction and Artifact Flagging for Kepler Pixel Time Series

NASA Technical Reports Server (NTRS)

Kolodziejczak, J. J.; Clarke, B. D.; Caldwell, D. A.

2011-01-01

Methods applied to the calibration stage of Kepler pipeline data processing [1] (CAL) do not currently use all of the information available to identify and correct several instrument-induced artifacts. These include time-varying crosstalk from the fine guidance sensor (FGS) clock signals, and manifestations of drifting moire pattern as locally correlated nonstationary noise, and rolling bands in the images which find their way into the time series [2], [3]. As the Kepler Mission continues to improve the fidelity of its science data products, we are evaluating the benefits of adding pipeline steps to more completely model and dynamically correct the FGS crosstalk, then use the residuals from these model fits to detect and flag spatial regions and time intervals of strong time-varying black-level which may complicate later processing or lead to misinterpretation of instrument behavior as stellar activity.

Kepler Data Validation I—Architecture, Diagnostic Tests, and Data Products for Vetting Transiting Planet Candidates

NASA Astrophysics Data System (ADS)

Twicken, Joseph D.; Catanzarite, Joseph H.; Clarke, Bruce D.; Girouard, Forrest; Jenkins, Jon M.; Klaus, Todd C.; Li, Jie; McCauliff, Sean D.; Seader, Shawn E.; Tenenbaum, Peter; Wohler, Bill; Bryson, Stephen T.; Burke, Christopher J.; Caldwell, Douglas A.; Haas, Michael R.; Henze, Christopher E.; Sanderfer, Dwight T.

2018-06-01

The Kepler Mission was designed to identify and characterize transiting planets in the Kepler Field of View and to determine their occurrence rates. Emphasis was placed on identification of Earth-size planets orbiting in the Habitable Zone of their host stars. Science data were acquired for a period of four years. Long-cadence data with 29.4 min sampling were obtained for ∼200,000 individual stellar targets in at least one observing quarter in the primary Kepler Mission. Light curves for target stars are extracted in the Kepler Science Data Processing Pipeline, and are searched for transiting planet signatures. A Threshold Crossing Event is generated in the transit search for targets where the transit detection threshold is exceeded and transit consistency checks are satisfied. These targets are subjected to further scrutiny in the Data Validation (DV) component of the Pipeline. Transiting planet candidates are characterized in DV, and light curves are searched for additional planets after transit signatures are modeled and removed. A suite of diagnostic tests is performed on all candidates to aid in discrimination between genuine transiting planets and instrumental or astrophysical false positives. Data products are generated per target and planet candidate to document and display transiting planet model fit and diagnostic test results. These products are exported to the Exoplanet Archive at the NASA Exoplanet Science Institute, and are available to the community. We describe the DV architecture and diagnostic tests, and provide a brief overview of the data products. Transiting planet modeling and the search for multiple planets on individual targets are described in a companion paper. The final revision of the Kepler Pipeline code base is available to the general public through GitHub. The Kepler Pipeline has also been modified to support the Transiting Exoplanet Survey Satellite (TESS) Mission which is expected to commence in 2018.

Kepler Data Validation I: Architecture, Diagnostic Tests, and Data Products for Vetting Transiting Planet Candidates

NASA Technical Reports Server (NTRS)

Twicken, Joseph D.; Catanzarite, Joseph H.; Clarke, Bruce D.; Giroud, Forrest; Jenkins, Jon M.; Klaus, Todd C.; Li, Jie; McCauliff, Sean D.; Seader, Shawn E.; Tennenbaum, Peter;

MTI science, data products, and ground-data processing overview

NASA Astrophysics Data System (ADS)

Szymanski, John J.; Atkins, William H.; Balick, Lee K.; Borel, Christoph C.; Clodius, William B.; Christensen, R. Wynn; Davis, Anthony B.; Echohawk, J. C.; Galbraith, Amy E.; Hirsch, Karen L.; Krone, James B.; Little, Cynthia K.; McLachlan, Peter M.; Morrison, Aaron; Pollock, Kimberly A.; Pope, Paul A.; Novak, Curtis; Ramsey, Keri A.; Riddle, Emily E.; Rohde, Charles A.; Roussel-Dupre, Diane C.; Smith, Barham W.; Smith, Kathy; Starkovich, Kim; Theiler, James P.; Weber, Paul G.

2001-08-01

The mission of the Multispectral Thermal Imager (MTI) satellite is to demonstrate the efficacy of highly accurate multispectral imaging for passive characterization of urban and industrial areas, as well as sites of environmental interest. The satellite makes top-of-atmosphere radiance measurements that are subsequently processed into estimates of surface properties such as vegetation health, temperatures, material composition and others. The MTI satellite also provides simultaneous data for atmospheric characterization at high spatial resolution. To utilize these data the MTI science program has several coordinated components, including modeling, comprehensive ground-truth measurements, image acquisition planning, data processing and data interpretation and analysis. Algorithms have been developed to retrieve a multitude of physical quantities and these algorithms are integrated in a processing pipeline architecture that emphasizes automation, flexibility and programmability. In addition, the MTI science team has produced detailed site, system and atmospheric models to aid in system design and data analysis. This paper provides an overview of the MTI research objectives, data products and ground data processing.

Discrete pre-processing step effects in registration-based pipelines, a preliminary volumetric study on T1-weighted images

PubMed Central

2017-01-01

Pre-processing MRI scans prior to performing volumetric analyses is common practice in MRI studies. As pre-processing steps adjust the voxel intensities, the space in which the scan exists, and the amount of data in the scan, it is possible that the steps have an effect on the volumetric output. To date, studies have compared between and not within pipelines, and so the impact of each step is unknown. This study aims to quantify the effects of pre-processing steps on volumetric measures in T1-weighted scans within a single pipeline. It was our hypothesis that pre-processing steps would significantly impact ROI volume estimations. One hundred fifteen participants from the OASIS dataset were used, where each participant contributed three scans. All scans were then pre-processed using a step-wise pipeline. Bilateral hippocampus, putamen, and middle temporal gyrus volume estimations were assessed following each successive step, and all data were processed by the same pipeline 5 times. Repeated-measures analyses tested for a main effects of pipeline step, scan-rescan (for MRI scanner consistency) and repeated pipeline runs (for algorithmic consistency). A main effect of pipeline step was detected, and interestingly an interaction between pipeline step and ROI exists. No effect for either scan-rescan or repeated pipeline run was detected. We then supply a correction for noise in the data resulting from pre-processing. PMID:29023597

Why the Scientific Pipeline Is Still Leaking? Women Scientists and Their Work-Life Balance in Poland

ERIC Educational Resources Information Center

Polkowska, Dominika

2014-01-01

In the contemporary scholarly discourse, the under-representation of women in science is often explained by the phenomenon of women "in the pipeline". The pipeline carries a flow from one stage to another, and the flow of women diminishes between the stages. Based on the literature and qualitative studies, it can be inferred that one of…

AmeriFlux Data Processing: Integrating automated and manual data management across software technologies and an international network to generate timely data products

NASA Astrophysics Data System (ADS)

Christianson, D. S.; Beekwilder, N.; Chan, S.; Cheah, Y. W.; Chu, H.; Dengel, S.; O'Brien, F.; Pastorello, G.; Sandesh, M.; Torn, M. S.; Agarwal, D.

2017-12-01

AmeriFlux is a network of scientists who independently collect eddy covariance and related environmental observations at over 250 locations across the Americas. As part of the AmeriFlux Management Project, the AmeriFlux Data Team manages standardization, collection, quality assurance / quality control (QA/QC), and distribution of data submitted by network members. To generate data products that are timely, QA/QC'd, and repeatable, and have traceable provenance, we developed a semi-automated data processing pipeline. The new pipeline consists of semi-automated format and data QA/QC checks. Results are communicated via on-line reports as well as an issue-tracking system. Data processing time has been reduced from 2-3 days to a few hours of manual review time, resulting in faster data availability from the time of data submission. The pipeline is scalable to the network level and has the following key features. (1) On-line results of the format QA/QC checks are available immediately for data provider review. This enables data providers to correct and resubmit data quickly. (2) The format QA/QC assessment includes an automated attempt to fix minor format errors. Data submissions that are formatted in the new AmeriFlux FP-In standard can be queued for the data QA/QC assessment, often with minimal delay. (3) Automated data QA/QC checks identify and communicate potentially erroneous data via online, graphical quick views that highlight observations with unexpected values, incorrect units, time drifts, invalid multivariate correlations, and/or radiation shadows. (4) Progress through the pipeline is integrated with an issue-tracking system that facilitates communications between data providers and the data processing team in an organized and searchable fashion. Through development of these and other features of the pipeline, we present solutions to challenges that include optimizing automated with manual processing, bridging legacy data management infrastructure with various software tools, and working across interdisciplinary and international science cultures. Additionally, we discuss results from community member feedback that helped refine QA/QC communications for efficient data submission and revision.

BioImageXD: an open, general-purpose and high-throughput image-processing platform.

PubMed

Kankaanpää, Pasi; Paavolainen, Lassi; Tiitta, Silja; Karjalainen, Mikko; Päivärinne, Joacim; Nieminen, Jonna; Marjomäki, Varpu; Heino, Jyrki; White, Daniel J

2012-06-28

BioImageXD puts open-source computer science tools for three-dimensional visualization and analysis into the hands of all researchers, through a user-friendly graphical interface tuned to the needs of biologists. BioImageXD has no restrictive licenses or undisclosed algorithms and enables publication of precise, reproducible and modifiable workflows. It allows simple construction of processing pipelines and should enable biologists to perform challenging analyses of complex processes. We demonstrate its performance in a study of integrin clustering in response to selected inhibitors.

A Java-based fMRI processing pipeline evaluation system for assessment of univariate general linear model and multivariate canonical variate analysis-based pipelines.

PubMed

Zhang, Jing; Liang, Lichen; Anderson, Jon R; Gatewood, Lael; Rottenberg, David A; Strother, Stephen C

2008-01-01

As functional magnetic resonance imaging (fMRI) becomes widely used, the demands for evaluation of fMRI processing pipelines and validation of fMRI analysis results is increasing rapidly. The current NPAIRS package, an IDL-based fMRI processing pipeline evaluation framework, lacks system interoperability and the ability to evaluate general linear model (GLM)-based pipelines using prediction metrics. Thus, it can not fully evaluate fMRI analytical software modules such as FSL.FEAT and NPAIRS.GLM. In order to overcome these limitations, a Java-based fMRI processing pipeline evaluation system was developed. It integrated YALE (a machine learning environment) into Fiswidgets (a fMRI software environment) to obtain system interoperability and applied an algorithm to measure GLM prediction accuracy. The results demonstrated that the system can evaluate fMRI processing pipelines with univariate GLM and multivariate canonical variates analysis (CVA)-based models on real fMRI data based on prediction accuracy (classification accuracy) and statistical parametric image (SPI) reproducibility. In addition, a preliminary study was performed where four fMRI processing pipelines with GLM and CVA modules such as FSL.FEAT and NPAIRS.CVA were evaluated with the system. The results indicated that (1) the system can compare different fMRI processing pipelines with heterogeneous models (NPAIRS.GLM, NPAIRS.CVA and FSL.FEAT) and rank their performance by automatic performance scoring, and (2) the rank of pipeline performance is highly dependent on the preprocessing operations. These results suggest that the system will be of value for the comparison, validation, standardization and optimization of functional neuroimaging software packages and fMRI processing pipelines.

78 FR 32010 - Pipeline Safety: Public Workshop on Integrity Verification Process

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-28

.... PHMSA-2013-0119] Pipeline Safety: Public Workshop on Integrity Verification Process AGENCY: Pipeline and... announcing a public workshop to be held on the concept of ``Integrity Verification Process.'' The Integrity Verification Process shares similar characteristics with fitness for service processes. At this workshop, the...

The American Science Pipeline: Sustaining Innovation in a Time of Economic Crisis

PubMed Central

Hue, Gillian; Sales, Jessica; Comeau, Dawn; Lynn, David G.

2010-01-01

Significant limitations have emerged in America's science training pipeline, including inaccessibility, inflexibility, financial limitations, and lack of diversity. We present three effective programs that collectively address these challenges. The programs are grounded in rigorous science and integrate through diverse disciplines across undergraduate, graduate, and postdoctoral students, and resonate with the broader community. We discuss these models in the context of current economic constraints on higher education and the urgent need for our institutions to recruit and retain diverse student populations and sustain the successful American record in scientific education and innovation. PMID:21123689

MER Telemetry Processor

NASA Technical Reports Server (NTRS)

Lee, Hyun H.

2012-01-01

MERTELEMPROC processes telemetered data in data product format and generates Experiment Data Records (EDRs) for many instruments (HAZCAM, NAVCAM, PANCAM, microscopic imager, Moessbauer spectrometer, APXS, RAT, and EDLCAM) on the Mars Exploration Rover (MER). If the data is compressed, then MERTELEMPROC decompresses the data with an appropriate decompression algorithm. There are two compression algorithms (ICER and LOCO) used in MER. This program fulfills a MER specific need to generate Level 1 products within a 60-second time requirement. EDRs generated by this program are used by merinverter, marscahv, marsrad, and marsjplstereo to generate higher-level products for the mission operations. MERTELEPROC was the first GDS program to process the data product. Metadata of the data product is in XML format. The software allows user-configurable input parameters, per-product processing (not streambased processing), and fail-over is allowed if the leading image header is corrupted. It is used within the MER automated pipeline. MERTELEMPROC is part of the OPGS (Operational Product Generation Subsystem) automated pipeline, which analyzes images returned by in situ spacecraft and creates level 1 products to assist in operations, science, and outreach.

Enabling Near Real-Time Remote Search for Fast Transient Events with Lossy Data Compression

NASA Astrophysics Data System (ADS)

Vohl, Dany; Pritchard, Tyler; Andreoni, Igor; Cooke, Jeffrey; Meade, Bernard

2017-09-01

We present a systematic evaluation of JPEG2000 (ISO/IEC 15444) as a transport data format to enable rapid remote searches for fast transient events as part of the Deeper Wider Faster programme. Deeper Wider Faster programme uses 20 telescopes from radio to gamma rays to perform simultaneous and rapid-response follow-up searches for fast transient events on millisecond-to-hours timescales. Deeper Wider Faster programme search demands have a set of constraints that is becoming common amongst large collaborations. Here, we focus on the rapid optical data component of Deeper Wider Faster programme led by the Dark Energy Camera at Cerro Tololo Inter-American Observatory. Each Dark Energy Camera image has 70 total coupled-charged devices saved as a 1.2 gigabyte FITS file. Near real-time data processing and fast transient candidate identifications-in minutes for rapid follow-up triggers on other telescopes-requires computational power exceeding what is currently available on-site at Cerro Tololo Inter-American Observatory. In this context, data files need to be transmitted rapidly to a foreign location for supercomputing post-processing, source finding, visualisation and analysis. This step in the search process poses a major bottleneck, and reducing the data size helps accommodate faster data transmission. To maximise our gain in transfer time and still achieve our science goals, we opt for lossy data compression-keeping in mind that raw data is archived and can be evaluated at a later time. We evaluate how lossy JPEG2000 compression affects the process of finding transients, and find only a negligible effect for compression ratios up to 25:1. We also find a linear relation between compression ratio and the mean estimated data transmission speed-up factor. Adding highly customised compression and decompression steps to the science pipeline considerably reduces the transmission time-validating its introduction to the Deeper Wider Faster programme science pipeline and enabling science that was otherwise too difficult with current technology.

Amateur Image Pipeline Processing using Python plus PyRAF

NASA Astrophysics Data System (ADS)

Green, Wayne

2012-05-01

A template pipeline spanning observing planning to publishing is offered as a basis for establishing a long term observing program. The data reduction pipeline encapsulates all policy and procedures, providing an accountable framework for data analysis and a teaching framework for IRAF. This paper introduces the technical details of a complete pipeline processing environment using Python, PyRAF and a few other languages. The pipeline encapsulates all processing decisions within an auditable framework. The framework quickly handles the heavy lifting of image processing. It also serves as an excellent teaching environment for astronomical data management and IRAF reduction decisions.

A Conceptual Model of the Air Force Logistics Pipeline

DTIC Science & Technology

1989-09-01

Contracting Process . ....... 138 Industrial Capacity .. ......... 140 The Disposal Pipeline Subsystem ....... 142 Collective Pipeline Models...Explosion of " Industry ," Acquisition and Production Process .... ............ 202 60. First Level Explosion of "Attrition," the Disposal Process...Terminology and Phrases, a publication of The American Production and Inventory Control Society ( APICS ). This dictionary defines 5 "pipeline stock" as the

Enrichment programs to create a pipeline to biomedical science careers.

PubMed

Cregler, L L

1993-01-01

The Student Educational Enrichment Programs at the Medical College of Georgia in the School of Medicine were created to increase underrepresented minorities in the pipeline to biomedical science careers. Eight-week summer programs are conducted for high school, research apprentice, and intermediate and advanced college students. There is a prematriculation program for accepted medical, dental, and graduate students. Between 1979 and 1990, 245 high school students attended 12 summer programs. Of these, 240 (98%) entered college 1 year later. In 1986, after eight programs, 162 (68%) high school participants graduated from college with a baccalaureate degree, and 127 responded to a follow-up survey. Sixty-two (49%) of the college graduates attended health science schools, and 23 (18%) of these matriculated to medical school. Of college students, 504 participated in 13 summer programs. Four hundred (79%) of these students responded to a questionnaire, which indicated that 348 (87%) of the 400 entered health science occupations and/or professional schools; 179 (45%) of these students matriculated to medical school. Minority students participating in enrichment programs have greater success in gaining acceptance to college and professional school. These data suggest that early enrichment initiatives increase the number of underrepresented minorities in the biomedical science pipeline.

Integrating Semantic Information in Metadata Descriptions for a Geoscience-wide Resource Inventory.

NASA Astrophysics Data System (ADS)

Zaslavsky, I.; Richard, S. M.; Gupta, A.; Valentine, D.; Whitenack, T.; Ozyurt, I. B.; Grethe, J. S.; Schachne, A.

2016-12-01

Integrating semantic information into legacy metadata catalogs is a challenging issue and so far has been mostly done on a limited scale. We present experience of CINERGI (Community Inventory of Earthcube Resources for Geoscience Interoperability), an NSF Earthcube Building Block project, in creating a large cross-disciplinary catalog of geoscience information resources to enable cross-domain discovery. The project developed a pipeline for automatically augmenting resource metadata, in particular generating keywords that describe metadata documents harvested from multiple geoscience information repositories or contributed by geoscientists through various channels including surveys and domain resource inventories. The pipeline examines available metadata descriptions using text parsing, vocabulary management and semantic annotation and graph navigation services of GeoSciGraph. GeoSciGraph, in turn, relies on a large cross-domain ontology of geoscience terms, which bridges several independently developed ontologies or taxonomies including SWEET, ENVO, YAGO, GeoSciML, GCMD, SWO, and CHEBI. The ontology content enables automatic extraction of keywords reflecting science domains, equipment used, geospatial features, measured properties, methods, processes, etc. We specifically focus on issues of cross-domain geoscience ontology creation, resolving several types of semantic conflicts among component ontologies or vocabularies, and constructing and managing facets for improved data discovery and navigation. The ontology and keyword generation rules are iteratively improved as pipeline results are presented to data managers for selective manual curation via a CINERGI Annotator user interface. We present lessons learned from applying CINERGI metadata augmentation pipeline to a number of federal agency and academic data registries, in the context of several use cases that require data discovery and integration across multiple earth science data catalogs of varying quality and completeness. The inventory is accessible at http://cinergi.sdsc.edu, and the CINERGI project web page is http://earthcube.org/group/cinergi

Presearch Data Conditioning in the Kepler Science Operations Center Pipeline

NASA Technical Reports Server (NTRS)

Twicken, Joseph D.; Chandrasekaran, Hema; Jenkins, Jon M.; Gunter, Jay P.; Girouard, Forrest; Klaus, Todd C.

2010-01-01

We describe the Presearch Data Conditioning (PDC) software component and its context in the Kepler Science Operations Center (SOC) pipeline. The primary tasks of this component are to correct systematic and other errors, remove excess flux due to aperture crowding, and condition the raw flux light curves for over 160,000 long cadence (thirty minute) and 512 short cadence (one minute) targets across the focal plane array. Long cadence corrected flux light curves are subjected to a transiting planet search in a subsequent pipeline module. We discuss the science algorithms for long and short cadence PDC: identification and correction of unexplained (i.e., unrelated to known anomalies) discontinuities; systematic error correction; and excess flux removal. We discuss the propagation of uncertainties from raw to corrected flux. Finally, we present examples of raw and corrected flux time series for flight data to illustrate PDC performance. Corrected flux light curves produced by PDC are exported to the Multi-mission Archive at Space Telescope [Science Institute] (MAST) and will be made available to the general public in accordance with the NASA/Kepler data release policy.

Developing an ESIP-wide Process "Pipeline" to Extract Data-driven Stories from Compelling Agriculture and Energy Research on Climate Resilience

NASA Astrophysics Data System (ADS)

Hoebelheinrich, N. J.; Eckman, R.; Teng, W. L.; Beltz, C.

2016-12-01

The classic approach to scientific storytelling, especially for publication, is to establish the research problem, describe the potential solution and the efforts to solve the problem, and end with the results - whether "successful" or not - as the "Ta Da!" of the story. This classic approach, however, does not necessarily adapt well to the kind of storytelling that policy-making and general public end-users find more compelling, i.e., with the "Ta Da!" element of the story immediately evident. Working with the U.S. Climate Resilience Toolkit (CRT) staff, two collaborative groups of the Earth Science Information Partners (ESIP), Agriculture and Climate and Energy and Climate, have begun to assist agriculture and energy researchers in making the switch in story telling approach and, thus, get more easily understood and actionable information out to potential end-users about how the research data produced can help them. The CRT is a platform for telling stories based on both end-user needs and the data that are used to meet those needs. The ESIP groups are establishing an ESIP-wide process "pipeline," through which research results and data, with the help of group discussions and the use of CRT templates, are transformed into potential stories. When appropriate, the stories are handed off to the CRT staff to be fully developed. Two case studies that are in the process of being added to the CRT involve (1) the use of the RETScreen tool by Natural Resources Canada and (2) a fallow lands mapping project with the California Department of Water Resources to monitor ongoing drought conditions in California. These two case studies will be used to illustrate the process pipeline being developed, discuss lessons learned to date, and suggest future plans for further refining and expanding the process "pipeline."

Processing and Managing the Kepler Mission's Treasure Trove of Stellar and Exoplanet Data

NASA Technical Reports Server (NTRS)

Jenkins, Jon M.

2016-01-01

The Kepler telescope launched into orbit in March 2009, initiating NASAs first mission to discover Earth-size planets orbiting Sun-like stars. Kepler simultaneously collected data for 160,000 target stars at a time over its four-year mission, identifying over 4700 planet candidates, 2300 confirmed or validated planets, and over 2100 eclipsing binaries. While Kepler was designed to discover exoplanets, the long term, ultra- high photometric precision measurements it achieved made it a premier observational facility for stellar astrophysics, especially in the field of asteroseismology, and for variable stars, such as RR Lyraes. The Kepler Science Operations Center (SOC) was developed at NASA Ames Research Center to process the data acquired by Kepler from pixel-level calibrations all the way to identifying transiting planet signatures and subjecting them to a suite of diagnostic tests to establish or break confidence in their planetary nature. Detecting small, rocky planets transiting Sun-like stars presents a variety of daunting challenges, from achieving an unprecedented photometric precision of 20 parts per million (ppm) on 6.5-hour timescales, supporting the science operations, management, processing, and repeated reprocessing of the accumulating data stream. This paper describes how the design of the SOC meets these varied challenges, discusses the architecture of the SOC and how the SOC pipeline is operated and is run on the NAS Pleiades supercomputer, and summarizes the most important pipeline features addressing the multiple computational, image and signal processing challenges posed by Kepler.

Barriers to the Preclinical Development of Therapeutics that Target Aging Mechanisms.

PubMed

Burd, Christin E; Gill, Matthew S; Niedernhofer, Laura J; Robbins, Paul D; Austad, Steven N; Barzilai, Nir; Kirkland, James L

2016-11-01

Through the progress of basic science research, fundamental mechanisms that contribute to age-related decline are being described with increasing depth and detail. Although these efforts have identified new drug targets and compounds that extend life span in model organisms, clinical trials of therapeutics that target aging processes remain scarce. Progress in aging research is hindered by barriers associated with the translation of basic science discoveries into the clinic. This report summarizes discussions held at a 2014 Geroscience Network retreat focused on identifying hurdles that currently impede the preclinical development of drugs targeting fundamental aging processes. From these discussions, it was evident that aging researchers have varied perceptions of the ideal preclinical pipeline. To forge a clear and cohesive path forward, several areas of controversy must first be resolved and new tools developed. Here, we focus on five key issues in preclinical drug development (drug discovery, lead compound development, translational preclinical biomarkers, funding, and integration between researchers and clinicians), expanding upon discussions held at the Geroscience Retreat and suggesting areas for further research. By bringing these findings to the attention of the aging research community, we hope to lay the foundation for a concerted preclinical drug development pipeline. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America.

When complexity science meets implementation science: a theoretical and empirical analysis of systems change.

PubMed

Braithwaite, Jeffrey; Churruca, Kate; Long, Janet C; Ellis, Louise A; Herkes, Jessica

2018-04-30

Implementation science has a core aim - to get evidence into practice. Early in the evidence-based medicine movement, this task was construed in linear terms, wherein the knowledge pipeline moved from evidence created in the laboratory through to clinical trials and, finally, via new tests, drugs, equipment, or procedures, into clinical practice. We now know that this straight-line thinking was naïve at best, and little more than an idealization, with multiple fractures appearing in the pipeline. The knowledge pipeline derives from a mechanistic and linear approach to science, which, while delivering huge advances in medicine over the last two centuries, is limited in its application to complex social systems such as healthcare. Instead, complexity science, a theoretical approach to understanding interconnections among agents and how they give rise to emergent, dynamic, systems-level behaviors, represents an increasingly useful conceptual framework for change. Herein, we discuss what implementation science can learn from complexity science, and tease out some of the properties of healthcare systems that enable or constrain the goals we have for better, more effective, more evidence-based care. Two Australian examples, one largely top-down, predicated on applying new standards across the country, and the other largely bottom-up, adopting medical emergency teams in over 200 hospitals, provide empirical support for a complexity-informed approach to implementation. The key lessons are that change can be stimulated in many ways, but a triggering mechanism is needed, such as legislation or widespread stakeholder agreement; that feedback loops are crucial to continue change momentum; that extended sweeps of time are involved, typically much longer than believed at the outset; and that taking a systems-informed, complexity approach, having regard for existing networks and socio-technical characteristics, is beneficial. Construing healthcare as a complex adaptive system implies that getting evidence into routine practice through a step-by-step model is not feasible. Complexity science forces us to consider the dynamic properties of systems and the varying characteristics that are deeply enmeshed in social practices, whilst indicating that multiple forces, variables, and influences must be factored into any change process, and that unpredictability and uncertainty are normal properties of multi-part, intricate systems.

Interacting with the National Database for Autism Research (NDAR) via the LONI Pipeline workflow environment.

PubMed

Torgerson, Carinna M; Quinn, Catherine; Dinov, Ivo; Liu, Zhizhong; Petrosyan, Petros; Pelphrey, Kevin; Haselgrove, Christian; Kennedy, David N; Toga, Arthur W; Van Horn, John Darrell

2015-03-01

Under the umbrella of the National Database for Clinical Trials (NDCT) related to mental illnesses, the National Database for Autism Research (NDAR) seeks to gather, curate, and make openly available neuroimaging data from NIH-funded studies of autism spectrum disorder (ASD). NDAR has recently made its database accessible through the LONI Pipeline workflow design and execution environment to enable large-scale analyses of cortical architecture and function via local, cluster, or "cloud"-based computing resources. This presents a unique opportunity to overcome many of the customary limitations to fostering biomedical neuroimaging as a science of discovery. Providing open access to primary neuroimaging data, workflow methods, and high-performance computing will increase uniformity in data collection protocols, encourage greater reliability of published data, results replication, and broaden the range of researchers now able to perform larger studies than ever before. To illustrate the use of NDAR and LONI Pipeline for performing several commonly performed neuroimaging processing steps and analyses, this paper presents example workflows useful for ASD neuroimaging researchers seeking to begin using this valuable combination of online data and computational resources. We discuss the utility of such database and workflow processing interactivity as a motivation for the sharing of additional primary data in ASD research and elsewhere.

Ironing Out the Wrinkles

NASA Astrophysics Data System (ADS)

Ayres, Thomas

2009-07-01

This is a Calibration Archival proposal to develop, implement, and test enhancements to the pipeline wavelength scales of STIS echelle spectra, to take full advantage of the extremely high performance of which the instrument is capable. The motivation is a recent extensive investigation--The Deep Lamp Project--which identified systematic wavelength distortions in all 44 primary and secondary settings of the four STIS echelle modes: E140M, E140H, E230M, and E230H. The method was to process deep exposures of the onboard Pt/Cr-Ne calibration source as if they were science images, and measure deviations of the lamp lines from their laboratory wavelengths. An approach has been developed to correct the distortions post facto, but it would be preferable to implement a more robust dispersion model in the pipeline itself. The proposed study will examine a more extensive set of WAVECALs than in the exploratory Deep Lamp effort, and will benefit from a new laboratory line list specifically for the STIS lamps. Ironing out the wrinkles in the STIS wavelength scales will impact many diverse science investigations, especially the Legacy Archival project "StarCAT."

WFIRST: STScI Science Operations Center (SSOC) Activities and Plans

NASA Astrophysics Data System (ADS)

Gilbert, Karoline M.; STScI WFIRST Team

2018-01-01

The science operations for the WFIRST Mission will be distributed between Goddard Space Flight Center, the Space Telescope Science Institute (STScI), and the Infrared Processing and Analysis Center (IPAC). The STScI Science Operations Center (SSOC) will schedule and archive all WFIRST observations, will calibrate and produce pipeline-reduced data products for the Wide Field Instrument, and will support the astronomical community in planning WFI observations and analyzing WFI data. During the formulation phase, WFIRST team members at STScI have developed operations concepts for scheduling, data management, and the archive; have performed technical studies investigating the impact of WFIRST design choices on data quality and analysis; and have built simulation tools to aid the community in exploring WFIRST’s capabilities. We will highlight examples of each of these efforts.

Redefining the Data Pipeline Using GPUs

NASA Astrophysics Data System (ADS)

Warner, C.; Eikenberry, S. S.; Gonzalez, A. H.; Packham, C.

2013-10-01

There are two major challenges facing the next generation of data processing pipelines: 1) handling an ever increasing volume of data as array sizes continue to increase and 2) the desire to process data in near real-time to maximize observing efficiency by providing rapid feedback on data quality. Combining the power of modern graphics processing units (GPUs), relational database management systems (RDBMSs), and extensible markup language (XML) to re-imagine traditional data pipelines will allow us to meet these challenges. Modern GPUs contain hundreds of processing cores, each of which can process hundreds of threads concurrently. Technologies such as Nvidia's Compute Unified Device Architecture (CUDA) platform and the PyCUDA (http://mathema.tician.de/software/pycuda) module for Python allow us to write parallel algorithms and easily link GPU-optimized code into existing data pipeline frameworks. This approach has produced speed gains of over a factor of 100 compared to CPU implementations for individual algorithms and overall pipeline speed gains of a factor of 10-25 compared to traditionally built data pipelines for both imaging and spectroscopy (Warner et al., 2011). However, there are still many bottlenecks inherent in the design of traditional data pipelines. For instance, file input/output of intermediate steps is now a significant portion of the overall processing time. In addition, most traditional pipelines are not designed to be able to process data on-the-fly in real time. We present a model for a next-generation data pipeline that has the flexibility to process data in near real-time at the observatory as well as to automatically process huge archives of past data by using a simple XML configuration file. XML is ideal for describing both the dataset and the processes that will be applied to the data. Meta-data for the datasets would be stored using an RDBMS (such as mysql or PostgreSQL) which could be easily and rapidly queried and file I/O would be kept at a minimum. We believe this redefined data pipeline will be able to process data at the telescope, concurrent with continuing observations, thus maximizing precious observing time and optimizing the observational process in general. We also believe that using this design, it is possible to obtain a speed gain of a factor of 30-40 over traditional data pipelines when processing large archives of data.

Key Provenance of Earth Science Observational Data Products

NASA Astrophysics Data System (ADS)

Conover, H.; Plale, B.; Aktas, M.; Ramachandran, R.; Purohit, P.; Jensen, S.; Graves, S. J.

2011-12-01

As the sheer volume of data increases, particularly evidenced in the earth and environmental sciences, local arrangements for sharing data need to be replaced with reliable records about the what, who, how, and where of a data set or collection. This is frequently called the provenance of a data set. While observational data processing systems in the earth sciences have a long history of capturing metadata about the processing pipeline, current processes are limited in both what is captured and how it is disseminated to the science community. Provenance capture plays a role in scientific data preservation and stewardship precisely because it can automatically capture and represent a coherent picture of the what, how and who of a particular scientific collection. It reflects the transformations that a data collection underwent prior to its current form and the sequence of tasks that were executed and data products applied to generate a new product. In the NASA-funded Instant Karma project, we examine provenance capture in earth science applications, specifically the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) Science Investigator-led Processing system (SIPS). The project is integrating the Karma provenance collection and representation tool into the AMSR-E SIPS production environment, with an initial focus on Sea Ice. This presentation will describe capture and representation of provenance that is guided by the Open Provenance Model (OPM). Several things have become clear during the course of the project to date. One is that core OPM entities and relationships are not adequate for expressing the kinds of provenance that is of interest in the science domain. OPM supports name-value pair annotations that can be used to augment what is known about the provenance entities and relationships, but in Karma, annotations cannot be added during capture, but only after the fact. This limits the capture system's ability to record something it learned about an entity after the event of its creation in the provenance record. We will discuss extensions to the Open Provenance Model (OPM) and modifications to the Karma tool suite to address this issue, more efficient representations of earth science kinds of provenance, and definition of metadata structures for capturing related knowledge about the data products and science algorithms used to generate them. Use scenarios for provenance information is an active topic of investigation. It has additionally become clear through the project that not all provenance is created equal. In processing pipelines, some provenance is repetitive and uninteresting. Because of the volume of provenance, this obscures what are the interesting pieces of provenance. Methodologies to reveal science-relevant provenance will be presented, along with a preview of the AMSR-E Provenance Browser.

The bachelor's to Ph.D. STEM pipeline no longer leaks more women than men: a 30-year analysis.

PubMed

Miller, David I; Wai, Jonathan

2015-01-01

For decades, research and public discourse about gender and science have often assumed that women are more likely than men to "leak" from the science pipeline at multiple points after entering college. We used retrospective longitudinal methods to investigate how accurately this "leaky pipeline" metaphor has described the bachelor's to Ph.D. transition in science, technology, engineering, and mathematics (STEM) fields in the U.S. since the 1970s. Among STEM bachelor's degree earners in the 1970s and 1980s, women were less likely than men to later earn a STEM Ph.D. However, this gender difference closed in the 1990s. Qualitatively similar trends were found across STEM disciplines. The leaky pipeline metaphor therefore partially explains historical gender differences in the U.S., but no longer describes current gender differences in the bachelor's to Ph.D. transition in STEM. The results help constrain theories about women's underrepresentation in STEM. Overall, these results point to the need to understand gender differences at the bachelor's level and below to understand women's representation in STEM at the Ph.D. level and above. Consistent with trends at the bachelor's level, women's representation at the Ph.D. level has been recently declining for the first time in over 40 years.

DIVERSITY IN THE BIOMEDICAL RESEARCH WORKFORCE: DEVELOPING TALENT

PubMed Central

McGee, Richard; Saran, Suman; Krulwich, Terry A.

2012-01-01

Much has been written about the need for and barriers to achievement of greater diversity in the biomedical workforce from the perspectives of gender, race and ethnicity; this is not a new topic. These discussions often center around a ‘pipeline metaphor’ which imagines students flowing through a series of experiences to eventually arrive at a science career. Here we argue that diversity will only be achieved if the primary focus is on: what is happening within the pipeline, not just counting individuals entering and leaving it; de-emphasizing achieving academic milestones by ‘typical’ ages; and adopting approaches that most effectively develop talent. Students may develop skills at different rates based on factors such as earlier access to educational resources, exposure to science (especially research experiences), and competing demands for time and attention during high school and college. Therefore, there is wide variety among students at any point along the pipeline. Taking this view requires letting go of imagining the pipeline as a sequence of age-dependent steps in favor of milestones of skill and talent development decoupled from age or educational stage. Emphasizing talent development opens up many new approaches for science training outside of traditional degree programs. This article provides examples of such approaches, including interventions at the post-baccalaureate and PhD levels, as well as a novel coaching model that incorporates well-established social science theories and complements traditional mentoring. These approaches could significantly impact diversity by developing scientific talent, especially among currently underrepresented minorities. PMID:22678863

The Next Generation of HLA Image Products

NASA Astrophysics Data System (ADS)

Gaffney, N. I.; Casertano, S.; Ferguson, B.

2012-09-01

We present the re-engineered pipeline based on existing and improved algorithms with the aim of improving processing quality, cross-instrument portability, data flow management, and software maintenance. The Hubble Legacy Archive (HLA) is a project to add value to the Hubble Space Telescope data archive by producing and delivering science-ready drizzled data products and source lists derived from these products. Initially, ACS, NICMOS, and WFCP2 data were combined using instrument-specific pipelines based on scripts developed to process the ACS GOODS data and a separate set of scripts to generate source extractor and DAOPhot source lists. The new pipeline, initially designed for WFC3 data, isolates instrument-specific processing and is easily extendable to other instruments and to generating wide-area mosaics. Significant improvements have been made in image combination using improved alignment, source detection, and background equalization routines. It integrates improved alignment procedures, better noise model, and source list generation within a single code base. Wherever practical, PyRAF based routines have been replaced with non-IRAF based python libraries (e.g. NumPy and PyFITS). The data formats have been modified to handle better and more consistent propagation of information from individual exposures to the combined products. A new exposure layer stores the effective exposure time for each pixel in the sky which is key in properly interpreting combined images from diverse data that were not initially planned to be mosaiced. We worked to improve the validity of the metadata within our FITS headers for these products relative to standard IRAF/PyRAF processing. Any keywords that pertain to individual exposures have been removed from the primary and extension headers and placed in a table extension for more direct and efficient perusal. This mechanism also allows for more detailed information on the processing of individual images to be stored and propagated providing a more hierarchical metadata storage system than key value pair FITS headers provide. In this poster we will discuss the changes to the pipeline processing and source list generation and the lessons learned which may be applicable to other archive projects as well as discuss our new metadata curation and preservation process.

Kepler Data Release 3 Notes

NASA Technical Reports Server (NTRS)

Cleve, Jeffrey E.

2010-01-01

This describes the collection of data and the processing done on it so when researchers around the world get the Kepler data sets (which are a set of pixels from the telescope of a particular target (star, galaxy or whatever) over a 3 month period) they can adjust their algorithms fro things that were done (like subtracting all of one particular wavelength for example). This is used to calibrate their own algorithms so that they know what it is they are starting with. It is posted so that whoever is accessing the publicly available data (not all of it is made public) can understand it .. (most of the Kepler data is under restriction for 1 - 4 years and is not available, but the handbook is for everyone (public and restricted) The Data Analysis Working Group have released long and short cadence materials, including FFls and Dropped Targets for the Public. The Kepler Science Office considers Data Release 3 to provide "browse quality" data. These notes have been prepared to give Kepler users of the Multimission Archive at STScl (MAST) a summary of how the data were collected and prepared, and how well the data processing pipeline is functioning on flight data. They will be updated for each release of data to the public archive and placed on MAST along with other Kepler documentation, at http:// archive.stsci.edu/kepler/documents.html .Data release 3 is meant to give users the opportunity to examine the data for possibly interesting science and to involve the users in improving the pipeline for future data releases. To perform the latter service, users are encouraged to notice and document artifacts, either in the raw or processed data, and report them to the Science Office.

Using modern imaging techniques to old HST data: a summary of the ALICE program.

NASA Astrophysics Data System (ADS)

Choquet, Elodie; Soummer, Remi; Perrin, Marshall; Pueyo, Laurent; Hagan, James Brendan; Zimmerman, Neil; Debes, John Henry; Schneider, Glenn; Ren, Bin; Milli, Julien; Wolff, Schuyler; Stark, Chris; Mawet, Dimitri; Golimowski, David A.; Hines, Dean C.; Roberge, Aki; Serabyn, Eugene

2018-01-01

Direct imaging of extrasolar systems is a powerful technique to study the physical properties of exoplanetary systems and understand their formation and evolution mechanisms. The detection and characterization of these objects are challenged by their high contrast with their host star. Several observing strategies and post-processing algorithms have been developed for ground-based high-contrast imaging instruments, enabling the discovery of directly-imaged and spectrally-characterized exoplanets. The Hubble Space Telescope (HST), pioneer in directly imaging extrasolar systems, has yet been often limited to the detection of bright debris disks systems, with sensitivity limited by the difficulty to implement an optimal PSF subtraction stategy, which is readily offered on ground-based telescopes in pupil tracking mode.The Archival Legacy Investigations of Circumstellar Environments (ALICE) program is a consistent re-analysis of the 10 year old coronagraphic archive of HST's NICMOS infrared imager. Using post-processing methods developed for ground-based observations, we used the whole archive to calibrate PSF temporal variations and improve NICMOS's detection limits. We have now delivered ALICE-reprocessed science products for the whole NICMOS archival data back to the community. These science products, as well as the ALICE pipeline, were used to prototype the JWST coronagraphic data and reduction pipeline. The ALICE program has enabled the detection of 10 faint debris disk systems never imaged before in the near-infrared and several substellar companion candidates, which we are all in the process of characterizing through follow-up observations with both ground-based facilities and HST-STIS coronagraphy. In this publication, we provide a summary of the results of the ALICE program, advertise its science products and discuss the prospects of the program.

Improving oceanographic data delivery through pipeline processing in a Commercial Cloud Services environment: the Australian Integrated Marine Observing System

NASA Astrophysics Data System (ADS)

Besnard, Laurent; Blain, Peter; Mancini, Sebastien; Proctor, Roger

2017-04-01

The Integrated Marine Observing System (IMOS) is a national project funded by the Australian government established to deliver ocean observations to the marine and climate science community. Now in its 10th year its mission is to undertake systematic and sustained observations and to turn them into data, products and analyses that can be freely used and reused for broad societal benefits. As IMOS has matured as an observing system expectation on the system's availability and reliability has also increased and IMOS is now seen as delivering 'operational' information. In responding to this expectation, IMOS has relocated its services to the commercial cloud service Amazon Web Services. This has enabled IMOS to improve the system architecture, utilizing more advanced features like object storage (S3 - Simple Storage Service) and autoscaling features, and introducing new checking procedures in a pipeline approach. This has improved data availability and resilience while protecting against human errors in data handling and providing a more efficient ingestion process.

Improved discovery of NEON data and samples though vocabularies, workflows, and web tools

NASA Astrophysics Data System (ADS)

Laney, C. M.; Elmendorf, S.; Flagg, C.; Harris, T.; Lunch, C. K.; Gulbransen, T.

2017-12-01

The National Ecological Observatory Network (NEON) is a continental-scale ecological observation facility sponsored by the National Science Foundation and operated by Battelle. NEON supports research on the impacts of invasive species, land use change, and environmental change on natural resources and ecosystems by gathering and disseminating a full suite of observational, instrumented, and airborne datasets from field sites across the U.S. NEON also collects thousands of samples from soil, water, and organisms every year, and partners with numerous institutions to analyze and archive samples. We have developed numerous new technologies to support processing and discovery of this highly diverse collection of data. These technologies include applications for data collection and sample management, processing pipelines specific to each collection system (field observations, installed sensors, and airborne instruments), and publication pipelines. NEON data and metadata are discoverable and downloadable via both a public API and data portal. We solicit continued engagement and advice from the informatics and environmental research communities, particularly in the areas of data versioning, usability, and visualization.

A Five-Year University/Community College Collaboration to Build STEM Pipeline Capacity

ERIC Educational Resources Information Center

Strawn, Clare; Livelybrooks, Dean

2012-01-01

This article investigates the mechanisms through which undergraduate research experiences for community college students can have second-order and multiplier effects on other students and home community college science, technology, engineering, and mathematics (STEM) departments and thus build STEM pipeline capacity. Focus groups with the science…

Teaching Cell and Molecular Biology for Gender Equity

ERIC Educational Resources Information Center

Sible, Jill C.; Wilhelm, Dayna E.; Lederman, Muriel

2006-01-01

Science, technology, engineering, and math (STEM) fields, including cell biology, are characterized by the "leaky pipeline" syndrome in which, over time, women leave the discipline. The pipeline itself and the pond into which it empties may not be neutral. Explicating invisible norms, attitudes, and practices by integrating social…

A Concept for the One Degree Imager (ODI) Data Reduction Pipeline and Archiving System

NASA Astrophysics Data System (ADS)

Knezek, Patricia; Stobie, B.; Michael, S.; Valdes, F.; Marru, S.; Henschel, R.; Pierce, M.

2010-05-01

The One Degree Imager (ODI), currently being built by the WIYN Observatory, will provide tremendous possibilities for conducting diverse scientific programs. ODI will be a complex instrument, using non-conventional Orthogonal Transfer Array (OTA) detectors. Due to its large field of view, small pixel size, use of OTA technology, and expected frequent use, ODI will produce vast amounts of astronomical data. If ODI is to achieve its full potential, a data reduction pipeline must be developed. Long-term archiving must also be incorporated into the pipeline system to ensure the continued value of ODI data. This paper presents a concept for an ODI data reduction pipeline and archiving system. To limit costs and development time, our plan leverages existing software and hardware, including existing pipeline software, Science Gateways, Computational Grid & Cloud Technology, Indiana University's Data Capacitor and Massive Data Storage System, and TeraGrid compute resources. Existing pipeline software will be augmented to add functionality required to meet challenges specific to ODI, enhance end-user control, and enable the execution of the pipeline on grid resources including national grid resources such as the TeraGrid and Open Science Grid. The planned system offers consistent standard reductions and end-user flexibility when working with images beyond the initial instrument signature removal. It also gives end-users access to computational and storage resources far beyond what are typically available at most institutions. Overall, the proposed system provides a wide array of software tools and the necessary hardware resources to use them effectively.

Academic computer science and gender: A naturalistic study investigating the causes of attrition

NASA Astrophysics Data System (ADS)

Declue, Timothy Hall

Far fewer women than men take computer science classes in high school, enroll in computer science programs in college, or complete advanced degrees in computer science. The computer science pipeline begins to shrink for women even before entering college, but it is at the college level that the "brain drain" is the most evident numerically, especially in the first class taken by most computer science majors called "Computer Science 1" or CS-I. The result, for both academia and industry, is a pronounced technological gender disparity in academic and industrial computer science. The study revealed the existence of several factors influencing success in CS-I. First, and most clearly, the effect of attribution processes seemed to be quite strong. These processes tend to work against success for females and in favor of success for males. Likewise, evidence was discovered which strengthens theories related to prior experience and the perception that computer science has a culture which is hostile to females. Two unanticipated themes related to the motivation and persistence of successful computer science majors. The findings did not support the belief that females have greater logistical problems in computer science than males, or that females tend to have a different programming style than males which adversely affects the females' ability to succeed in CS-I.

The bench vs. the blackboard: learning to teach during graduate school.

PubMed

Ciaccia, Laura

2011-09-01

Many science, technology, engineering, and mathematics (STEM) graduate students travel through the academic career pipeline without ever learning how to teach effectively, an oversight that negatively affects the quality of undergraduate science education and cheats trainees of valuable professional development. This article argues that all STEM graduate students and postdoctoral fellows should undergo training in teaching to strengthen their resumes, polish their oral presentation skills, and improve STEM teaching at the undergraduate level. Though this may seem like a large undertaking, the author outlines a three-step process that allows busy scientists to fit pedagogical training into their research schedules in order to make a significant investment both in their academic career and in the continuing improvement of science education. Copyright © 2011.

The Kepler DB: a database management system for arrays, sparse arrays, and binary data

NASA Astrophysics Data System (ADS)

McCauliff, Sean; Cote, Miles T.; Girouard, Forrest R.; Middour, Christopher; Klaus, Todd C.; Wohler, Bill

2010-07-01

The Kepler Science Operations Center stores pixel values on approximately six million pixels collected every 30 minutes, as well as data products that are generated as a result of running the Kepler science processing pipeline. The Kepler Database management system (Kepler DB)was created to act as the repository of this information. After one year of flight usage, Kepler DB is managing 3 TiB of data and is expected to grow to over 10 TiB over the course of the mission. Kepler DB is a non-relational, transactional database where data are represented as one-dimensional arrays, sparse arrays or binary large objects. We will discuss Kepler DB's APIs, implementation, usage and deployment at the Kepler Science Operations Center.

The Kepler DB, a Database Management System for Arrays, Sparse Arrays and Binary Data

NASA Technical Reports Server (NTRS)

McCauliff, Sean; Cote, Miles T.; Girouard, Forrest R.; Middour, Christopher; Klaus, Todd C.; Wohler, Bill

2010-01-01

The Kepler Science Operations Center stores pixel values on approximately six million pixels collected every 30-minutes, as well as data products that are generated as a result of running the Kepler science processing pipeline. The Kepler Database (Kepler DB) management system was created to act as the repository of this information. After one year of ight usage, Kepler DB is managing 3 TiB of data and is expected to grow to over 10 TiB over the course of the mission. Kepler DB is a non-relational, transactional database where data are represented as one dimensional arrays, sparse arrays or binary large objects. We will discuss Kepler DB's APIs, implementation, usage and deployment at the Kepler Science Operations Center.

CROSS-DISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Depletion interactions in a cylindric pipeline

NASA Astrophysics Data System (ADS)

Huang, Li-Xin; Gao, Hai-Xia; Li, Chun-Shu; Xiao, Chang-Ming

2009-08-01

In a colloidal system confined by a small cylindric pipeline, the depletion interaction between two large spheres is different to the system confined by two plates, and the influence on depletion interaction from the pipeline is related to both the size and shape of it. In this paper, the depletion interactions in the systems confined by pipelines of different sizes or different shapes are studied by Monte Carlo simulations. The numerical results show that the influence on depletion force from the cylindric pipeline is stronger than that from two parallel plates, and the depletion force will be strengthened when the diameter of the cylinder is decreased. In addition, we also find that the depletion interaction is rather affected if the shape change of the pipeline is slightly changed, and the influence on depletion force from the shape change is stronger than that from the size change.

The X-shooter pipeline

NASA Astrophysics Data System (ADS)

Goldoni, P.

2011-03-01

The X-shooter data reduction pipeline is an integral part of the X-shooter project, it allows the production of reduced data in physical quantities from the raw data produced by the instrument. The pipeline is based on the data reduction library developed by the X-shooter consortium with contributions from France, The Netherlands and ESO and it uses the Common Pipeline Library (CPL) developed at ESO. The pipeline has been developed for two main functions. The first function is to monitor the operation of the instrument through the reduction of the acquired data, both at Paranal, for a quick-look control, and in Garching, for a more thorough evaluation. The second function is to allow an optimized data reduction for a scientific user. In the following I will first outline the main steps of data reduction with the pipeline then I will briefly show two examples of optimization of the results for science reduction.

Closing the race and gender gaps in computer science education

NASA Astrophysics Data System (ADS)

Robinson, John Henry

Life in a technological society brings new paradigms and pressures to bear on education. These pressures are magnified for underrepresented students and must be addressed if they are to play a vital part in society. Educational pipelines need to be established to provide at risk students with the means and opportunity to succeed in science, technology, engineering, and mathematics (STEM) majors. STEM educational pipelines are programs consisting of components that seek to facilitate students' completion of a college degree by providing access to higher education, intervention, mentoring, support infrastructure, and programs that encourage academic success. Successes in the STEM professions mean that more educators, scientist, engineers, and researchers will be available to add diversity to the professions and to provide role models for future generations. The issues that the educational pipelines must address are improving at risk groups' perceptions and awareness of the math, science, and engineering professions. Additionally, the educational pipelines must provide intervention in math preparation, overcome gender and race socialization, and provide mentors and counseling to help students achieve better self perceptions and provide positive role models. This study was designed to explorer the underrepresentation of minorities and women in the computer science major at Rowan University through a multilayered action research methodology. The purpose of this research study was to define and understand the needs of underrepresented students in computer science, to examine current policies and enrollment data for Rowan University, to develop a historical profile of the Computer Science program from the standpoint of ethnicity and gender enrollment to ascertain trends in students' choice of computer science as a major, and an attempt to determine if raising awareness about computer science for incoming freshmen, and providing an alternate route into the computer science major will entice more women and minorities to pursue a degree in computer science at Rowan University. Finally, this study examined my espoused leadership theories and my leadership theories in use through reflective practices as I progressed through the cycles of this project. The outcomes of this study indicated a large downward trend in women enrollment in computer science and a relatively flat trend in minority enrollment. The enrollment data at Rowan University was found to follow a nationwide trend for underrepresented students' enrollment in STEM majors. The study also indicated that students' mental models are based upon their race and gender socialization and their understanding of the world and society. The mental models were shown to play a large role in the students' choice of major. Finally, a computer science pipeline was designed and piloted as part of this study in an attempt to entice more students into the major and facilitate their success. Additionally, the mental models of the participants were challenged through interactions to make them aware of what possibilities are available with a degree in computer science. The entire study was wrapped in my leadership, which was practiced and studied over the course of this work.

BRITE Constellation: data processing and photometry

NASA Astrophysics Data System (ADS)

Popowicz, A.; Pigulski, A.; Bernacki, K.; Kuschnig, R.; Pablo, H.; Ramiaramanantsoa, T.; Zocłońska, E.; Baade, D.; Handler, G.; Moffat, A. F. J.; Wade, G. A.; Neiner, C.; Rucinski, S. M.; Weiss, W. W.; Koudelka, O.; Orleański, P.; Schwarzenberg-Czerny, A.; Zwintz, K.

2017-09-01

Context. The BRIght Target Explorer (BRITE) mission is a pioneering space project aimed at the long-term photometric monitoring of the brightest stars in the sky by means of a constellation of nanosatellites. Its main advantage is high photometric accuracy and time coverage which are inaccessible from the ground. Its main drawback is the lack of cooling of the CCD detectors and the absence of good shielding that would protect them from energetic particles. Aims: The main aim of this paper is the presentation of procedures used to obtain high-precision photometry from a series of images acquired by the BRITE satellites in two modes of observing, stare and chopping. The other aim is a comparison of the photometry obtained with two different pipelines and a comparison of the real scatter with expectations. Methods: We developed two pipelines corresponding to the two modes of observing. They are based on aperture photometry with a constant aperture, circular for stare mode of observing and thresholded for chopping mode. Impulsive noise is a serious problem for observations made in the stare mode of observing and therefore in the pipeline developed for observations made in this mode, hot pixels are replaced using the information from shifted images in a series obtained during a single orbit of a satellite. In the other pipeline, the hot pixel replacement is not required because the photometry is made in difference images. Results: The assessment of the performance of both pipelines is presented. It is based on two comparisons, which use data from six runs of the UniBRITE satellite: (I) comparison of photometry obtained by both pipelines on the same data, which were partly affected by charge transfer inefficiency (CTI), (II) comparison of real scatter with theoretical expectations. It is shown that for CTI-affected observations, the chopping pipeline provides much better photometry than the other pipeline. For other observations, the results are comparable only for data obtained shortly after switching to chopping mode. Starting from about 2.5 years in orbit, the chopping mode of observing provides significantly better photometry for UniBRITE data than the stare mode. Conclusions: This paper shows that high-precision space photometry with low-cost nanosatellites is achievable. The proposed methods, used to obtain photometry from images affected by high impulsive noise, can be applied to data from other space missions or even to data acquired from ground-based observations. Based on data collected by the BRITE Constellation satellite mission, designed, built, launched, operated and supported by the Austrian Research Promotion Agency (FFG), the University of Vienna, the Technical University of Graz, the Canadian Space Agency (CSA), the University of Toronto Institute for Aerospace Studies (UTIAS), the Foundation for Polish Science & Technology (FNiTP MNiSW), and National Science Centre (NCN).

Van Allen Probes Science Gateway and Space Weather Data Processing

NASA Astrophysics Data System (ADS)

Romeo, G.; Barnes, R. J.; Weiss, M.; Fox, N. J.; Mauk, B.; Potter, M.; Kessel, R.

2014-12-01

The Van Allen Probes Science Gateway acts as a centralized interface to the instrument Science Operation Centers (SOCs), provides mission planning tools, and hosts a number of science related activities such as the mission bibliography. Most importantly, the Gateway acts as the primary site for processing and delivering the VAP Space Weather data to users. Over the past year, the web-site has been completely redesigned with the focus on easier navigation and improvements of the existing tools such as the orbit plotter, position calculator and magnetic footprint tool. In addition, a new data plotting facility has been added. Based on HTML5, which allows users to interactively plot Van Allen Probes summary and space weather data. The user can tailor the tool to display exactly the plot they wish to see and then share this with other users via either a URL or by QR code. Various types of plots can be created, including simple time series, data plotted as a function of orbital location, and time versus L-Shell. We discuss the new Van Allen Probes Science Gateway and the Space Weather Data Pipeline.

Taking the Lead in Science Education: Forging Next-Generation Science Standards. International Science Benchmarking Report

ERIC Educational Resources Information Center

Achieve, Inc., 2010

2010-01-01

In response to concerns over the need for a scientifically literate workforce, increasing the STEM pipeline, and aging science standards documents, the scientific and science education communities are embarking on the development of a new conceptual framework for science, led by the National Research Council (NRC), and aligned next generation…

Corral framework: Trustworthy and fully functional data intensive parallel astronomical pipelines

NASA Astrophysics Data System (ADS)

Cabral, J. B.; Sánchez, B.; Beroiz, M.; Domínguez, M.; Lares, M.; Gurovich, S.; Granitto, P.

2017-07-01

Data processing pipelines represent an important slice of the astronomical software library that include chains of processes that transform raw data into valuable information via data reduction and analysis. In this work we present Corral, a Python framework for astronomical pipeline generation. Corral features a Model-View-Controller design pattern on top of an SQL Relational Database capable of handling: custom data models; processing stages; and communication alerts, and also provides automatic quality and structural metrics based on unit testing. The Model-View-Controller provides concept separation between the user logic and the data models, delivering at the same time multi-processing and distributed computing capabilities. Corral represents an improvement over commonly found data processing pipelines in astronomysince the design pattern eases the programmer from dealing with processing flow and parallelization issues, allowing them to focus on the specific algorithms needed for the successive data transformations and at the same time provides a broad measure of quality over the created pipeline. Corral and working examples of pipelines that use it are available to the community at https://github.com/toros-astro.

Hubble Goes IMAX: 3D Visualization of the GOODS Southern Field for a Large Format Short Film

NASA Astrophysics Data System (ADS)

Summers, F. J.; Stoke, J. M.; Albert, L. J.; Bacon, G. T.; Barranger, C. L.; Feild, A. R.; Frattare, L. M.; Godfrey, J. P.; Levay, Z. G.; Preston, B. S.; Fletcher, L. M.; GOODS Team

2003-12-01

The Office of Public Outreach at the Space Telescope Science Institute is producing a several minute IMAX film that will have its world premiere at the January 2004 AAS meeting. The film explores the rich tapestry of galaxies in the GOODS Survey Southern Field in both two and three dimensions. This poster describes the visualization efforts from FITS files through the galaxy processing pipeline to 3D modelling and the rendering of approximately 100 billion pixels. The IMAX film will be shown at a special session at Fernbank Science Center, and the video will be shown at the STScI booth.

Fully automated rodent brain MR image processing pipeline on a Midas server: from acquired images to region-based statistics.

PubMed

Budin, Francois; Hoogstoel, Marion; Reynolds, Patrick; Grauer, Michael; O'Leary-Moore, Shonagh K; Oguz, Ipek

2013-01-01

Magnetic resonance imaging (MRI) of rodent brains enables study of the development and the integrity of the brain under certain conditions (alcohol, drugs etc.). However, these images are difficult to analyze for biomedical researchers with limited image processing experience. In this paper we present an image processing pipeline running on a Midas server, a web-based data storage system. It is composed of the following steps: rigid registration, skull-stripping, average computation, average parcellation, parcellation propagation to individual subjects, and computation of region-based statistics on each image. The pipeline is easy to configure and requires very little image processing knowledge. We present results obtained by processing a data set using this pipeline and demonstrate how this pipeline can be used to find differences between populations.

Research on numerical simulation and protection of transient process in long-distance slurry transportation pipelines

NASA Astrophysics Data System (ADS)

Lan, G.; Jiang, J.; Li, D. D.; Yi, W. S.; Zhao, Z.; Nie, L. N.

2013-12-01

The calculation of water-hammer pressure phenomenon of single-phase liquid is already more mature for a pipeline of uniform characteristics, but less research has addressed the calculation of slurry water hammer pressure in complex pipelines with slurry flows carrying solid particles. In this paper, based on the developments of slurry pipelines at home and abroad, the fundamental principle and method of numerical simulation of transient processes are presented, and several boundary conditions are given. Through the numerical simulation and analysis of transient processes of a practical engineering of long-distance slurry transportation pipeline system, effective protection measures and operating suggestions are presented. A model for calculating the water impact of solid and fluid phases is established based on a practical engineering of long-distance slurry pipeline transportation system. After performing a numerical simulation of the transient process, analyzing and comparing the results, effective protection measures and operating advice are recommended, which has guiding significance to the design and operating management of practical engineering of longdistance slurry pipeline transportation system.

77 FR 15455 - Notice of Delays in Processing of Special Permits Applications

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-15

... DEPARTMENT OF TRANSPORTATION Pipeline and Hazardous Materials Safety Administration Notice of Delays in Processing of Special Permits Applications AGENCY: Pipeline and Hazardous Materials Safety... and Approvals, Pipeline and Hazardous Materials Safety Administration, U.S. Department of...

Bridging the Gap between Research and Practice: Implementation Science

ERIC Educational Resources Information Center

Olswang, Lesley B.; Prelock, Patricia A.

2015-01-01

Purpose: This article introduces implementation science, which focuses on research methods that promote the systematic application of research findings to practice. Method: The narrative defines implementation science and highlights the importance of moving research along the pipeline from basic science to practice as one way to facilitate…

The Stanford Medical Youth Science Program: Educational and Science-Related Outcomes

ERIC Educational Resources Information Center

Crump, Casey; Ned, Judith; Winkleby, Marilyn A.

2015-01-01

Biomedical preparatory programs (pipeline programs) have been developed at colleges and universities to better prepare youth for entering science- and health-related careers, but outcomes of such programs have seldom been rigorously evaluated. We conducted a matched cohort study to evaluate the Stanford Medical Youth Science Program's Summer…

Improving Kepler Pipeline Sensitivity with Pixel Response Function Photometry.

NASA Astrophysics Data System (ADS)

Morris, Robert L.; Bryson, Steve; Jenkins, Jon Michael; Smith, Jeffrey C

2014-06-01

We present the results of our investigation into the feasibility and expected benefits of implementing PRF-fitting photometry in the Kepler Science Processing Pipeline. The Kepler Pixel Response Function (PRF) describes the expected system response to a point source at infinity and includes the effects of the optical point spread function, the CCD detector responsivity function, and spacecraft pointing jitter. Planet detection in the Kepler pipeline is currently based on simple aperture photometry (SAP), which is most effective when applied to uncrowded bright stars. Its effectiveness diminishes rapidly as target brightness decreases relative to the effects of noise sources such as detector electronics, background stars, and image motion. In contrast, PRF photometry is based on fitting an explicit model of image formation to the data and naturally accounts for image motion and contributions of background stars. The key to obtaining high-quality photometry from PRF fitting is a high-quality model of the system's PRF, while the key to efficiently processing the large number of Kepler targets is an accurate catalog and accurate mapping of celestial coordinates onto the focal plane. If the CCD coordinates of stellar centroids are known a priori then the problem of PRF fitting becomes linear. A model of the Kepler PRF was constructed at the time of spacecraft commissioning by fitting piecewise polynomial surfaces to data from dithered full frame images. While this model accurately captured the initial state of the system, the PRF has evolved dynamically since then and has been seen to deviate significantly from the initial (static) model. We construct a dynamic PRF model which is then used to recover photometry for all targets of interest. Both simulation tests and results from Kepler flight data demonstrate the effectiveness of our approach. Kepler was selected as the 10th mission of the Discovery Program. Funding for this mission is provided by NASA’s Science Mission Directorate.Kepler was selected as the 10th mission of the Discovery Program. Funding for this mission is provided by NASA’s Science Mission Directorate.

Photometric Analysis in the Kepler Science Operations Center Pipeline

NASA Technical Reports Server (NTRS)

Twicken, Joseph D.; Clarke, Bruce D.; Bryson, Stephen T.; Tenenbaum, Peter; Wu, Hayley; Jenkins, Jon M.; Girouard, Forrest; Klaus, Todd C.

2010-01-01

We describe the Photometric Analysis (PA) software component and its context in the Kepler Science Operations Center (SOC) pipeline. The primary tasks of this module are to compute the photometric flux and photocenters (centroids) for over 160,000 long cadence (thirty minute) and 512 short cadence (one minute) stellar targets from the calibrated pixels in their respective apertures. We discuss the science algorithms for long and short cadence PA: cosmic ray cleaning; background estimation and removal; aperture photometry; and flux-weighted centroiding. We discuss the end-to-end propagation of uncertainties for the science algorithms. Finally, we present examples of photometric apertures, raw flux light curves, and centroid time series from Kepler flight data. PA light curves, centroid time series, and barycentric timestamp corrections are exported to the Multi-mission Archive at Space Telescope [Science Institute] (MAST) and are made available to the general public in accordance with the NASA/Kepler data release policy.

VizieR Online Data Catalog: Galaxy structural parameters from 3.6um images (Kim+, 2014)

NASA Astrophysics Data System (ADS)

Kim, T.; Gadotti, D. A.; Sheth, K.; Athanassoula, E.; Bosma, A.; Lee, M. G.; Madore, B. F.; Elmegreen, B.; Knapen, J. H.; Zaritsky, D.; Ho, L. C.; Comeron, S.; Holwerda, B.; Hinz, J. L.; Munoz-Mateos, J.-C.; Cisternas, M.; Erroz-Ferrer, S.; Buta, R.; Laurikainen, E.; Salo, H.; Laine, J.; Menendez-Delmestre, K.; Regan, M. W.; de Swardt, B.; Gil de Paz, A.; Seibert, M.; Mizusawa, T.

2016-03-01

We select our samples from the Spitzer Survey of Stellar Structure in Galaxies (S4G; Sheth et al. 2010, cat. J/PASP/122/1397). We chose galaxies that had already been processed by the first three S4G pipelines (Pipelines 1, 2, and 3; Sheth et al. 2010, cat. J/PASP/122/1397) at the moment of this study (2011 November). In brief, Pipeline processes images and provides science-ready images. Pipeline 2 prepares mask images (to exclude foreground and background objects) for further analysis, and Pipeline 3 derives surface brightness profiles and total magnitudes using IRAF ellipse fits. We excluded highly inclined (b/a<0.5), significantly disturbed, very faint, or irregular galaxies. Galaxies were also discarded if their images are unsuitable for decomposition due to contamination such as a bright foreground star or significant stray light from stars in the IRAC scattering zones. Then we chose barred galaxies from all Hubble types from S0 to Sdm using the numerical Hubble types from Hyperleda (Paturel et al. 2003, cat. VII/237, VII/238). The assessment of the presence of a bar was done visually by K. Sheth, T. Kim, and B. de Swardt. Later, we also confirmed the presence of a bar by checking the mid-infrared classification (Buta et al. 2010, cat. J/ApJS/190/147; Buta et al. 2015, cat. J/ApJS/217/32). A total of 144 barred galaxies were selected that satisfy our criteria, and we list our sample in Table1 with basic information. Table2 presents the measures of structural parameters for all galaxies in the sample obtained from the 2D model fit with BUDDA (BUlge/disk Decomposition Analysis, de Souza et al., 2004ApJS..153..411D; Gadotti, 2008MNRAS.384..420G) code. (2 data files).

BigDataScript: a scripting language for data pipelines.

PubMed

Cingolani, Pablo; Sladek, Rob; Blanchette, Mathieu

2015-01-01

The analysis of large biological datasets often requires complex processing pipelines that run for a long time on large computational infrastructures. We designed and implemented a simple script-like programming language with a clean and minimalist syntax to develop and manage pipeline execution and provide robustness to various types of software and hardware failures as well as portability. We introduce the BigDataScript (BDS) programming language for data processing pipelines, which improves abstraction from hardware resources and assists with robustness. Hardware abstraction allows BDS pipelines to run without modification on a wide range of computer architectures, from a small laptop to multi-core servers, server farms, clusters and clouds. BDS achieves robustness by incorporating the concepts of absolute serialization and lazy processing, thus allowing pipelines to recover from errors. By abstracting pipeline concepts at programming language level, BDS simplifies implementation, execution and management of complex bioinformatics pipelines, resulting in reduced development and debugging cycles as well as cleaner code. BigDataScript is available under open-source license at http://pcingola.github.io/BigDataScript. © The Author 2014. Published by Oxford University Press.

BigDataScript: a scripting language for data pipelines

PubMed Central

Cingolani, Pablo; Sladek, Rob; Blanchette, Mathieu

2015-01-01

Motivation: The analysis of large biological datasets often requires complex processing pipelines that run for a long time on large computational infrastructures. We designed and implemented a simple script-like programming language with a clean and minimalist syntax to develop and manage pipeline execution and provide robustness to various types of software and hardware failures as well as portability. Results: We introduce the BigDataScript (BDS) programming language for data processing pipelines, which improves abstraction from hardware resources and assists with robustness. Hardware abstraction allows BDS pipelines to run without modification on a wide range of computer architectures, from a small laptop to multi-core servers, server farms, clusters and clouds. BDS achieves robustness by incorporating the concepts of absolute serialization and lazy processing, thus allowing pipelines to recover from errors. By abstracting pipeline concepts at programming language level, BDS simplifies implementation, execution and management of complex bioinformatics pipelines, resulting in reduced development and debugging cycles as well as cleaner code. Availability and implementation: BigDataScript is available under open-source license at http://pcingola.github.io/BigDataScript. Contact: pablo.e.cingolani@gmail.com PMID:25189778

Diversity in the biomedical research workforce: developing talent.

PubMed

McGee, Richard; Saran, Suman; Krulwich, Terry A

2012-01-01

Much has been written about the need for and barriers to achievement of greater diversity in the biomedical workforce from the perspectives of gender, race, and ethnicity; this is not a new topic. These discussions often center around a "pipeline" metaphor that imagines students flowing through a series of experiences to eventually arrive at a science career. Here we argue that diversity will only be achieved if the primary focus is on (1) what is happening within the pipeline, not just counting individuals entering and leaving it; (2) de-emphasizing the achievement of academic milestones by typical ages; and (3) adopting approaches that most effectively develop talent. Students may develop skills at different rates based on factors such as earlier access to educational resources, exposure to science (especially research experiences), and competing demands for time and attention during high school and college. Therefore, there is wide variety among students at any point along the pipeline. Taking this view requires letting go of imagining the pipeline as a sequence of age-dependent steps in favor of milestones of skill and talent development decoupled from age or educational stage. Emphasizing talent development opens up many new approaches for science training outside of traditional degree programs. This article provides examples of such approaches, including interventions at the postbaccalaureate and PhD levels, as well as a novel coaching model that incorporates well-established social science theories and complements traditional mentoring. These approaches could significantly impact diversity by developing scientific talent, especially among currently underrepresented minorities. © 2012 Mount Sinai School of Medicine.

Gender, race, ethnicity, and science education in the middle grades

NASA Astrophysics Data System (ADS)

Catsambis, Sophia

This article examines gender differences in science achievements and attitudes during the middle grade, when our nation's scientific pipeline begins to emerge. It uses data from a large, nationally representative sample of eighth-grade students (NELS-88). The findings show that in these grades female students do not lag behind their male classmates in science achievements tests, grades, and course enrollments. Actually, some female students have higher probabilities of enrolling in high-ability classes than males. However, female students have less positive attitudes toward science, participate in fewer relevant extracurricular activities, and aspire less often to science careers than males. Students' science attitudes and career interests vary according to students' gender as well as their racial or ethnic background. These findings emphasize the need to further examine the interrelationships between gender and race or ethnicity in our efforts to understand the processes leading to women's limited participation in science-related careers.Received: 2 August 1993; Revised: 8 August 1994;

78 FR 53751 - Dominion NGL Pipelines, LLC; Notice of Petition for Declaratory Order

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-30

... new ethane pipeline (Natrium Ethane Pipeline) extending from a new natural gas processing and... utilize, or pay for, significant capacity on the Natrium Ethane Pipeline (Committed Shipper); and (3) the...

49 CFR 192.937 - What is a continual process of evaluation and assessment to maintain a pipeline's integrity?

Code of Federal Regulations, 2010 CFR

2010-10-01

... Relating to Transportation (Continued) PIPELINE AND HAZARDOUS MATERIALS SAFETY ADMINISTRATION, DEPARTMENT OF TRANSPORTATION (CONTINUED) PIPELINE SAFETY TRANSPORTATION OF NATURAL AND OTHER GAS BY PIPELINE: MINIMUM FEDERAL SAFETY STANDARDS Gas Transmission Pipeline Integrity Management § 192.937 What is a...

The Stanford Medical Youth Science Program: educational and science-related outcomes.

PubMed

Crump, Casey; Ned, Judith; Winkleby, Marilyn A

2015-05-01

Biomedical preparatory programs (pipeline programs) have been developed at colleges and universities to better prepare youth for entering science- and health-related careers, but outcomes of such programs have seldom been rigorously evaluated. We conducted a matched cohort study to evaluate the Stanford Medical Youth Science Program's Summer Residential Program (SRP), a 25-year-old university-based biomedical pipeline program that reaches out to low-income and underrepresented ethnic minority high school students. Five annual surveys were used to assess educational outcomes and science-related experience among 96 SRP participants and a comparison group of 192 youth who applied but were not selected to participate in the SRP, using ~2:1 matching on sociodemographic and academic background to control for potential confounders. SRP participants were more likely than the comparison group to enter college (100.0 vs. 84.4 %, p = 0.002), and both of these matriculation rates were more than double the statewide average (40.8 %). In most areas of science-related experience, SRP participants reported significantly more experience (>twofold odds) than the comparison group at 1 year of follow-up, but these differences did not persist after 2-4 years. The comparison group reported substantially more participation in science or college preparatory programs, more academic role models, and less personal adversity than SRP participants, which likely influenced these findings toward the null hypothesis. SRP applicants, irrespective of whether selected for participation, had significantly better educational outcomes than population averages. Short-term science-related experience was better among SRP participants, although longer-term outcomes were similar, most likely due to college and science-related opportunities among the comparison group. We discuss implications for future evaluations of other biomedical pipeline programs.

FACE-IT. A Science Gateway for Food Security Research

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

Montella, Raffaele; Kelly, David; Xiong, Wei

Progress in sustainability science is hindered by challenges in creating and managing complex data acquisition, processing, simulation, post-processing, and intercomparison pipelines. To address these challenges, we developed the Framework to Advance Climate, Economic, and Impact Investigations with Information Technology (FACE-IT) for crop and climate impact assessments. This integrated data processing and simulation framework enables data ingest from geospatial archives; data regridding, aggregation, and other processing prior to simulation; large-scale climate impact simulations with agricultural and other models, leveraging high-performance and cloud computing; and post-processing to produce aggregated yields and ensemble variables needed for statistics, for model intercomparison, and to connectmore » biophysical models to global and regional economic models. FACE-IT leverages the capabilities of the Globus Galaxies platform to enable the capture of workflows and outputs in well-defined, reusable, and comparable forms. We describe FACE-IT and applications within the Agricultural Model Intercomparison and Improvement Project and the Center for Robust Decision-making on Climate and Energy Policy.« less

Architecting the Finite Element Method Pipeline for the GPU.

PubMed

Fu, Zhisong; Lewis, T James; Kirby, Robert M; Whitaker, Ross T

2014-02-01

The finite element method (FEM) is a widely employed numerical technique for approximating the solution of partial differential equations (PDEs) in various science and engineering applications. Many of these applications benefit from fast execution of the FEM pipeline. One way to accelerate the FEM pipeline is by exploiting advances in modern computational hardware, such as the many-core streaming processors like the graphical processing unit (GPU). In this paper, we present the algorithms and data-structures necessary to move the entire FEM pipeline to the GPU. First we propose an efficient GPU-based algorithm to generate local element information and to assemble the global linear system associated with the FEM discretization of an elliptic PDE. To solve the corresponding linear system efficiently on the GPU, we implement a conjugate gradient method preconditioned with a geometry-informed algebraic multi-grid (AMG) method preconditioner. We propose a new fine-grained parallelism strategy, a corresponding multigrid cycling stage and efficient data mapping to the many-core architecture of GPU. Comparison of our on-GPU assembly versus a traditional serial implementation on the CPU achieves up to an 87 × speedup. Focusing on the linear system solver alone, we achieve a speedup of up to 51 × versus use of a comparable state-of-the-art serial CPU linear system solver. Furthermore, the method compares favorably with other GPU-based, sparse, linear solvers.

Dynamic Black-Level Correction and Artifact Flagging in the Kepler Data Pipeline

NASA Technical Reports Server (NTRS)

Clarke, B. D.; Kolodziejczak, J. J.; Caldwell, D. A.

2013-01-01

Instrument-induced artifacts in the raw Kepler pixel data include time-varying crosstalk from the fine guidance sensor (FGS) clock signals, manifestations of drifting moiré pattern as locally correlated nonstationary noise and rolling bands in the images which find their way into the calibrated pixel time series and ultimately into the calibrated target flux time series. Using a combination of raw science pixel data, full frame images, reverse-clocked pixel data and ancillary temperature data the Keplerpipeline models and removes the FGS crosstalk artifacts by dynamically adjusting the black level correction. By examining the residuals to the model fits, the pipeline detects and flags spatial regions and time intervals of strong time-varying blacklevel (rolling bands ) on a per row per cadence basis. These flags are made available to downstream users of the data since the uncorrected rolling band artifacts could complicate processing or lead to misinterpretation of instrument behavior as stellar. This model fitting and artifact flagging is performed within the new stand-alone pipeline model called Dynablack. We discuss the implementation of Dynablack in the Kepler data pipeline and present results regarding the improvement in calibrated pixels and the expected improvement in cotrending performances as a result of including FGS corrections in the calibration. We also discuss the effectiveness of the rolling band flagging for downstream users and illustrate with some affected light curves.

Increasing Diversity and Gender Parity by working with Professional Organizations and HBCUs

NASA Astrophysics Data System (ADS)

Wims, T. R.

2017-12-01

Context/Purpose: This abstract proposes tactics for recruiting diverse applicants and addressing gender parity in the geoscience workforce. Methods: The geoscience community should continue to develop and expand a pipeline of qualified potential employees and managers at all levels. Recruitment from professional organizations, which are minority based, such as the National Society of Black Engineers (NSBE), and the Society of Hispanic Professional Engineers (SHPE) provides senior and midlevel scientists, engineers, program managers, and corporate managers/administrators with proven track records of success. Geoscience organizations should consider increasing hiring from the 100+ Historically Black Colleges and Universities (HBCU) which have a proven track records of producing high quality graduates with math, science, computer science, and engineering backgrounds. HBCU alumni have been working in all levels of government and corporate organizations for more than 50 years. Results: Professional organizations, like NSBE, have members with one to 40 years of applicable work experience, who are prime candidates for employment in the geoscience community at all levels. NSBE, also operates pipeline programs to graduate 10,000 bachelor degree minority candidates per year by 2025, up from the current 3,620/year. HBCUs have established educational programs and several pipelines for attracting undergraduate students into the engineering and science fields. Since many HBCUs enroll more women than men, they are also addressing gender parity. Both professional organizations and HBCU's have pipeline programs that reach children in high school. Interpretation: Qualified and capable minority and women candidates are available in the United States. Pipelines for employing senior, mid-level, and junior skill sets are in place, but underutilized by some geoscience companies and organizations.

Helping parents to motivate adolescents in mathematics and science: an experimental test of a utility-value intervention.

PubMed

Harackiewicz, Judith M; Rozek, Christopher S; Hulleman, Chris S; Hyde, Janet S

2012-08-01

The pipeline toward careers in science, technology, engineering, and mathematics (STEM) begins to leak in high school, when some students choose not to take advanced mathematics and science courses. We conducted a field experiment testing whether a theory-based intervention that was designed to help parents convey the importance of mathematics and science courses to their high school-aged children would lead them to take more mathematics and science courses in high school. The three-part intervention consisted of two brochures mailed to parents and a Web site, all highlighting the usefulness of STEM courses. This relatively simple intervention led students whose parents were in the experimental group to take, on average, nearly one semester more of science and mathematics in the last 2 years of high school, compared with the control group. Parents are an untapped resource for increasing STEM motivation in adolescents, and the results demonstrate that motivational theory can be applied to this important pipeline problem.

75 FR 5167 - Office of Hazardous Materials Safety; Notice of Delays In Processing of Special Permits Applications

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-01

... DEPARTMENT OF TRANSPORTATION Pipeline and Hazardous Materials Safety Administration Office of Hazardous Materials Safety; Notice of Delays In Processing of Special Permits Applications AGENCY: Pipeline..., Office of Hazardous Materials Special Permits and Approvals, Pipeline and Hazardous Materials Safety...

75 FR 78800 - Office of Hazardous Materials Safety; Notice of Delays in Processing of Special Permits Applications

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-16

... DEPARTMENT OF TRANSPORTATION Pipeline and Hazardous Materials Safety Administration Office of Hazardous Materials Safety; Notice of Delays in Processing of Special Permits Applications AGENCY: Pipeline..., Office of Hazardous Materials Special Permits and Approvals, Pipeline and Hazardous Materials Safety...

Closing the Gaps and Filling the STEM Pipeline: A Multidisciplinary Approach

ERIC Educational Resources Information Center

Doerschuk, Peggy; Bahrim, Cristian; Daniel, Jennifer; Kruger, Joseph; Mann, Judith; Martin, Cristopher

2016-01-01

There is a growing demand for degreed science, technology, engineering and mathematics (STEM) professionals, but the production of degreed STEM students is not keeping pace. Problems exist at every juncture along the pipeline. Too few students choose to major in STEM disciplines. Many of those who do major in STEM drop out or change majors.…

Astro-H Data Analysis, Processing and Archive

NASA Technical Reports Server (NTRS)

Angelini, Lorella; Terada, Yukikatsu; Loewenstein, Michael; Miller, Eric D.; Yamaguchi, Hiroya; Yaqoob, Tahir; Krimm, Hans; Harrus, Ilana; Takahashi, Hiromitsu; Nobukawa, Masayoshi;

Description of the TCERT Vetting Reports for Data Release 25

NASA Technical Reports Server (NTRS)

Van Cleve, Jeffrey E.; Caldwell, Douglas A.

2016-01-01

This document, the Kepler Instrument Handbook (KIH), is for Kepler and K2 observers, which includes the Kepler Science Team, Guest Observers (GOs), and astronomers doing archival research on Kepler and K2 data in NASAs Astrophysics Data Analysis Program (ADAP). The KIH provides information about the design, performance, and operational constraints of the Kepler flight hardware and software, and an overview of the pixel data sets available. The KIH is meant to be read with these companion documents:1. Kepler Data Processing Handbook (KSCI-19081) or KDPH (Jenkins et al., 2016). The KDPH describes how pixels downlinked from the spacecraft are converted by the Kepler Data Processing Pipeline (henceforth just the pipeline) into the data products delivered to the MAST archive. 2. Kepler Archive Manual (KDMC-10008) or KAM (Thompson et al., 2016). The KAM describes the format and content of the data products, and how to search for them.3. Kepler Data Characteristics Handbook (KSCI-19040) or KDCH (Christiansen et al., 2016). The KDCH describes recurring non-astrophysical features of the Kepler data due to instrument signatures, spacecraft events, or solar activity, and explains how these characteristics are handled by the pipeline.4. Kepler Data Release Notes 25 (KSCI-19065) or DRN 25 (Thompson et al., 2015). DRN 25 describes signatures and events peculiar to individual quarters, and the pipeline software changes between a data release and the one preceding it.Together, these documents supply the information necessary for obtaining and understanding Kepler results, given the real properties of the hardware and the data analysis methods used, and for an independent evaluation of the methods used if so desired.

Building Alaska's Science and Engineering Pipeline: Evaluation of the Alaska Native Science & Engineering Program

ERIC Educational Resources Information Center

Bernstein, Hamutal; Martin, Carlos; Eyster, Lauren; Anderson, Theresa; Owen, Stephanie; Martin-Caughey, Amanda

2015-01-01

The Urban Institute conducted an implementation and participant-outcomes evaluation of the Alaska Native Science & Engineering Program (ANSEP). ANSEP is a multi-stage initiative designed to prepare and support Alaska Native students from middle school through graduate school to succeed in science, technology, engineering, and math (STEM)…

Computing Whether She Belongs: Stereotypes Undermine Girls' Interest and Sense of Belonging in Computer Science

ERIC Educational Resources Information Center

Master, Allison; Cheryan, Sapna; Meltzoff, Andrew N.

2016-01-01

Computer science has one of the largest gender disparities in science, technology, engineering, and mathematics. An important reason for this disparity is that girls are less likely than boys to enroll in necessary "pipeline courses," such as introductory computer science. Two experiments investigated whether high-school girls' lower…

Traveling the road to success: A discourse on persistence throughout the science pipeline with African American students at a predominantly white institution

NASA Astrophysics Data System (ADS)

Russell, Melody L.; Atwater, Mary M.

2005-08-01

This study focuses on 11 African American undergraduate seniors in a biology degree program at a predominantly white research institution in the southeastern United States. These 11 respondents shared their journeys throughout the high school and college science pipeline. Participants described similar precollege factors and experiences that contributed to their academic success and persistence at a predominantly white institution. One of the most critical factors in their academic persistence was participation in advanced science and mathematics courses as part of their high school college preparatory program. Additional factors that had a significant impact on their persistence and academic success were family support, teacher encouragement, intrinsic motivation, and perseverance.

Computational Challenges in Processing the Q1-Q16 Kepler Data Set

NASA Astrophysics Data System (ADS)

Klaus, Todd C.; Henze, C.; Twicken, J. D.; Hall, J.; McCauliff, S. D.; Girouard, F.; Cote, M.; Morris, R. L.; Clarke, B.; Jenkins, J. M.; Caldwell, D.; Kepler Science Operations Center

2013-10-01

Since launch on March 6th, 2009, NASA’s Kepler Space Telescope has collected 48 months of data on over 195,000 targets. The raw data are rife with instrumental and astrophysical noise that must be removed in order to detect and model the transit-like signals present in the data. Calibrating the raw pixels, generating and correcting the flux light curves, and detecting and characterizing the signals require significant computational power. In addition, the algorithms that make up the Kepler Science Pipeline and their parameters are still undergoing changes (most of which increase the computational cost), creating the need to reprocess the entire data set on a regular basis. We discuss how we have ported all of the core elements of the pipeline to the Pleiades cluster at the NASA Advanced Supercomputing (NAS) Division, the needs driving the port, and the technical challenges we faced. In 2011 we ported the Transiting Planet Search (TPS) and Data Validation (DV) modules to Pleiades. These pipeline modules operate on the full data set and the computational complexity increases roughly by the square of the number of data points. At the time of the port it had become infeasible to run these modules on our local hardware, necessitating the move to Pleiades. In 2012 and 2013 we turned our attention to the front end of the pipeline; Pixel-level Calibration (CAL), Photometric Analysis (PA), and Pre-Search Data Conditioning (PDC). Porting these modules to Pleiades will allow us to reprocess the complete data set on a more frequent basis. The last time we reprocessed all data for the front end we only had 24 months of data. We estimate that the full 48-month data set would take over 200 days to complete on local hardware. When the port is complete we expect to reprocess this data set on Pleiades in about a month. The NASA Science Mission Directorate provided funding for the Kepler Mission.

SUPRA: open-source software-defined ultrasound processing for real-time applications : A 2D and 3D pipeline from beamforming to B-mode.

PubMed

Göbl, Rüdiger; Navab, Nassir; Hennersperger, Christoph

2018-06-01

Research in ultrasound imaging is limited in reproducibility by two factors: First, many existing ultrasound pipelines are protected by intellectual property, rendering exchange of code difficult. Second, most pipelines are implemented in special hardware, resulting in limited flexibility of implemented processing steps on such platforms. With SUPRA, we propose an open-source pipeline for fully software-defined ultrasound processing for real-time applications to alleviate these problems. Covering all steps from beamforming to output of B-mode images, SUPRA can help improve the reproducibility of results and make modifications to the image acquisition mode accessible to the research community. We evaluate the pipeline qualitatively, quantitatively, and regarding its run time. The pipeline shows image quality comparable to a clinical system and backed by point spread function measurements a comparable resolution. Including all processing stages of a usual ultrasound pipeline, the run-time analysis shows that it can be executed in 2D and 3D on consumer GPUs in real time. Our software ultrasound pipeline opens up the research in image acquisition. Given access to ultrasound data from early stages (raw channel data, radiofrequency data), it simplifies the development in imaging. Furthermore, it tackles the reproducibility of research results, as code can be shared easily and even be executed without dedicated ultrasound hardware.

Development of Protective Coatings for Co-Sequestration Processes and Pipelines

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

Bierwagen, Gordon; Huang, Yaping

2011-11-30

The program, entitled Development of Protective Coatings for Co-Sequestration Processes and Pipelines, examined the sensitivity of existing coating systems to supercritical carbon dioxide (SCCO2) exposure and developed new coating system to protect pipelines from their corrosion under SCCO2 exposure. A literature review was also conducted regarding pipeline corrosion sensors to monitor pipes used in handling co-sequestration fluids. Research was to ensure safety and reliability for a pipeline involving transport of SCCO2 from the power plant to the sequestration site to mitigate the greenhouse gas effect. Results showed that one commercial coating and one designed formulation can both be supplied asmore » potential candidates for internal pipeline coating to transport SCCO2.« less

WFIRST Science Operations at STScI

NASA Astrophysics Data System (ADS)

Gilbert, Karoline; STScI WFIRST Team

2018-06-01

With sensitivity and resolution comparable the Hubble Space Telescope, and a field of view 100 times larger, the Wide Field Instrument (WFI) on WFIRST will be a powerful survey instrument. STScI will be the Science Operations Center (SOC) for the WFIRST Mission, with additional science support provided by the Infrared Processing and Analysis Center (IPAC) and foreign partners. STScI will schedule and archive all WFIRST observations, calibrate and produce pipeline-reduced data products for imaging with the Wide Field Instrument, support the High Latitude Imaging and Supernova Survey Teams, and support the astronomical community in planning WFI imaging observations and analyzing the data. STScI has developed detailed concepts for WFIRST operations, including a data management system integrating data processing and the archive which will include a novel, cloud-based framework for high-level data processing, providing a common environment accessible to all users (STScI operations, Survey Teams, General Observers, and archival investigators). To aid the astronomical community in examining the capabilities of WFIRST, STScI has built several simulation tools. We describe the functionality of each tool and give examples of its use.

An integrated SNP mining and utilization (ISMU) pipeline for next generation sequencing data.

PubMed

Azam, Sarwar; Rathore, Abhishek; Shah, Trushar M; Telluri, Mohan; Amindala, BhanuPrakash; Ruperao, Pradeep; Katta, Mohan A V S K; Varshney, Rajeev K

2014-01-01

Open source single nucleotide polymorphism (SNP) discovery pipelines for next generation sequencing data commonly requires working knowledge of command line interface, massive computational resources and expertise which is a daunting task for biologists. Further, the SNP information generated may not be readily used for downstream processes such as genotyping. Hence, a comprehensive pipeline has been developed by integrating several open source next generation sequencing (NGS) tools along with a graphical user interface called Integrated SNP Mining and Utilization (ISMU) for SNP discovery and their utilization by developing genotyping assays. The pipeline features functionalities such as pre-processing of raw data, integration of open source alignment tools (Bowtie2, BWA, Maq, NovoAlign and SOAP2), SNP prediction (SAMtools/SOAPsnp/CNS2snp and CbCC) methods and interfaces for developing genotyping assays. The pipeline outputs a list of high quality SNPs between all pairwise combinations of genotypes analyzed, in addition to the reference genome/sequence. Visualization tools (Tablet and Flapjack) integrated into the pipeline enable inspection of the alignment and errors, if any. The pipeline also provides a confidence score or polymorphism information content value with flanking sequences for identified SNPs in standard format required for developing marker genotyping (KASP and Golden Gate) assays. The pipeline enables users to process a range of NGS datasets such as whole genome re-sequencing, restriction site associated DNA sequencing and transcriptome sequencing data at a fast speed. The pipeline is very useful for plant genetics and breeding community with no computational expertise in order to discover SNPs and utilize in genomics, genetics and breeding studies. The pipeline has been parallelized to process huge datasets of next generation sequencing. It has been developed in Java language and is available at http://hpc.icrisat.cgiar.org/ISMU as a standalone free software.

The Herschel Data Processing System — HIPE and Pipelines — Up and Running Since the Start of the Mission

NASA Astrophysics Data System (ADS)

Ott, S.

2010-12-01

The Herschel Space Observatory is the fourth cornerstone mission in the ESA science programme and performs photometry and spectroscopy in the 55 - 672 micron range. The development of the Herschel Data Processing System started in 2002 to support the data analysis for Instrument Level Tests. The Herschel Data Processing System was used for the pre-flight characterisation of the instruments, and during various ground segment test campaigns. Following the successful launch of Herschel 14th of May 2009 the Herschel Data Processing System demonstrated its maturity when the first PACS preview observation of M51 was processed within 30 minutes of reception of the first science data after launch. Also the first HIFI observations on DR21 were successfully reduced to high quality spectra, followed by SPIRE observations on M66 and M74. A fast turn-around cycle between data retrieval and the production of science-ready products was demonstrated during the Herschel Science Demonstration Phase Initial Results Workshop held 7 months after launch, which is a clear proof that the system has reached a good level of maturity. We will summarise the scope, the management and development methodology of the Herschel Data Processing system, present some key software elements and give an overview about the current status and future development milestones.

A distributed pipeline for DIDSON data processing

USGS Publications Warehouse

Li, Liling; Danner, Tyler; Eickholt, Jesse; McCann, Erin L.; Pangle, Kevin; Johnson, Nicholas

2018-01-01

Technological advances in the field of ecology allow data on ecological systems to be collected at high resolution, both temporally and spatially. Devices such as Dual-frequency Identification Sonar (DIDSON) can be deployed in aquatic environments for extended periods and easily generate several terabytes of underwater surveillance data which may need to be processed multiple times. Due to the large amount of data generated and need for flexibility in processing, a distributed pipeline was constructed for DIDSON data making use of the Hadoop ecosystem. The pipeline is capable of ingesting raw DIDSON data, transforming the acoustic data to images, filtering the images, detecting and extracting motion, and generating feature data for machine learning and classification. All of the tasks in the pipeline can be run in parallel and the framework allows for custom processing. Applications of the pipeline include monitoring migration times, determining the presence of a particular species, estimating population size and other fishery management tasks.

Performance Management of High Performance Computing for Medical Image Processing in Amazon Web Services.

PubMed

Bao, Shunxing; Damon, Stephen M; Landman, Bennett A; Gokhale, Aniruddha

2016-02-27

Adopting high performance cloud computing for medical image processing is a popular trend given the pressing needs of large studies. Amazon Web Services (AWS) provide reliable, on-demand, and inexpensive cloud computing services. Our research objective is to implement an affordable, scalable and easy-to-use AWS framework for the Java Image Science Toolkit (JIST). JIST is a plugin for Medical-Image Processing, Analysis, and Visualization (MIPAV) that provides a graphical pipeline implementation allowing users to quickly test and develop pipelines. JIST is DRMAA-compliant allowing it to run on portable batch system grids. However, as new processing methods are implemented and developed, memory may often be a bottleneck for not only lab computers, but also possibly some local grids. Integrating JIST with the AWS cloud alleviates these possible restrictions and does not require users to have deep knowledge of programming in Java. Workflow definition/management and cloud configurations are two key challenges in this research. Using a simple unified control panel, users have the ability to set the numbers of nodes and select from a variety of pre-configured AWS EC2 nodes with different numbers of processors and memory storage. Intuitively, we configured Amazon S3 storage to be mounted by pay-for-use Amazon EC2 instances. Hence, S3 storage is recognized as a shared cloud resource. The Amazon EC2 instances provide pre-installs of all necessary packages to run JIST. This work presents an implementation that facilitates the integration of JIST with AWS. We describe the theoretical cost/benefit formulae to decide between local serial execution versus cloud computing and apply this analysis to an empirical diffusion tensor imaging pipeline.

Performance management of high performance computing for medical image processing in Amazon Web Services

NASA Astrophysics Data System (ADS)

Bao, Shunxing; Damon, Stephen M.; Landman, Bennett A.; Gokhale, Aniruddha

2016-03-01

Adopting high performance cloud computing for medical image processing is a popular trend given the pressing needs of large studies. Amazon Web Services (AWS) provide reliable, on-demand, and inexpensive cloud computing services. Our research objective is to implement an affordable, scalable and easy-to-use AWS framework for the Java Image Science Toolkit (JIST). JIST is a plugin for Medical- Image Processing, Analysis, and Visualization (MIPAV) that provides a graphical pipeline implementation allowing users to quickly test and develop pipelines. JIST is DRMAA-compliant allowing it to run on portable batch system grids. However, as new processing methods are implemented and developed, memory may often be a bottleneck for not only lab computers, but also possibly some local grids. Integrating JIST with the AWS cloud alleviates these possible restrictions and does not require users to have deep knowledge of programming in Java. Workflow definition/management and cloud configurations are two key challenges in this research. Using a simple unified control panel, users have the ability to set the numbers of nodes and select from a variety of pre-configured AWS EC2 nodes with different numbers of processors and memory storage. Intuitively, we configured Amazon S3 storage to be mounted by pay-for- use Amazon EC2 instances. Hence, S3 storage is recognized as a shared cloud resource. The Amazon EC2 instances provide pre-installs of all necessary packages to run JIST. This work presents an implementation that facilitates the integration of JIST with AWS. We describe the theoretical cost/benefit formulae to decide between local serial execution versus cloud computing and apply this analysis to an empirical diffusion tensor imaging pipeline.

Performance Management of High Performance Computing for Medical Image Processing in Amazon Web Services

PubMed Central

Bao, Shunxing; Damon, Stephen M.; Landman, Bennett A.; Gokhale, Aniruddha

2016-01-01

Adopting high performance cloud computing for medical image processing is a popular trend given the pressing needs of large studies. Amazon Web Services (AWS) provide reliable, on-demand, and inexpensive cloud computing services. Our research objective is to implement an affordable, scalable and easy-to-use AWS framework for the Java Image Science Toolkit (JIST). JIST is a plugin for Medical-Image Processing, Analysis, and Visualization (MIPAV) that provides a graphical pipeline implementation allowing users to quickly test and develop pipelines. JIST is DRMAA-compliant allowing it to run on portable batch system grids. However, as new processing methods are implemented and developed, memory may often be a bottleneck for not only lab computers, but also possibly some local grids. Integrating JIST with the AWS cloud alleviates these possible restrictions and does not require users to have deep knowledge of programming in Java. Workflow definition/management and cloud configurations are two key challenges in this research. Using a simple unified control panel, users have the ability to set the numbers of nodes and select from a variety of pre-configured AWS EC2 nodes with different numbers of processors and memory storage. Intuitively, we configured Amazon S3 storage to be mounted by pay-for-use Amazon EC2 instances. Hence, S3 storage is recognized as a shared cloud resource. The Amazon EC2 instances provide pre-installs of all necessary packages to run JIST. This work presents an implementation that facilitates the integration of JIST with AWS. We describe the theoretical cost/benefit formulae to decide between local serial execution versus cloud computing and apply this analysis to an empirical diffusion tensor imaging pipeline. PMID:27127335

The CWF pipeline system from Shen mu to the Yellow Sea

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

Ercolani, D.

1993-12-31

A feasibility study on the applicability of coal-water fuel (CWF) technology in the People`s Republic of China (PRC) is in progress. This study, awarded to Snamprogetti by the International Centre for Scientific Culture (World Laboratory) of Geneva, Switzerland, is performed on behalf of Chinese Organizations led by the Ministry of Energy Resources and the Academy of Sciences of the People`s Republic of China. Slurry pipelines appear to be a solution for solving the logistic problems created by a progressively increasing coal consumption and a limited availability of conventional transport infrastructures in the PRC. Within this framework, CWF pipelines are themore » most innovative technological option in consideration of the various advantages the technology offers with respect to conventional slurry pipelines. The PRC CWF pipeline system study evaluates two alternative transport streams, but originating from the same slurry production plant, located at Shachuanguo, about 100 km from Sheng Mu.« less

Risk Analysis using Corrosion Rate Parameter on Gas Transmission Pipeline

NASA Astrophysics Data System (ADS)

Sasikirono, B.; Kim, S. J.; Haryadi, G. D.; Huda, A.

2017-05-01

In the oil and gas industry, the pipeline is a major component in the transmission and distribution process of oil and gas. Oil and gas distribution process sometimes performed past the pipeline across the various types of environmental conditions. Therefore, in the transmission and distribution process of oil and gas, a pipeline should operate safely so that it does not harm the surrounding environment. Corrosion is still a major cause of failure in some components of the equipment in a production facility. In pipeline systems, corrosion can cause failures in the wall and damage to the pipeline. Therefore it takes care and periodic inspections or checks on the pipeline system. Every production facility in an industry has a level of risk for damage which is a result of the opportunities and consequences of damage caused. The purpose of this research is to analyze the level of risk of 20-inch Natural Gas Transmission Pipeline using Risk-based inspection semi-quantitative based on API 581 associated with the likelihood of failure and the consequences of the failure of a component of the equipment. Then the result is used to determine the next inspection plans. Nine pipeline components were observed, such as a straight pipes inlet, connection tee, and straight pipes outlet. The risk assessment level of the nine pipeline’s components is presented in a risk matrix. The risk level of components is examined at medium risk levels. The failure mechanism that is used in this research is the mechanism of thinning. Based on the results of corrosion rate calculation, remaining pipeline components age can be obtained, so the remaining lifetime of pipeline components are known. The calculation of remaining lifetime obtained and the results vary for each component. Next step is planning the inspection of pipeline components by NDT external methods.

Fueling the STEMM Pipeline: How Historically Black Colleges and Universities Improve the Presence of African American Scholars in STEMM

ERIC Educational Resources Information Center

Adams, Tempestt; Robinson, Derrick; Covington, Azure; Talley-Matthews, Sheikia

2017-01-01

The purpose of this article is to assess areas of opportunity and access for students of color to participate in the science, technology, engineering, mathematics, and medicine pipeline (STEMM). Using a Critical Race Theory framework, this position paper reviews occupational outcomes and stratification in STEMM fields, examines the pertinence of…

Becoming a Woman Engineer in the Community of Practice: Validity and Value in Engineering-Education Research.

ERIC Educational Resources Information Center

Wood, Shaunda L.

The analogy of the leaky pipeline, the notion of women leaving or failing to choose science in droves, is represented frequently by researchers and scientists. "If the structural and cultural causes for the leakages are ignored, attempts at increasing the representation of women at various pipeline segments may fall short" (G. Sonnert,…

Methodology for reducing energy and resource costs in construction of trenchless crossover of pipelines

NASA Astrophysics Data System (ADS)

Toropov, V. S.

2018-05-01

The paper suggests a set of measures to select the equipment and its components in order to reduce energy costs in the process of pulling the pipeline into the well in the constructing the trenchless pipeline crossings of various materials using horizontal directional drilling technology. A methodology for reducing energy costs has been developed by regulating the operation modes of equipment during the process of pulling the working pipeline into a drilled and pre-expanded well. Since the power of the drilling rig is the most important criterion in the selection of equipment for the construction of a trenchless crossover, an algorithm is proposed for calculating the required capacity of the rig when operating in different modes in the process of pulling the pipeline into the well.

Minority Ethnic Students and Science Participation: A Qualitative Mapping of Achievement, Aspiration, Interest and Capital

ERIC Educational Resources Information Center

Wong, Billy

2016-01-01

In the UK, the "leaky pipeline" metaphor has been used to describe the relationship between ethnicity and science participation. Fewer minority ethnic students continue with science in post-compulsory education, and little is known about the ways in which they participate and identify with science, particularly in the secondary school…

Within the Pipeline: Self-Regulated Learning and Academic Achievement among College Students in Science Courses

ERIC Educational Resources Information Center

DiBenedetto, Maria K.; Bembenutty, Hefer

2011-01-01

The present study examined the associations between self-regulated learning and science achievement and whether the academic self-regulation variables described, such as self-efficacy, delay of gratification, and help seeking, predict science achievement in courses deemed necessary for a major in science. It was hypothesized that students who do…

Reproducible research in vadose zone sciences

USDA-ARS?s Scientific Manuscript database

A significant portion of present-day soil and Earth science research is computational, involving complex data analysis pipelines, advanced mathematical and statistical models, and sophisticated computer codes. Opportunities for scientific progress are greatly diminished if reproducing and building o...

Photo-realistic Terrain Modeling and Visualization for Mars Exploration Rover Science Operations

NASA Technical Reports Server (NTRS)

Edwards, Laurence; Sims, Michael; Kunz, Clayton; Lees, David; Bowman, Judd

2005-01-01

Modern NASA planetary exploration missions employ complex systems of hardware and software managed by large teams of. engineers and scientists in order to study remote environments. The most complex and successful of these recent projects is the Mars Exploration Rover mission. The Computational Sciences Division at NASA Ames Research Center delivered a 30 visualization program, Viz, to the MER mission that provides an immersive, interactive environment for science analysis of the remote planetary surface. In addition, Ames provided the Athena Science Team with high-quality terrain reconstructions generated with the Ames Stereo-pipeline. The on-site support team for these software systems responded to unanticipated opportunities to generate 30 terrain models during the primary MER mission. This paper describes Viz, the Stereo-pipeline, and the experiences of the on-site team supporting the scientists at JPL during the primary MER mission.

Hipe, Hipe, Hooray

NASA Astrophysics Data System (ADS)

Ott, Stephan; Herschel Science Ground Segment Consortium

2010-05-01

The Herschel Space Observatory, the fourth cornerstone mission in the ESA science program, was launched 14th of May 2009. With a 3.5 m telescope, it is the largest space telescope ever launched. Herschel's three instruments (HIFI, PACS, and SPIRE) perform photometry and spectroscopy in the 55 - 672 micron range and will deliver exciting science for the astronomical community during at least three years of routine observations. Since 2nd of December 2009 Herschel has been performing and processing observations in routine science mode. The development of the Herschel Data Processing System started eight years ago to support the data analysis for Instrument Level Tests. To fulfil the expectations of the astronomical community, additional resources were made available to implement a freely distributable Data Processing System capable of interactively and automatically reducing Herschel data at different processing levels. The system combines data retrieval, pipeline execution and scientific analysis in one single environment. The Herschel Interactive Processing Environment (HIPE) is the user-friendly face of Herschel Data Processing. The software is coded in Java and Jython to be platform independent and to avoid the need for commercial licenses. It is distributed under the GNU Lesser General Public License (LGPL), permitting everyone to access and to re-use its code. We will summarise the current capabilities of the Herschel Data Processing System and give an overview about future development milestones and plans, and how the astronomical community can contribute to HIPE. The Herschel Data Processing System is a joint development by the Herschel Science Ground Segment Consortium, consisting of ESA, the NASA Herschel Science Center, and the HIFI, PACS and SPIRE consortium members.

DDBJ read annotation pipeline: a cloud computing-based pipeline for high-throughput analysis of next-generation sequencing data.

PubMed

Nagasaki, Hideki; Mochizuki, Takako; Kodama, Yuichi; Saruhashi, Satoshi; Morizaki, Shota; Sugawara, Hideaki; Ohyanagi, Hajime; Kurata, Nori; Okubo, Kousaku; Takagi, Toshihisa; Kaminuma, Eli; Nakamura, Yasukazu

2013-08-01

High-performance next-generation sequencing (NGS) technologies are advancing genomics and molecular biological research. However, the immense amount of sequence data requires computational skills and suitable hardware resources that are a challenge to molecular biologists. The DNA Data Bank of Japan (DDBJ) of the National Institute of Genetics (NIG) has initiated a cloud computing-based analytical pipeline, the DDBJ Read Annotation Pipeline (DDBJ Pipeline), for a high-throughput annotation of NGS reads. The DDBJ Pipeline offers a user-friendly graphical web interface and processes massive NGS datasets using decentralized processing by NIG supercomputers currently free of charge. The proposed pipeline consists of two analysis components: basic analysis for reference genome mapping and de novo assembly and subsequent high-level analysis of structural and functional annotations. Users may smoothly switch between the two components in the pipeline, facilitating web-based operations on a supercomputer for high-throughput data analysis. Moreover, public NGS reads of the DDBJ Sequence Read Archive located on the same supercomputer can be imported into the pipeline through the input of only an accession number. This proposed pipeline will facilitate research by utilizing unified analytical workflows applied to the NGS data. The DDBJ Pipeline is accessible at http://p.ddbj.nig.ac.jp/.

DDBJ Read Annotation Pipeline: A Cloud Computing-Based Pipeline for High-Throughput Analysis of Next-Generation Sequencing Data

PubMed Central

Nagasaki, Hideki; Mochizuki, Takako; Kodama, Yuichi; Saruhashi, Satoshi; Morizaki, Shota; Sugawara, Hideaki; Ohyanagi, Hajime; Kurata, Nori; Okubo, Kousaku; Takagi, Toshihisa; Kaminuma, Eli; Nakamura, Yasukazu

2013-01-01

High-performance next-generation sequencing (NGS) technologies are advancing genomics and molecular biological research. However, the immense amount of sequence data requires computational skills and suitable hardware resources that are a challenge to molecular biologists. The DNA Data Bank of Japan (DDBJ) of the National Institute of Genetics (NIG) has initiated a cloud computing-based analytical pipeline, the DDBJ Read Annotation Pipeline (DDBJ Pipeline), for a high-throughput annotation of NGS reads. The DDBJ Pipeline offers a user-friendly graphical web interface and processes massive NGS datasets using decentralized processing by NIG supercomputers currently free of charge. The proposed pipeline consists of two analysis components: basic analysis for reference genome mapping and de novo assembly and subsequent high-level analysis of structural and functional annotations. Users may smoothly switch between the two components in the pipeline, facilitating web-based operations on a supercomputer for high-throughput data analysis. Moreover, public NGS reads of the DDBJ Sequence Read Archive located on the same supercomputer can be imported into the pipeline through the input of only an accession number. This proposed pipeline will facilitate research by utilizing unified analytical workflows applied to the NGS data. The DDBJ Pipeline is accessible at http://p.ddbj.nig.ac.jp/. PMID:23657089

The ExoMars science data archive: status and plans

NASA Astrophysics Data System (ADS)

Heather, David

2016-07-01

The ExoMars program, a cooperation between ESA and Roscosmos, comprises two missions: the Trace Gas Orbiter, to be launched in 2016, and a rover and surface platform, due for launch in 2018. This will be the first time ESA has operated a rover, and the archiving and management of the science data to be returned will require a significant effort in development of the new Planetary Science Archive (PSA). The ExoMars mission data will also be formatted according to the new PDS4 Standards, based in XML, and this will be the first data of that format to be archived in the PSA. There are significant differences in the way in which a scientist will want to query, retrieve, and use data from a suite of rover instruments as opposed to remote sensing instrumentation from an orbiter. The PSA data holdings and the accompanying services are currently driven more towards the management of remote sensing data, so some significant changes will be needed. Among them will be a much closer link to the operational information than is currently available for our missions. NASA have a strong user community interaction with their analysts notebook, which provides detailed operational information to explain why, where and when operations took place. A similar approach will be needed for the future PSA, which is currently being designed. In addition to the archiving interface itself, there are differences with the overall archiving process being followed for ExoMars compared to previous ESA planetary missions. The Trace Gas Orbiter data pipelines for the first level of processing from telemetry to raw data, will be hosted directly by ESA's ground segment at ESAC in Madrid, where the archive itself resides. Data will have a continuous flow direct to the PSA, where after the given proprietary period, it will be directly released to the community via the new user interface. For the rover mission, the data pipelines are being developed by European industry, in close collaboration with ESA PSA experts and with the instrument teams. The first level of data processing will be carried out for all instruments at ALTEC in Turin where the pipelines are developed, and from where the rover operations will also be run. The PDS4 data will be directly produced and used for planning purposes within the operations centre before being passed on the the PSA for long term archiving. While this has clear advantages in the long-term regarding the timely population of the archive with at least the first level of data, the outsourcing of the pipelines to industry introduces complications. Firstly, it is difficult to have the necessary expertise on hand to train the individuals designing the pipelines, and to define the archiving conventions needed to meet the scientific needs of the mission. It also introduces issues in terms of driving the schedule, as industry is committed to making deliveries within fixed budgets and time-frames that may not necessarily be in line with the needs of archiving, and may not be able to respond well to the ongoing evolution of the PDS4 standards. This presentation will focus on the challenges involved in archiving rover data for the PSA, and will outline the plans and current status of the system being developed to respond to the needs of the mission.

Text-based Analytics for Biosurveillance

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

Charles, Lauren E.; Smith, William P.; Rounds, Jeremiah

The ability to prevent, mitigate, or control a biological threat depends on how quickly the threat is identified and characterized. Ensuring the timely delivery of data and analytics is an essential aspect of providing adequate situational awareness in the face of a disease outbreak. This chapter outlines an analytic pipeline for supporting an advanced early warning system that can integrate multiple data sources and provide situational awareness of potential and occurring disease situations. The pipeline, includes real-time automated data analysis founded on natural language processing (NLP), semantic concept matching, and machine learning techniques, to enrich content with metadata related tomore » biosurveillance. Online news articles are presented as an example use case for the pipeline, but the processes can be generalized to any textual data. In this chapter, the mechanics of a streaming pipeline are briefly discussed as well as the major steps required to provide targeted situational awareness. The text-based analytic pipeline includes various processing steps as well as identifying article relevance to biosurveillance (e.g., relevance algorithm) and article feature extraction (who, what, where, why, how, and when). The ability to prevent, mitigate, or control a biological threat depends on how quickly the threat is identified and characterized. Ensuring the timely delivery of data and analytics is an essential aspect of providing adequate situational awareness in the face of a disease outbreak. This chapter outlines an analytic pipeline for supporting an advanced early warning system that can integrate multiple data sources and provide situational awareness of potential and occurring disease situations. The pipeline, includes real-time automated data analysis founded on natural language processing (NLP), semantic concept matching, and machine learning techniques, to enrich content with metadata related to biosurveillance. Online news articles are presented as an example use case for the pipeline, but the processes can be generalized to any textual data. In this chapter, the mechanics of a streaming pipeline are briefly discussed as well as the major steps required to provide targeted situational awareness. The text-based analytic pipeline includes various processing steps as well as identifying article relevance to biosurveillance (e.g., relevance algorithm) and article feature extraction (who, what, where, why, how, and when).« less

75 FR 35632 - Transparency Provisions of Section 23 of the Natural Gas Act

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-23

... pipeline- quality natural gas. For instance, some Respondents questioned whether pipeline-quality natural gas that is sold directly into an interstate or intrastate natural gas pipeline without processing... reported transactions of pipeline-quality gas under the assumption that ``unprocessed natural gas'' was...

Planck 2015 results: VII. High Frequency Instrument data processing: Time-ordered information and beams

DOE PAGES

Adam, R.; Ade, P. A. R.; Aghanim, N.; ...

2016-09-20

The Planck High Frequency Instrument (HFI) has observed the full sky at six frequencies (100, 143, 217, 353, 545, and 857 GHz) in intensity and at four frequencies in linear polarization (100, 143, 217, and 353 GHz). In order to obtain sky maps, the time-ordered information (TOI) containing the detector and pointing samples must be processed and the angular response must be assessed. The full mission TOI is included in the Planck 2015 release. This study describes the HFI TOI and beam processing for the 2015 release. HFI calibration and map making are described in a companion paper. The mainmore » pipeline has been modified since the last release (2013 nominal mission in intensity only), by including a correction for the nonlinearity of the warm readout and by improving the model of the bolometer time response. The beam processing is an essential tool that derives the angular response used in all the Planck science papers and we report an improvement in the effective beam window function uncertainty of more than a factor of 10 relative to the2013 release. Noise correlations introduced by pipeline filtering function are assessed using dedicated simulations. Finally, angular cross-power spectra using data sets that are decorrelated in time are immune to the main systematic effects.« less

Planck 2015 results. VII. High Frequency Instrument data processing: Time-ordered information and beams

NASA Astrophysics Data System (ADS)

Planck Collaboration; Adam, R.; Ade, P. A. R.; Aghanim, N.; Arnaud, M.; Ashdown, M.; Aumont, J.; Baccigalupi, C.; Banday, A. J.; Barreiro, R. B.; Bartolo, N.; Battaner, E.; Benabed, K.; Benoît, A.; Benoit-Lévy, A.; Bernard, J.-P.; Bersanelli, M.; Bertincourt, B.; Bielewicz, P.; Bock, J. J.; Bonavera, L.; Bond, J. R.; Borrill, J.; Bouchet, F. R.; Boulanger, F.; Bucher, M.; Burigana, C.; Calabrese, E.; Cardoso, J.-F.; Catalano, A.; Challinor, A.; Chamballu, A.; Chary, R.-R.; Chiang, H. C.; Christensen, P. R.; Clements, D. L.; Colombi, S.; Colombo, L. P. L.; Combet, C.; Couchot, F.; Coulais, A.; Crill, B. P.; Curto, A.; Cuttaia, F.; Danese, L.; Davies, R. D.; Davis, R. J.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Delouis, J.-M.; Désert, F.-X.; Diego, J. M.; Dole, H.; Donzelli, S.; Doré, O.; Douspis, M.; Ducout, A.; Dupac, X.; Efstathiou, G.; Elsner, F.; Enßlin, T. A.; Eriksen, H. K.; Falgarone, E.; Fergusson, J.; Finelli, F.; Forni, O.; Frailis, M.; Fraisse, A. A.; Franceschi, E.; Frejsel, A.; Galeotta, S.; Galli, S.; Ganga, K.; Ghosh, T.; Giard, M.; Giraud-Héraud, Y.; Gjerløw, E.; González-Nuevo, J.; Górski, K. M.; Gratton, S.; Gruppuso, A.; Gudmundsson, J. E.; Hansen, F. K.; Hanson, D.; Harrison, D. L.; Henrot-Versillé, S.; Herranz, D.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Holmes, W. A.; Hornstrup, A.; Hovest, W.; Huffenberger, K. M.; Hurier, G.; Jaffe, A. H.; Jaffe, T. R.; Jones, W. C.; Juvela, M.; Keihänen, E.; Keskitalo, R.; Kisner, T. S.; Kneissl, R.; Knoche, J.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lamarre, J.-M.; Lasenby, A.; Lattanzi, M.; Lawrence, C. R.; Le Jeune, M.; Leahy, J. P.; Lellouch, E.; Leonardi, R.; Lesgourgues, J.; Levrier, F.; Liguori, M.; Lilje, P. B.; Linden-Vørnle, M.; López-Caniego, M.; Lubin, P. M.; Macías-Pérez, J. F.; Maggio, G.; Maino, D.; Mandolesi, N.; Mangilli, A.; Maris, M.; Martin, P. G.; Martínez-González, E.; Masi, S.; Matarrese, S.; McGehee, P.; Melchiorri, A.; Mendes, L.; Mennella, A.; Migliaccio, M.; Mitra, S.; Miville-Deschênes, M.-A.; Moneti, A.; Montier, L.; Moreno, R.; Morgante, G.; Mortlock, D.; Moss, A.; Mottet, S.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Nati, F.; Natoli, P.; Netterfield, C. B.; Nørgaard-Nielsen, H. U.; Noviello, F.; Novikov, D.; Novikov, I.; Oxborrow, C. A.; Paci, F.; Pagano, L.; Pajot, F.; Paoletti, D.; Pasian, F.; Patanchon, G.; Pearson, T. J.; Perdereau, O.; Perotto, L.; Perrotta, F.; Pettorino, V.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Pietrobon, D.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Pratt, G. W.; Prézeau, G.; Prunet, S.; Puget, J.-L.; Rachen, J. P.; Reinecke, M.; Remazeilles, M.; Renault, C.; Renzi, A.; Ristorcelli, I.; Rocha, G.; Rosset, C.; Rossetti, M.; Roudier, G.; Rowan-Robinson, M.; Rusholme, B.; Sandri, M.; Santos, D.; Sauvé, A.; Savelainen, M.; Savini, G.; Scott, D.; Seiffert, M. D.; Shellard, E. P. S.; Spencer, L. D.; Stolyarov, V.; Stompor, R.; Sudiwala, R.; Sutton, D.; Suur-Uski, A.-S.; Sygnet, J.-F.; Tauber, J. A.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tristram, M.; Tucci, M.; Tuovinen, J.; Valenziano, L.; Valiviita, J.; Van Tent, B.; Vibert, L.; Vielva, P.; Villa, F.; Wade, L. A.; Wandelt, B. D.; Watson, R.; Wehus, I. K.; Yvon, D.; Zacchei, A.; Zonca, A.

2016-09-01

The Planck High Frequency Instrument (HFI) has observed the full sky at six frequencies (100, 143, 217, 353, 545, and 857 GHz) in intensity and at four frequencies in linear polarization (100, 143, 217, and 353 GHz). In order to obtain sky maps, the time-ordered information (TOI) containing the detector and pointing samples must be processed and the angular response must be assessed. The full mission TOI is included in the Planck 2015 release. This paper describes the HFI TOI and beam processing for the 2015 release. HFI calibration and map making are described in a companion paper. The main pipeline has been modified since the last release (2013 nominal mission in intensity only), by including a correction for the nonlinearity of the warm readout and by improving the model of the bolometer time response. The beam processing is an essential tool that derives the angular response used in all the Planck science papers and we report an improvement in the effective beam window function uncertainty of more than a factor of 10 relative to the2013 release. Noise correlations introduced by pipeline filtering function are assessed using dedicated simulations. Angular cross-power spectra using data sets that are decorrelated in time are immune to the main systematic effects.

Planck 2015 results: VII. High Frequency Instrument data processing: Time-ordered information and beams

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

Adam, R.; Ade, P. A. R.; Aghanim, N.

The Planck High Frequency Instrument (HFI) has observed the full sky at six frequencies (100, 143, 217, 353, 545, and 857 GHz) in intensity and at four frequencies in linear polarization (100, 143, 217, and 353 GHz). In order to obtain sky maps, the time-ordered information (TOI) containing the detector and pointing samples must be processed and the angular response must be assessed. The full mission TOI is included in the Planck 2015 release. This study describes the HFI TOI and beam processing for the 2015 release. HFI calibration and map making are described in a companion paper. The mainmore » pipeline has been modified since the last release (2013 nominal mission in intensity only), by including a correction for the nonlinearity of the warm readout and by improving the model of the bolometer time response. The beam processing is an essential tool that derives the angular response used in all the Planck science papers and we report an improvement in the effective beam window function uncertainty of more than a factor of 10 relative to the2013 release. Noise correlations introduced by pipeline filtering function are assessed using dedicated simulations. Finally, angular cross-power spectra using data sets that are decorrelated in time are immune to the main systematic effects.« less

Why aren't women sticking with science in Taiwan?

PubMed

Cheng, Ling-Fang

2010-06-01

This paper explores the factors that contribute to the "leaky pipeline" in science, technology and medicine in Taiwan. The term "leaky pipeline" refers to the steady attrition of women throughout their careers in science, technology and medicine-fields in which men constitute the majority. As a result of this attrition, women are under-represented in the top positions. This phenomenon has been well studied in the United States, and based on the available data in the Chinese and English-language literature, this paper focuses on: (1) the social-cultural factors that keep young women away from science and medicine; (2) the difficulties faced by woman scientists when trying to balance work and family responsibilities; and (3) the impact of the pervasive masculine culture on training and promotion in career development. Conclusions include suggestions for improvements for equality between the sexes in science education, family responsive policies, and institutional reform. 2010 Elsevier. Published by Elsevier B.V. All rights reserved.

Development and Applications of Pipeline Steel in Long-Distance Gas Pipeline of China

NASA Astrophysics Data System (ADS)

Chunyong, Huo; Yang, Li; Lingkang, Ji

In past decades, with widely utilizing of Microalloying and Thermal Mechanical Control Processing (TMCP) technology, the good matching of strength, toughness, plasticity and weldability on pipeline steel has been reached so that oil and gas pipeline has been greatly developed in China to meet the demand of strong domestic consumption of energy. In this paper, development history of pipeline steel and gas pipeline in china is briefly reviewed. The microstructure characteristic and mechanical performance of pipeline steel used in some representative gas pipelines of china built in different stage are summarized. Through the analysis on the evolution of pipeline service environment, some prospective development trend of application of pipeline steel in China is also presented.

ARTIP: Automated Radio Telescope Image Processing Pipeline

NASA Astrophysics Data System (ADS)

Sharma, Ravi; Gyanchandani, Dolly; Kulkarni, Sarang; Gupta, Neeraj; Pathak, Vineet; Pande, Arti; Joshi, Unmesh

2018-02-01

The Automated Radio Telescope Image Processing Pipeline (ARTIP) automates the entire process of flagging, calibrating, and imaging for radio-interferometric data. ARTIP starts with raw data, i.e. a measurement set and goes through multiple stages, such as flux calibration, bandpass calibration, phase calibration, and imaging to generate continuum and spectral line images. Each stage can also be run independently. The pipeline provides continuous feedback to the user through various messages, charts and logs. It is written using standard python libraries and the CASA package. The pipeline can deal with datasets with multiple spectral windows and also multiple target sources which may have arbitrary combinations of flux/bandpass/phase calibrators.

Increasing Diversity in the Geosciences at the City University of New York

NASA Astrophysics Data System (ADS)

Damas, C.; Johnson, L.; McHugh, C.; Marchese, P. J.

2007-12-01

The City University of New York (CUNY) is the nation's largest urban university, with 23 institutions serving a large number of underrepresented minority (URM) and women students at all levels of the pipeline - community college to graduate school. CUNY has a strong record of recruiting, enrolling, retaining and graduating URMs in science, technology, engineering and mathematics (STEM) fields. Current efforts are underway to increase the number of URMs in the geosciences. These efforts include: 1) involving students in research at all levels of the pipeline; 2) incorporating innovative and proven pedagogical methods into the classroom; and 3) mentoring of students by research scientists from CUNY and other participating institutions. At all levels of the pipeline, students are actively engaged in Space and Earth Science research. At the community college level, students are introduced to the scientific research process through familiar software such as MS Excel to analyze simple time series. At the senior colleges, students progress to multi-variate data analysis, and they also have the opportunity to go into the field to collect data. As graduate students, they are involved as mentors and supervise undergraduate student research. Program initiatives such as the CUNY pipeline provide stipends and academic enrichment activities (i.e., GRE training, applying to graduate school, etc.) throughout the summer and academic year. During the summer, students also have the opportunity to work with and be mentored by research scientists at a CUNY campus, at a NASA center or a national laboratory. Mentors advise students about graduate school and careers, serve as role models, and perhaps more importantly, provide encouragement to students who lack confidence in their ability to do scientific research. Students also are expected to present their research findings at meetings and conferences, both locally and nationally. In addition to their research experiences, students also benefit from classroom instructions that emphasize active learning, and the integration of research related activities. Proven educational materials and pedagogical methods developed at Medgar Evers College and Queensborough Community College have proven quite effective at engaging and assisting students who have conceptual difficulties in their science and mathematics courses. Overall, students demonstrate an increase in their conceptual understanding of the subject matter, as well an increase in their confidence to solve scientific problems and to become scientists.

77 FR 26760 - Kinder Morgan, Inc.; Analysis of Proposed Agreement Containing Consent Orders To Aid Public Comment

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-07

... to as natural gas liquids or NGLs. Interstate pipelines have a limit on how much NGLs natural gas can... gas processing plant to remove those liquids before it can be transported on interstate pipelines... Gas Transmission, and Trailblazer pipelines, as well as associated processing and storage capacity. On...

Data Processing Factory for the Sloan Digital Sky Survey

NASA Astrophysics Data System (ADS)

Stoughton, Christopher; Adelman, Jennifer; Annis, James T.; Hendry, John; Inkmann, John; Jester, Sebastian; Kent, Steven M.; Kuropatkin, Nickolai; Lee, Brian; Lin, Huan; Peoples, John, Jr.; Sparks, Robert; Tucker, Douglas; Vanden Berk, Dan; Yanny, Brian; Yocum, Dan

2002-12-01

The Sloan Digital Sky Survey (SDSS) data handling presents two challenges: large data volume and timely production of spectroscopic plates from imaging data. A data processing factory, using technologies both old and new, handles this flow. Distribution to end users is via disk farms, to serve corrected images and calibrated spectra, and a database, to efficiently process catalog queries. For distribution of modest amounts of data from Apache Point Observatory to Fermilab, scripts use rsync to update files, while larger data transfers are accomplished by shipping magnetic tapes commercially. All data processing pipelines are wrapped in scripts to address consecutive phases: preparation, submission, checking, and quality control. We constructed the factory by chaining these pipelines together while using an operational database to hold processed imaging catalogs. The science database catalogs all imaging and spectroscopic object, with pointers to the various external files associated with them. Diverse computing systems address particular processing phases. UNIX computers handle tape reading and writing, as well as calibration steps that require access to a large amount of data with relatively modest computational demands. Commodity CPUs process steps that require access to a limited amount of data with more demanding computations requirements. Disk servers optimized for cost per Gbyte serve terabytes of processed data, while servers optimized for disk read speed run SQLServer software to process queries on the catalogs. This factory produced data for the SDSS Early Data Release in June 2001, and it is currently producing Data Release One, scheduled for January 2003.

Data as a Service: A Seismic Web Service Pipeline

NASA Astrophysics Data System (ADS)

Martinez, E.

2016-12-01

Publishing data as a service pipeline provides an improved, dynamic approach over static data archives. A service pipeline is a collection of micro web services that each perform a specific task and expose the results of that task. Structured request/response formats allow micro web services to be chained together into a service pipeline to provide more complex results. The U.S. Geological Survey adopted service pipelines to publish seismic hazard and design data supporting both specific and generalized audiences. The seismic web service pipeline starts at source data and exposes probability and deterministic hazard curves, response spectra, risk-targeted ground motions, and seismic design provision metadata. This pipeline supports public/private organizations and individual engineers/researchers. Publishing data as a service pipeline provides a variety of benefits. Exposing the component services enables advanced users to inspect or use the data at each processing step. Exposing a composite service enables new users quick access to published data with a very low barrier to entry. Advanced users may re-use micro web services by chaining them in new ways or injecting new micros services into the pipeline. This allows the user to test hypothesis and compare their results to published results. Exposing data at each step in the pipeline enables users to review and validate the data and process more quickly and accurately. Making the source code open source, per USGS policy, further enables this transparency. Each micro service may be scaled independent of any other micro service. This ensures data remains available and timely in a cost-effective manner regardless of load. Additionally, if a new or more efficient approach to processing the data is discovered, this new approach may replace the old approach at any time, keeping the pipeline running while not affecting other micro services.

Significantly reducing the processing times of high-speed photometry data sets using a distributed computing model

NASA Astrophysics Data System (ADS)

Doyle, Paul; Mtenzi, Fred; Smith, Niall; Collins, Adrian; O'Shea, Brendan

2012-09-01

The scientific community is in the midst of a data analysis crisis. The increasing capacity of scientific CCD instrumentation and their falling costs is contributing to an explosive generation of raw photometric data. This data must go through a process of cleaning and reduction before it can be used for high precision photometric analysis. Many existing data processing pipelines either assume a relatively small dataset or are batch processed by a High Performance Computing centre. A radical overhaul of these processing pipelines is required to allow reduction and cleaning rates to process terabyte sized datasets at near capture rates using an elastic processing architecture. The ability to access computing resources and to allow them to grow and shrink as demand fluctuates is essential, as is exploiting the parallel nature of the datasets. A distributed data processing pipeline is required. It should incorporate lossless data compression, allow for data segmentation and support processing of data segments in parallel. Academic institutes can collaborate and provide an elastic computing model without the requirement for large centralized high performance computing data centers. This paper demonstrates how a base 10 order of magnitude improvement in overall processing time has been achieved using the "ACN pipeline", a distributed pipeline spanning multiple academic institutes.

RISA: Remote Interface for Science Analysis

NASA Astrophysics Data System (ADS)

Gabriel, C.; Ibarra, A.; de La Calle, I.; Salgado, J.; Osuna, P.; Tapiador, D.

2008-08-01

The Scientific Analysis System (SAS) is the package for interactive and pipeline data reduction of all XMM-Newton data. Freely distributed by ESA to run under many different operating systems, the SAS has been used by almost every one of the 1600 refereed scientific publications obtained so far from the mission. We are developing RISA, the Remote Interface for Science Analysis, which makes it possible to run SAS through fully configurable web service workflows, enabling observers to access and analyse data making use of all of the existing SAS functionalities, without any installation/download of software/data. The workflows run primarily but not exclusively on the ESAC Grid, which offers scalable processing resources, directly connected to the XMM-Newton Science Archive. A first project internal version of RISA was issued in May 2007, a public release is expected already within this year.

Constructing Flexible, Configurable, ETL Pipelines for the Analysis of "Big Data" with Apache OODT

NASA Astrophysics Data System (ADS)

Hart, A. F.; Mattmann, C. A.; Ramirez, P.; Verma, R.; Zimdars, P. A.; Park, S.; Estrada, A.; Sumarlidason, A.; Gil, Y.; Ratnakar, V.; Krum, D.; Phan, T.; Meena, A.

2013-12-01

A plethora of open source technologies for manipulating, transforming, querying, and visualizing 'big data' have blossomed and matured in the last few years, driven in large part by recognition of the tremendous value that can be derived by leveraging data mining and visualization techniques on large data sets. One facet of many of these tools is that input data must often be prepared into a particular format (e.g.: JSON, CSV), or loaded into a particular storage technology (e.g.: HDFS) before analysis can take place. This process, commonly known as Extract-Transform-Load, or ETL, often involves multiple well-defined steps that must be executed in a particular order, and the approach taken for a particular data set is generally sensitive to the quantity and quality of the input data, as well as the structure and complexity of the desired output. When working with very large, heterogeneous, unstructured or semi-structured data sets, automating the ETL process and monitoring its progress becomes increasingly important. Apache Object Oriented Data Technology (OODT) provides a suite of complementary data management components called the Process Control System (PCS) that can be connected together to form flexible ETL pipelines as well as browser-based user interfaces for monitoring and control of ongoing operations. The lightweight, metadata driven middleware layer can be wrapped around custom ETL workflow steps, which themselves can be implemented in any language. Once configured, it facilitates communication between workflow steps and supports execution of ETL pipelines across a distributed cluster of compute resources. As participants in a DARPA-funded effort to develop open source tools for large-scale data analysis, we utilized Apache OODT to rapidly construct custom ETL pipelines for a variety of very large data sets to prepare them for analysis and visualization applications. We feel that OODT, which is free and open source software available through the Apache Software Foundation, is particularly well suited to developing and managing arbitrary large-scale ETL processes both for the simplicity and flexibility of its wrapper framework, as well as the detailed provenance information it exposes throughout the process. Our experience using OODT to manage processing of large-scale data sets in domains as diverse as radio astronomy, life sciences, and social network analysis demonstrates the flexibility of the framework, and the range of potential applications to a broad array of big data ETL challenges.

Secondary Education Systemic Issues: Addressing Possible Contributors to a Leak in the Science Education Pipeline and Potential Solutions

ERIC Educational Resources Information Center

Young, Hollie

2005-01-01

To maintain the legacy of cutting edge scientific innovation in the United States our country must address the many pressing issues facing science education today. One of the most important issues relating to science education is the under-representation of African Americans and Hispanics in the science, technology, and engineering workforce.…

Considerations and Recommendations for Implementing a Dual-Enrollment Program: Bridging the Gap between High School and College Level Science

ERIC Educational Resources Information Center

Lukes, Laura A.

2014-01-01

Dual-enrollment (DE) science courses offer a way to strengthen the science, technology, engineering, and mathematics pipeline between high school and college. These courses offer high school students the opportunity to experience college science in a more supported environment, allowing them to adjust to the different academic and social demands…

Puncturing the pipeline: Do technology companies alienate women in recruiting sessions?

PubMed

Wynn, Alison T; Correll, Shelley J

2018-02-01

A 'chilly' environment limits women's advancement through the educational pipeline leading to jobs in science and technology. However, we know relatively little about the environment women encounter after making it through the educational pipeline. Do technology companies create environments that may dampen women's interest at the juncture when they are launching their careers? Using original observational data from 84 recruiting sessions hosted by technology companies at a prominent university on the US West Coast, we find that company representatives often engage in behaviors that are known to create a chilly environment for women. Through gender-imbalanced presenter roles, geek culture references, overt use of gender stereotypes, and other gendered speech and actions, representatives may puncture the pipeline, lessening the interest of women at the point of recruitment into technology careers.

The ExoMars Science Data Archive: Status and Plans

NASA Astrophysics Data System (ADS)

Heather, David; Barbarisi, Isa; Brumfitt, Jon; Lim, Tanya; Metcalfe, Leo; Villacorta, Antonio

2017-04-01

The ExoMars program is a co-operation between ESA and Roscosmos comprising two missions: the first, launched on 14 March 2016, included the Trace Gas Orbiter and Schiaparelli lander; the second, due for launch in 2020, will be a Rover and Surface Platform (RSP). The archiving and management of the science data to be returned from ExoMars will require a significant development effort for the new Planetary Science Archive (PSA). These are the first data in the PSA to be formatted according to the new PDS4 Standards, and there are also significant differences in the way in which a scientist will want to query, retrieve, and use data from a suite of rover instruments as opposed to remote sensing instrumentation from an orbiter. NASA has a strong user community interaction for their rovers, and a similar approach to their 'Analysts Notebook' will be needed for the future PSA. In addition to the archiving interface itself, there are differences with the overall archiving process being followed for ExoMars compared to previous ESA planetary missions. The first level of data processing for the 2016 mission, from telemetry to raw, is completed by ESA at ESAC in Madrid, where the archive itself resides. Data continuously flow direct to the PSA, where after the given proprietary period, they will be released to the community via the user interfaces. For the rover mission, the data pipelines are being developed by European industry, in close collaboration with ESA PSA experts and with the instrument teams. The first level of data processing will be carried out for all instruments at ALTEC in Turin where the pipelines are developed, and from where the rover operations will also be run. This presentation will focus on the challenges involved in archiving the data from the ExoMars Program, and will outline the plans and current status of the system being developed to respond to the needs of the missions.

Persistence in STEM: An investigation of the relationship between high school experiences in science and mathematics and college degree completion in STEM fields

NASA Astrophysics Data System (ADS)

Maltese, Adam V.

While the number of Bachelor's degrees awarded annually has nearly tripled over the past 40 years (NSF, 2008), the same cannot be said for degrees in the STEM (science, technology, engineering and mathematics) fields. The Bureau of Labor Statistics projects that by the year 2014 the combination of new positions and retirements will lead to 2 million job openings in STEM (BLS, 2005). Thus, the research questions I sought to answer with this study were: (1)What are the most common enrollment patterns for students who enter into and exit from the STEM pipeline during high school and college? (2) Controlling for differences in student background and early interest in STEM careers, what are the high school science and mathematics classroom experiences that characterize student completion of a college major in STEM? Using data from NELS:88 I analyzed descriptive statistics and completed logistic regressions to gain an understanding of factors related to student persistence in STEM. Approximately 4700 students with transcript records and who participated in all survey rounds were included in the analyses. The results of the descriptive analysis demonstrated that most students who went on to complete majors in STEM completed at least three or four years of STEM courses during high school, and enrolled in advanced high school mathematics and science courses at higher rates. At almost every pipeline checkpoint indicators of the level of coursework and achievement were significant in predicting student completion of a STEM degree. The results also support previous research that showed demographic variables have little effect on persistence once the sample is limited to those who have the intrinsic ability and desire to complete a college degree. The most significant finding is that measures of student interest and engagement in science and mathematics were significant in predicting completion of a STEM degree, above and beyond the effects of course enrollment and performance. A final analysis, which involved the comparison of descriptive statistics for students who switched into and out of the STEM pipeline during high school, suggested that attitudes toward mathematics and science play a major role in choices regarding pipeline persistence.

Science Camp: Just for the Girls

ERIC Educational Resources Information Center

Cavanagh, Sean

2007-01-01

Research shows that girls tend to lose interest in science and math as they move through the education pipeline--a retreat that often begins during middle school. Summer science camps can be part of reversing that trend, some say. Academic camps are on the rise across the country, including ones to get adolescent girls excited about the…

Expanding Girls' Horizons: Strengthening Persistence in the Early Math and Science Education Pipeline

NASA Astrophysics Data System (ADS)

Virnoche, Mary E.

Little longitudinal or follow-up data is available on the impact of Expanding Your Horizons (EYH) conferences. The purpose of the conferences is to encourage girls to take more math and science in high school by exposing them to hands-on activities and role models in math and science professions. This paper is based on 2005 and 2006 one-to-one and small-group interview data from 22 high school girls who attended an EYH conference during their middle school years. The data suggests that EYH strengthens girls' persistence in math and science pathways. Most girls came to the conferences already interested in math and science and at the urging of parents or teachers. Most felt empowered through the shared experience with hundreds of other girls and women, and relayed detailed and enthusiastic descriptions of hands-on activities. Many of the girls also drew connections between EYH and their course-taking actions and career goals. This paper highlights examples of these experiences and makes recommendations for future math and science early pipeline diversity work.

In Pursuit of LSST Science Requirements: A Comparison of Photometry Algorithms

NASA Astrophysics Data System (ADS)

Becker, Andrew C.; Silvestri, Nicole M.; Owen, Russell E.; Ivezić, Željko; Lupton, Robert H.

2007-12-01

We have developed an end-to-end photometric data-processing pipeline to compare current photometric algorithms commonly used on ground-based imaging data. This test bed is exceedingly adaptable and enables us to perform many research and development tasks, including image subtraction and co-addition, object detection and measurements, the production of photometric catalogs, and the creation and stocking of database tables with time-series information. This testing has been undertaken to evaluate existing photometry algorithms for consideration by a next-generation image-processing pipeline for the Large Synoptic Survey Telescope (LSST). We outline the results of our tests for four packages: the Sloan Digital Sky Survey's Photo package, DAOPHOT and ALLFRAME, DOPHOT, and two versions of Source Extractor (SExtractor). The ability of these algorithms to perform point-source photometry, astrometry, shape measurements, and star-galaxy separation and to measure objects at low signal-to-noise ratio is quantified. We also perform a detailed crowded-field comparison of DAOPHOT and ALLFRAME, and profile the speed and memory requirements in detail for SExtractor. We find that both DAOPHOT and Photo are able to perform aperture photometry to high enough precision to meet LSST's science requirements, and less adequately at PSF-fitting photometry. Photo performs the best at simultaneous point- and extended-source shape and brightness measurements. SExtractor is the fastest algorithm, and recent upgrades in the software yield high-quality centroid and shape measurements with little bias toward faint magnitudes. ALLFRAME yields the best photometric results in crowded fields.

Numerical research on the lateral global buckling characteristics of a high temperature and pressure pipeline with two initial imperfections

PubMed Central

Liu, Wenbin; Liu, Aimin

2018-01-01

With the exploitation of offshore oil and gas gradually moving to deep water, higher temperature differences and pressure differences are applied to the pipeline system, making the global buckling of the pipeline more serious. For unburied deep-water pipelines, the lateral buckling is the major buckling form. The initial imperfections widely exist in the pipeline system due to manufacture defects or the influence of uneven seabed, and the distribution and geometry features of initial imperfections are random. They can be divided into two kinds based on shape: single-arch imperfections and double-arch imperfections. This paper analyzed the global buckling process of a pipeline with 2 initial imperfections by using a numerical simulation method and revealed how the ratio of the initial imperfection’s space length to the imperfection’s wavelength and the combination of imperfections affects the buckling process. The results show that a pipeline with 2 initial imperfections may suffer the superposition of global buckling. The growth ratios of buckling displacement, axial force and bending moment in the superposition zone are several times larger than no buckling superposition pipeline. The ratio of the initial imperfection’s space length to the imperfection’s wavelength decides whether a pipeline suffers buckling superposition. The potential failure point of pipeline exhibiting buckling superposition is as same as the no buckling superposition pipeline, but the failure risk of pipeline exhibiting buckling superposition is much higher. The shape and direction of two nearby imperfections also affects the failure risk of pipeline exhibiting global buckling superposition. The failure risk of pipeline with two double-arch imperfections is higher than pipeline with two single-arch imperfections. PMID:29554123

76 FR 54531 - Pipeline Safety: Potential for Damage to Pipeline Facilities Caused by the Passage of Hurricanes

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-01

... production and processing is prone to disruption by hurricanes. In 2005, Hurricanes Katrina and Rita caused... Hurricanes AGENCY: Pipeline and Hazardous Materials Safety Administration (PHMSA), DOT. ACTION: Notice... the passage of Hurricanes. ADDRESSES: This document can be viewed on the Office of Pipeline Safety...

75 FR 17397 - Hydrogen Energy California's Integrated Gasification Combined Cycle Project, Kern County, CA...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-06

... and potable water pipelines, a transmission line, a natural gas supply pipeline, a CO 2 pipeline... line. HECA would also construct an approximately 8-mile natural gas supply pipeline extending southeast... produce synthesis gas (syngas), which would then be processed and purified to produce a hydrogen-rich fuel...

Assessing fugitive emissions of CH4 from high-pressure gas pipelines

NASA Astrophysics Data System (ADS)

Worrall, Fred; Boothroyd, Ian; Davies, Richard

2017-04-01

The impact of unconventional natural gas production using hydraulic fracturing methods from shale gas basins has been assessed using life-cycle emissions inventories, covering areas such as pre-production, production and transmission processes. The transmission of natural gas from well pad to processing plants and its transport to domestic sites is an important source of fugitive CH4, yet emissions factors and fluxes from transmission processes are often based upon ver out of date measurements. It is important to determine accurate measurements of natural gas losses when compressed and transported between production and processing facilities so as to accurately determine life-cycle CH4 emissions. This study considers CH4 emissions from the UK National Transmission System (NTS) of high pressure natural gas pipelines. Mobile surveys of CH4 emissions using a Picarro Surveyor cavity-ring-down spectrometer were conducted across four areas in the UK, with routes bisecting high pressure pipelines and separate control routes away from the pipelines. A manual survey of soil gas measurements was also conducted along one of the high pressure pipelines using a tunable diode laser. When wind adjusted 92 km of high pressure pipeline and 72 km of control route were drive over a 10 day period. When wind and distance adjusted CH4 fluxes were significantly greater on routes with a pipeline than those without. The smallest leak detectable was 3% above ambient (1.03 relative concentration) with any leaks below 3% above ambient assumed ambient. The number of leaks detected along the pipelines correlate to the estimated length of pipe joints, inferring that there are constant fugitive CH4 emissions from these joints. When scaled up to the UK's National Transmission System pipeline length of 7600 km gives a fugitive CH4 flux of 4700 ± 2864 kt CH4/yr - this fugitive emission from high pressure pipelines is 0.016% of the annual gas supply.

An Integrated SNP Mining and Utilization (ISMU) Pipeline for Next Generation Sequencing Data

PubMed Central

Azam, Sarwar; Rathore, Abhishek; Shah, Trushar M.; Telluri, Mohan; Amindala, BhanuPrakash; Ruperao, Pradeep; Katta, Mohan A. V. S. K.; Varshney, Rajeev K.

2014-01-01

Open source single nucleotide polymorphism (SNP) discovery pipelines for next generation sequencing data commonly requires working knowledge of command line interface, massive computational resources and expertise which is a daunting task for biologists. Further, the SNP information generated may not be readily used for downstream processes such as genotyping. Hence, a comprehensive pipeline has been developed by integrating several open source next generation sequencing (NGS) tools along with a graphical user interface called Integrated SNP Mining and Utilization (ISMU) for SNP discovery and their utilization by developing genotyping assays. The pipeline features functionalities such as pre-processing of raw data, integration of open source alignment tools (Bowtie2, BWA, Maq, NovoAlign and SOAP2), SNP prediction (SAMtools/SOAPsnp/CNS2snp and CbCC) methods and interfaces for developing genotyping assays. The pipeline outputs a list of high quality SNPs between all pairwise combinations of genotypes analyzed, in addition to the reference genome/sequence. Visualization tools (Tablet and Flapjack) integrated into the pipeline enable inspection of the alignment and errors, if any. The pipeline also provides a confidence score or polymorphism information content value with flanking sequences for identified SNPs in standard format required for developing marker genotyping (KASP and Golden Gate) assays. The pipeline enables users to process a range of NGS datasets such as whole genome re-sequencing, restriction site associated DNA sequencing and transcriptome sequencing data at a fast speed. The pipeline is very useful for plant genetics and breeding community with no computational expertise in order to discover SNPs and utilize in genomics, genetics and breeding studies. The pipeline has been parallelized to process huge datasets of next generation sequencing. It has been developed in Java language and is available at http://hpc.icrisat.cgiar.org/ISMU as a standalone free software. PMID:25003610

Plant genome and transcriptome annotations: from misconceptions to simple solutions

PubMed Central

Bolger, Marie E; Arsova, Borjana; Usadel, Björn

2018-01-01

Abstract Next-generation sequencing has triggered an explosion of available genomic and transcriptomic resources in the plant sciences. Although genome and transcriptome sequencing has become orders of magnitudes cheaper and more efficient, often the functional annotation process is lagging behind. This might be hampered by the lack of a comprehensive enumeration of simple-to-use tools available to the plant researcher. In this comprehensive review, we present (i) typical ontologies to be used in the plant sciences, (ii) useful databases and resources used for functional annotation, (iii) what to expect from an annotated plant genome, (iv) an automated annotation pipeline and (v) a recipe and reference chart outlining typical steps used to annotate plant genomes/transcriptomes using publicly available resources. PMID:28062412

Empowering pharmacoinformatics by linked life science data

NASA Astrophysics Data System (ADS)

Goldmann, Daria; Zdrazil, Barbara; Digles, Daniela; Ecker, Gerhard F.

2017-03-01

With the public availability of large data sources such as ChEMBLdb and the Open PHACTS Discovery Platform, retrieval of data sets for certain protein targets of interest with consistent assay conditions is no longer a time consuming process. Especially the use of workflow engines such as KNIME or Pipeline Pilot allows complex queries and enables to simultaneously search for several targets. Data can then directly be used as input to various ligand- and structure-based studies. In this contribution, using in-house projects on P-gp inhibition, transporter selectivity, and TRPV1 modulation we outline how the incorporation of linked life science data in the daily execution of projects allowed to expand our approaches from conventional Hansch analysis to complex, integrated multilayer models.

The PREP pipeline: standardized preprocessing for large-scale EEG analysis.

PubMed

Bigdely-Shamlo, Nima; Mullen, Tim; Kothe, Christian; Su, Kyung-Min; Robbins, Kay A

2015-01-01

The technology to collect brain imaging and physiological measures has become portable and ubiquitous, opening the possibility of large-scale analysis of real-world human imaging. By its nature, such data is large and complex, making automated processing essential. This paper shows how lack of attention to the very early stages of an EEG preprocessing pipeline can reduce the signal-to-noise ratio and introduce unwanted artifacts into the data, particularly for computations done in single precision. We demonstrate that ordinary average referencing improves the signal-to-noise ratio, but that noisy channels can contaminate the results. We also show that identification of noisy channels depends on the reference and examine the complex interaction of filtering, noisy channel identification, and referencing. We introduce a multi-stage robust referencing scheme to deal with the noisy channel-reference interaction. We propose a standardized early-stage EEG processing pipeline (PREP) and discuss the application of the pipeline to more than 600 EEG datasets. The pipeline includes an automatically generated report for each dataset processed. Users can download the PREP pipeline as a freely available MATLAB library from http://eegstudy.org/prepcode.

Technology as a Tool for Understanding: a Pipeline of Curriculum-based Programs for Grades 4 to high school

NASA Astrophysics Data System (ADS)

Schuster, G.

2006-05-01

New NASA-funded educational initiatives make for a pipeline of products meeting the needs of today's educators in inner city schools, for NASA Explorer Schools and across the nation. Three projects include training and include: 1) WDLC [Weather Data Learning Center] , a math achievement program with data entry, inquiry-based investigations, and the application of math using weather maps and imagery for Grade 4; 2) Project 3D-VIEW, where students in Grades 5 and 6 become experts in air, life, water, land and Earth systems using 3D technologies requiring 3D glasses. A formal literacy and math piece are included, and 1200 teachers will be provided training and materials free beginning in Fall 2006, and 3) Signals of Spring, where students in Grades 7 to 8, or high school, use NASA data to explain the movement of dozens of birds, land and marine animals that are tracked by satellite. Comprehensive content in life and Earth science is taught with curricular activities, interactive mapping, image interpretation, and online journals and common misconceptions are dispelled. Scientist involvement and support for a project is essential for students who are developing process skills and performing science activities. Current research partners include Columbia University's Teachers College and Stanford University's School of Education.

Creating a Pipeline for African American Computing Science Faculty: An Innovative Faculty/Research Mentoring Program Model

ERIC Educational Resources Information Center

Charleston, LaVar J.; Gilbert, Juan E.; Escobar, Barbara; Jackson, Jerlando F. L.

2014-01-01

African Americans represent 1.3% of all computing sciences faculty in PhD-granting departments, underscoring the severe underrepresentation of Black/African American tenure-track faculty in computing (CRA, 2012). The Future Faculty/Research Scientist Mentoring (FFRM) program, funded by the National Science Foundation, was found to be an effective…

Early Science Learning among Low-Income Latino Preschool Children: The Role of Parent and Teacher Values, Beliefs, and Practices

ERIC Educational Resources Information Center

Choi, Bailey

2016-01-01

Science Technology Engineering and Math (STEM) education has become a top priority, particularly for low-income Latino students, who are vastly underrepresented in STEM fields, largely due to various inequities in the PK-20 pipeline (Villareal, Cabrera, & Friedrich, 2012). Implementing effective science instruction in preschool has been…

Is Science Me? High School Students' Identities, Participation and Aspirations in Science, Engineering, and Medicine

ERIC Educational Resources Information Center

Aschbacher, Pamela R.; Li, Erika; Roth, Ellen J.

2010-01-01

This study follows an ethnically and economically diverse sample of 33 high school students to explore why some who were once very interested in science, engineering, or medicine (SEM) majors or careers decided to leave the pipeline in high school while others persisted. Through longitudinal interviews and surveys, students shared narratives about…

New Developments At The Science Archives Of The NASA Exoplanet Science Institute

NASA Astrophysics Data System (ADS)

Berriman, G. Bruce

2018-06-01

The NASA Exoplanet Science Institute (NExScI) at Caltech/IPAC is the science center for NASA's Exoplanet Exploration Program and as such, NExScI operates three scientific archives: the NASA Exoplanet Archive (NEA) and Exoplanet Follow-up Observation Program Website (ExoFOP), and the Keck Observatory Archive (KOA).The NASA Exoplanet Archive supports research and mission planning by the exoplanet community by operating a service that provides confirmed and candidate planets, numerous project and contributed data sets and integrated analysis tools. The ExoFOP provides an environment for exoplanet observers to share and exchange data, observing notes, and information regarding the Kepler, K2, and TESS candidates. KOA serves all raw science and calibration observations acquired by all active and decommissioned instruments at the W. M. Keck Observatory, as well as reduced data sets contributed by Keck observers.In the coming years, the NExScI archives will support a series of major endeavours allowing flexible, interactive analysis of the data available at the archives. These endeavours exploit a common infrastructure based upon modern interfaces such as JuypterLab and Python. The first service will enable reduction and analysis of precision radial velocity data from the HIRES Keck instrument. The Exoplanet Archive is developing a JuypterLab environment based on the HIRES PRV interactive environment. Additionally, KOA is supporting an Observatory initiative to develop modern, Python based pipelines, and as part of this work, it has delivered a NIRSPEC reduction pipeline. The ensemble of pipelines will be accessible through the same environments.

78 FR 56268 - Pipeline Safety: Public Workshop on Integrity Verification Process, Comment Extension

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-12

.... PHMSA-2013-0119] Pipeline Safety: Public Workshop on Integrity Verification Process, Comment Extension... public workshop on ``Integrity Verification Process'' which took place on August 7, 2013. The notice also sought comments on the proposed ``Integrity Verification Process.'' In response to the comments received...

Vision, Identity, and Career in the Clinical and Translational Sciences: Building upon the Formative Years.

PubMed

Manson, Spero M; Martinez, Dominic F; Buchwald, Dedra S; Rubio, Doris M; Moss, Marc

2015-10-01

This paper is the second in a five-part series on the clinical and translational science educational pipeline. It focuses on the role that Clinical and Translational Science Award (CTSA) programs can play in supporting science, technology, engineering, and math (STEM) education in primary and secondary schools, as well as in facilitating these interests during transition to undergraduate training. Special emphasis should be placed on helping to form and sustain an identity as a scientist, and on instilling the persistence necessary to overcome numerous barriers to its actualization. CTSAs can contribute to cementing this sense of self by facilitating peer support, mentorship, and family involvement that will reinforce early educational decisions leading to clinical and translational science research careers. Meanwhile, the interests, skills, and motivation induced by participation in STEM programs must be sustained in transition to the next level in the educational pipeline, typically undergraduate study. Examples of CTSA collaborations with local schools, businesses, interest groups, and communities at large illustrate the emerging possibilities and promising directions with respect to each of these challenges. © 2015 Wiley Periodicals, Inc.

Vision, Identity, and Career in the Clinical and Translational Sciences: Building upon the Formative Years

PubMed Central

Martinez, Dominic F.; Buchwald, Dedra S.; Rubio, Doris M.; Moss, Marc

2015-01-01

Abstract This paper is the second in a five‐part series on the clinical and translational science educational pipeline. It focuses on the role that Clinical and Translational Science Award (CTSA) programs can play in supporting science, technology, engineering, and math (STEM) education in primary and secondary schools, as well as in facilitating these interests during transition to undergraduate training. Special emphasis should be placed on helping to form and sustain an identity as a scientist, and on instilling the persistence necessary to overcome numerous barriers to its actualization. CTSAs can contribute to cementing this sense of self by facilitating peer support, mentorship, and family involvement that will reinforce early educational decisions leading to clinical and translational science research careers. Meanwhile, the interests, skills, and motivation induced by participation in STEM programs must be sustained in transition to the next level in the educational pipeline, typically undergraduate study. Examples of CTSA collaborations with local schools, businesses, interest groups, and communities at large illustrate the emerging possibilities and promising directions with respect to each of these challenges. PMID:26271774

A low-cost transportable ground station for capture and processing of direct broadcast EOS satellite data

NASA Technical Reports Server (NTRS)

Davis, Don; Bennett, Toby; Short, Nicholas M., Jr.

1994-01-01

The Earth Observing System (EOS), part of a cohesive national effort to study global change, will deploy a constellation of remote sensing spacecraft over a 15 year period. Science data from the EOS spacecraft will be processed and made available to a large community of earth scientists via NASA institutional facilities. A number of these spacecraft are also providing an additional interface to broadcast data directly to users. Direct broadcast of real-time science data from overhead spacecraft has valuable applications including validation of field measurements, planning science campaigns, and science and engineering education. The success and usefulness of EOS direct broadcast depends largely on the end-user cost of receiving the data. To extend this capability to the largest possible user base, the cost of receiving ground stations must be as low as possible. To achieve this goal, NASA Goddard Space Flight Center is developing a prototype low-cost transportable ground station for EOS direct broadcast data based on Very Large Scale Integration (VLSI) components and pipelined, multiprocessing architectures. The targeted reproduction cost of this system is less than $200K. This paper describes a prototype ground station and its constituent components.

The JCSG high-throughput structural biology pipeline.

PubMed

Elsliger, Marc André; Deacon, Ashley M; Godzik, Adam; Lesley, Scott A; Wooley, John; Wüthrich, Kurt; Wilson, Ian A

2010-10-01

The Joint Center for Structural Genomics high-throughput structural biology pipeline has delivered more than 1000 structures to the community over the past ten years. The JCSG has made a significant contribution to the overall goal of the NIH Protein Structure Initiative (PSI) of expanding structural coverage of the protein universe, as well as making substantial inroads into structural coverage of an entire organism. Targets are processed through an extensive combination of bioinformatics and biophysical analyses to efficiently characterize and optimize each target prior to selection for structure determination. The pipeline uses parallel processing methods at almost every step in the process and can adapt to a wide range of protein targets from bacterial to human. The construction, expansion and optimization of the JCSG gene-to-structure pipeline over the years have resulted in many technological and methodological advances and developments. The vast number of targets and the enormous amounts of associated data processed through the multiple stages of the experimental pipeline required the development of variety of valuable resources that, wherever feasible, have been converted to free-access web-based tools and applications.

Study and Implementation of the End-to-End Data Pipeline for the Virtis Imaging Spectrometer Onbaord Venus Express: "From Science Operations Planning to Data Archiving and Higher Lever Processing"

NASA Astrophysics Data System (ADS)

Cardesín Moinelo, Alejandro

2010-04-01

This PhD Thesis describes the activities performed during the Research Program undertaken for two years at the Istituto Nazionale di AstroFisica in Rome, Italy, as active member of the VIRTIS Technical and Scientific Team, and one additional year at the European Space Astronomy Center in Madrid, Spain, as member of the Mars Express Science Ground Segment. This document will show a study of all sections of the Science Ground Segment of the Venus Express mission, from the planning of the scientific operations, to the generation, calibration and archiving of the science data, including the production of valuable high level products. We will present and discuss here the end-to-end diagram of the ground segment from the technical and scientific point of view, in order to describe the overall flow of information: from the original scientific requests of the principal investigator and interdisciplinary teams, up to the spacecraft, and down again for the analysis of the measurements and interpretation of the scientific results. These scientific results drive to new and more elaborated scientific requests, which are used as feedback to the planning cycle, closing the circle. Special attention is given here to describe the implementation and development of the data pipeline for the VIRTIS instrument onboard Venus Express. During the research program, both the raw data generation pipeline and the data calibration pipeline were developed and automated in order to produce the final raw and calibrated data products from the input telemetry of the instrument. The final raw and calibrated products presented in this work are currently being used by the VIRTIS Science team for data analysis and are distributed to the whole scientific community via the Planetary Science Archive. More than 20,000 raw data files and 10,000 calibrated products have already been generated after almost 4 years of mission. In the final part of the Thesis, we will also present some high level data processing methods developed for the Mapping channel of the VIRTIS instrument. These methods have been implemented for the generation of high level global maps of measured radiance over the whole planet, which can then be used for the understanding of the global dynamics and morphology of the Venusian atmosphere. This method is currently being used to compare different emissions probing at different altitudes from the low cloud layers up to the upper mesosphere, by using the averaged projected values of radiance observed by the instrument, such as the near infrared windows at 1.7 μm and 2.3μm, the thermal region at 3.8μm and 5μm plus the analysis of particular emissions in the night and day side of the planet. This research has been undertaken under guidance and supervision of Giuseppe Piccioni, VIRTIS co-Principal Investigator, with support of the entire VIRTIS technical and scientific team, in particular of the Archiving team in Paris (LESIA-Meudon). The work has also been done in close collaboration with the Science and Mission Operations Centres in Madrid and Darmstadt (European Space Agency), the EGSE software developer (Techno Systems), the manufacturer of the VIRTIS instrument (Galileo Avionica) and the developer of the VIRTIS onboard software (DLR Berlin). The outcome of the technical and scientific work presented in this thesis is currently being used by the VIRTIS team to continue the investigations on the Venusian atmosphere and plan new scientific observations to improve the overall knowledge of the solar system. At the end of this document we show some of the many technical and scientific contributions, which have already been published in several international journals and conferences, and some articles of the European Space Agency used for public outreach.

Rapid Processing of Radio Interferometer Data for Transient Surveys

NASA Astrophysics Data System (ADS)

Bourke, S.; Mooley, K.; Hallinan, G.

2014-05-01

We report on a software infrastructure and pipeline developed to process large radio interferometer datasets. The pipeline is implemented using a radical redesign of the AIPS processing model. An infrastructure we have named AIPSlite is used to spawn, at runtime, minimal AIPS environments across a cluster. The pipeline then distributes and processes its data in parallel. The system is entirely free of the traditional AIPS distribution and is self configuring at runtime. This software has so far been used to process a EVLA Stripe 82 transient survey, the data for the JVLA-COSMOS project, and has been used to process most of the EVLA L-Band data archive imaging each integration to search for short duration transients.

Research &Discover: A Pipeline of the Next Generation of Earth System Scientists

NASA Astrophysics Data System (ADS)

Hurtt, G. C.; Einaudi, F.; Moore, B.; Salomonson, V.; Campbell, J.

2006-12-01

In 2002, the University of New Hampshire (UNH) and NASA Goddard Space Flight Center (GSFC) started the educational initiative Research &Discover with the goals to: (i) recruit outstanding young scientists into research careers in Earth science and Earth remote sensing (broadly defined), and (ii) support Earth science graduate students enrolled at UNH through a program of collaborative partnerships with GSFC scientists and UNH faculty. To meet these goals, the program consists of a linked set of educational opportunities that begins with a paid summer research internship at UNH for students following their Junior year of college, and is followed by a second paid summer internship at GSFC for students following their Senior year of college. These summer internships are then followed by two-year fellowship opportunities at UNH for graduate studies jointly supervised by UNH faculty and GSFC scientists. After 5 years of implementation, the program has awarded summer research internships to 22 students, and graduate research fellowships to 6 students. These students have produced more than 78 scientific research presentations, 5 undergraduate theses, 2 Masters theses, and 4 peer-reviewed publications. More than 80% of alums are actively pursuing careers in Earth sciences now. In the process, the program has engaged 19 faculty from UNH and 15 scientists from GSFC as advisors/mentors. New collaborations between these scientists have resulted in new joint research proposals, and the development, delivery, and assessment of a new course in Earth System Science at UNH. Research &Discover represents an educational model of collaboration between a national lab and university to create a pipeline of the next generation of Earth system scientists.

Study of sleeper’s impact on the deep-water pipeline lateral global buckling

NASA Astrophysics Data System (ADS)

Liu, Wenbin; Li, Bin

2017-08-01

Pipelines are the most important transportation way for offshore oil and gas, and the lateral buckling is the main global buckling form for deep-water pipelines. The sleeper is an economic and efficient device to trigger the lateral buckling in preset location. This paper analyzed the lateral buckling features for on-bottom pipeline and pipeline with sleeper. The stress and strain variation during buckling process is shown to reveal the impact of sleeper on buckling.

A review of bioinformatic methods for forensic DNA analyses.

PubMed

Liu, Yao-Yuan; Harbison, SallyAnn

2018-03-01

Short tandem repeats, single nucleotide polymorphisms, and whole mitochondrial analyses are three classes of markers which will play an important role in the future of forensic DNA typing. The arrival of massively parallel sequencing platforms in forensic science reveals new information such as insights into the complexity and variability of the markers that were previously unseen, along with amounts of data too immense for analyses by manual means. Along with the sequencing chemistries employed, bioinformatic methods are required to process and interpret this new and extensive data. As more is learnt about the use of these new technologies for forensic applications, development and standardization of efficient, favourable tools for each stage of data processing is being carried out, and faster, more accurate methods that improve on the original approaches have been developed. As forensic laboratories search for the optimal pipeline of tools, sequencer manufacturers have incorporated pipelines into sequencer software to make analyses convenient. This review explores the current state of bioinformatic methods and tools used for the analyses of forensic markers sequenced on the massively parallel sequencing (MPS) platforms currently most widely used. Copyright © 2017 Elsevier B.V. All rights reserved.

Improving Graduate Education to Support a Branching Career Pipeline: Recommendations Based on a Survey of Doctoral Students in the Basic Biomedical Sciences

PubMed Central

Fuhrmann, C. N.; Halme, D. G.; O’Sullivan, P. S.; Lindstaedt, B.

2011-01-01

Today's doctoral programs continue to prepare students for a traditional academic career path despite the inadequate supply of research-focused faculty positions. We advocate for a broader doctoral curriculum that prepares trainees for a wide range of science-related career paths. In support of this argument, we describe data from our survey of doctoral students in the basic biomedical sciences at University of California, San Francisco (UCSF). Midway through graduate training, UCSF students are already considering a broad range of career options, with one-third intending to pursue a non–research career path. To better support this branching career pipeline, we recommend that national standards for training and mentoring include emphasis on career planning and professional skills development to ensure the success of PhD-level scientists as they contribute to a broadly defined global scientific enterprise. PMID:21885820

Improving graduate education to support a branching career pipeline: recommendations based on a survey of doctoral students in the basic biomedical sciences.

PubMed

Fuhrmann, C N; Halme, D G; O'Sullivan, P S; Lindstaedt, B

2011-01-01

Today's doctoral programs continue to prepare students for a traditional academic career path despite the inadequate supply of research-focused faculty positions. We advocate for a broader doctoral curriculum that prepares trainees for a wide range of science-related career paths. In support of this argument, we describe data from our survey of doctoral students in the basic biomedical sciences at University of California, San Francisco (UCSF). Midway through graduate training, UCSF students are already considering a broad range of career options, with one-third intending to pursue a non-research career path. To better support this branching career pipeline, we recommend that national standards for training and mentoring include emphasis on career planning and professional skills development to ensure the success of PhD-level scientists as they contribute to a broadly defined global scientific enterprise.

Identifying Comprehensive Public Institutions that Develop Minority Scientists

ERIC Educational Resources Information Center

Hubbard, Steven M.; Stage, Frances K.

2010-01-01

The ratio of minority students earning baccalaureate degrees in science, technology, engineering, and mathematics (STEM) continues to decline. In the past three decades, research on students of color in the mathematics/science pipeline has rapidly expanded. Many government agencies and nonprofit organizations have supported research and…

Diversifying the STEM Pipeline: The Model Replication Institutions Program

ERIC Educational Resources Information Center

Cullinane, Jenna

2009-01-01

In 2006, the National Science Foundation (NSF) began funding the Model Replication Institutions (MRI) program, which sought to improve the quality, availability, and diversity of science, technology, engineering, and mathematics (STEM) education. Faced with pressing national priorities in the STEM fields and chronic gaps in postsecondary…

The 50th Anniversary of Brown v. Board of Education: Continued Impacts on Minority Life Science Education

ERIC Educational Resources Information Center

Ricks, Irelene

2004-01-01

This article provides a brief history of affirmative action in the United States. The author describes the impact of the "Brown v. Board of Education" on minority life science education. She also discusses how The American Society for Cell Biology (ASCB) Minorities Affairs Committee (MAC) can improve the minority science pipeline.…

Women and Minorities in the Science, Mathematics and Engineering Pipeline. ERIC Digest.

ERIC Educational Resources Information Center

Chang, June C.

Over the next ten years, the United States will need to train an additional 1.9 million workers in the sciences. Increased participation of women and minorities is essential in meeting the projected need for Science, Mathematics, and Engineering (SME) workers. Women, who received 56% of B.A.'s overall, comprised 37% of the SME bachelor degrees…

Integration of a neuroimaging processing pipeline into a pan-canadian computing grid

NASA Astrophysics Data System (ADS)

Lavoie-Courchesne, S.; Rioux, P.; Chouinard-Decorte, F.; Sherif, T.; Rousseau, M.-E.; Das, S.; Adalat, R.; Doyon, J.; Craddock, C.; Margulies, D.; Chu, C.; Lyttelton, O.; Evans, A. C.; Bellec, P.

2012-02-01

The ethos of the neuroimaging field is quickly moving towards the open sharing of resources, including both imaging databases and processing tools. As a neuroimaging database represents a large volume of datasets and as neuroimaging processing pipelines are composed of heterogeneous, computationally intensive tools, such open sharing raises specific computational challenges. This motivates the design of novel dedicated computing infrastructures. This paper describes an interface between PSOM, a code-oriented pipeline development framework, and CBRAIN, a web-oriented platform for grid computing. This interface was used to integrate a PSOM-compliant pipeline for preprocessing of structural and functional magnetic resonance imaging into CBRAIN. We further tested the capacity of our infrastructure to handle a real large-scale project. A neuroimaging database including close to 1000 subjects was preprocessed using our interface and publicly released to help the participants of the ADHD-200 international competition. This successful experiment demonstrated that our integrated grid-computing platform is a powerful solution for high-throughput pipeline analysis in the field of neuroimaging.

Bioinformatic pipelines in Python with Leaf

PubMed Central

2013-01-01

Background An incremental, loosely planned development approach is often used in bioinformatic studies when dealing with custom data analysis in a rapidly changing environment. Unfortunately, the lack of a rigorous software structuring can undermine the maintainability, communicability and replicability of the process. To ameliorate this problem we propose the Leaf system, the aim of which is to seamlessly introduce the pipeline formality on top of a dynamical development process with minimum overhead for the programmer, thus providing a simple layer of software structuring. Results Leaf includes a formal language for the definition of pipelines with code that can be transparently inserted into the user’s Python code. Its syntax is designed to visually highlight dependencies in the pipeline structure it defines. While encouraging the developer to think in terms of bioinformatic pipelines, Leaf supports a number of automated features including data and session persistence, consistency checks between steps of the analysis, processing optimization and publication of the analytic protocol in the form of a hypertext. Conclusions Leaf offers a powerful balance between plan-driven and change-driven development environments in the design, management and communication of bioinformatic pipelines. Its unique features make it a valuable alternative to other related tools. PMID:23786315

The PREP pipeline: standardized preprocessing for large-scale EEG analysis

PubMed Central

Bigdely-Shamlo, Nima; Mullen, Tim; Kothe, Christian; Su, Kyung-Min; Robbins, Kay A.

2015-01-01

The technology to collect brain imaging and physiological measures has become portable and ubiquitous, opening the possibility of large-scale analysis of real-world human imaging. By its nature, such data is large and complex, making automated processing essential. This paper shows how lack of attention to the very early stages of an EEG preprocessing pipeline can reduce the signal-to-noise ratio and introduce unwanted artifacts into the data, particularly for computations done in single precision. We demonstrate that ordinary average referencing improves the signal-to-noise ratio, but that noisy channels can contaminate the results. We also show that identification of noisy channels depends on the reference and examine the complex interaction of filtering, noisy channel identification, and referencing. We introduce a multi-stage robust referencing scheme to deal with the noisy channel-reference interaction. We propose a standardized early-stage EEG processing pipeline (PREP) and discuss the application of the pipeline to more than 600 EEG datasets. The pipeline includes an automatically generated report for each dataset processed. Users can download the PREP pipeline as a freely available MATLAB library from http://eegstudy.org/prepcode. PMID:26150785

A Framework for Propagation of Uncertainties in the Kepler Data Analysis Pipeline

NASA Technical Reports Server (NTRS)

Clarke, Bruce D.; Allen, Christopher; Bryson, Stephen T.; Caldwell, Douglas A.; Chandrasekaran, Hema; Cote, Miles T.; Girouard, Forrest; Jenkins, Jon M.; Klaus, Todd C.; Li, Jie;

Remaining Sites Verification Package for the 100-F-26:12, 1.8-m (72-in.) Main Process Sewer Pipeline, Waste Site Reclassification Form 2007-034

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

J. M. Capron

2008-04-29

The 100-F-26:12 waste site was an approximately 308-m-long, 1.8-m-diameter east-west-trending reinforced concrete pipe that joined the North Process Sewer Pipelines (100-F-26:1) and the South Process Pipelines (100-F-26:4) with the 1.8-m reactor cooling water effluent pipeline (100-F-19). In accordance with this evaluation, the verification sampling results support a reclassification of this site to Interim Closed Out. The results of verification sampling show that residual contaminant concentrations do not preclude any future uses and allow for unrestricted use of shallow zone soils. The results also demonstrate that residual contaminant concentrations are protective of groundwater and the Columbia River.

From Pipelines to Tasting Lemonade: Reconceptualizing College Access

ERIC Educational Resources Information Center

Pitcher, Erich N.; Shahjahan, Riyad A.

2017-01-01

Pipeline metaphors are ubiquitous in theorizing and interpreting college access processes. In this conceptual article, we explore how a lemonade metaphor can open new possibilities to reimagining higher education access and going processes. We argue that using food metaphors, particularly the processes of mixing, tasting, and digesting lemonade,…

Diversifying the STEM Pipeline: Recommendations from the Model Replication Institutions Program

ERIC Educational Resources Information Center

Institute for Higher Education Policy, 2010

2010-01-01

Launched in 2006 to address issues of national competitiveness and equity in science, technology, engineering, and mathematics (STEM) fields, the National Science Foundation-funded Model Replication Institutions (MRI) program sought to improve the quality, availability, and diversity of STEM education. The project offered technical assistance to…

Filling the Educator Pipeline: Recruiting Male Family and Consumer Sciences Teachers

ERIC Educational Resources Information Center

Godfrey, Roxie V.; Manis, Kerry T.

2017-01-01

To encourage males to enter the teaching field, specifically in family and consumer sciences (FCS), FCS professionals should participate in recruitment initiatives aimed at males. Administrators, teacher educators, career counselors, and FCS teachers can play a significant role in this comprehensive and systematic effort. This paper adopts the…

Diversifying the STEM Pipeline

ERIC Educational Resources Information Center

Boelter, Christina; Link, Tanja C.; Perry, Brea L.; Leukefeld, Carl

2015-01-01

Middle school students from low-income and minority backgrounds (n = 166) were targeted to participate in a 2-year, intensive, hands-on science and technology intervention to increase their interest in biomedical and health sciences. Qualitative student responses collected during the 2nd year of participation revealed positive attitudes toward the…

The Chandra Source Catalog 2.0: Data Processing Pipelines

NASA Astrophysics Data System (ADS)

Miller, Joseph; Allen, Christopher E.; Budynkiewicz, Jamie A.; Gibbs, Danny G., II; Paxson, Charles; Chen, Judy C.; Anderson, Craig S.; Burke, Douglas; Civano, Francesca Maria; D'Abrusco, Raffaele; Doe, Stephen M.; Evans, Ian N.; Evans, Janet D.; Fabbiano, Giuseppina; Glotfelty, Kenny J.; Graessle, Dale E.; Grier, John D.; Hain, Roger; Hall, Diane M.; Harbo, Peter N.; Houck, John C.; Lauer, Jennifer L.; Laurino, Omar; Lee, Nicholas P.; Martínez-Galarza, Juan Rafael; McCollough, Michael L.; McDowell, Jonathan C.; McLaughlin, Warren; Morgan, Douglas L.; Mossman, Amy E.; Nguyen, Dan T.; Nichols, Joy S.; Nowak, Michael A.; Plummer, David A.; Primini, Francis Anthony; Rots, Arnold H.; Siemiginowska, Aneta; Sundheim, Beth A.; Tibbetts, Michael; Van Stone, David W.; Zografou, Panagoula

2018-01-01

With the construction of the Second Chandra Source Catalog (CSC2.0), came new requirements and new techniques to create a software system that can process 10,000 observations and identify nearly 320,000 point and compact X-ray sources. A new series of processing pipelines have been developed to allow for deeper more complete exploration of the Chanda observations. In CSC1.0 there were 4 general pipelines, whereas in CSC2.0 there are 20 data processing pipelines that have been organized into 3 distinct phases of operation - detection, master matching and source property characterization.With CSC2.0, observations within one arcminute of each other are stacked before searching for sources. The detection phase of processing combines the data, adjusts for shifts in fine astrometry, detects sources, and assesses the likelihood that sources are real. During the master source phase, detections across stacks of observations are analyzed for coverage of the same source to produce a master source. Finally, in the source property phase, each source is characterized with aperture photometry, spectrometry, variability and other properties at theobservation, stack and master levels over several energy bands.We present how these pipelines were constructed and the challenges we faced in how we processed data ranging from virtually no counts to millions of counts, how pipelines were tuned to work optimally on a computational cluster, and how we ensure the data produced was correct through various quality assurance steps.This work has been supported by NASA under contract NAS 8-03060 to the Smithsonian Astrophysical Observatory for operation of the Chandra X-ray Center.

Meta!Blast computer game: a pipeline from science to 3D art to education

NASA Astrophysics Data System (ADS)

Schneller, William; Campbell, P. J.; Bassham, Diane; Wurtele, Eve Syrkin

2012-03-01

Meta!Blast (http://www.metablast.org) is designed to address the challenges students often encounter in understanding cell and metabolic biology. Developed by faculty and students in biology, biochemistry, computer science, game design, pedagogy, art and story, Meta!Blast is being created using Maya (http://usa.autodesk.com/maya/) and the Unity 3D (http://unity3d.com/) game engine, for Macs and PCs in classrooms; it has also been exhibited in an immersive environment. Here, we describe the pipeline from protein structural data and holographic information to art to the threedimensional (3D) environment to the game engine, by which we provide a publicly-available interactive 3D cellular world that mimics a photosynthetic plant cell.

Improved coal-slurry pipeline

NASA Technical Reports Server (NTRS)

Dowler, W. L.

1979-01-01

High strength steel pipeline carries hot mixture of powdered coal and coal derived oil to electric-power-generating station. Slurry is processed along way to remove sulfur, ash, and nitrogen and to recycle part of oil. System eliminates hazards and limitations associated with anticipated coal/water-slurry pipelines.

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

Hansen, E.A.; Smed, P.F.; Bryndum, M.B.

The paper describes the numerical program, PIPESIN, that simulates the behavior of a pipeline placed on an erodible seabed. PIPEline Seabed INteraction from installation until a stable pipeline seabed configuration has occurred is simulated in the time domain including all important physical processes. The program is the result of the joint research project, ``Free Span Development and Self-lowering of Offshore Pipelines`` sponsored by EU and a group of companies and carried out by the Danish Hydraulic Institute and Delft Hydraulics. The basic modules of PIPESIN are described. The description of the scouring processes has been based on and verified throughmore » physical model tests carried out as part of the research project. The program simulates a section of the pipeline (typically 500 m) in the time domain, the main input being time series of the waves and current. The main results include predictions of the onset of free spans, their length distribution, their variation in time, and the lowering of the pipeline as function of time.« less

Lateral instability of high temperature pipelines, the 20-in. Sleipner Vest pipeline

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

Saevik, S.; Levold, E.; Johnsen, O.K.

1996-12-01

The present paper addresses methods to control snaking behavior of high temperature pipelines resting on a flat sea bed. A case study is presented based on the detail engineering of the 12.5 km long 20 inch gas pipeline connecting the Sleipner Vest wellhead platform to the Sleipner T processing platform in the North Sea. The study includes screening and evaluation of alternative expansion control methods, ending up with a recommended method. The methodology and philosophy, used as basis to ensure sufficient structural strength throughout the lifetime of the pipeline, are thereafter presented. The results show that in order to findmore » the optimum technical solution to control snaking behavior, many aspects need to be considered such as process requirements, allowable strain, hydrodynamic stability, vertical profile, pipelay installation and trawlboard loading. It is concluded that by proper consideration of all the above aspects, the high temperature pipeline can be designed to obtain sufficient safety level.« less

Enhancement of Hydrodynamic Processes in Oil Pipelines Considering Rheologically Complex High-Viscosity Oils

NASA Astrophysics Data System (ADS)

Konakhina, I. A.; Khusnutdinova, E. M.; Khamidullina, G. R.; Khamidullina, A. F.

2016-06-01

This paper describes a mathematical model of flow-related hydrodynamic processes for rheologically complex high-viscosity bitumen oil and oil-water suspensions and presents methods to improve the design and performance of oil pipelines.

Natural language processing pipelines to annotate BioC collections with an application to the NCBI disease corpus

PubMed Central

Comeau, Donald C.; Liu, Haibin; Islamaj Doğan, Rezarta; Wilbur, W. John

2014-01-01

BioC is a new format and associated code libraries for sharing text and annotations. We have implemented BioC natural language preprocessing pipelines in two popular programming languages: C++ and Java. The current implementations interface with the well-known MedPost and Stanford natural language processing tool sets. The pipeline functionality includes sentence segmentation, tokenization, part-of-speech tagging, lemmatization and sentence parsing. These pipelines can be easily integrated along with other BioC programs into any BioC compliant text mining systems. As an application, we converted the NCBI disease corpus to BioC format, and the pipelines have successfully run on this corpus to demonstrate their functionality. Code and data can be downloaded from http://bioc.sourceforge.net. Database URL: http://bioc.sourceforge.net PMID:24935050

The Hubble Catalog of Variables

NASA Astrophysics Data System (ADS)

Gavras, P.; Bonanos, A. Z.; Bellas-Velidis, I.; Charmandaris, V.; Georgantopoulos, I.; Hatzidimitriou, D.; Kakaletris, G.; Karampelas, A.; Laskaris, N.; Lennon, D. J.; Moretti, M. I.; Pouliasis, E.; Sokolovsky, K.; Spetsieri, Z. T.; Tsinganos, K.; Whitmore, B. C.; Yang, M.

2017-06-01

The Hubble Catalog of Variables (HCV) is a 3 year ESA funded project that aims to develop a set of algorithms to identify variables among the sources included in the Hubble Source Catalog (HSC) and produce the HCV. We will process all HSC sources with more than a predefined number of measurements in a single filter/instrument combination and compute a range of lightcurve features to determine the variability status of each source. At the end of the project, the first release of the Hubble Catalog of Variables will be made available at the Mikulski Archive for Space Telescopes (MAST) and the ESA Science Archives. The variability detection pipeline will be implemented at the Space Telescope Science Institute (STScI) so that updated versions of the HCV may be created following the future releases of the HSC.

Why students drop out of the pipeline to health professions careers: a follow-up of gifted minority high school students.

PubMed

Thurmond, V B; Cregler, L L

1999-04-01

To track gifted underrepresented minority (URM) students who entered the pipeline to health professional school when they were in high school and to determine whether and why students left the pipeline to enter other professions. A questionnaire was mailed to 162 students who had participated in the Student Educational Enrichment Program (SEEP) in health sciences at the Medical College of Georgia between 1984 and 1991; 123 (75%) responded. Students in the study population had higher graduation rates than the average state or national student. Fifty-nine (48%) of the students had entered health care careers; 98% had stated that intention when they were in high school. Although some of the students stated trouble with course work and GPA as reasons for their decisions to change career tracks, many students said that their interests in non-medical careers had been fostered by mentors or by opportunities to serve internships. Early intervention is important to retaining students in a pipeline that leads to a health care career. Summer programs are successful, but may not be enough to help students with difficult science courses in college, especially chemistry. However, another important conclusion is that much more needs to be done to help students find mentors with whom they can develop relationships and to give them opportunities to work in health care settings.

Integration and Visualization of Translational Medicine Data for Better Understanding of Human Diseases

PubMed Central

Satagopam, Venkata; Gu, Wei; Eifes, Serge; Gawron, Piotr; Ostaszewski, Marek; Gebel, Stephan; Barbosa-Silva, Adriano; Balling, Rudi; Schneider, Reinhard

2016-01-01

Abstract Translational medicine is a domain turning results of basic life science research into new tools and methods in a clinical environment, for example, as new diagnostics or therapies. Nowadays, the process of translation is supported by large amounts of heterogeneous data ranging from medical data to a whole range of -omics data. It is not only a great opportunity but also a great challenge, as translational medicine big data is difficult to integrate and analyze, and requires the involvement of biomedical experts for the data processing. We show here that visualization and interoperable workflows, combining multiple complex steps, can address at least parts of the challenge. In this article, we present an integrated workflow for exploring, analysis, and interpretation of translational medicine data in the context of human health. Three Web services—tranSMART, a Galaxy Server, and a MINERVA platform—are combined into one big data pipeline. Native visualization capabilities enable the biomedical experts to get a comprehensive overview and control over separate steps of the workflow. The capabilities of tranSMART enable a flexible filtering of multidimensional integrated data sets to create subsets suitable for downstream processing. A Galaxy Server offers visually aided construction of analytical pipelines, with the use of existing or custom components. A MINERVA platform supports the exploration of health and disease-related mechanisms in a contextualized analytical visualization system. We demonstrate the utility of our workflow by illustrating its subsequent steps using an existing data set, for which we propose a filtering scheme, an analytical pipeline, and a corresponding visualization of analytical results. The workflow is available as a sandbox environment, where readers can work with the described setup themselves. Overall, our work shows how visualization and interfacing of big data processing services facilitate exploration, analysis, and interpretation of translational medicine data. PMID:27441714

Science Achievement Gaps by Gender and Race/Ethnicity in Elementary and Middle School: Trends and Predictors

ERIC Educational Resources Information Center

Quinn, David M.; Cooc, North

2015-01-01

Research on science achievement disparities by gender and race/ethnicity often neglects the beginning of the pipeline in the early grades. We address this limitation using nationally representative data following students from Grades 3 to 8. We find that the Black-White science test score gap (-1.07 SD in Grade 3) remains stable over these years,…

77 FR 58217 - Notice of Delays in Processing of Special Permits Applications

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-19

... DEPARTMENT OF TRANSPORTATION Pipeline and Hazardous Materials Safety Administration Notice of Delays in Processing of Special Permits Applications AGENCY: Pipeline and Hazardous Materials Safety.... FOR FURTHER INFORMATION CONTACT: Ryan Paquet, Director, Office of Hazardous Materials Special Permits...

77 FR 64846 - Notice of Delays in Processing of Special Permits Applications

Federal Register 2010, 2011, 2012, 2013, 2014

2012-10-23

... DEPARTMENT OF TRANSPORTATION Pipeline and Hazardous Materials Safety Administration Notice of Delays in Processing of Special Permits Applications AGENCY: Pipeline and Hazardous Materials Safety.... FOR FURTHER INFORMATION CONTACT: Ryan Paquet, Director, Office of Hazardous Materials Special Permits...

HiCUP: pipeline for mapping and processing Hi-C data.

PubMed

Wingett, Steven; Ewels, Philip; Furlan-Magaril, Mayra; Nagano, Takashi; Schoenfelder, Stefan; Fraser, Peter; Andrews, Simon

2015-01-01

HiCUP is a pipeline for processing sequence data generated by Hi-C and Capture Hi-C (CHi-C) experiments, which are techniques used to investigate three-dimensional genomic organisation. The pipeline maps data to a specified reference genome and removes artefacts that would otherwise hinder subsequent analysis. HiCUP also produces an easy-to-interpret yet detailed quality control (QC) report that assists in refining experimental protocols for future studies. The software is freely available and has already been used for processing Hi-C and CHi-C data in several recently published peer-reviewed studies.

To Grab and To Hold: Cultivating communal goals to overcome cultural and structural barriers in first generation college students' science interest

PubMed Central

Allen, Jill M.; Muragishi, Gregg A.; Smith, Jessi L.; Thoman, Dustin B.; Brown, Elizabeth R.

2015-01-01

Homogeneity within science limits creativity and discovery, and can feed into a perpetuating cycle of underrepresentation. From enhancing social justice to alleviating health and economic disadvantages, broadening participation in science is imperative. We focus here on first-generation students (FGS) and identify factors which grab and hold science interest among this underrepresented group. Might the culture and norms within science unintentionally limit FGS' participation? We argue that two distinct aspects of communal goals contribute to FGS' underrepresentation at different stages of the STEM pipeline: cultural perceptions of science as uncommunal (little emphasis on prosocial behavior and collaboration) and the uncommunal structure of STEM graduate education and training. Across 2 studies we investigated factors that catch (Study 1) and hold (Study 2) FGS' science interest. In Study 1, we find only when FGS believe that working in science will allow them to fulfill prosocial communal purpose goals are they more intrinsically interested in science. Yet, later in the pipeline science education devalues prosocial communal goals creating a structural mobility barrier among FGS. Study 2 found that FGS generally want to stay close to home instead of relocating to pursue a graduate education. For FGS (versus continuing-generation students), higher prosocial communal goal orientation significantly predicted lower residential mobility. We discuss implications for interventions to counteract the uncommunal science education and training culture to help improve access to FGS and other similarly situated underrepresented populations. PMID:26807431

African-American males in computer science---Examining the pipeline for clogs

NASA Astrophysics Data System (ADS)

Stone, Daryl Bryant

The literature on African-American males (AAM) begins with a statement to the effect that "Today young Black men are more likely to be killed or sent to prison than to graduate from college." Why are the numbers of African-American male college graduates decreasing? Why are those enrolled in college not majoring in the science, technology, engineering, and mathematics (STEM) disciplines? This research explored why African-American males are not filling the well-recognized industry need for Computer Scientist/Technologists by choosing college tracks to these careers. The literature on STEM disciplines focuses largely on women in STEM, as opposed to minorities, and within minorities, there is a noticeable research gap in addressing the needs and opportunities available to African-American males. The primary goal of this study was therefore to examine the computer science "pipeline" from the African-American male perspective. The method included a "Computer Science Degree Self-Efficacy Scale" be distributed to five groups of African-American male students, to include: (1) fourth graders, (2) eighth graders, (3) eleventh graders, (4) underclass undergraduate computer science majors, and (5) upperclass undergraduate computer science majors. In addition to a 30-question self-efficacy test, subjects from each group were asked to participate in a group discussion about "African-American males in computer science." The audio record of each group meeting provides qualitative data for the study. The hypotheses include the following: (1) There is no significant difference in "Computer Science Degree" self-efficacy between fourth and eighth graders. (2) There is no significant difference in "Computer Science Degree" self-efficacy between eighth and eleventh graders. (3) There is no significant difference in "Computer Science Degree" self-efficacy between eleventh graders and lower-level computer science majors. (4) There is no significant difference in "Computer Science Degree" self-efficacy between lower-level computer science majors and upper-level computer science majors. (5) There is no significant difference in "Computer Science Degree" self-efficacy between each of the five groups of students. Finally, the researcher selected African-American male students attending six primary schools, including the predominately African-American elementary, middle and high school that the researcher attended during his own academic career. Additionally, a racially mixed elementary, middle and high school was selected from the same county in Maryland. Bowie State University provided both the underclass and upperclass computer science majors surveyed in this study. Of the five hypotheses, the sample provided enough evidence to support the claim that there are significant differences in the "Computer Science Degree" self-efficacy between each of the five groups of students. ANOVA analysis by question and total self-efficacy scores provided more results of statistical significance. Additionally, factor analysis and review of the qualitative data provide more insightful results. Overall, the data suggest 'a clog' may exist in the middle school level and students attending racially mixed schools were more confident in their computer, math and science skills. African-American males admit to spending lots of time on social networking websites and emailing, but are 'dis-aware' of the skills and knowledge needed to study in the computing disciplines. The majority of the subjects knew little, if any, AAMs in the 'computing discipline pipeline'. The collegian African-American males, in this study, agree that computer programming is a difficult area and serves as a 'major clog in the pipeline'.

Science Gateways, Scientific Workflows and Open Community Software

NASA Astrophysics Data System (ADS)

Pierce, M. E.; Marru, S.

2014-12-01

Science gateways and scientific workflows occupy different ends of the spectrum of user-focused cyberinfrastructure. Gateways, sometimes called science portals, provide a way for enabling large numbers of users to take advantage of advanced computing resources (supercomputers, advanced storage systems, science clouds) by providing Web and desktop interfaces and supporting services. Scientific workflows, at the other end of the spectrum, support advanced usage of cyberinfrastructure that enable "power users" to undertake computational experiments that are not easily done through the usual mechanisms (managing simulations across multiple sites, for example). Despite these different target communities, gateways and workflows share many similarities and can potentially be accommodated by the same software system. For example, pipelines to process InSAR imagery sets or to datamine GPS time series data are workflows. The results and the ability to make downstream products may be made available through a gateway, and power users may want to provide their own custom pipelines. In this abstract, we discuss our efforts to build an open source software system, Apache Airavata, that can accommodate both gateway and workflow use cases. Our approach is general, and we have applied the software to problems in a number of scientific domains. In this talk, we discuss our applications to usage scenarios specific to earth science, focusing on earthquake physics examples drawn from the QuakSim.org and GeoGateway.org efforts. We also examine the role of the Apache Software Foundation's open community model as a way to build up common commmunity codes that do not depend upon a single "owner" to sustain. Pushing beyond open source software, we also see the need to provide gateways and workflow systems as cloud services. These services centralize operations, provide well-defined programming interfaces, scale elastically, and have global-scale fault tolerance. We discuss our work providing Apache Airavata as a hosted service to provide these features.

The bachelor’s to Ph.D. STEM pipeline no longer leaks more women than men: a 30-year analysis

PubMed Central

Miller, David I.; Wai, Jonathan

2015-01-01

For decades, research and public discourse about gender and science have often assumed that women are more likely than men to “leak” from the science pipeline at multiple points after entering college. We used retrospective longitudinal methods to investigate how accurately this “leaky pipeline” metaphor has described the bachelor’s to Ph.D. transition in science, technology, engineering, and mathematics (STEM) fields in the U.S. since the 1970s. Among STEM bachelor’s degree earners in the 1970s and 1980s, women were less likely than men to later earn a STEM Ph.D. However, this gender difference closed in the 1990s. Qualitatively similar trends were found across STEM disciplines. The leaky pipeline metaphor therefore partially explains historical gender differences in the U.S., but no longer describes current gender differences in the bachelor’s to Ph.D. transition in STEM. The results help constrain theories about women’s underrepresentation in STEM. Overall, these results point to the need to understand gender differences at the bachelor’s level and below to understand women’s representation in STEM at the Ph.D. level and above. Consistent with trends at the bachelor’s level, women’s representation at the Ph.D. level has been recently declining for the first time in over 40 years. PMID:25741293

Data Validation in the Kepler Science Operations Center Pipeline

NASA Technical Reports Server (NTRS)

Wu, Hayley; Twicken, Joseph D.; Tenenbaum, Peter; Clarke, Bruce D.; Li, Jie; Quintana, Elisa V.; Allen, Christopher; Chandrasekaran, Hema; Jenkins, Jon M.; Caldwell, Douglas A.;

Bridging EO Research, Operations and Collaborative Learning

NASA Astrophysics Data System (ADS)

Scarth, Peter

2016-04-01

Building flexible and responsive processing and delivery systems is key to getting EO information used by researchers, policy agents and the public. There are typically three distinct processes we tackle to get product uptake: undertake research, operationalise the validated research, and deliver information and garner feedback in an appropriate way. In many cases however, the gaps between these process elements are large and lead to poor outcomes. Good research may be "lost" and not adopted, there may be resistance to uptake by government or NGOs of significantly better operational products based on EO data, and lack of accessibility means that there is no use of interactive science outputs to improve cross disciplinary science or to start a dialog with citizens. So one of the the most important tasks, if we wish to have broad uptake of EO information and accelerate further research, is to link these processes together in a formal but flexible way. One of the ways to operationalize research output is by building a platform that can take research code and scale it across much larger areas. In remote sensing, this is typically a system that has access to current and historical corrected imagery with a processing pipeline built over the top. To reduce the demand on high level scientific programmers and allowing cross disciplinary researchers to hack and play and refine, this pipeline needs to be easy to use, collaborative and link to existing tools to encourage code experimentation and reuse. It is also critical to have efficient, tight integration with information delivery and extension components so that the science relevant to your user is available quickly and efficiently. The rapid expansion of open data licensing has helped this process, but building top-down web portals and tools without flexibility and regard for end user needs has limited the use of EO information in many areas. This research reports on the operalization of a scale independent time series query API that allows the interrogation of the entire current processed Australian Landsat archive in web time. The system containerises data interrogation and time series tasks to allow easy scaling and expansion and is currently in operational use by several land management portals across the country to deliver EO land information products to government agents, NGOs and individual farmers. Plans to ingest and process the Sentinel 2 archive are well underway, and the logistics of scaling this globally using an open source project based on the Earth Engine Platform will be discussed.

Natural language processing pipelines to annotate BioC collections with an application to the NCBI disease corpus.

PubMed

Comeau, Donald C; Liu, Haibin; Islamaj Doğan, Rezarta; Wilbur, W John

2014-01-01

BioC is a new format and associated code libraries for sharing text and annotations. We have implemented BioC natural language preprocessing pipelines in two popular programming languages: C++ and Java. The current implementations interface with the well-known MedPost and Stanford natural language processing tool sets. The pipeline functionality includes sentence segmentation, tokenization, part-of-speech tagging, lemmatization and sentence parsing. These pipelines can be easily integrated along with other BioC programs into any BioC compliant text mining systems. As an application, we converted the NCBI disease corpus to BioC format, and the pipelines have successfully run on this corpus to demonstrate their functionality. Code and data can be downloaded from http://bioc.sourceforge.net. Database URL: http://bioc.sourceforge.net. © The Author(s) 2014. Published by Oxford University Press.

Scientists Reflect on Why They Chose to Study Science

ERIC Educational Resources Information Center

Venville, Grady; Rennie, Léonie; Hanbury, Colin; Longnecker, Nancy

2013-01-01

A concern commonly raised in literature and in media relates to the declining proportions of students who enter and remain in the "science pipeline", and whether many countries, including Australia and New Zealand, have enough budding scientists to fill research and industry positions in the coming years. In addition, there is concern…

Latinos in Science: Trends and Opportunities

ERIC Educational Resources Information Center

Rochin, Refugio I.; Mello, Stephen F.

2007-01-01

In U.S. coverage of leadership in science and engineering (S&E), Latinos are generally dismissed from consideration. The pipeline metaphor tends to ignore advances made by Latinos in completing doctoral degrees in S&E. New data suggest a better metaphor, the pyramid of higher education, for understanding the progress of Latinos in S&E. Questions…

A Pipeline to the Tenure Track

ERIC Educational Resources Information Center

Roach, Ronald

2009-01-01

Despite U.S. higher education facing a wave of retirements by older baby boomer and World War II-era born professors, there remain large pockets in the academic work force, such as life science faculties at research universities and humanities/social science faculties across all of academia, where tenure-track jobs are scarce and the market is…

The Equity Education. Fostering the Advancement of Women in the Sciences, Mathematics, and Engineering.

ERIC Educational Resources Information Center

Davis, Cinda-Sue; And Others

This volume includes 10 reports that present findings and recommendations for advancing women in science, mathematics and engineering. Critical issues facing women in these disciplines are addressed, including demographic myths and realities at various educational levels; the educational pipeline for girls and women; involvement in education and…

3D Visualization for Phoenix Mars Lander Science Operations

NASA Technical Reports Server (NTRS)

Edwards, Laurence; Keely, Leslie; Lees, David; Stoker, Carol

2012-01-01

Planetary surface exploration missions present considerable operational challenges in the form of substantial communication delays, limited communication windows, and limited communication bandwidth. A 3D visualization software was developed and delivered to the 2008 Phoenix Mars Lander (PML) mission. The components of the system include an interactive 3D visualization environment called Mercator, terrain reconstruction software called the Ames Stereo Pipeline, and a server providing distributed access to terrain models. The software was successfully utilized during the mission for science analysis, site understanding, and science operations activity planning. A terrain server was implemented that provided distribution of terrain models from a central repository to clients running the Mercator software. The Ames Stereo Pipeline generates accurate, high-resolution, texture-mapped, 3D terrain models from stereo image pairs. These terrain models can then be visualized within the Mercator environment. The central cross-cutting goal for these tools is to provide an easy-to-use, high-quality, full-featured visualization environment that enhances the mission science team s ability to develop low-risk productive science activity plans. In addition, for the Mercator and Viz visualization environments, extensibility and adaptability to different missions and application areas are key design goals.

Graduate Education for the Future: New Models and Methods for the Clinical and Translational Workforce

PubMed Central

Bennett, L. Michelle; Cicutto, Lisa; Gadlin, Howard; Moss, Marc; Tentler, John; Schoenbaum, Ellie

2015-01-01

Abstract This paper is the third in a five‐part series on the clinical and translational science educational pipeline, and it focuses on strategies for enhancing graduate research education to improve skills for interdisciplinary team science. Although some of the most cutting edge science takes place at the borders between disciplines, it is widely perceived that advancements in clinical and translational science are hindered by the “siloed” efforts of researchers who are comfortable working in their separate domains, and reluctant to stray from their own discipline when conducting research. Without appropriate preparation for career success as members and leaders of interdisciplinary teams, talented scientists may choose to remain siloed or to leave careers in clinical and translational science all together, weakening the pipeline and depleting the future biomedical research workforce. To address this threat, it is critical to begin at what is perhaps the most formative moment for academics: graduate training. This paper focuses on designs for graduate education, and contrasts the methods and outcomes from traditional educational approaches with those skills perceived as essential for the workforce of the future, including the capacity for research collaboration that crosses disciplinary boundaries. PMID:26643714

A Controlled Evaluation of a High School Biomedical Pipeline Program: Design and Methods

NASA Astrophysics Data System (ADS)

Winkleby, Marilyn A.; Ned, Judith; Ahn, David; Koehler, Alana; Fagliano, Kathleen; Crump, Casey

2014-02-01

Given limited funding for school-based science education, non-school-based programs have been developed at colleges and universities to increase the number of students entering science- and health-related careers and address critical workforce needs. However, few evaluations of such programs have been conducted. We report the design and methods of a controlled trial to evaluate the Stanford Medical Youth Science Program's Summer Residential Program (SRP), a 25-year-old university-based biomedical pipeline program. This 5-year matched cohort study uses an annual survey to assess educational and career outcomes among four cohorts of students who participate in the SRP and a matched comparison group of applicants who were not chosen to participate in the SRP. Matching on sociodemographic and academic background allows control for potential confounding. This design enables the testing of whether the SRP has an independent effect on educational- and career-related outcomes above and beyond the effects of other factors such as gender, ethnicity, socioeconomic background, and pre-intervention academic preparation. The results will help determine which curriculum components contribute most to successful outcomes and which students benefit most. After 4 years of follow-up, the results demonstrate high response rates from SRP participants and the comparison group with completion rates near 90 %, similar response rates by gender and ethnicity, and little attrition with each additional year of follow-up. This design and methods can potentially be replicated to evaluate and improve other biomedical pipeline programs, which are increasingly important for equipping more students for science- and health-related careers.

Navigating the science, technology, engineering, and mathematics pipeline: How social capital impacts the educational attainment of college-bound female students

NASA Astrophysics Data System (ADS)

Lee, Rebecca Elizabeth

Despite the proliferation of women in higher education and the workforce, they have yet to achieve parity with men in many of the science, technology, engineering, and math (STEM) majors and careers. The gap is even greater in the representation of women from lower socioeconomic backgrounds. This study examined pre-college intervention strategies provided by the University of Southern California's Math, Engineering, Science Achievement (MESA) program, as well as the relationships and experiences that contributed to the success of underrepresented female high school students in the STEM pipeline. A social capital framework provided the backdrop to the study. This qualitative study takes an ethnographic approach, incorporating 11 interviews, 42 hours of observation, and document analysis to address the research questions: How does involvement in the MESA program impact female students' decisions to pursue a mathematics or science major in college? What is the role of significant others in supporting and encouraging student success? The findings revealed a continuous cycle of support for these students. The cycle started in the home environment, where parents were integral in the early influence on the students' decisions to pursue higher education. Relationships with teachers, counselors, and peers provided critical networks of support in helping these students to achieve their academic goals. Participation in the MESA program empowered the students and provided additional connections to knowledge-based resources. This study highlights the interplay among family, school, and the MESA program in the overall support of underrepresented female students in the STEM pipeline.

A CONTROLLED EVALUATION OF A HIGH SCHOOL BIOMEDICAL PIPELINE PROGRAM: DESIGN AND METHODS.

PubMed

Winkleby, Marilyn A; Ned, Judith; Ahn, David; Koehler, Alana; Fagliano, Kathleen; Crump, Casey

2014-02-01

Given limited funding for school-based science education, non-school-based programs have been developed at colleges and universities to increase the number of students entering science- and health-related careers and address critical workforce needs. However, few evaluations of such programs have been conducted. We report the design and methods of a controlled trial to evaluate the Stanford Medical Youth Science Program's Summer Residential Program (SRP), a 25-year-old university-based biomedical pipeline program. This 5-year matched cohort study uses an annual survey to assess educational and career outcomes among four cohorts of students who participate in the SRP and a matched comparison group of applicants who were not chosen to participate in the SRP. Matching on sociodemographic and academic background allows control for potential confounding. This design enables the testing of whether the SRP has an independent effect on educational- and career-related outcomes above and beyond the effects of other factors such as gender, ethnicity, socioeconomic background, and pre-intervention academic preparation. The results will help determine which curriculum components contribute most to successful outcomes and which students benefit most. After 4 years of follow-up, the results demonstrate high response rates from SRP participants and the comparison group with completion rates near 90%, similar response rates by gender and ethnicity, and little attrition with each additional year of follow-up. This design and methods can potentially be replicated to evaluate and improve other biomedical pipeline programs, which are increasingly important for equipping more students for science- and health-related careers.

A CONTROLLED EVALUATION OF A HIGH SCHOOL BIOMEDICAL PIPELINE PROGRAM: DESIGN AND METHODS

PubMed Central

Winkleby, Marilyn A.; Ned, Judith; Ahn, David; Koehler, Alana; Fagliano, Kathleen; Crump, Casey

2013-01-01

Given limited funding for school-based science education, non-school-based programs have been developed at colleges and universities to increase the number of students entering science- and health-related careers and address critical workforce needs. However, few evaluations of such programs have been conducted. We report the design and methods of a controlled trial to evaluate the Stanford Medical Youth Science Program’s Summer Residential Program (SRP), a 25-year-old university-based biomedical pipeline program. This 5-year matched cohort study uses an annual survey to assess educational and career outcomes among four cohorts of students who participate in the SRP and a matched comparison group of applicants who were not chosen to participate in the SRP. Matching on sociodemographic and academic background allows control for potential confounding. This design enables the testing of whether the SRP has an independent effect on educational- and career-related outcomes above and beyond the effects of other factors such as gender, ethnicity, socioeconomic background, and pre-intervention academic preparation. The results will help determine which curriculum components contribute most to successful outcomes and which students benefit most. After 4 years of follow-up, the results demonstrate high response rates from SRP participants and the comparison group with completion rates near 90%, similar response rates by gender and ethnicity, and little attrition with each additional year of follow-up. This design and methods can potentially be replicated to evaluate and improve other biomedical pipeline programs, which are increasingly important for equipping more students for science- and health-related careers. PMID:24563603

A Pipeline Tool for CCD Image Processing

NASA Astrophysics Data System (ADS)

Bell, Jon F.; Young, Peter J.; Roberts, William H.; Sebo, Kim M.

MSSSO is part of a collaboration developing a wide field imaging CCD mosaic (WFI). As part of this project, we have developed a GUI based pipeline tool that is an integrated part of MSSSO's CICADA data acquisition environment and processes CCD FITS images as they are acquired. The tool is also designed to run as a stand alone program to process previously acquired data. IRAF tasks are used as the central engine, including the new NOAO mscred package for processing multi-extension FITS files. The STScI OPUS pipeline environment may be used to manage data and process scheduling. The Motif GUI was developed using SUN Visual Workshop. C++ classes were written to facilitate launching of IRAF and OPUS tasks. While this first version implements calibration processing up to and including flat field corrections, there is scope to extend it to other processing.

The High Level Data Reduction Library

NASA Astrophysics Data System (ADS)

Ballester, P.; Gabasch, A.; Jung, Y.; Modigliani, A.; Taylor, J.; Coccato, L.; Freudling, W.; Neeser, M.; Marchetti, E.

2015-09-01

The European Southern Observatory (ESO) provides pipelines to reduce data for most of the instruments at its Very Large telescope (VLT). These pipelines are written as part of the development of VLT instruments, and are used both in the ESO's operational environment and by science users who receive VLT data. All the pipelines are highly specific geared toward instruments. However, experience showed that the independently developed pipelines include significant overlap, duplication and slight variations of similar algorithms. In order to reduce the cost of development, verification and maintenance of ESO pipelines, and at the same time improve the scientific quality of pipelines data products, ESO decided to develop a limited set of versatile high-level scientific functions that are to be used in all future pipelines. The routines are provided by the High-level Data Reduction Library (HDRL). To reach this goal, we first compare several candidate algorithms and verify them during a prototype phase using data sets from several instruments. Once the best algorithm and error model have been chosen, we start a design and implementation phase. The coding of HDRL is done in plain C and using the Common Pipeline Library (CPL) functionality. HDRL adopts consistent function naming conventions and a well defined API to minimise future maintenance costs, implements error propagation, uses pixel quality information, employs OpenMP to take advantage of multi-core processors, and is verified with extensive unit and regression tests. This poster describes the status of the project and the lesson learned during the development of reusable code implementing algorithms of high scientific quality.

Developing Healthcare Data Analytics APPs with Open Data Science Tools.

PubMed

Hao, Bibo; Sun, Wen; Yu, Yiqin; Xie, Guotong

2017-01-01

Recent advances in big data analytics provide more flexible, efficient, and open tools for researchers to gain insight from healthcare data. Whilst many tools require researchers to develop programs with programming languages like Python, R and so on, which is not a skill set grasped by many researchers in the healthcare data analytics area. To make data science more approachable, we explored existing tools and developed a practice that can help data scientists convert existing analytics pipelines to user-friendly analytics APPs with rich interactions and features of real-time analysis. With this practice, data scientists can develop customized analytics pipelines as APPs in Jupyter Notebook and disseminate them to other researchers easily, and researchers can benefit from the shared notebook to perform analysis tasks or reproduce research results much more easily.

76 FR 56009 - Mandatory Reporting of Greenhouse Gases: Technical Revisions to the Electronics Manufacturing and...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-09

... Pipeline transportation of natural gas. 221210 Natural gas distribution facilities. 211 Extractors of crude... natural gas processing facilities in transmission pipelines or into storage. 40 CFR Sec. 98.230(a)(4). A... and inaccuracies in reporting''. Pipeline Quality Yes. Natural Gas. CEC/ AXPC asserted that ``[t]here...

76 FR 60478 - Record of Decision, Texas Clean Energy Project

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-29

... the plant with one or both of the nearby power grids; process water supply pipelines; a natural gas... per year. The CO 2 will be delivered through a regional pipeline network to existing oil fields in the... proposed Fort Stockton Holdings water supply pipeline; Possible changes in discharges to Monahans Draw and...

Relationship between Pipeline Wall Thickness (Gr. X60) and Water Depth towards Avoiding Failure during Installation

NASA Astrophysics Data System (ADS)

Razak, K. Abdul; Othman, M. I. H.; Mat Yusuf, S.; Fuad, M. F. I. Ahmad; yahaya, Effah

2018-05-01

Oil and gas today being developed at different water depth characterized as shallow, deep and ultra-deep waters. Among the major components involved during the offshore installation is pipelines. Pipelines are a transportation method of material through a pipe. In oil and gas industry, pipeline come from a bunch of line pipe that welded together to become a long pipeline and can be divided into two which is gas pipeline and oil pipeline. In order to perform pipeline installation, we need pipe laying barge or pipe laying vessel. However, pipe laying vessel can be divided into two types: S-lay vessel and J-lay vessel. The function of pipe lay vessel is not only to perform pipeline installation. It also performed installation of umbilical or electrical cables. In the simple words, pipe lay vessel is performing the installation of subsea in all the connecting infrastructures. Besides that, the installation processes of pipelines require special focus to make the installation succeed. For instance, the heavy pipelines may exceed the lay vessel’s tension capacities in certain kind of water depth. Pipeline have their own characteristic and we can group it or differentiate it by certain parameters such as grade of material, type of material, size of diameter, size of wall thickness and the strength. For instances, wall thickness parameter studies indicate that if use the higher steel grade of the pipelines will have a significant contribution in pipeline wall thickness reduction. When running the process of pipe lay, water depth is the most critical thing that we need to monitor and concern about because of course we cannot control the water depth but we can control the characteristic of the pipe like apply line pipe that have wall thickness suitable with current water depth in order to avoid failure during the installation. This research will analyse whether the pipeline parameter meet the requirements limit and minimum yield stress. It will overlook to simulate pipe grade API 5L X60 which size from 8 to 20mm thickness with a water depth of 50 to 300m. Result shown that pipeline installation will fail from the wall thickness of 18mm onwards since it has been passed the critical yield percentage.

Unipro UGENE NGS pipelines and components for variant calling, RNA-seq and ChIP-seq data analyses.

PubMed

Golosova, Olga; Henderson, Ross; Vaskin, Yuriy; Gabrielian, Andrei; Grekhov, German; Nagarajan, Vijayaraj; Oler, Andrew J; Quiñones, Mariam; Hurt, Darrell; Fursov, Mikhail; Huyen, Yentram

2014-01-01

The advent of Next Generation Sequencing (NGS) technologies has opened new possibilities for researchers. However, the more biology becomes a data-intensive field, the more biologists have to learn how to process and analyze NGS data with complex computational tools. Even with the availability of common pipeline specifications, it is often a time-consuming and cumbersome task for a bench scientist to install and configure the pipeline tools. We believe that a unified, desktop and biologist-friendly front end to NGS data analysis tools will substantially improve productivity in this field. Here we present NGS pipelines "Variant Calling with SAMtools", "Tuxedo Pipeline for RNA-seq Data Analysis" and "Cistrome Pipeline for ChIP-seq Data Analysis" integrated into the Unipro UGENE desktop toolkit. We describe the available UGENE infrastructure that helps researchers run these pipelines on different datasets, store and investigate the results and re-run the pipelines with the same parameters. These pipeline tools are included in the UGENE NGS package. Individual blocks of these pipelines are also available for expert users to create their own advanced workflows.

Electricity Transmission, Pipelines, and National Trails: An Analysis of Current and Potential Intersections on Federal Lands in the Eastern United States, Alaska, and Hawaii

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

Kuiper, James A.; Krummel, John R.; Hlava, Kevin J.

As has been noted in many reports and publications, acquiring new or expanded rights-of-way for transmission is a challenging process, because numerous land use and land ownership constraints must be overcome to develop pathways suitable for energy transmission infrastructure. In the eastern U.S., more than twenty federally protected national trails (some of which are thousands of miles long, and cross many states) pose a potential obstacle to the development of new or expanded electricity transmission capacity. However, the scope of this potential problem is not well-documented, and there is no baseline information available that could allow all stakeholders to studymore » routing scenarios that could mitigate impacts on national trails. This report, Electricity Transmission, Pipelines, and National Trails: An Analysis of Current and Potential Intersections on Federal Lands in the Eastern United States, was prepared by the Environmental Science Division of Argonne National Laboratory (Argonne). Argonne was tasked by DOE to analyze the “footprint” of the current network of National Historic and Scenic Trails and the electricity transmission system in the 37 eastern contiguous states, Alaska, and Hawaii; assess the extent to which national trails are affected by electrical transmission; and investigate the extent to which national trails and other sensitive land use types may be affected in the near future by planned transmission lines. Pipelines are secondary to transmission lines for analysis, but are also within the analysis scope in connection with the overall directives of Section 368 of the Energy Policy Act of 2005, and because of the potential for electrical transmission lines being collocated with pipelines.« less

Practical Approach for Hyperspectral Image Processing in Python

NASA Astrophysics Data System (ADS)

Annala, L.; Eskelinen, M. A.; Hämäläinen, J.; Riihinen, A.; Pölönen, I.

2018-04-01

Python is a very popular programming language among data scientists around the world. Python can also be used in hyperspectral data analysis. There are some toolboxes designed for spectral imaging, such as Spectral Python and HyperSpy, but there is a need for analysis pipeline, which is easy to use and agile for different solutions. We propose a Python pipeline which is built on packages xarray, Holoviews and scikit-learn. We have developed some of own tools, MaskAccessor, VisualisorAccessor and a spectral index library. They also fulfill our goal of easy and agile data processing. In this paper we will present our processing pipeline and demonstrate it in practice.

Advanced Methodologies for NASA Science Missions

NASA Astrophysics Data System (ADS)

Hurlburt, N. E.; Feigelson, E.; Mentzel, C.

2017-12-01

Most of NASA's commitment to computational space science involves the organization and processing of Big Data from space-based satellites, and the calculations of advanced physical models based on these datasets. But considerable thought is also needed on what computations are needed. The science questions addressed by space data are so diverse and complex that traditional analysis procedures are often inadequate. The knowledge and skills of the statistician, applied mathematician, and algorithmic computer scientist must be incorporated into programs that currently emphasize engineering and physical science. NASA's culture and administrative mechanisms take full cognizance that major advances in space science are driven by improvements in instrumentation. But it is less well recognized that new instruments and science questions give rise to new challenges in the treatment of satellite data after it is telemetered to the ground. These issues might be divided into two stages: data reduction through software pipelines developed within NASA mission centers; and science analysis that is performed by hundreds of space scientists dispersed through NASA, U.S. universities, and abroad. Both stages benefit from the latest statistical and computational methods; in some cases, the science result is completely inaccessible using traditional procedures. This paper will review the current state of NASA and present example applications using modern methodologies.

UOE Pipe Numerical Model: Manufacturing Process And Von Mises Residual Stresses Resulted After Each Technological Step

NASA Astrophysics Data System (ADS)

Delistoian, Dmitri; Chirchor, Mihael

2017-12-01

Fluid transportation from production areas to final customer is effectuated by pipelines. For oil and gas industry, pipeline safety and reliability represents a priority. From this reason, pipe quality guarantee directly influence pipeline designed life, but first of all protects environment. A significant number of longitudinally welded pipes, for onshore/offshore pipelines, are manufactured by UOE method. This method is based on cold forming. In present study, using finite element method is modeled UOE pipe manufacturing process and is obtained von Mises stresses for each step. Numerical simulation is performed for L415 MB (X60) steel plate with 7,9 mm thickness, length 30 mm and width 1250mm, as result it is obtained a DN 400 pipe.

Kentucky DOE-EPSCoR Program

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

Stencel, J.M.; Ochsenbein, M.P.

2003-04-14

The KY DOE EPSCoR Program included efforts to impact positively the pipeline of science and engineering students and to establish research, education and business infrastructure, sustainable beyond DOE EPSCoR funding.

Telecommunications issues of intelligent database management for ground processing systems in the EOS era

NASA Technical Reports Server (NTRS)

Touch, Joseph D.

1994-01-01

Future NASA earth science missions, including the Earth Observing System (EOS), will be generating vast amounts of data that must be processed and stored at various locations around the world. Here we present a stepwise-refinement of the intelligent database management (IDM) of the distributed active archive center (DAAC - one of seven regionally-located EOSDIS archive sites) architecture, to showcase the telecommunications issues involved. We develop this architecture into a general overall design. We show that the current evolution of protocols is sufficient to support IDM at Gbps rates over large distances. We also show that network design can accommodate a flexible data ingestion storage pipeline and a user extraction and visualization engine, without interference between the two.

MarsSI: Martian surface data processing information system

NASA Astrophysics Data System (ADS)

Quantin-Nataf, C.; Lozac'h, L.; Thollot, P.; Loizeau, D.; Bultel, B.; Fernando, J.; Allemand, P.; Dubuffet, F.; Poulet, F.; Ody, A.; Clenet, H.; Leyrat, C.; Harrisson, S.

2018-01-01

MarsSI (Acronym for Mars System of Information, https://emars.univ-lyon1.fr/MarsSI/, is a web Geographic Information System application which helps managing and processing martian orbital data. The MarsSI facility is part of the web portal called PSUP (Planetary SUrface Portal) developed by the Observatories of Paris Sud (OSUPS) and Lyon (OSUL) to provide users with efficient and easy access to data products dedicated to the martian surface. The portal proposes 1) the management and processing of data thanks to MarsSI and 2) the visualization and merging of high level (imagery, spectral, and topographic) products and catalogs via a web-based user interface (MarsVisu). The portal PSUP as well as the facility MarsVisu is detailed in a companion paper (Poulet et al., 2018). The purpose of this paper is to describe the facility MarsSI. From this application, users are able to easily and rapidly select observations, process raw data via automatic pipelines, and get back final products which can be visualized under Geographic Information Systems. Moreover, MarsSI also contains an automatic stereo-restitution pipeline in order to produce Digital Terrain Models (DTM) on demand from HiRISE (High Resolution Imaging Science Experiment) or CTX (Context Camera) pair-images. This application is funded by the European Union's Seventh Framework Programme (FP7/2007-2013) (ERC project eMars, No. 280168) and has been developed in the scope of Mars, but the design is applicable to any other planetary body of the solar system.

An image processing pipeline to detect and segment nuclei in muscle fiber microscopic images.

PubMed

Guo, Yanen; Xu, Xiaoyin; Wang, Yuanyuan; Wang, Yaming; Xia, Shunren; Yang, Zhong

2014-08-01

Muscle fiber images play an important role in the medical diagnosis and treatment of many muscular diseases. The number of nuclei in skeletal muscle fiber images is a key bio-marker of the diagnosis of muscular dystrophy. In nuclei segmentation one primary challenge is to correctly separate the clustered nuclei. In this article, we developed an image processing pipeline to automatically detect, segment, and analyze nuclei in microscopic image of muscle fibers. The pipeline consists of image pre-processing, identification of isolated nuclei, identification and segmentation of clustered nuclei, and quantitative analysis. Nuclei are initially extracted from background by using local Otsu's threshold. Based on analysis of morphological features of the isolated nuclei, including their areas, compactness, and major axis lengths, a Bayesian network is trained and applied to identify isolated nuclei from clustered nuclei and artifacts in all the images. Then a two-step refined watershed algorithm is applied to segment clustered nuclei. After segmentation, the nuclei can be quantified for statistical analysis. Comparing the segmented results with those of manual analysis and an existing technique, we find that our proposed image processing pipeline achieves good performance with high accuracy and precision. The presented image processing pipeline can therefore help biologists increase their throughput and objectivity in analyzing large numbers of nuclei in muscle fiber images. © 2014 Wiley Periodicals, Inc.

Development of an automated data acquisition and processing pipeline using multiple telescopes for observing transient phenomena

NASA Astrophysics Data System (ADS)

Savant, Vaibhav; Smith, Niall

2016-07-01

We report on the current status in the development of a pilot automated data acquisition and reduction pipeline based around the operation of two nodes of remotely operated robotic telescopes based in California, USA and Cork, Ireland. The observatories are primarily used as a testbed for automation and instrumentation and as a tool to facilitate STEM (Science Technology Engineering Mathematics) promotion. The Ireland node is situated at Blackrock Castle Observatory (operated by Cork Institute of Technology) and consists of two optical telescopes - 6" and 16" OTAs housed in two separate domes while the node in California is its 6" replica. Together they form a pilot Telescope ARrAy known as TARA. QuickPhot is an automated data reduction pipeline designed primarily to throw more light on the microvariability of blazars employing precision optical photometry and using data from the TARA telescopes as they constantly monitor predefined targets whenever observing conditions are favourable. After carrying out aperture photometry, if any variability above a given threshold is observed, the reporting telescope will communicate the source concerned and the other nodes will follow up with multi-band observations, taking advantage that they are located in strategically separated time-zones. Ultimately we wish to investigate the applicability of Shock-in-Jet and Geometric models. These try to explain the processes at work in AGNs which result in the formation of jets, by looking for temporal and spectral variability in TARA multi-band observations. We are also experimenting with using a Twochannel Optical PHotometric Imaging CAMera (TOΦCAM) that we have developed and which has been optimised for simultaneous two-band photometry on our 16" OTA.

Spatial Thinking in Atmospheric Science Education

NASA Astrophysics Data System (ADS)

McNeal, P. M.; Petcovic, H. L.; Ellis, T. D.

2016-12-01

Atmospheric science is a STEM discipline that involves the visualization of three-dimensional processes from two-dimensional maps, interpretation of computer-generated graphics and hand plotting of isopleths. Thus, atmospheric science draws heavily upon spatial thinking. Research has shown that spatial thinking ability can be a predictor of early success in STEM disciplines and substantial evidence demonstrates that spatial thinking ability is improved through various interventions. Therefore, identification of the spatial thinking skills and cognitive processes used in atmospheric science is the first step toward development of instructional strategies that target these skills and scaffold the learning of students in atmospheric science courses. A pilot study of expert and novice meteorologists identified mental animation and disembedding as key spatial skills used in the interpretation of multiple weather charts and images. Using this as a starting point, we investigated how these spatial skills, together with expertise, domain specific knowledge, and working memory capacity affect the ability to produce an accurate forecast. Participants completed a meteorology concept inventory, experience questionnaire and psychometric tests of spatial thinking ability and working memory capacity prior to completing a forecasting task. A quantitative analysis of the collected data investigated the effect of the predictor variables on the outcome task. A think-aloud protocol with individual participants provided a qualitative look at processes such as task decomposition, rule-based reasoning and the formation of mental models in an attempt to understand how individuals process this complex data and describe outcomes of particular meteorological scenarios. With our preliminary results we aim to inform atmospheric science education from a cognitive science perspective. The results point to a need to collaborate with the atmospheric science community broadly, such that multiple educational pipelines are affected including university meteorology courses for majors and non-majors, military weather forecaster preparation and professional training for operational meteorologists, thus improving student learning and the continued development of the current and future workforce.

The X-shooter pipeline

NASA Astrophysics Data System (ADS)

Modigliani, Andrea; Goldoni, Paolo; Royer, Frédéric; Haigron, Regis; Guglielmi, Laurent; François, Patrick; Horrobin, Matthew; Bristow, Paul; Vernet, Joel; Moehler, Sabine; Kerber, Florian; Ballester, Pascal; Mason, Elena; Christensen, Lise

2010-07-01

The X-shooter data reduction pipeline, as part of the ESO-VLT Data Flow System, provides recipes for Paranal Science Operations, and for Data Product and Quality Control Operations at Garching headquarters. At Paranal, it is used for the quick-look data evaluation. The pipeline recipes can be executed either with EsoRex at the command line level or through the Gasgano graphical user interface. The recipes are implemented with the ESO Common Pipeline Library (CPL). X-shooter is the first of the second generation of VLT instruments. It makes possible to collect in one shot the full spectrum of the target from 300 to 2500 nm, subdivided in three arms optimised for UVB, VIS and NIR ranges, with an efficiency between 15% and 35% including the telescope and the atmosphere, and a spectral resolution varying between 3000 and 17,000. It allows observations in stare, offset modes, using the slit or an IFU, and observing sequences nodding the target along the slit. Data reduction can be performed either with a classical approach, by determining the spectral format via 2D-polynomial transformations, or with the help of a dedicated instrument physical model to gain insight on the instrument and allowing a constrained solution that depends on a few parameters with a physical meaning. In the present paper we describe the steps of data reduction necessary to fully reduce science observations in the different modes with examples on typical data calibrations and observations sequences.

A pipeline for comprehensive and automated processing of electron diffraction data in IPLT.

PubMed

Schenk, Andreas D; Philippsen, Ansgar; Engel, Andreas; Walz, Thomas

2013-05-01

Electron crystallography of two-dimensional crystals allows the structural study of membrane proteins in their native environment, the lipid bilayer. Determining the structure of a membrane protein at near-atomic resolution by electron crystallography remains, however, a very labor-intense and time-consuming task. To simplify and accelerate the data processing aspect of electron crystallography, we implemented a pipeline for the processing of electron diffraction data using the Image Processing Library and Toolbox (IPLT), which provides a modular, flexible, integrated, and extendable cross-platform, open-source framework for image processing. The diffraction data processing pipeline is organized as several independent modules implemented in Python. The modules can be accessed either from a graphical user interface or through a command line interface, thus meeting the needs of both novice and expert users. The low-level image processing algorithms are implemented in C++ to achieve optimal processing performance, and their interface is exported to Python using a wrapper. For enhanced performance, the Python processing modules are complemented with a central data managing facility that provides a caching infrastructure. The validity of our data processing algorithms was verified by processing a set of aquaporin-0 diffraction patterns with the IPLT pipeline and comparing the resulting merged data set with that obtained by processing the same diffraction patterns with the classical set of MRC programs. Copyright © 2013 Elsevier Inc. All rights reserved.

A pipeline for comprehensive and automated processing of electron diffraction data in IPLT

PubMed Central

Schenk, Andreas D.; Philippsen, Ansgar; Engel, Andreas; Walz, Thomas

2013-01-01

Electron crystallography of two-dimensional crystals allows the structural study of membrane proteins in their native environment, the lipid bilayer. Determining the structure of a membrane protein at near-atomic resolution by electron crystallography remains, however, a very labor-intense and time-consuming task. To simplify and accelerate the data processing aspect of electron crystallography, we implemented a pipeline for the processing of electron diffraction data using the Image Processing Library & Toolbox (IPLT), which provides a modular, flexible, integrated, and extendable cross-platform, open-source framework for image processing. The diffraction data processing pipeline is organized as several independent modules implemented in Python. The modules can be accessed either from a graphical user interface or through a command line interface, thus meeting the needs of both novice and expert users. The low-level image processing algorithms are implemented in C++ to achieve optimal processing performance, and their interface is exported to Python using a wrapper. For enhanced performance, the Python processing modules are complemented with a central data managing facility that provides a caching infrastructure. The validity of our data processing algorithms was verified by processing a set of aquaporin-0 diffraction patterns with the IPLT pipeline and comparing the resulting merged data set with that obtained by processing the same diffraction patterns with the classical set of MRC programs. PMID:23500887

NASA Virtual Glovebox: An Immersive Virtual Desktop Environment for Training Astronauts in Life Science Experiments

NASA Technical Reports Server (NTRS)

Twombly, I. Alexander; Smith, Jeffrey; Bruyns, Cynthia; Montgomery, Kevin; Boyle, Richard

2003-01-01

The International Space Station will soon provide an unparalleled research facility for studying the near- and longer-term effects of microgravity on living systems. Using the Space Station Glovebox Facility - a compact, fully contained reach-in environment - astronauts will conduct technically challenging life sciences experiments. Virtual environment technologies are being developed at NASA Ames Research Center to help realize the scientific potential of this unique resource by facilitating the experimental hardware and protocol designs and by assisting the astronauts in training. The Virtual GloveboX (VGX) integrates high-fidelity graphics, force-feedback devices and real- time computer simulation engines to achieve an immersive training environment. Here, we describe the prototype VGX system, the distributed processing architecture used in the simulation environment, and modifications to the visualization pipeline required to accommodate the display configuration.

Kepler Planet Detection Metrics: Statistical Bootstrap Test

NASA Technical Reports Server (NTRS)

Jenkins, Jon M.; Burke, Christopher J.

2016-01-01

This document describes the data produced by the Statistical Bootstrap Test over the final three Threshold Crossing Event (TCE) deliveries to NExScI: SOC 9.1 (Q1Q16)1 (Tenenbaum et al. 2014), SOC 9.2 (Q1Q17) aka DR242 (Seader et al. 2015), and SOC 9.3 (Q1Q17) aka DR253 (Twicken et al. 2016). The last few years have seen significant improvements in the SOC science data processing pipeline, leading to higher quality light curves and more sensitive transit searches. The statistical bootstrap analysis results presented here and the numerical results archived at NASAs Exoplanet Science Institute (NExScI) bear witness to these software improvements. This document attempts to introduce and describe the main features and differences between these three data sets as a consequence of the software changes.

Towards Portable Large-Scale Image Processing with High-Performance Computing.

PubMed

Huo, Yuankai; Blaber, Justin; Damon, Stephen M; Boyd, Brian D; Bao, Shunxing; Parvathaneni, Prasanna; Noguera, Camilo Bermudez; Chaganti, Shikha; Nath, Vishwesh; Greer, Jasmine M; Lyu, Ilwoo; French, William R; Newton, Allen T; Rogers, Baxter P; Landman, Bennett A

2018-05-03

High-throughput, large-scale medical image computing demands tight integration of high-performance computing (HPC) infrastructure for data storage, job distribution, and image processing. The Vanderbilt University Institute for Imaging Science (VUIIS) Center for Computational Imaging (CCI) has constructed a large-scale image storage and processing infrastructure that is composed of (1) a large-scale image database using the eXtensible Neuroimaging Archive Toolkit (XNAT), (2) a content-aware job scheduling platform using the Distributed Automation for XNAT pipeline automation tool (DAX), and (3) a wide variety of encapsulated image processing pipelines called "spiders." The VUIIS CCI medical image data storage and processing infrastructure have housed and processed nearly half-million medical image volumes with Vanderbilt Advanced Computing Center for Research and Education (ACCRE), which is the HPC facility at the Vanderbilt University. The initial deployment was natively deployed (i.e., direct installations on a bare-metal server) within the ACCRE hardware and software environments, which lead to issues of portability and sustainability. First, it could be laborious to deploy the entire VUIIS CCI medical image data storage and processing infrastructure to another HPC center with varying hardware infrastructure, library availability, and software permission policies. Second, the spiders were not developed in an isolated manner, which has led to software dependency issues during system upgrades or remote software installation. To address such issues, herein, we describe recent innovations using containerization techniques with XNAT/DAX which are used to isolate the VUIIS CCI medical image data storage and processing infrastructure from the underlying hardware and software environments. The newly presented XNAT/DAX solution has the following new features: (1) multi-level portability from system level to the application level, (2) flexible and dynamic software development and expansion, and (3) scalable spider deployment compatible with HPC clusters and local workstations.

Hybrid Pluggable Processing Pipeline (HyP3): Programmatic Access to Cloud-Based Processing of SAR Data

NASA Astrophysics Data System (ADS)

Weeden, R.; Horn, W. B.; Dimarchi, H.; Arko, S. A.; Hogenson, K.

2017-12-01

A problem often faced by Earth science researchers is the question of how to scale algorithms that were developed against few datasets and take them to regional or global scales. This problem only gets worse as we look to a future with larger and larger datasets becoming available. One significant hurdle can be having the processing and storage resources available for such a task, not to mention the administration of those resources. As a processing environment, the cloud offers nearly unlimited potential for compute and storage, with limited administration required. The goal of the Hybrid Pluggable Processing Pipeline (HyP3) project was to demonstrate the utility of the Amazon cloud to process large amounts of data quickly and cost effectively. Principally built by three undergraduate students at the ASF DAAC, the HyP3 system relies on core Amazon cloud services such as Lambda, Relational Database Service (RDS), Elastic Compute Cloud (EC2), Simple Storage Service (S3), and Elastic Beanstalk. HyP3 provides an Application Programming Interface (API) through which users can programmatically interface with the HyP3 system; allowing them to monitor and control processing jobs running in HyP3, and retrieve the generated HyP3 products when completed. This presentation will focus on the development techniques and enabling technologies that were used in developing the HyP3 system. Data and process flow, from new subscription through to order completion will be shown, highlighting the benefits of the cloud for each step. Because the HyP3 system can be accessed directly from a user's Python scripts, powerful applications leveraging SAR products can be put together fairly easily. This is the true power of HyP3; allowing people to programmatically leverage the power of the cloud.

The connectome mapper: an open-source processing pipeline to map connectomes with MRI.

PubMed

Daducci, Alessandro; Gerhard, Stephan; Griffa, Alessandra; Lemkaddem, Alia; Cammoun, Leila; Gigandet, Xavier; Meuli, Reto; Hagmann, Patric; Thiran, Jean-Philippe

2012-01-01

Researchers working in the field of global connectivity analysis using diffusion magnetic resonance imaging (MRI) can count on a wide selection of software packages for processing their data, with methods ranging from the reconstruction of the local intra-voxel axonal structure to the estimation of the trajectories of the underlying fibre tracts. However, each package is generally task-specific and uses its own conventions and file formats. In this article we present the Connectome Mapper, a software pipeline aimed at helping researchers through the tedious process of organising, processing and analysing diffusion MRI data to perform global brain connectivity analyses. Our pipeline is written in Python and is freely available as open-source at www.cmtk.org.

77 FR 48112 - Pipeline Safety: Administrative Procedures; Updates and Technical Corrections

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-13

...This Notice of Proposed Rulemaking updates the administrative civil penalty maximums for violation of the pipeline safety regulations to conform to current law, updates the informal hearing and adjudication process for pipeline enforcement matters to conform to current law, amends other administrative procedures used by PHMSA personnel, and makes other technical corrections and updates to certain administrative procedures. The proposed amendments do not impose any new operating, maintenance, or other substantive requirements on pipeline owners or operators.

The VLITE Post-Processing Pipeline

NASA Astrophysics Data System (ADS)

Richards, Emily E.; Clarke, Tracy; Peters, Wendy; Polisensky, Emil; Kassim, Namir E.

2018-01-01

A post-processing pipeline to adaptively extract and catalog point sources is being developed to enhance the scientific value and accessibility of data products generated by the VLA Low-band Ionosphere and Transient Experiment (VLITE; ) on the Karl G. Jansky Very Large Array (VLA). In contrast to other radio sky surveys, the commensal observing mode of VLITE results in varying depths, sensitivities, and spatial resolutions across the sky based on the configuration of the VLA, location on the sky, and time on source specified by the primary observer for their independent science objectives. Therefore, previously developed tools and methods for generating source catalogs and survey statistics are not always appropriate for VLITE's diverse and growing set of data. A raw catalog of point sources extracted from every VLITE image will be created from source fit parameters stored in a queryable database. Point sources will be measured using the Python Blob Detector and Source Finder software (PyBDSF; Mohan & Rafferty 2015). Sources in the raw catalog will be associated with previous VLITE detections in a resolution- and sensitivity-dependent manner, and cross-matched to other radio sky surveys to aid in the detection of transient and variable sources. Final data products will include separate, tiered point source catalogs grouped by sensitivity limit and spatial resolution.

The Pipeline and Student Perceptions of Schooling: Good News and Bad News.

ERIC Educational Resources Information Center

Moses, Michele S.; And Others

The existence of a math/science "ipieline" in public schooling is well documented in which the number of female students, students with lower socioeconomic status, and students of color in proportion to white males in advanced math and science progressively shrinks during high school. As part of an ongoing gender equity project, separate versions…

High School Math and Science Preparation and Postsecondary STEM Participation for Students with an Autism Spectrum Disorder

ERIC Educational Resources Information Center

Wei, Xin; Yu, Jennifer; Shattuck, Paul; Blackorby, Jose

2017-01-01

Previous studies suggest that individuals with an Autism Spectrum Disorder (ASD) are more likely than other disability groups and the general population to gravitate toward science, technology, engineering, and mathematics (STEM) fields. However, the field knows little about which factors influenced the STEM pipeline between high school and…

High School Math and Science Preparation and Postsecondary STEM Participation for Students with an Autism Spectrum Disorder

ERIC Educational Resources Information Center

Wei, Xin; Yu, Jennifer W.; Shattuck, Paul; Blackorby, Jose

2017-01-01

Previous studies suggest that individuals with an autism spectrum disorder (ASD) are more likely than other disability groups and the general population to gravitate toward science, technology, engineering, and mathematics (STEM) fields. However, the field knows little about which factors influence the STEM pipeline between high school and…

Social Class and the STEM Career Pipeline an Ethnographic Investigation of Opportunity Structures in a High-Poverty versus Affluent High School

ERIC Educational Resources Information Center

Nikischer, Andrea B.

2013-01-01

This research investigates science, technology, engineering and mathematics (STEM) high school opportunity structures, including student experiences with math and science course sequences and progress, college guidance and counseling, and STEM extracurricular activities (Weis and Eisenhart, 2009), specifically related to STEM fields and career and…

Public Dialogue with Science and Development for Teachers of STEM: Linking Public Dialogue with Pedagogic Praxis

ERIC Educational Resources Information Center

Watermeyer, Richard; Montgomery, Catherine

2018-01-01

Despite evidence of quality teaching in Science, Technology, Engineering and Mathematics (STEM) subject domains and insistence on the part of many national governments on the economic value of STEM, education, recruitment and retention into STEM subject fields and occupations is said to be continually blighted by a "leaky pipeline". In…

Assessing the Impact of a Research-Based STEM Program on STEM Majors' Attitudes and Beliefs

ERIC Educational Resources Information Center

Huziak-Clark, Tracy; Sondergeld, Toni; Staaden, Moira; Knaggs, Christine; Bullerjahn, Anne

2015-01-01

The Science, Engineering, and Technology Gateway of Ohio (SETGO) program has a three-pronged approach to meeting the needs at different levels of students in the science, technology, engineering, and mathematics (STEM) pipeline. The SETGO program was an extensive collaboration between a two-year community college and a nearby four-year…

Introduction of a Population Balance Based Design Problem in a Particle Science and Technology Course for Chemical Engineers

ERIC Educational Resources Information Center

Ehrman, Sheryl H.; Castellanos, Patricia; Dwivedi, Vivek; Diemer, R. Bertrum

2007-01-01

A particle technology design problem incorporating population balance modeling was developed and assigned to senior and first-year graduate students in a Particle Science and Technology course. The problem focused on particle collection, with a pipeline agglomerator, Cyclone, and baghouse comprising the collection system. The problem was developed…

Advanced Technological Education (ATE) Program: Building a Pipeline of Skilled Workers. Policy Brief

ERIC Educational Resources Information Center

American Youth Policy Forum, 2010

2010-01-01

In the Fall of 2008, the American Youth Policy Forum hosted a series of three Capitol Hill forums showcasing the Advanced Technological Education (ATE) program supported by the National Science Foundation (NSF). The goal of these forums was to educate national policymakers about the importance of: (1) improving the science and math competencies of…

Kinks in the STEM Pipeline: Tracking STEM Graduation Rates Using Science and Mathematics Performance

ERIC Educational Resources Information Center

Redmond-Sanogo, Adrienne; Angle, Julie; Davis, Evan

2016-01-01

In an effort to maintain the global competitiveness of the United States, ensuring a strong Science, Technology, Engineering and Mathematics (STEM) workforce is essential. The purpose of this study was to identify high school courses that serve as predictors of success in college level gatekeeper courses, which in turn led to the successful…

Increasing Internal Stakeholder Consensus about a University Science Center's Outreach Policies and Procedures

ERIC Educational Resources Information Center

Fisher, Richard D.

2013-01-01

For decades the United States has tried to increase the number of students pursuing science, technology, engineering, and mathematics (STEM) education and careers. Educators and policy makers continue to seek strategies to increase the number of students in the STEM education pipeline. Public institutions of higher education are involved in this…

A Controlled Evaluation of a High School Biomedical Pipeline Program: Design and Methods

ERIC Educational Resources Information Center

Winkleby, Marilyn A.; Ned, Judith; Ahn, David; Koehler, Alana; Fagliano, Kathleen; Crump, Casey

2014-01-01

Given limited funding for school-based science education, non-school-based programs have been developed at colleges and universities to increase the number of students entering science- and health-related careers and address critical workforce needs. However, few evaluations of such programs have been conducted. We report the design and methods of…

78 FR 50087 - Notice of Intent To Prepare a Supplemental Environmental Impact Statement for the Alpine...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-16

... the majority of the infield road and pipeline route. CPAI proposes placement of fill material on 73.1..., gas, and water produced from the reservoir would be carried via pipeline to CD-1 for processing. Sales... construct, operate, and maintain a drill site, access road, pipelines, and ancillary facilities to support...

Non-biological synthetic spike-in controls and the AMPtk software pipeline improve mycobiome data

Treesearch

Jonathan M. Palmer; Michelle A. Jusino; Mark T. Banik; Daniel L. Lindner

2018-01-01

High-throughput amplicon sequencing (HTAS) of conserved DNA regions is a powerful technique to characterize microbial communities. Recently, spike-in mock communities have been used to measure accuracy of sequencing platforms and data analysis pipelines. To assess the ability of sequencing platforms and data processing pipelines using fungal internal transcribed spacer...

Computer Science, Biology and Biomedical Informatics academy: Outcomes from 5 years of Immersing High-school Students into Informatics Research.

PubMed

King, Andrew J; Fisher, Arielle M; Becich, Michael J; Boone, David N

2017-01-01

The University of Pittsburgh's Department of Biomedical Informatics and Division of Pathology Informatics created a Science, Technology, Engineering, and Mathematics (STEM) pipeline in 2011 dedicated to providing cutting-edge informatics research and career preparatory experiences to a diverse group of highly motivated high-school students. In this third editorial installment describing the program, we provide a brief overview of the pipeline, report on achievements of the past scholars, and present results from self-reported assessments by the 2015 cohort of scholars. The pipeline continues to expand with the 2015 addition of the innovation internship, and the introduction of a program in 2016 aimed at offering first-time research experiences to undergraduates who are underrepresented in pathology and biomedical informatics. Achievements of program scholars include authorship of journal articles, symposium and summit presentations, and attendance at top 25 universities. All of our alumni matriculated into higher education and 90% remain in STEM majors. The 2015 high-school program had ten participating scholars who self-reported gains in confidence in their research abilities and understanding of what it means to be a scientist.

Computer Science, Biology and Biomedical Informatics academy: Outcomes from 5 years of Immersing High-school Students into Informatics Research

PubMed Central

King, Andrew J.; Fisher, Arielle M.; Becich, Michael J.; Boone, David N.

2017-01-01

The University of Pittsburgh's Department of Biomedical Informatics and Division of Pathology Informatics created a Science, Technology, Engineering, and Mathematics (STEM) pipeline in 2011 dedicated to providing cutting-edge informatics research and career preparatory experiences to a diverse group of highly motivated high-school students. In this third editorial installment describing the program, we provide a brief overview of the pipeline, report on achievements of the past scholars, and present results from self-reported assessments by the 2015 cohort of scholars. The pipeline continues to expand with the 2015 addition of the innovation internship, and the introduction of a program in 2016 aimed at offering first-time research experiences to undergraduates who are underrepresented in pathology and biomedical informatics. Achievements of program scholars include authorship of journal articles, symposium and summit presentations, and attendance at top 25 universities. All of our alumni matriculated into higher education and 90% remain in STEM majors. The 2015 high-school program had ten participating scholars who self-reported gains in confidence in their research abilities and understanding of what it means to be a scientist. PMID:28400991

Generation of ethylene tracer by noncatalytic pyrolysis of natural gas at elevated pressure

USGS Publications Warehouse

Lu, Y.; Chen, S.; Rostam-Abadi, M.; Ruch, R.; Coleman, D.; Benson, L.J.

2005-01-01

There is a critical need within the pipeline gas industry for an inexpensive and reliable technology to generate an identification tag or tracer that can be added to pipeline gas to identify gas that may escape and improve the deliverability and management of gas in underground storage fields. Ethylene is an ideal tracer, because it does not exist naturally in the pipeline gas, and because its physical properties are similar to the pipeline gas components. A pyrolysis process, known as the Tragen process, has been developed to continuously convert the ???2%-4% ethane component present in pipeline gas into ethylene at common pipeline pressures of 800 psi. In our studies of the Tragen process, pyrolysis without steam addition achieved a maximum ethylene yield of 28%-35% at a temperature range of 700-775 ??C, corresponding to an ethylene concentration of 4600-5800 ppm in the product gas. Coke deposition was determined to occur at a significant rate in the pyrolysis reactor without steam addition. The ?? 13C isotopic analysis of gas components showed a ?? 13C value of ethylene similar to ethane in the pipeline gas, indicating that most of the ethylene was generated from decomposition of the ethane in the raw gas. However, ?? 13C isotopic analysis of the deposited coke showed that coke was primarily produced from methane, rather than from ethane or other heavier hydrocarbons. No coke deposition was observed with the addition of steam at concentrations of > 20% by volume. The dilution with steam also improved the ethylene yield. ?? 2005 American Chemical Society.

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

Reggio, R.; Haun, R.

This paper reviews the engineering and design work along with the installation procedures for a Persian Gulf natural gas pipeline. OPMI Ltd., a joint venture of Offshore Pipelines, Inc., Houston, and Maritime Industrial Services Co., Ltd., United Arab Emirates (UAE), successfully completed this 57.4 mile, 16-inch gas export pipeline for Consolidated Transmissions Inc. The pipeline begins at a platform in the Mubarek field offshore Sharjah, UAE, and runs to a beach termination at the Dugas treatment plant, Jebel Ali, Dubai. The paper describes the site preparation required for installation of the pipeline along with the specific design of the pipelinemore » itself to deal with corrosion, welding processes, condensate dropout, and temperature gradients.« less

Social class and the STEM career pipeline an ethnographic investigation of opportunity structures in a high-poverty versus affluent high school

NASA Astrophysics Data System (ADS)

Nikischer, Andrea B.

This research investigates science, technology, engineering and mathematics (STEM) high school opportunity structures, including student experiences with math and science course sequences and progress, college guidance and counseling, and STEM extracurricular activities (Weis and Eisenhart, 2009), specifically related to STEM fields and career and college choice, for top-performing math and science students. Differences in these structures and processes as they play out in two representative high schools that vary by social class and racial/ethnic makeup are examined. This comparative ethnography includes 36 school and classroom observations, 56 semi-structured individual interviews, and a review of relevant documents, all gathered during the focal students' junior year of high school. Three data chapters are presented, discussing three distinct, yet interconnected themes. In the first, I examine the ways in which chronic attendance problems and classroom distractions negatively impact math and science instruction time and lead to an instruction (time) deficit. In the second, I compare the math and science course and extra-curricular offerings at each school, and discuss the significant differences between sites regarding available STEM exposure and experience, also known as "STEM educational dose" (Wai, et al., 2010). In the third, I investigate available guidance counseling services and STEM and college-linking at each site. Perceived failures in the counseling services available are discussed. This dissertation is grounded in the literature on differences in academic achievement based on school setting, the nature/distribution of knowledge based on social class, and STEM opportunity structures. The concepts of "social capital" and "STEM capital" are engaged throughout. Ultimately, I argue through this dissertation that segregation by race, and most importantly social class, both between and within districts, damages the STEM pipeline for high-performing math and science students located in high-poverty, low-performing schools. I further argue that both federal and state accountability-based school reform efforts are failing to improve outcomes for students with proficiency and interest in STEM learning and STEM fields, and in fact, these reforms are harming top performing students and high school STEM opportunity structures. Recommendations for changes in policy and practice, and for further research, are provided.

Pipeline Modernization and Consumer Protection Act

THOMAS, 113th Congress

Sen. Markey, Edward J. [D-MA

2013-11-21

Senate - 11/21/2013 Read twice and referred to the Committee on Commerce, Science, and Transportation. (All Actions) Tracker: This bill has the status IntroducedHere are the steps for Status of Legislation:

Building an academic-community partnership for increasing representation of minorities in the health professions.

PubMed

Erwin, Katherine; Blumenthal, Daniel S; Chapel, Thomas; Allwood, L Vernon

2004-11-01

We evaluated collaboration among academic and community partners in a program to recruit African American youth into the health professions. Six institutions of higher education, an urban school system, two community organizations, and two private enterprises became partners to create a health career pipeline for this population. The pipeline consisted of 14 subprograms designed to enrich academic science curricula, stimulate the interest of students in health careers, and facilitate entry into professional schools and other graduate-level educational programs. Subprogram directors completed questionnaires regarding a sense of common mission/vision and coordination/collaboration three times during the 3-year project. The partners strongly shared a common mission and vision throughout the duration of the program, although there was some weakening in the last phase. Subprogram directors initially viewed coordination/collaboration as weak, but by midway through the project period viewed it as stronger. Feared loss of autonomy was foremost among several factors that threatened collaboration among the partners. Collaboration was improved largely through a process of building trust among the partners.

Social networks to biological networks: systems biology of Mycobacterium tuberculosis.

PubMed

Vashisht, Rohit; Bhardwaj, Anshu; Osdd Consortium; Brahmachari, Samir K

2013-07-01

Contextualizing relevant information to construct a network that represents a given biological process presents a fundamental challenge in the network science of biology. The quality of network for the organism of interest is critically dependent on the extent of functional annotation of its genome. Mostly the automated annotation pipelines do not account for unstructured information present in volumes of literature and hence large fraction of genome remains poorly annotated. However, if used, this information could substantially enhance the functional annotation of a genome, aiding the development of a more comprehensive network. Mining unstructured information buried in volumes of literature often requires manual intervention to a great extent and thus becomes a bottleneck for most of the automated pipelines. In this review, we discuss the potential of scientific social networking as a solution for systematic manual mining of data. Focusing on Mycobacterium tuberculosis, as a case study, we discuss our open innovative approach for the functional annotation of its genome. Furthermore, we highlight the strength of such collated structured data in the context of drug target prediction based on systems level analysis of pathogen.

The Kepler Data Processing Handbook: A Field Guide to Prospecting for Habitable Worlds

NASA Technical Reports Server (NTRS)

Jenkins, Jon M.

2017-01-01

The Kepler telescope hurtled into orbit in March 2009, initiating NASA's first mission to discover Earth-size planets orbiting Sun-like stars. Kepler simultaneously collected data for approximately 165,000 target stars at a time over its four-year mission, identifying over 4700 planet candidates, over 2300 confirmed or validated planets, and over 2100 eclipsing binaries. While Kepler was designed to discover exoplanets, the long-term, ultrahigh photometric precision measurements it achieved made it a premier observational facility for stellar astrophysics, especially in the field of asteroseismology, and for variable stars, such as RR Lyrae. The Kepler Science Operations Center (SOC) was developed at NASA Ames Research Center to process the data acquired by Kepler from pixel-level calibrations all the way to identifying transiting planet signatures and subjecting them to a suite of diagnostic tests to establish or break confidence in their planetary nature. Detecting small, rocky planets transiting Sun-like stars presents a variety of daunting challenges, including achieving an unprecedented photometric precision of 20 ppm on 6.5-hour timescales, and supporting the science operations, management, processing, and repeated reprocessing of the accumulating data stream. A newly revised and expanded version of the Kepler Data Processing Handbook (KDPH) has been released to support the legacy archival products. The KDPH details the theory, design and performance of the algorithms supporting each data processing step. This paper presents an overview of the KDPH and features illustrations of several key algorithms in the Kepler Science Data Processing Pipeline. Kepler was selected as the 10th mission of the Discovery Program. Funding for this mission is provided by NASA, Science Mission Directorate.

Integrated pipeline for inferring the evolutionary history of a gene family embedded in the species tree: a case study on the STIMATE gene family.

PubMed

Song, Jia; Zheng, Sisi; Nguyen, Nhung; Wang, Youjun; Zhou, Yubin; Lin, Kui

2017-10-03

Because phylogenetic inference is an important basis for answering many evolutionary problems, a large number of algorithms have been developed. Some of these algorithms have been improved by integrating gene evolution models with the expectation of accommodating the hierarchy of evolutionary processes. To the best of our knowledge, however, there still is no single unifying model or algorithm that can take all evolutionary processes into account through a stepwise or simultaneous method. On the basis of three existing phylogenetic inference algorithms, we built an integrated pipeline for inferring the evolutionary history of a given gene family; this pipeline can model gene sequence evolution, gene duplication-loss, gene transfer and multispecies coalescent processes. As a case study, we applied this pipeline to the STIMATE (TMEM110) gene family, which has recently been reported to play an important role in store-operated Ca 2+ entry (SOCE) mediated by ORAI and STIM proteins. We inferred their phylogenetic trees in 69 sequenced chordate genomes. By integrating three tree reconstruction algorithms with diverse evolutionary models, a pipeline for inferring the evolutionary history of a gene family was developed, and its application was demonstrated.

The visual and radiological inspection of a pipeline using a teleoperated pipe crawler

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

Fogle, R.F.; Kuelske, K.; Kellner, R.

1995-01-01

In the 1950s, the Savannah River Site built an open, unlined retention basin to temporarily store potentially radionuclide contaminated cooling water from a chemical separations process and storm water drainage from a nearby waste management facility that stored large quantities of nuclear fission byproducts in carbon steel tanks. The retention basin was retired from service in 1972 when a new, lined basin was completed. In 1978, the old retention basin was excavated, backfilled with uncontaminated dirt, and covered with grass. At the same time, much of the underground process pipeline leading to the basin was abandoned. Since the closure ofmore » the retention basin, new environmental regulations require that the basin undergo further assessment to determine whether additional remediation is required. A visual and radiological inspection of the pipeline was necessary to aid in the remediation decision making process for the retention basin system. A teleoperated pipe crawler inspection system was developed to survey the abandoned sections of underground pipelines leading to the retired retention basin. This paper will describe the background to this project, the scope of the investigation, the equipment requirements, and the results of the pipeline inspection.« less

The inspection of a radiologically contaminated pipeline using a teleoperated pipe crawler

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

Fogle, R.F.; Kuelske, K.; Kellner, R.A.

1995-08-01

In the 1950s, the Savannah River Site built an open, unlined retention basin to temporarily store potentially radionuclide contaminated cooling water from a chemical separations process and storm water drainage from a nearby waste management facility that stored large quantities of nuclear fission byproducts in carbon steel tanks. The retention basin was retired from service in 1972 when a new, lined basin was completed. In 1978, the old retention basin was excavated, backfilled with uncontaminated dirt, and covered with grass. At the same time, much of the underground process pipeline leading to the basin was abandoned. Since the closure ofmore » the retention basin, new environmental regulations require that the basin undergo further assessment to determine whether additional remediation is required. A visual and radiological inspection of the pipeline was necessary to aid in the remediation decision making process for the retention basin system. A teleoperated pipe crawler inspection system was developed to survey the abandoned sections of underground pipelines leading to the retired retention basin. This paper will describe the background to this project, the scope of the investigation, the equipment requirements, and the results of the pipeline inspection.« less

Multinode reconfigurable pipeline computer

NASA Technical Reports Server (NTRS)

Nosenchuck, Daniel M. (Inventor); Littman, Michael G. (Inventor)

1989-01-01

A multinode parallel-processing computer is made up of a plurality of innerconnected, large capacity nodes each including a reconfigurable pipeline of functional units such as Integer Arithmetic Logic Processors, Floating Point Arithmetic Processors, Special Purpose Processors, etc. The reconfigurable pipeline of each node is connected to a multiplane memory by a Memory-ALU switch NETwork (MASNET). The reconfigurable pipeline includes three (3) basic substructures formed from functional units which have been found to be sufficient to perform the bulk of all calculations. The MASNET controls the flow of signals from the memory planes to the reconfigurable pipeline and vice versa. the nodes are connectable together by an internode data router (hyperspace router) so as to form a hypercube configuration. The capability of the nodes to conditionally configure the pipeline at each tick of the clock, without requiring a pipeline flush, permits many powerful algorithms to be implemented directly.

Natural Language Processing Accurately Calculates Adenoma and Sessile Serrated Polyp Detection Rates.

PubMed

Nayor, Jennifer; Borges, Lawrence F; Goryachev, Sergey; Gainer, Vivian S; Saltzman, John R

2018-07-01

ADR is a widely used colonoscopy quality indicator. Calculation of ADR is labor-intensive and cumbersome using current electronic medical databases. Natural language processing (NLP) is a method used to extract meaning from unstructured or free text data. (1) To develop and validate an accurate automated process for calculation of adenoma detection rate (ADR) and serrated polyp detection rate (SDR) on data stored in widely used electronic health record systems, specifically Epic electronic health record system, Provation ® endoscopy reporting system, and Sunquest PowerPath pathology reporting system. Screening colonoscopies performed between June 2010 and August 2015 were identified using the Provation ® reporting tool. An NLP pipeline was developed to identify adenomas and sessile serrated polyps (SSPs) on pathology reports corresponding to these colonoscopy reports. The pipeline was validated using a manual search. Precision, recall, and effectiveness of the natural language processing pipeline were calculated. ADR and SDR were then calculated. We identified 8032 screening colonoscopies that were linked to 3821 pathology reports (47.6%). The NLP pipeline had an accuracy of 100% for adenomas and 100% for SSPs. Mean total ADR was 29.3% (range 14.7-53.3%); mean male ADR was 35.7% (range 19.7-62.9%); and mean female ADR was 24.9% (range 9.1-51.0%). Mean total SDR was 4.0% (0-9.6%). We developed and validated an NLP pipeline that accurately and automatically calculates ADRs and SDRs using data stored in Epic, Provation ® and Sunquest PowerPath. This NLP pipeline can be used to evaluate colonoscopy quality parameters at both individual and practice levels.

Fast parallel algorithm for slicing STL based on pipeline

NASA Astrophysics Data System (ADS)

Ma, Xulong; Lin, Feng; Yao, Bo

2016-05-01

In Additive Manufacturing field, the current researches of data processing mainly focus on a slicing process of large STL files or complicated CAD models. To improve the efficiency and reduce the slicing time, a parallel algorithm has great advantages. However, traditional algorithms can't make full use of multi-core CPU hardware resources. In the paper, a fast parallel algorithm is presented to speed up data processing. A pipeline mode is adopted to design the parallel algorithm. And the complexity of the pipeline algorithm is analyzed theoretically. To evaluate the performance of the new algorithm, effects of threads number and layers number are investigated by a serial of experiments. The experimental results show that the threads number and layers number are two remarkable factors to the speedup ratio. The tendency of speedup versus threads number reveals a positive relationship which greatly agrees with the Amdahl's law, and the tendency of speedup versus layers number also keeps a positive relationship agreeing with Gustafson's law. The new algorithm uses topological information to compute contours with a parallel method of speedup. Another parallel algorithm based on data parallel is used in experiments to show that pipeline parallel mode is more efficient. A case study at last shows a suspending performance of the new parallel algorithm. Compared with the serial slicing algorithm, the new pipeline parallel algorithm can make full use of the multi-core CPU hardware, accelerate the slicing process, and compared with the data parallel slicing algorithm, the new slicing algorithm in this paper adopts a pipeline parallel model, and a much higher speedup ratio and efficiency is achieved.

Planck 2015 results. II. Low Frequency Instrument data processings

NASA Astrophysics Data System (ADS)

Planck Collaboration; Ade, P. A. R.; Aghanim, N.; Ashdown, M.; Aumont, J.; Baccigalupi, C.; Ballardini, M.; Banday, A. J.; Barreiro, R. B.; Bartolo, N.; Basak, S.; Battaglia, P.; Battaner, E.; Benabed, K.; Benoît, A.; Benoit-Lévy, A.; Bernard, J.-P.; Bersanelli, M.; Bielewicz, P.; Bock, J. J.; Bonaldi, A.; Bonavera, L.; Bond, J. R.; Borrill, J.; Bouchet, F. R.; Bucher, M.; Burigana, C.; Butler, R. C.; Calabrese, E.; Cardoso, J.-F.; Castex, G.; Catalano, A.; Chamballu, A.; Christensen, P. R.; Colombi, S.; Colombo, L. P. L.; Crill, B. P.; Curto, A.; Cuttaia, F.; Danese, L.; Davies, R. D.; Davis, R. J.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Dickinson, C.; Diego, J. M.; Dole, H.; Donzelli, S.; Doré, O.; Douspis, M.; Ducout, A.; Dupac, X.; Efstathiou, G.; Elsner, F.; Enßlin, T. A.; Eriksen, H. K.; Fergusson, J.; Finelli, F.; Forni, O.; Frailis, M.; Franceschet, C.; Franceschi, E.; Frejsel, A.; Galeotta, S.; Galli, S.; Ganga, K.; Giard, M.; Giraud-Héraud, Y.; Gjerløw, E.; González-Nuevo, J.; Górski, K. M.; Gratton, S.; Gregorio, A.; Gruppuso, A.; Hansen, F. K.; Hanson, D.; Harrison, D. L.; Henrot-Versillé, S.; Herranz, D.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Holmes, W. A.; Hornstrup, A.; Hovest, W.; Huffenberger, K. M.; Hurier, G.; Jaffe, A. H.; Jaffe, T. R.; Juvela, M.; Keihänen, E.; Keskitalo, R.; Kiiveri, K.; Kisner, T. S.; Knoche, J.; Krachmalnicoff, N.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lähteenmäki, A.; Lamarre, J.-M.; Lasenby, A.; Lattanzi, M.; Lawrence, C. R.; Leahy, J. P.; Leonardi, R.; Lesgourgues, J.; Levrier, F.; Liguori, M.; Lilje, P. B.; Linden-Vørnle, M.; Lindholm, V.; López-Caniego, M.; Lubin, P. M.; Macías-Pérez, J. F.; Maggio, G.; Maino, D.; Mandolesi, N.; Mangilli, A.; Maris, M.; Martin, P. G.; Martínez-González, E.; Masi, S.; Matarrese, S.; Mazzotta, P.; McGehee, P.; Meinhold, P. R.; Melchiorri, A.; Mendes, L.; Mennella, A.; Migliaccio, M.; Mitra, S.; Montier, L.; Morgante, G.; Morisset, N.; Mortlock, D.; Moss, A.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Nati, F.; Natoli, P.; Netterfield, C. B.; Nørgaard-Nielsen, H. U.; Novikov, D.; Novikov, I.; Oppermann, N.; Paci, F.; Pagano, L.; Paoletti, D.; Partridge, B.; Pasian, F.; Patanchon, G.; Pearson, T. J.; Peel, M.; Perdereau, O.; Perotto, L.; Perrotta, F.; Pettorino, V.; Piacentini, F.; Pierpaoli, E.; Pietrobon, D.; Pointecouteau, E.; Polenta, G.; Pratt, G. W.; Prézeau, G.; Prunet, S.; Puget, J.-L.; Rachen, J. P.; Rebolo, R.; Reinecke, M.; Remazeilles, M.; Renzi, A.; Rocha, G.; Romelli, E.; Rosset, C.; Rossetti, M.; Roudier, G.; Rubiño-Martín, J. A.; Rusholme, B.; Sandri, M.; Santos, D.; Savelainen, M.; Scott, D.; Seiffert, M. D.; Shellard, E. P. S.; Spencer, L. D.; Stolyarov, V.; Sutton, D.; Suur-Uski, A.-S.; Sygnet, J.-F.; Tauber, J. A.; Tavagnacco, D.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tristram, M.; Tucci, M.; Tuovinen, J.; Türler, M.; Umana, G.; Valenziano, L.; Valiviita, J.; Van Tent, B.; Vassallo, T.; Vielva, P.; Villa, F.; Wade, L. A.; Wandelt, B. D.; Watson, R.; Wehus, I. K.; Wilkinson, A.; Yvon, D.; Zacchei, A.; Zonca, A.

2016-09-01

We present an updated description of the Planck Low Frequency Instrument (LFI) data processing pipeline, associated with the 2015 data release. We point out the places where our results and methods have remained unchanged since the 2013 paper and we highlight the changes made for the 2015 release, describing the products (especially timelines) and the ways in which they were obtained. We demonstrate that the pipeline is self-consistent (principally based on simulations) and report all null tests. For the first time, we present LFI maps in Stokes Q and U polarization. We refer to other related papers where more detailed descriptions of the LFI data processing pipeline may be found if needed.

Evaluation of Big Data Containers for Popular Storage, Retrieval, and Computation Primitives in Earth Science Analysis

NASA Astrophysics Data System (ADS)

Das, K.; Clune, T.; Kuo, K. S.; Mattmann, C. A.; Huang, T.; Duffy, D.; Yang, C. P.; Habermann, T.

2015-12-01

Data containers are infrastructures that facilitate storage, retrieval, and analysis of data sets. Big data applications in Earth Science require a mix of processing techniques, data sources and storage formats that are supported by different data containers. Some of the most popular data containers used in Earth Science studies are Hadoop, Spark, SciDB, AsterixDB, and RasDaMan. These containers optimize different aspects of the data processing pipeline and are, therefore, suitable for different types of applications. These containers are expected to undergo rapid evolution and the ability to re-test, as they evolve, is very important to ensure the containers are up to date and ready to be deployed to handle large volumes of observational data and model output. Our goal is to develop an evaluation plan for these containers to assess their suitability for Earth Science data processing needs. We have identified a selection of test cases that are relevant to most data processing exercises in Earth Science applications and we aim to evaluate these systems for optimal performance against each of these test cases. The use cases identified as part of this study are (i) data fetching, (ii) data preparation for multivariate analysis, (iii) data normalization, (iv) distance (kernel) computation, and (v) optimization. In this study we develop a set of metrics for performance evaluation, define the specifics of governance, and test the plan on current versions of the data containers. The test plan and the design mechanism are expandable to allow repeated testing with both new containers and upgraded versions of the ones mentioned above, so that we can gauge their utility as they evolve.

Strengthening Pipeline Safety and Enforcement Act of 2010

THOMAS, 111th Congress

Sen. Feinstein, Dianne [D-CA

2010-09-22

Senate - 09/22/2010 Read twice and referred to the Committee on Commerce, Science, and Transportation. (All Actions) Tracker: This bill has the status IntroducedHere are the steps for Status of Legislation:

Strengthening Pipeline Safety and Enforcement Act of 2011

THOMAS, 112th Congress

Sen. Feinstein, Dianne [D-CA

2011-01-31

Senate - 01/31/2011 Read twice and referred to the Committee on Commerce, Science, and Transportation. (All Actions) Tracker: This bill has the status IntroducedHere are the steps for Status of Legislation:

Pipeline Transportation Safety Improvement Act of 2010

THOMAS, 111th Congress

Sen. Lautenberg, Frank R. [D-NJ

2010-09-28

Senate - 09/28/2010 Read twice and referred to the Committee on Commerce, Science, and Transportation. (All Actions) Tracker: This bill has the status IntroducedHere are the steps for Status of Legislation:

Pipeline Revolving Fund and Job Creation Act

THOMAS, 113th Congress

Sen. Markey, Edward J. [D-MA

2013-11-21

Senate - 11/21/2013 Read twice and referred to the Committee on Commerce, Science, and Transportation. (All Actions) Tracker: This bill has the status IntroducedHere are the steps for Status of Legislation:

30 CFR 250.1003 - Installation, testing, and repair requirements for DOI pipelines.

Code of Federal Regulations, 2011 CFR

2011-07-01

... installed in water depths of less than 200 feet shall be buried to a depth of at least 3 feet unless they... damage potential exists. (b)(1) Pipelines shall be pressure tested with water at a stabilized pressure of... repair, the pipeline shall be pressure tested with water or processed natural gas at a minimum stabilized...

A Mitigation Process for Impacts of the All American Pipeline on Oak Woodlands in Santa Barbara County

Treesearch

Germaine Reyes-French; Timothy J. Cohen

1991-01-01

This paper outlines a mitigation program for pipeline construction impacts to oak tree habitat by describing the requirements for the Offsite Oak Mitigation Program for the All American Pipeline (AAPL) in Santa Barbara County, California. After describing the initial environmental analysis, the County regulatory structure is described under which the plan was required...

Open source pipeline for ESPaDOnS reduction and analysis

NASA Astrophysics Data System (ADS)

Martioli, Eder; Teeple, Doug; Manset, Nadine; Devost, Daniel; Withington, Kanoa; Venne, Andre; Tannock, Megan

2012-09-01

OPERA is a Canada-France-Hawaii Telescope (CFHT) open source collaborative software project currently under development for an ESPaDOnS echelle spectro-polarimetric image reduction pipeline. OPERA is designed to be fully automated, performing calibrations and reduction, producing one-dimensional intensity and polarimetric spectra. The calibrations are performed on two-dimensional images. Spectra are extracted using an optimal extraction algorithm. While primarily designed for CFHT ESPaDOnS data, the pipeline is being written to be extensible to other echelle spectrographs. A primary design goal is to make use of fast, modern object-oriented technologies. Processing is controlled by a harness, which manages a set of processing modules, that make use of a collection of native OPERA software libraries and standard external software libraries. The harness and modules are completely parametrized by site configuration and instrument parameters. The software is open- ended, permitting users of OPERA to extend the pipeline capabilities. All these features have been designed to provide a portable infrastructure that facilitates collaborative development, code re-usability and extensibility. OPERA is free software with support for both GNU/Linux and MacOSX platforms. The pipeline is hosted on SourceForge under the name "opera-pipeline".

STEMujeres: A case study of the life stories of first-generation Latina engineers and scientists

NASA Astrophysics Data System (ADS)

Vielma, Karina I.

Research points to the many obstacles that first-generation, Latina students face when attempting to enter fields in science, technology, engineering, and mathematics, STEM. This qualitative, case study examined the personal and educational experiences of first-generation Latina women who successfully navigated the STEM educational pipeline earning bachelor's, master's, and doctoral degrees in various fields of engineering. Three research questions guided the study: (1) How does a first-generation Latina engineer and scientist describe her life experiences as she became interested in STEM? (2) How does she describe her educational experiences as she navigated the educational pipeline in the physics, mathematics, and/or engineering field(s)? (3) How did she respond to challenges, obstacles and microaggressions, if any, while navigating the STEM educational pipeline? The study was designed using a combination of Critical Race Theory frameworks---Chicana feminist theory and racial microaggressions. Through a life history case study approach, the women shared their stories of success. With the participants' help, influential persons in their educational paths were identified and interviewed. Data were analyzed using crystallization and thematic results indicated that all women in this study identified their parents as planting the seed of interest through the introduction of mathematics. The women unknowingly prepared to enter the STEM fields by taking math and science coursework. They were guided to apply to STEM universities and academic programs by others who knew about their interest in math and science including teachers, counselors, and level-up peers---students close in age who were just a step more advanced in the educational pipeline. The women also drew from previous familial struggles to guide their perseverance and motivation toward educational degree completion. The lives of the women where complex and intersected with various forms of racism including gender, race, class, legality and power. In many instances, the women used their knowledge to help other STEMujeres advance.

Teaching cell and molecular biology for gender equity.

PubMed

Sible, Jill C; Wilhelm, Dayna E; Lederman, Muriel

2006-01-01

Science, technology, engineering, and math (STEM) fields, including cell biology, are characterized by the "leaky pipeline" syndrome in which, over time, women leave the discipline. The pipeline itself and the pond into which it empties may not be neutral. Explicating invisible norms, attitudes, and practices by integrating social studies of science into science education may be the necessary first step in helping female students persist in STEM disciplines. In 2003 and 2004, a sophomore Cell and Molecular Biology course at Virginia Tech (Blacksburg, VA) was taught integrating social studies of science with standard material. The course was successfully implemented, teaching students factual content while increasing awareness of the cultures of science and their self-confidence in engaging with the subject. Course evaluation data indicated that females in particular perceived greater gains in logical thinking and problem-solving abilities than females in a traditional cell biology course. Consistent with K-12 studies, males in this class were likely to view scientists as male only, whereas females viewed scientists as male and female. This pilot project demonstrates that social studies can be integrated successfully in a cell biology course. Longitudinal studies of this cohort of students will indicate whether this approach contributes to the retention of women in the field.

Setting the standard: 25 years of operating the JCMT

NASA Astrophysics Data System (ADS)

Dempsey, Jessica T.; Bell, Graham S.; Chrysostomou, Antonio; Coulson, Iain M.; Davis, Gary R.; Economou, Frossie; Friberg, Per; Jenness, Timothy; Johnstone, Doug; Tilanus, Remo P. J.; Thomas, Holly S.; Walther, Craig A.

2014-08-01

The James Clerk Maxwell Telescope (JCMT) is the largest single-dish submillimetre telescope in the world, and throughout its lifetime the volume and impact of its science output have steadily increased. A key factor for this continuing productivity is an ever-evolving approach to optimising operations, data acquisition, and science product pipelines and archives. The JCMT was one of the first common-user telescopes to adopt flexible scheduling in 2003, and its impact over a decade of observing will be presented. The introduction of an advanced data-reduction pipeline played an integral role, both for fast real-time reduction during observing, and for science-grade reduction in support of individual projects, legacy surveys, and the JCMT Science Archive. More recently, these foundations have facilitated the commencement of remote observing in addition to traditional on-site operations to further increase on-sky science time. The contribution of highly-trained and engaged operators, support and technical staff to efficient operations will be described. The long-term returns of this evolution are presented here, noting they were achieved in face of external pressures for leaner operating budgets and reduced staffing levels. In an era when visiting observers are being phased out of many observatories, we argue that maintaining a critical level of observer participation is vital to improving and maintaining scientific productivity and facility longevity.

HIPE, HIPE, Hooray!

NASA Astrophysics Data System (ADS)

Ott, S.

2011-07-01

(On behalf of all contributors to the Herschel mission) The Herschel Space Observatory, the fourth cornerstone mission in the ESA science program, was launched 14th of May 2009. With a 3.5 m telescope, it is the largest space telescope ever launched. Herschel's three instruments (HIFI, PACS, and SPIRE) perform photometry and spectroscopy in the 55-671 micron range and will deliver exciting science for the astronomical community during at least three years of routine observations. Starting October 2009 Herschel has been performing and processing observations in routine science mode. The development of the Herschel Data Processing System (HIPE) started nine years ago to support the data analysis for Instrument Level Tests. To fulfil the expectations of the astronomical community, additional resources were made available to implement a freely distributable Data Processing System capable of interactively and automatically reducing Herschel data at different processing levels. The system combines data retrieval, pipeline execution, data quality checking and scientific analysis in one single environment. HIPE is the user-friendly face of Herschel interactive Data Processing. The software is coded in Java and Jython to be platform independent and to avoid the need for commercial licenses. It is distributed under the GNU Lesser General Public License (LGPL), permitting everyone to access and to re-use its code. We will summarise the current capabilities of the Herschel Data Processing system, highlight how the Herschel Data Processing system supported the Herschel observatory to meet the challenges of this large project, give an overview about future development milestones and plans, and how the astronomical community can contribute to HIPE.

Early Entry for Youth into the Ocean Science Pipeline Through Ocean Science School Camp and Summer Camp Programs: A Key Strategy for Enhancing Diversity in the Ocean Sciences

NASA Astrophysics Data System (ADS)

Crane, N. L.; Wasser, A.; Weiss, T.; Sullivan, M.; Jones, A.

2004-12-01

Educators, policymakers, employers and other stakeholders in ocean and other geo-science fields face the continuing challenge of a lack of diversity in these fields. A particular challenge for educators and geo-science professionals promoting ocean sciences is to create programs that have broad access, including access for underrepresented youth. Experiential learning in environments such as intensive multi-day science and summer camps can be a critical captivator and motivator for young people. Our data suggest that youth, especially underrepresented youth, may benefit from exposure to the oceans and ocean science through intensive, sustained (eg more than just an afternoon), hands-on, science-based experiences. Data from the more than 570 youth who have participated in Camp SEA Lab's academically based experiential ocean science camp and summer programs provide compelling evidence for the importance of such programs in motivating young people. We have paid special attention to factors that might play a role in recruiting and retaining these young people in ocean science fields. Over 50% of program attendees were underrepresented youth and on scholarship, which gives us a closer look at the impact of such programs on youth who would otherwise not have the opportunity to participate. Both cognitive (knowledge) and affective (personal growth and motivation) indicators were assessed through surveys and questionnaires. Major themes drawn from the data for knowledge growth and personal growth in Camp SEA Lab youth attendees will be presented. These will be placed into the larger context of critical factors that enhance recruitment and retention in the geo-science pipeline. Successful strategies and challenges for involving families and broadening access to specialized programs such as Camp SEA Lab will also be discussed.

VizieR Online Data Catalog: New Kepler planetary candidates (Ofir+, 2013)

NASA Astrophysics Data System (ADS)

Ofir, A.; Dreizler, S.

2013-10-01

We present first results of our efforts to re-analyze the Kepler photometric dataset, searching for planetary transits using an alternative processing pipeline to the one used by the Kepler mission The SARS pipeline was tried and tested extensively by processing all available CoRoT mission data. For this first paper of the series we used this pipeline to search for (additional) planetary transits only in a small subset of stars - the Kepler objects of interest (KOIs), which are already known to include at least one promising planet candidate. (2 data files).

Quantification technology study on flaws in steam-filled pipelines based on image processing

NASA Astrophysics Data System (ADS)

Sun, Lina; Yuan, Peixin

2009-07-01

Starting from exploiting the applied detection system of gas transmission pipeline, a set of X-ray image processing methods and pipeline flaw quantificational evaluation methods are proposed. Defective and non-defective strings and rows in gray image were extracted and oscillogram was obtained. We can distinguish defects in contrast with two gray images division. According to the gray value of defects with different thicknesses, the gray level depth curve is founded. Through exponential and polynomial fitting way to obtain the attenuation mathematical model which the beam penetrates pipeline, thus attain flaw deep dimension. This paper tests on the PPR pipe in the production of simulated holes flaw and cracks flaw, 135KV used the X-ray source on the testing. Test results show that X-ray image processing method, which meet the needs of high efficient flaw detection and provide quality safeguard for thick oil recovery, can be used successfully in detecting corrosion of insulated pipe.

Quantification technology study on flaws in steam-filled pipelines based on image processing

NASA Astrophysics Data System (ADS)

Yuan, Pei-xin; Cong, Jia-hui; Chen, Bo

2008-03-01

Starting from exploiting the applied detection system of gas transmission pipeline, a set of X-ray image processing methods and pipeline flaw quantificational evaluation methods are proposed. Defective and non-defective strings and rows in gray image were extracted and oscillogram was obtained. We can distinguish defects in contrast with two gray images division. According to the gray value of defects with different thicknesses, the gray level depth curve is founded. Through exponential and polynomial fitting way to obtain the attenuation mathematical model which the beam penetrates pipeline, thus attain flaw deep dimension. This paper tests on the PPR pipe in the production of simulated holes flaw and cracks flaw. The X-ray source tube voltage was selected as 130kv and valve current was 1.5mA.Test results show that X-ray image processing methods, which meet the needs of high efficient flaw detection and provide quality safeguard for thick oil recovery, can be used successfully in detecting corrosion of insulated pipe.

Seqping: gene prediction pipeline for plant genomes using self-training gene models and transcriptomic data.

PubMed

Chan, Kuang-Lim; Rosli, Rozana; Tatarinova, Tatiana V; Hogan, Michael; Firdaus-Raih, Mohd; Low, Eng-Ti Leslie

2017-01-27

Gene prediction is one of the most important steps in the genome annotation process. A large number of software tools and pipelines developed by various computing techniques are available for gene prediction. However, these systems have yet to accurately predict all or even most of the protein-coding regions. Furthermore, none of the currently available gene-finders has a universal Hidden Markov Model (HMM) that can perform gene prediction for all organisms equally well in an automatic fashion. We present an automated gene prediction pipeline, Seqping that uses self-training HMM models and transcriptomic data. The pipeline processes the genome and transcriptome sequences of the target species using GlimmerHMM, SNAP, and AUGUSTUS pipelines, followed by MAKER2 program to combine predictions from the three tools in association with the transcriptomic evidence. Seqping generates species-specific HMMs that are able to offer unbiased gene predictions. The pipeline was evaluated using the Oryza sativa and Arabidopsis thaliana genomes. Benchmarking Universal Single-Copy Orthologs (BUSCO) analysis showed that the pipeline was able to identify at least 95% of BUSCO's plantae dataset. Our evaluation shows that Seqping was able to generate better gene predictions compared to three HMM-based programs (MAKER2, GlimmerHMM and AUGUSTUS) using their respective available HMMs. Seqping had the highest accuracy in rice (0.5648 for CDS, 0.4468 for exon, and 0.6695 nucleotide structure) and A. thaliana (0.5808 for CDS, 0.5955 for exon, and 0.8839 nucleotide structure). Seqping provides researchers a seamless pipeline to train species-specific HMMs and predict genes in newly sequenced or less-studied genomes. We conclude that the Seqping pipeline predictions are more accurate than gene predictions using the other three approaches with the default or available HMMs.

Historical analysis of US pipeline accidents triggered by natural hazards

NASA Astrophysics Data System (ADS)

Girgin, Serkan; Krausmann, Elisabeth

2015-04-01

Natural hazards, such as earthquakes, floods, landslides, or lightning, can initiate accidents in oil and gas pipelines with potentially major consequences on the population or the environment due to toxic releases, fires and explosions. Accidents of this type are also referred to as Natech events. Many major accidents highlight the risk associated with natural-hazard impact on pipelines transporting dangerous substances. For instance, in the USA in 1994, flooding of the San Jacinto River caused the rupture of 8 and the undermining of 29 pipelines by the floodwaters. About 5.5 million litres of petroleum and related products were spilled into the river and ignited. As a results, 547 people were injured and significant environmental damage occurred. Post-incident analysis is a valuable tool for better understanding the causes, dynamics and impacts of pipeline Natech accidents in support of future accident prevention and mitigation. Therefore, data on onshore hazardous-liquid pipeline accidents collected by the US Pipeline and Hazardous Materials Safety Administration (PHMSA) was analysed. For this purpose, a database-driven incident data analysis system was developed to aid the rapid review and categorization of PHMSA incident reports. Using an automated data-mining process followed by a peer review of the incident records and supported by natural hazard databases and external information sources, the pipeline Natechs were identified. As a by-product of the data-collection process, the database now includes over 800,000 incidents from all causes in industrial and transportation activities, which are automatically classified in the same way as the PHMSA record. This presentation describes the data collection and reviewing steps conducted during the study, provides information on the developed database and data analysis tools, and reports the findings of a statistical analysis of the identified hazardous liquid pipeline incidents in terms of accident dynamics and consequences.

Is it Really a Man's World? Black Men in Science, Technology, Engineering, and Mathematics at Historically Black Colleges and Universities

ERIC Educational Resources Information Center

Lundy-Wagner, Valerie C.

2013-01-01

Efforts to improve the Black science, technology, engineering and mathematics (STEM) pipeline have focused on historically Black colleges and universities (HBCUs); however, this work generally fails to acknowledge men. This article characterized Black male receipts of bachelor's degrees from HBCUs in STEM fields between 1981 and 2009 using a…

The Influence of Female Social Models in Corporate STEM Initiatives on Girls' Math and Science Attitudes

ERIC Educational Resources Information Center

Medeiros, Donald J.

2011-01-01

The United States' Science, Technology, Engineering, and Mathematics (STEM) workforce is growing slower than in the past, in comparison to demand, and in comparison to other countries. Competitive talent conditions require the United States to develop a strong pipeline of STEM talent within its own citizens. Given the number of female college…

Slow off the Mark: Elementary School Teachers and the Crisis in Science, Technology, Engineering, and Math Education

ERIC Educational Resources Information Center

Epstein, Diana; Miller, Raegen T.

2011-01-01

One can't throw a stone without hitting a STEM initiative these days, but most science, technology, engineering, and math initiatives--thus the STEM acronym--overlook a fundamental problem. In general, the workforce pipeline of elementary school teachers fails to ensure that the teachers who inform children's early academic trajectories have the…

The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction.

PubMed

Makropoulos, Antonios; Robinson, Emma C; Schuh, Andreas; Wright, Robert; Fitzgibbon, Sean; Bozek, Jelena; Counsell, Serena J; Steinweg, Johannes; Vecchiato, Katy; Passerat-Palmbach, Jonathan; Lenz, Gregor; Mortari, Filippo; Tenev, Tencho; Duff, Eugene P; Bastiani, Matteo; Cordero-Grande, Lucilio; Hughes, Emer; Tusor, Nora; Tournier, Jacques-Donald; Hutter, Jana; Price, Anthony N; Teixeira, Rui Pedro A G; Murgasova, Maria; Victor, Suresh; Kelly, Christopher; Rutherford, Mary A; Smith, Stephen M; Edwards, A David; Hajnal, Joseph V; Jenkinson, Mark; Rueckert, Daniel

2018-06-01

The Developing Human Connectome Project (dHCP) seeks to create the first 4-dimensional connectome of early life. Understanding this connectome in detail may provide insights into normal as well as abnormal patterns of brain development. Following established best practices adopted by the WU-MINN Human Connectome Project (HCP), and pioneered by FreeSurfer, the project utilises cortical surface-based processing pipelines. In this paper, we propose a fully automated processing pipeline for the structural Magnetic Resonance Imaging (MRI) of the developing neonatal brain. This proposed pipeline consists of a refined framework for cortical and sub-cortical volume segmentation, cortical surface extraction, and cortical surface inflation, which has been specifically designed to address considerable differences between adult and neonatal brains, as imaged using MRI. Using the proposed pipeline our results demonstrate that images collected from 465 subjects ranging from 28 to 45 weeks post-menstrual age (PMA) can be processed fully automatically; generating cortical surface models that are topologically correct, and correspond well with manual evaluations of tissue boundaries in 85% of cases. Results improve on state-of-the-art neonatal tissue segmentation models and significant errors were found in only 2% of cases, where these corresponded to subjects with high motion. Downstream, these surfaces will enhance comparisons of functional and diffusion MRI datasets, supporting the modelling of emerging patterns of brain connectivity. Copyright © 2018 Elsevier Inc. All rights reserved.

Automated processing pipeline for neonatal diffusion MRI in the developing Human Connectome Project.

PubMed

Bastiani, Matteo; Andersson, Jesper L R; Cordero-Grande, Lucilio; Murgasova, Maria; Hutter, Jana; Price, Anthony N; Makropoulos, Antonios; Fitzgibbon, Sean P; Hughes, Emer; Rueckert, Daniel; Victor, Suresh; Rutherford, Mary; Edwards, A David; Smith, Stephen M; Tournier, Jacques-Donald; Hajnal, Joseph V; Jbabdi, Saad; Sotiropoulos, Stamatios N

2018-05-28

The developing Human Connectome Project is set to create and make available to the scientific community a 4-dimensional map of functional and structural cerebral connectivity from 20 to 44 weeks post-menstrual age, to allow exploration of the genetic and environmental influences on brain development, and the relation between connectivity and neurocognitive function. A large set of multi-modal MRI data from fetuses and newborn infants is currently being acquired, along with genetic, clinical and developmental information. In this overview, we describe the neonatal diffusion MRI (dMRI) image processing pipeline and the structural connectivity aspect of the project. Neonatal dMRI data poses specific challenges, and standard analysis techniques used for adult data are not directly applicable. We have developed a processing pipeline that deals directly with neonatal-specific issues, such as severe motion and motion-related artefacts, small brain sizes, high brain water content and reduced anisotropy. This pipeline allows automated analysis of in-vivo dMRI data, probes tissue microstructure, reconstructs a number of major white matter tracts, and includes an automated quality control framework that identifies processing issues or inconsistencies. We here describe the pipeline and present an exemplar analysis of data from 140 infants imaged at 38-44 weeks post-menstrual age. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Microcomputers, software combine to provide daily product, movement inventory

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

Cable, T.

1985-06-01

This paper describes the efforts of Sante Fe Pipelines Inc. in keeping track of product inventory on the 810 mile, 12-in. Chapparal Pipeline and the 1,913 mile, 8- and 10-in. Gulf Central Pipeline. The decision to use a PC for monitoring the inventory was significant. The application was completed by TRON, Inc. The system is actually two major subsystems. The pipeline system accounts for injections into the pipeline and deliveries of product. This feeds the storage and the terminal inventory system where inventories are maintained at storage locations by shipper and supplier account. The paper further explains the inventory monitoringmore » process in detail. Communications software is described as well.« less

Neuroimaging Study Designs, Computational Analyses and Data Provenance Using the LONI Pipeline

PubMed Central

Dinov, Ivo; Lozev, Kamen; Petrosyan, Petros; Liu, Zhizhong; Eggert, Paul; Pierce, Jonathan; Zamanyan, Alen; Chakrapani, Shruthi; Van Horn, John; Parker, D. Stott; Magsipoc, Rico; Leung, Kelvin; Gutman, Boris; Woods, Roger; Toga, Arthur

2010-01-01

Modern computational neuroscience employs diverse software tools and multidisciplinary expertise to analyze heterogeneous brain data. The classical problems of gathering meaningful data, fitting specific models, and discovering appropriate analysis and visualization tools give way to a new class of computational challenges—management of large and incongruous data, integration and interoperability of computational resources, and data provenance. We designed, implemented and validated a new paradigm for addressing these challenges in the neuroimaging field. Our solution is based on the LONI Pipeline environment [3], [4], a graphical workflow environment for constructing and executing complex data processing protocols. We developed study-design, database and visual language programming functionalities within the LONI Pipeline that enable the construction of complete, elaborate and robust graphical workflows for analyzing neuroimaging and other data. These workflows facilitate open sharing and communication of data and metadata, concrete processing protocols, result validation, and study replication among different investigators and research groups. The LONI Pipeline features include distributed grid-enabled infrastructure, virtualized execution environment, efficient integration, data provenance, validation and distribution of new computational tools, automated data format conversion, and an intuitive graphical user interface. We demonstrate the new LONI Pipeline features using large scale neuroimaging studies based on data from the International Consortium for Brain Mapping [5] and the Alzheimer's Disease Neuroimaging Initiative [6]. User guides, forums, instructions and downloads of the LONI Pipeline environment are available at http://pipeline.loni.ucla.edu. PMID:20927408

ESO Advanced Data Products for the Virtual Observatory

NASA Astrophysics Data System (ADS)

Retzlaff, J.; Delmotte, N.; Rite, C.; Rosati, P.; Slijkhuis, R.; Vandame, B.

2006-07-01

Advanced Data Products, that is, completely reduced, fully characterized science-ready data sets, play a crucial role for the success of the Virtual Observatory as a whole. We report on on-going work at ESO towards the creation and publication of Advanced Data Products in compliance with present VO standards on resource metadata. The new deep NIR multi-color mosaic of the GOODS/CDF-S region is used to showcase different aspects of the entire process: data reduction employing our MVM-based reduction pipeline, calibration and data characterization procedures, standardization of metadata content, and, finally, a prospect of the scientific potential illustrated by new results on deep galaxy number counts.

Design and Implementation of CIA, the ISOCAM Interactive Analysis System

NASA Astrophysics Data System (ADS)

Ott, S.; Abergel, A.; Altieri, B.; Augueres, J.-L.; Aussel, H.; Bernard, J.-P.; Biviano, A.; Blommaert, J.; Boulade, O.; Boulanger, F.; Cesarsky, C.; Cesarsky, D. A.; Claret, A.; Delattre, C.; Delaney, M.; Deschamps, T.; Desert, F.-X.; Didelon, P.; Elbaz, D.; Gallais, P.; Gastaud, R.; Guest, S.; Helou, G.; Kong, M.; Lacombe, F.; Li, J.; Landriu, D.; Metcalfe, L.; Okumura, K.; Perault, M.; Pollock, A. M. T.; Rouan, D.; Sam-Lone, J.; Sauvage, M.; Siebenmorgen, R.; Starck, J.-L.; Tran, D.; van Buren, D.; Vigroux, L.; Vivares, F.

This paper presents an overview of the Interactive Analysis System for ISOCAM (CIA). With this system ISOCAM data can be analysed for calibration and engineering purposes, the ISOCAM pipeline software validated and refined, and astronomical data processing can be performed. The system is mainly IDL-based but contains \\fortran, C, and C++ parts for special tasks. It represents an effort of 15 man-years and is comprised of over 1000 IDL and 200 \\fortran, C, and C++ modules. CIA is a joint development by the ESA Astrophysics Division and the ISOCAM Consortium led by the ISOCAM PI, C. Cesarsky, Direction des Sciences de la Matiere, C.E.A., France.

Data processing pipeline for serial femtosecond crystallography at SACLA.

PubMed

Nakane, Takanori; Joti, Yasumasa; Tono, Kensuke; Yabashi, Makina; Nango, Eriko; Iwata, So; Ishitani, Ryuichiro; Nureki, Osamu

2016-06-01

A data processing pipeline for serial femtosecond crystallography at SACLA was developed, based on Cheetah [Barty et al. (2014). J. Appl. Cryst. 47 , 1118-1131] and CrystFEL [White et al. (2016). J. Appl. Cryst. 49 , 680-689]. The original programs were adapted for data acquisition through the SACLA API, thread and inter-node parallelization, and efficient image handling. The pipeline consists of two stages: The first, online stage can analyse all images in real time, with a latency of less than a few seconds, to provide feedback on hit rate and detector saturation. The second, offline stage converts hit images into HDF5 files and runs CrystFEL for indexing and integration. The size of the filtered compressed output is comparable to that of a synchrotron data set. The pipeline enables real-time feedback and rapid structure solution during beamtime.

Proposal and design of a natural gas liquefaction process recovering the energy obtained from the pressure reducing stations of high-pressure pipelines

NASA Astrophysics Data System (ADS)

Tan, Hongbo; Zhao, Qingxuan; Sun, Nannan; Li, Yanzhong

2016-12-01

Taking advantage of the refrigerating effect in the expansion at an appropriate temperature, a fraction of high-pressure natural gas transported by pipelines could be liquefied in a city gate station through a well-organized pressure reducing process without consuming any extra energy. The authors proposed such a new process, which mainly consists of a turbo-expander driven booster, throttle valves, multi-stream heat exchangers and separators, to yield liquefied natural gas (LNG) and liquid light hydrocarbons (LLHs) utilizing the high-pressure of the pipelines. Based on the assessment of the effects of several key parameters on the system performance by a steady-state simulation in Aspen HYSYS, an optimal design condition of the proposed process was determined. The results showed that the new process is more appropriate to be applied in a pressure reducing station (PRS) for the pipelines with higher pressure. For the feed gas at the pressure of 10 MPa, the maximum total liquefaction rate (ytot) of 15.4% and the maximum exergy utilizing rate (EUR) of 21.7% could be reached at the optimal condition. The present process could be used as a small-scale natural gas liquefying and peak-shaving plant at a city gate station.

Jenkins-CI, an Open-Source Continuous Integration System, as a Scientific Data and Image-Processing Platform.

PubMed

Moutsatsos, Ioannis K; Hossain, Imtiaz; Agarinis, Claudia; Harbinski, Fred; Abraham, Yann; Dobler, Luc; Zhang, Xian; Wilson, Christopher J; Jenkins, Jeremy L; Holway, Nicholas; Tallarico, John; Parker, Christian N

2017-03-01

High-throughput screening generates large volumes of heterogeneous data that require a diverse set of computational tools for management, processing, and analysis. Building integrated, scalable, and robust computational workflows for such applications is challenging but highly valuable. Scientific data integration and pipelining facilitate standardized data processing, collaboration, and reuse of best practices. We describe how Jenkins-CI, an "off-the-shelf," open-source, continuous integration system, is used to build pipelines for processing images and associated data from high-content screening (HCS). Jenkins-CI provides numerous plugins for standard compute tasks, and its design allows the quick integration of external scientific applications. Using Jenkins-CI, we integrated CellProfiler, an open-source image-processing platform, with various HCS utilities and a high-performance Linux cluster. The platform is web-accessible, facilitates access and sharing of high-performance compute resources, and automates previously cumbersome data and image-processing tasks. Imaging pipelines developed using the desktop CellProfiler client can be managed and shared through a centralized Jenkins-CI repository. Pipelines and managed data are annotated to facilitate collaboration and reuse. Limitations with Jenkins-CI (primarily around the user interface) were addressed through the selection of helper plugins from the Jenkins-CI community.

Jenkins-CI, an Open-Source Continuous Integration System, as a Scientific Data and Image-Processing Platform

PubMed Central

Moutsatsos, Ioannis K.; Hossain, Imtiaz; Agarinis, Claudia; Harbinski, Fred; Abraham, Yann; Dobler, Luc; Zhang, Xian; Wilson, Christopher J.; Jenkins, Jeremy L.; Holway, Nicholas; Tallarico, John; Parker, Christian N.

2016-01-01

High-throughput screening generates large volumes of heterogeneous data that require a diverse set of computational tools for management, processing, and analysis. Building integrated, scalable, and robust computational workflows for such applications is challenging but highly valuable. Scientific data integration and pipelining facilitate standardized data processing, collaboration, and reuse of best practices. We describe how Jenkins-CI, an “off-the-shelf,” open-source, continuous integration system, is used to build pipelines for processing images and associated data from high-content screening (HCS). Jenkins-CI provides numerous plugins for standard compute tasks, and its design allows the quick integration of external scientific applications. Using Jenkins-CI, we integrated CellProfiler, an open-source image-processing platform, with various HCS utilities and a high-performance Linux cluster. The platform is web-accessible, facilitates access and sharing of high-performance compute resources, and automates previously cumbersome data and image-processing tasks. Imaging pipelines developed using the desktop CellProfiler client can be managed and shared through a centralized Jenkins-CI repository. Pipelines and managed data are annotated to facilitate collaboration and reuse. Limitations with Jenkins-CI (primarily around the user interface) were addressed through the selection of helper plugins from the Jenkins-CI community. PMID:27899692

Tajikistan Country Profile

DTIC Science & Technology

2009-07-01

light industry and therefore was largely an agricultural support base for the economy. Aluminum and uranium production and processing were the major...Tajikistan is not a producer/exporter of energy resources although has oil and natural gas reserves. The country has a pipeline importing natural gas from...Uzbekistan. The country also imports gas from Uzbekistan. The total length of gas pipeline is 549 km and 38 km of oil pipelines. Railroads

A Proposal to Investigate Outstanding Problems in Astronomy

NASA Technical Reports Server (NTRS)

Ford, Holland

2002-01-01

During the period leading up to the spectacular launch of the Space Shuttle Columbia (STS-109) on 1 March 2002 6:22 am EST, the team worked hard on a myriad of tasks to be ready for launch. Our launch support included preparations and rehearsals for the support during the mission, preparation for the SMOV and ERO program, and work to have the science team's data pipeline (APSIS) and data archive (SDA) ready by launch. A core of the team that was at the GSFC during the EVA that installed ACS monitored the turn-on and aliveness tests of ACS. One hour after installation of ACS in the HST George Hartig was showing those of us at Goddard the telemetry which demonstrated that the HRC and WFC CCDs were cooling to their preset temperatures. The TECs had survived launch! After launch, the team had several immediate and demanding tasks. We had to process the ERO observations through our pipeline and understand the limitations of the ground based-based calibrations, and simultaneously prepare the EROs for public release. The ERO images and the SMOV calibrations demonstrated that ACS met or exceeded its specifications for image quality and sensitivity. It is the most sensitive instrument that Hubble has had. The ERO images themselves made the front page of all of the major newspapers in the US. During the months after launch we have worked on the SMOV observations, and are analyzing the data from our science program.

Forecasting and Evaluation of Gas Pipelines Geometric Forms Breach Hazard

NASA Astrophysics Data System (ADS)

Voronin, K. S.

2016-10-01

Main gas pipelines during operation are under the influence of the permanent pressure drops which leads to their lengthening and as a result, to instability of their position in space. In dynamic systems that have feedback, phenomena, preceding emergencies, should be observed. The article discusses the forced vibrations of the gas pipeline cylindrical surface under the influence of dynamic loads caused by pressure surges, and the process of its geometric shape deformation. Frequency of vibrations, arising in the pipeline at the stage preceding its bending, is being determined. Identification of this frequency can be the basis for the development of a method of monitoring the technical condition of the gas pipeline, and forecasting possible emergency situations allows planning and carrying out in due time reconstruction works on sections of gas pipeline with a possible deviation from the design position.

The initial data products from the EUVE software - A photon's journey through the End-to-End System

NASA Technical Reports Server (NTRS)

Antia, Behram

1993-01-01

The End-to-End System (EES) is a unique collection of software modules created for use at the Center for EUV Astrophysics. The 'pipeline' is a shell script which executes selected EES modules and creates initial data products: skymaps, data sets for individual sources (called 'pigeonholes') and catalogs of sources. This article emphasizes the data from the all-sky survey, conducted between July 22, 1992 and January 21, 1993. A description of each of the major data products will be given and, as an example of how the pipeline works, the reader will follow a photon's path through the software pipeline into a pigeonhole. These data products are the primary goal of the EUVE all-sky survey mission, and so their relative importance for the follow-up science will also be discussed.

16 CFR 802.3 - Acquisitions of carbon-based mineral reserves.

Code of Federal Regulations, 2014 CFR

2014-01-01

... gas, shale or tar sands, or rights to reserves of oil, natural gas, shale or tar sands together with... gas, shale or tar sands, or rights to reserves of oil, natural gas, shale or tar sands and associated... pipeline and pipeline system or processing facility which transports or processes oil and gas after it...

16 CFR 802.3 - Acquisitions of carbon-based mineral reserves.

Code of Federal Regulations, 2010 CFR

2010-01-01

... gas, shale or tar sands, or rights to reserves of oil, natural gas, shale or tar sands together with... gas, shale or tar sands, or rights to reserves of oil, natural gas, shale or tar sands and associated... pipeline and pipeline system or processing facility which transports or processes oil and gas after it...

16 CFR 802.3 - Acquisitions of carbon-based mineral reserves.

Code of Federal Regulations, 2013 CFR

2013-01-01

... gas, shale or tar sands, or rights to reserves of oil, natural gas, shale or tar sands together with... gas, shale or tar sands, or rights to reserves of oil, natural gas, shale or tar sands and associated... pipeline and pipeline system or processing facility which transports or processes oil and gas after it...

16 CFR 802.3 - Acquisitions of carbon-based mineral reserves.

Code of Federal Regulations, 2012 CFR

2012-01-01

... gas, shale or tar sands, or rights to reserves of oil, natural gas, shale or tar sands together with... gas, shale or tar sands, or rights to reserves of oil, natural gas, shale or tar sands and associated... pipeline and pipeline system or processing facility which transports or processes oil and gas after it...

16 CFR 802.3 - Acquisitions of carbon-based mineral reserves.

Code of Federal Regulations, 2011 CFR

2011-01-01

... gas, shale or tar sands, or rights to reserves of oil, natural gas, shale or tar sands together with... gas, shale or tar sands, or rights to reserves of oil, natural gas, shale or tar sands and associated... pipeline and pipeline system or processing facility which transports or processes oil and gas after it...

18 CFR 157.21 - Pre-filing procedures and review process for LNG terminal facilities and other natural gas...

Code of Federal Regulations, 2010 CFR

2010-04-01

... the pre-filing review of any pipeline or other natural gas facilities, including facilities not... from the subject LNG terminal facilities to the existing natural gas pipeline infrastructure. (b) Other... and review process for LNG terminal facilities and other natural gas facilities prior to filing of...

Planck 2015 results: II. Low Frequency Instrument data processings

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

Ade, P. A. R.; Aghanim, N.; Ashdown, M.

In this paper, we present an updated description of the Planck Low Frequency Instrument (LFI) data processing pipeline, associated with the 2015 data release. We point out the places where our results and methods have remained unchanged since the 2013 paper and we highlight the changes made for the 2015 release, describing the products (especially timelines) and the ways in which they were obtained. We demonstrate that the pipeline is self-consistent (principally based on simulations) and report all null tests. For the first time, we present LFI maps in Stokes Q and U polarization. Finally, we refer to other relatedmore » papers where more detailed descriptions of the LFI data processing pipeline may be found if needed.« less

Planck 2015 results: II. Low Frequency Instrument data processings

DOE PAGES

Ade, P. A. R.; Aghanim, N.; Ashdown, M.; ...

2016-09-20

In this paper, we present an updated description of the Planck Low Frequency Instrument (LFI) data processing pipeline, associated with the 2015 data release. We point out the places where our results and methods have remained unchanged since the 2013 paper and we highlight the changes made for the 2015 release, describing the products (especially timelines) and the ways in which they were obtained. We demonstrate that the pipeline is self-consistent (principally based on simulations) and report all null tests. For the first time, we present LFI maps in Stokes Q and U polarization. Finally, we refer to other relatedmore » papers where more detailed descriptions of the LFI data processing pipeline may be found if needed.« less

Comparison of a semi-automatic annotation tool and a natural language processing application for the generation of clinical statement entries.

PubMed

Lin, Ching-Heng; Wu, Nai-Yuan; Lai, Wei-Shao; Liou, Der-Ming

2015-01-01

Electronic medical records with encoded entries should enhance the semantic interoperability of document exchange. However, it remains a challenge to encode the narrative concept and to transform the coded concepts into a standard entry-level document. This study aimed to use a novel approach for the generation of entry-level interoperable clinical documents. Using HL7 clinical document architecture (CDA) as the example, we developed three pipelines to generate entry-level CDA documents. The first approach was a semi-automatic annotation pipeline (SAAP), the second was a natural language processing (NLP) pipeline, and the third merged the above two pipelines. We randomly selected 50 test documents from the i2b2 corpora to evaluate the performance of the three pipelines. The 50 randomly selected test documents contained 9365 words, including 588 Observation terms and 123 Procedure terms. For the Observation terms, the merged pipeline had a significantly higher F-measure than the NLP pipeline (0.89 vs 0.80, p<0.0001), but a similar F-measure to that of the SAAP (0.89 vs 0.87). For the Procedure terms, the F-measure was not significantly different among the three pipelines. The combination of a semi-automatic annotation approach and the NLP application seems to be a solution for generating entry-level interoperable clinical documents. © The Author 2014. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.comFor numbered affiliation see end of article.

Strategies for Building a Reliable, Diverse Pipeline of Earth Data Scientists

NASA Astrophysics Data System (ADS)

Fowler, R.; Robinson, E.

2015-12-01

The grand challenges facing the geosciences are increasingly data-driven and require large-scale collaboration. Today's geoscience community is primarily self-taught or peer-taught as neither data science nor collaborative skills are traditionally part of the geoscience curriculum. This is not a sustainable model. By increasing understanding of the role of data science and collaboration in the geosciences, and Earth and space science informatics, an increased number of students pursuing STEM degrees may choose careers in these fields. Efforts to build a reliable pipeline of future Earth data scientists must incorporate the following: (1) improved communication: covering not only what data science is, but what a data scientist working in the geosciences does and the impact their work has; (2) effective identification and promotion of the skills and knowledge needed, including possible academic and career paths, the availability and types of jobs in the geosciences, and how to develop the necessary skills for these careers; (3) the employment of recruitment and engagement strategies that result in a diverse data science workforce, especially the recruitment and inclusion of underrepresented minority students; and (4) changing organizational cultures to better retain and advance women and other minority groups in data science. In this presentation we'll discuss strategies to increase the number of women and underrepresented minority students pursuing careers in data science, with an emphasis on effective strategies for recruiting and mentoring these groups, as well as challenges faced and lessons learned.

Strain-Based Design Methodology of Large Diameter Grade X80 Linepipe

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

Lower, Mark D.

2014-04-01

Continuous growth in energy demand is driving oil and natural gas production to areas that are often located far from major markets where the terrain is prone to earthquakes, landslides, and other types of ground motion. Transmission pipelines that cross this type of terrain can experience large longitudinal strains and plastic circumferential elongation as the pipeline experiences alignment changes resulting from differential ground movement. Such displacements can potentially impact pipeline safety by adversely affecting structural capacity and leak tight integrity of the linepipe steel. Planning for new long-distance transmission pipelines usually involves consideration of higher strength linepipe steels because theirmore » use allows pipeline operators to reduce the overall cost of pipeline construction and increase pipeline throughput by increasing the operating pressure. The design trend for new pipelines in areas prone to ground movement has evolved over the last 10 years from a stress-based design approach to a strain-based design (SBD) approach to further realize the cost benefits from using higher strength linepipe steels. This report presents an overview of SBD for pipelines subjected to large longitudinal strain and high internal pressure with emphasis on the tensile strain capacity of high-strength microalloyed linepipe steel. The technical basis for this report involved engineering analysis and examination of the mechanical behavior of Grade X80 linepipe steel in both the longitudinal and circumferential directions. Testing was conducted to assess effects on material processing including as-rolled, expanded, and heat treatment processing intended to simulate coating application. Elastic-plastic and low-cycle fatigue analyses were also performed with varying internal pressures. Proposed SBD models discussed in this report are based on classical plasticity theory and account for material anisotropy, triaxial strain, and microstructural damage effects developed from test data. The results are intended to enhance SBD and analysis methods for producing safe and cost effective pipelines capable of accommodating large plastic strains in seismically active arctic areas.« less

MIRATE: MIps RATional dEsign Science Gateway.

PubMed

Busato, Mirko; Distefano, Rosario; Bates, Ferdia; Karim, Kal; Bossi, Alessandra Maria; López Vilariño, José Manuel; Piletsky, Sergey; Bombieri, Nicola; Giorgetti, Alejandro

2018-06-13

Molecularly imprinted polymers (MIPs) are high affinity robust synthetic receptors, which can be optimally synthesized and manufactured more economically than their biological equivalents (i.e. antibody). In MIPs production, rational design based on molecular modeling is a commonly employed technique. This mostly aids in (i) virtual screening of functional monomers (FMs), (ii) optimization of monomer-template ratio, and (iii) selectivity analysis. We present MIRATE, an integrated science gateway for the intelligent design of MIPs. By combining and adapting multiple state-of-the-art bioinformatics tools into automated and innovative pipelines, MIRATE guides the user through the entire process of MIPs' design. The platform allows the user to fully customize each stage involved in the MIPs' design, with the main goal to support the synthesis in the wet-laboratory. MIRATE is freely accessible with no login requirement at http://mirate.di.univr.it/. All major browsers are supported.

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

Mainzer, A.; Masiero, J.; Bauer, J.

Enhancements to the science data processing pipeline of NASA's Wide-field Infrared Survey Explorer (WISE) mission, collectively known as NEOWISE, resulted in the detection of >158,000 minor planets in four infrared wavelengths during the fully cryogenic portion of the mission. Following the depletion of its cryogen, NASA's Planetary Science Directorate funded a four-month extension to complete the survey of the inner edge of the Main Asteroid Belt and to detect and discover near-Earth objects (NEOs). This extended survey phase, known as the NEOWISE Post-Cryogenic Survey, resulted in the detection of {approx}6500 large Main Belt asteroids and 86 NEOs in its 3.4more » and 4.6 {mu}m channels. During the Post-Cryogenic Survey, NEOWISE discovered and detected a number of asteroids co-orbital with the Earth and Mars, including the first known Earth Trojan. We present preliminary thermal fits for these and other NEOs detected during the 3-Band Cryogenic and Post-Cryogenic Surveys.« less

Reasons for decision in the matter of Maritimes and Northeast Pipeline Management Ltd. application dated 24 February 1998 for approval of the plan, profile and book of reference respecting the detailed pipeline route from Goldboro, N.S. to St. Stephen, N.B.: MH-3-98

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

NONE

1998-12-31

In December 1997, Maritimes and Northeast Pipeline Management Ltd. received approval to construct and operate a natural gas pipeline consisting of about 558 kilometers of 762-millimeter pipe to be located within a one-kilometer-wide corridor extending from Goldboro, Nova Scotia to the international border near St. Stephen, New Brunswick. This report covers the second stage of the pipeline approval process where the detailed route is determined. It presents the views of the pipeline company, various landowners and mineral rights holders objecting to the proposed detailed route, and the National Energy Board with regard to two issues: The best possible detailed routemore » for the pipeline, and the most appropriate methods and timing of constructing the pipeline. Specific land/mineral rights owner cases including the nature of the objection, possible alternate routes, and the Board decision in each case are described.« less

Limitations on diversity in basic science departments.

PubMed

Leboy, Phoebe S; Madden, Janice F

2012-08-01

It has been over 30 years since the beginning of efforts to improve diversity in academia. We can identify four major stages: (1) early and continuing efforts to diversify the pipeline by increasing numbers of women and minorities getting advanced degrees, particularly in science, technology, engineering, and math (STEM); (2) requiring academic institutions to develop their own "affirmative action plans" for hiring and promotion; (3) introducing mentoring programs and coping strategies to help women and minorities deal with faculty practices from an earlier era; (4) asking academic institutions to rethink their practices and policies with an eye toward enabling more faculty diversity, a process known as institutional transformation. The thesis of this article is that research-intensive basic science departments of highly ranked U.S. medical schools are stuck at stage 3, resulting in a less diverse tenured and tenure-track faculty than seen in well-funded science departments of major universities. A review of Web-based records of research-intensive departments in universities with both medical school and nonmedical school departments indicates that the proportion of women and Black faculty in science departments of medical schools is lower than the proportion in similarly research-intensive university science departments. Expectations for faculty productivity in research-intensive medical school departments versus university-based departments may lead to these differences in faculty diversity.

The Henry Cecil Ranson McBay Chair in Space Science

NASA Technical Reports Server (NTRS)

Bota, Kofi B.; King, James, Jr.

1999-01-01

The goals and objectives of the Henry Cecil Ransom McBay Chair in Space Sciences were to: (1) provide leadership in developing and expanding Space Science curriculum; (2) contribute to the research and education endeavors of NASA's Mission to Planet Earth program; (3) expand opportunities for education and hands-on research in Space and Earth Sciences; (4) enhance scientific and technological literacy at all educational levels and to increase awareness of opportunities in the Space Sciences; and (5) develop a pipeline, starting with high school, of African American students who will develop into a cadre of well-trained scientists with interest in Space Science Research and Development.

PICARD - A PIpeline for Combining and Analyzing Reduced Data

NASA Astrophysics Data System (ADS)

Gibb, Andrew G.; Jenness, Tim; Economou, Frossie

PICARD is a facility for combining and analyzing reduced data, normally the output from the ORAC-DR data reduction pipeline. This document describes an introduction to using PICARD for processing instrument-independent data.

The Chandra X-ray Center data system: supporting the mission of the Chandra X-ray Observatory

NASA Astrophysics Data System (ADS)

Evans, Janet D.; Cresitello-Dittmar, Mark; Doe, Stephen; Evans, Ian; Fabbiano, Giuseppina; Germain, Gregg; Glotfelty, Kenny; Hall, Diane; Plummer, David; Zografou, Panagoula

2006-06-01

The Chandra X-ray Center Data System provides end-to-end scientific software support for Chandra X-ray Observatory mission operations. The data system includes the following components: (1) observers' science proposal planning tools; (2) science mission planning tools; (3) science data processing, monitoring, and trending pipelines and tools; and (4) data archive and database management. A subset of the science data processing component is ported to multiple platforms and distributed to end-users as a portable data analysis package. Web-based user tools are also available for data archive search and retrieval. We describe the overall architecture of the data system and its component pieces, and consider the design choices and their impacts on maintainability. We discuss the many challenges involved in maintaining a large, mission-critical software system with limited resources. These challenges include managing continually changing software requirements and ensuring the integrity of the data system and resulting data products while being highly responsive to the needs of the project. We describe our use of COTS and OTS software at the subsystem and component levels, our methods for managing multiple release builds, and adapting a large code base to new hardware and software platforms. We review our experiences during the life of the mission so-far, and our approaches for keeping a small, but highly talented, development team engaged during the maintenance phase of a mission.

Sparking connections: An exploration of adolescent girls' relationships with science

NASA Astrophysics Data System (ADS)

Wheeler, Kathryn A.

Despite progress in narrowing the gender gap, fewer women than men pursue science careers. Adolescence is a critical age when girls' science interest is sparked or smothered. Prior research provides data on who drops out of the "science pipeline" and when, but few studies examine why and how girls disconnect from science. This thesis is an in-depth exploratory study of adolescent girls' relationships with science based on a series of interviews with four middle-class Caucasian girls---two from public schools, two homeschooled. The girls' stones about their experiences with, feelings about, and perspectives on science, the science process, and their science learning environments are examined with a theoretical and analytic approach grounded in relational psychology. The potential link between girls' voices and their involvement in science is investigated. Results indicate that girls' relationships with science are multitiered. Science is engaging and familiar in the sense that girls are curious about the world, enjoy learning about scientific phenomena, and informally use science in their everyday fives. However, the girls in this study differentiated between the science they do and the field of science, which they view as a mostly male endeavor (often despite real life experiences to the contrary) that uses rather rigid methods to investigate questions of limited scope and interest. In essence, how these girls defined science defined their relationship with science: those with narrow conceptions of science felt distant from it. Adolescent girls' decreased involvement in science activities may be a relational act---a move away from a patriarchical process, pedagogy, and institution that does not resonate with their experiences, questions, and learning styles. Girls often feel like outsiders to science; they resist considering science careers when they have concerns that implicitly or explicitly, doing so would involve sacrificing their knowledge, creativity, or relationships. Girls become disenchanted; they lose confidence not in themselves, but in science. Implication for pedagogy and policy center on paying attention to girls' feelings about science; portraying and practicing science broadly; and fostering growth-enhancing relationships and spaces where girls can have a voice in science.

Natural Gas Pipeline Permitting Reform Act

THOMAS, 113th Congress

Rep. Pompeo, Mike [R-KS-4

2013-05-09

Senate - 12/09/2013 Received in the Senate and Read twice and referred to the Committee on Commerce, Science, and Transportation. (All Actions) Tracker: This bill has the status Passed HouseHere are the steps for Status of Legislation:

Large-Scale Sentinel-1 Processing for Solid Earth Science and Urgent Response using Cloud Computing and Machine Learning

NASA Astrophysics Data System (ADS)

Hua, H.; Owen, S. E.; Yun, S. H.; Agram, P. S.; Manipon, G.; Starch, M.; Sacco, G. F.; Bue, B. D.; Dang, L. B.; Linick, J. P.; Malarout, N.; Rosen, P. A.; Fielding, E. J.; Lundgren, P.; Moore, A. W.; Liu, Z.; Farr, T.; Webb, F.; Simons, M.; Gurrola, E. M.

2017-12-01

With the increased availability of open SAR data (e.g. Sentinel-1 A/B), new challenges are being faced with processing and analyzing the voluminous SAR datasets to make geodetic measurements. Upcoming SAR missions such as NISAR are expected to generate close to 100TB per day. The Advanced Rapid Imaging and Analysis (ARIA) project can now generate geocoded unwrapped phase and coherence products from Sentinel-1 TOPS mode data in an automated fashion, using the ISCE software. This capability is currently being exercised on various study sites across the United States and around the globe, including Hawaii, Central California, Iceland and South America. The automated and large-scale SAR data processing and analysis capabilities use cloud computing techniques to speed the computations and provide scalable processing power and storage. Aspects such as how to processing these voluminous SLCs and interferograms at global scales, keeping up with the large daily SAR data volumes, and how to handle the voluminous data rates are being explored. Scene-partitioning approaches in the processing pipeline help in handling global-scale processing up to unwrapped interferograms with stitching done at a late stage. We have built an advanced science data system with rapid search functions to enable access to the derived data products. Rapid image processing of Sentinel-1 data to interferograms and time series is already being applied to natural hazards including earthquakes, floods, volcanic eruptions, and land subsidence due to fluid withdrawal. We will present the status of the ARIA science data system for generating science-ready data products and challenges that arise from being able to process SAR datasets to derived time series data products at large scales. For example, how do we perform large-scale data quality screening on interferograms? What approaches can be used to minimize compute, storage, and data movement costs for time series analysis in the cloud? We will also present some of our findings from applying machine learning and data analytics on the processed SAR data streams. We will also present lessons learned on how to ease the SAR community onto interfacing with these cloud-based SAR science data systems.

Trans-Proteomic Pipeline, a standardized data processing pipeline for large-scale reproducible proteomics informatics

PubMed Central

Deutsch, Eric W.; Mendoza, Luis; Shteynberg, David; Slagel, Joseph; Sun, Zhi; Moritz, Robert L.

2015-01-01

Democratization of genomics technologies has enabled the rapid determination of genotypes. More recently the democratization of comprehensive proteomics technologies is enabling the determination of the cellular phenotype and the molecular events that define its dynamic state. Core proteomic technologies include mass spectrometry to define protein sequence, protein:protein interactions, and protein post-translational modifications. Key enabling technologies for proteomics are bioinformatic pipelines to identify, quantitate, and summarize these events. The Trans-Proteomics Pipeline (TPP) is a robust open-source standardized data processing pipeline for large-scale reproducible quantitative mass spectrometry proteomics. It supports all major operating systems and instrument vendors via open data formats. Here we provide a review of the overall proteomics workflow supported by the TPP, its major tools, and how it can be used in its various modes from desktop to cloud computing. We describe new features for the TPP, including data visualization functionality. We conclude by describing some common perils that affect the analysis of tandem mass spectrometry datasets, as well as some major upcoming features. PMID:25631240

Leak detection in gas pipeline by acoustic and signal processing - A review

NASA Astrophysics Data System (ADS)

Adnan, N. F.; Ghazali, M. F.; Amin, M. M.; Hamat, A. M. A.

2015-12-01

The pipeline system is the most important part in media transport in order to deliver fluid to another station. The weak maintenance and poor safety will contribute to financial losses in term of fluid waste and environmental impacts. There are many classifications of techniques to make it easier to show their specific method and application. This paper's discussion about gas leak detection in pipeline system using acoustic method will be presented in this paper. The wave propagation in the pipeline is a key parameter in acoustic method when the leak occurs and the pressure balance of the pipe will generated by the friction between wall in the pipe. The signal processing is used to decompose the raw signal and show in time- frequency. Findings based on the acoustic method can be used for comparative study in the future. Acoustic signal and HHT is the best method to detect leak in gas pipelines. More experiments and simulation need to be carried out to get the fast result of leaking and estimation of their location.

Trans-Proteomic Pipeline, a standardized data processing pipeline for large-scale reproducible proteomics informatics.

PubMed

Deutsch, Eric W; Mendoza, Luis; Shteynberg, David; Slagel, Joseph; Sun, Zhi; Moritz, Robert L

2015-08-01

Democratization of genomics technologies has enabled the rapid determination of genotypes. More recently the democratization of comprehensive proteomics technologies is enabling the determination of the cellular phenotype and the molecular events that define its dynamic state. Core proteomic technologies include MS to define protein sequence, protein:protein interactions, and protein PTMs. Key enabling technologies for proteomics are bioinformatic pipelines to identify, quantitate, and summarize these events. The Trans-Proteomics Pipeline (TPP) is a robust open-source standardized data processing pipeline for large-scale reproducible quantitative MS proteomics. It supports all major operating systems and instrument vendors via open data formats. Here, we provide a review of the overall proteomics workflow supported by the TPP, its major tools, and how it can be used in its various modes from desktop to cloud computing. We describe new features for the TPP, including data visualization functionality. We conclude by describing some common perils that affect the analysis of MS/MS datasets, as well as some major upcoming features. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Pipeline for 3D Digital Optical Phenotyping Plant Root System Architecture

NASA Astrophysics Data System (ADS)

Davis, T. W.; Shaw, N. M.; Schneider, D. J.; Shaff, J. E.; Larson, B. G.; Craft, E. J.; Liu, Z.; Kochian, L. V.; Piñeros, M. A.

2017-12-01

This work presents a new pipeline for digital optical phenotyping the root system architecture of agricultural crops. The pipeline begins with a 3D root-system imaging apparatus for hydroponically grown crop lines of interest. The apparatus acts as a self-containing dark room, which includes an imaging tank, motorized rotating bearing and digital camera. The pipeline continues with the Plant Root Imaging and Data Acquisition (PRIDA) software, which is responsible for image capturing and storage. Once root images have been captured, image post-processing is performed using the Plant Root Imaging Analysis (PRIA) command-line tool, which extracts root pixels from color images. Following the pre-processing binarization of digital root images, 3D trait characterization is performed using the next-generation RootReader3D software. RootReader3D measures global root system architecture traits, such as total root system volume and length, total number of roots, and maximum rooting depth and width. While designed to work together, the four stages of the phenotyping pipeline are modular and stand-alone, which provides flexibility and adaptability for various research endeavors.

FMAP: Functional Mapping and Analysis Pipeline for metagenomics and metatranscriptomics studies.

PubMed

Kim, Jiwoong; Kim, Min Soo; Koh, Andrew Y; Xie, Yang; Zhan, Xiaowei

2016-10-10

Given the lack of a complete and comprehensive library of microbial reference genomes, determining the functional profile of diverse microbial communities is challenging. The available functional analysis pipelines lack several key features: (i) an integrated alignment tool, (ii) operon-level analysis, and (iii) the ability to process large datasets. Here we introduce our open-sourced, stand-alone functional analysis pipeline for analyzing whole metagenomic and metatranscriptomic sequencing data, FMAP (Functional Mapping and Analysis Pipeline). FMAP performs alignment, gene family abundance calculations, and statistical analysis (three levels of analyses are provided: differentially-abundant genes, operons and pathways). The resulting output can be easily visualized with heatmaps and functional pathway diagrams. FMAP functional predictions are consistent with currently available functional analysis pipelines. FMAP is a comprehensive tool for providing functional analysis of metagenomic/metatranscriptomic sequencing data. With the added features of integrated alignment, operon-level analysis, and the ability to process large datasets, FMAP will be a valuable addition to the currently available functional analysis toolbox. We believe that this software will be of great value to the wider biology and bioinformatics communities.

Physical and numerical modeling of hydrophysical proceses on the site of underwater pipelines

NASA Astrophysics Data System (ADS)

Garmakova, M. E.; Degtyarev, V. V.; Fedorova, N. N.; Shlychkov, V. A.

2018-03-01

The paper outlines issues related to ensuring the exploitation safety of underwater pipelines that are at risk of accidents. The performed research is based on physical and mathematical modeling of local bottom erosion in the area of pipeline location. The experimental studies were performed on the basis of the Hydraulics Laboratory of the Department of Hydraulic Engineering Construction, Safety and Ecology of NSUACE (Sibstrin). In the course of physical experiments it was revealed that the intensity of the bottom soil reforming depends on the deepening of the pipeline. The ANSYS software has been used for numerical modeling. The process of erosion of the sandy bottom was modeled under the pipeline. Comparison of computational results at various mass flow rates was made.

Navigating the Science, Technology, Engineering, and Mathematics Pipeline: How Social Capital Impacts the Educational Attainment of College-Bound Female Students

ERIC Educational Resources Information Center

Lee, Rebecca Elizabeth

2011-01-01

Despite the proliferation of women in higher education and the workforce, they have yet to achieve parity with men in many of the science, technology, engineering, and math (STEM) majors and careers. The gap is even greater in the representation of women from lower socioeconomic backgrounds. This study examined pre-college intervention strategies…

Apprenticeship of Immersion: College Access for High School Students Interested in Teaching Mathematics or Science

ERIC Educational Resources Information Center

Harkness, Shelly Sheats; Johnson, Iris DeLoach; Hensley, Billy; Stallworth, James A.

2011-01-01

Issues related to college access and the need for a pipeline of STEM teachers, provided the impetus for the Ohio Board of Regents (OBR) to issue a call for Ohio universities to design pre-college experiences for high school students with three major goals in mind: (a) improvement in mathematics, science, or foreign language learning; (b) increased…

Improving Graduate Education to Support a Branching Career Pipeline: Recommendations Based on a Survey of Doctoral Students in the Basic Biomedical Sciences

ERIC Educational Resources Information Center

Fuhrmann, C. N.; Halme, D. G.; O'Sullivan, P. S.; Lindstaedt, B.

2011-01-01

Today's doctoral programs continue to prepare students for a traditional academic career path despite the inadequate supply of research-focused faculty positions. We advocate for a broader doctoral curriculum that prepares trainees for a wide range of science-related career paths. In support of this argument, we describe data from our survey of…

Role of Community and Technical Colleges in Producing Nursing Graduates: Rethinking the Pipeline for Guided Pathways. Research Report 17-1

ERIC Educational Resources Information Center

Washington State Board for Community and Technical Colleges, 2017

2017-01-01

Though it is still possible to enter the nursing profession with a Licensed Practical Nursing Certificate (LPN) or an Associate's Degree in Nursing (ADN), it is becoming increasingly necessary to get a Bachelor of Science in Nursing (BSN) in order to be assured of continued employment. The Associate in Applied Science-T Nursing Degree prepares…

Kepler Planet Detection Metrics: Pixel-Level Transit Injection Tests of Pipeline Detection Efficiency for Data Release 25

NASA Technical Reports Server (NTRS)

Christiansen, Jessie L.

2017-01-01

This document describes the results of the fourth pixel-level transit injection experiment, which was designed to measure the detection efficiency of both the Kepler pipeline (Jenkins 2002, 2010; Jenkins et al. 2017) and the Robovetter (Coughlin 2017). Previous transit injection experiments are described in Christiansen et al. (2013, 2015a,b, 2016).In order to calculate planet occurrence rates using a given Kepler planet catalogue, produced with a given version of the Kepler pipeline, we need to know the detection efficiency of that pipeline. This can be empirically determined by injecting a suite of simulated transit signals into the Kepler data, processing the data through the pipeline, and examining the distribution of successfully recovered transits. This document describes the results for the pixel-level transit injection experiment performed to accompany the final Q1-Q17 Data Release 25 (DR25) catalogue (Thompson et al. 2017)of the Kepler Objects of Interest. The catalogue was generated using the SOC pipeline version 9.3 and the DR25 Robovetter acting on the uniformly processed Q1-Q17 DR25 light curves (Thompson et al. 2016a) and assuming the Q1-Q17 DR25 Kepler stellar properties (Mathur et al. 2017).

A Comparison between the Decimated Padé Approximant and Decimated Signal Diagonalization Methods for Leak Detection in Pipelines Equipped with Pressure Sensors.

PubMed

Lay-Ekuakille, Aimé; Fabbiano, Laura; Vacca, Gaetano; Kitoko, Joël Kidiamboko; Kulapa, Patrice Bibala; Telesca, Vito

2018-06-04

Pipelines conveying fluids are considered strategic infrastructures to be protected and maintained. They generally serve for transportation of important fluids such as drinkable water, waste water, oil, gas, chemicals, etc. Monitoring and continuous testing, especially on-line, are necessary to assess the condition of pipelines. The paper presents findings related to a comparison between two spectral response algorithms based on the decimated signal diagonalization (DSD) and decimated Padé approximant (DPA) techniques that allow to one to process signals delivered by pressure sensors mounted on an experimental pipeline.

Intermediate Palomar Transient Factory: Realtime Image Subtraction Pipeline

DOE PAGES

Cao, Yi; Nugent, Peter E.; Kasliwal, Mansi M.

2016-09-28

A fast-turnaround pipeline for realtime data reduction plays an essential role in discovering and permitting followup observations to young supernovae and fast-evolving transients in modern time-domain surveys. In this paper, we present the realtime image subtraction pipeline in the intermediate Palomar Transient Factory. By using highperformance computing, efficient databases, and machine-learning algorithms, this pipeline manages to reliably deliver transient candidates within 10 minutes of images being taken. Our experience in using high-performance computing resources to process big data in astronomy serves as a trailblazer to dealing with data from large-scale time-domain facilities in the near future.

Intermediate Palomar Transient Factory: Realtime Image Subtraction Pipeline

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

Cao, Yi; Nugent, Peter E.; Kasliwal, Mansi M.

A fast-turnaround pipeline for realtime data reduction plays an essential role in discovering and permitting followup observations to young supernovae and fast-evolving transients in modern time-domain surveys. In this paper, we present the realtime image subtraction pipeline in the intermediate Palomar Transient Factory. By using highperformance computing, efficient databases, and machine-learning algorithms, this pipeline manages to reliably deliver transient candidates within 10 minutes of images being taken. Our experience in using high-performance computing resources to process big data in astronomy serves as a trailblazer to dealing with data from large-scale time-domain facilities in the near future.

VPipe: Virtual Pipelining for Scheduling of DAG Stream Query Plans

NASA Astrophysics Data System (ADS)

Wang, Song; Gupta, Chetan; Mehta, Abhay

There are data streams all around us that can be harnessed for tremendous business and personal advantage. For an enterprise-level stream processing system such as CHAOS [1] (Continuous, Heterogeneous Analytic Over Streams), handling of complex query plans with resource constraints is challenging. While several scheduling strategies exist for stream processing, efficient scheduling of complex DAG query plans is still largely unsolved. In this paper, we propose a novel execution scheme for scheduling complex directed acyclic graph (DAG) query plans with meta-data enriched stream tuples. Our solution, called Virtual Pipelined Chain (or VPipe Chain for short), effectively extends the "Chain" pipelining scheduling approach to complex DAG query plans.

DPPP: Default Pre-Processing Pipeline

NASA Astrophysics Data System (ADS)

van Diepen, Ger; Dijkema, Tammo Jan

2018-04-01

DPPP (Default Pre-Processing Pipeline, also referred to as NDPPP) reads and writes radio-interferometric data in the form of Measurement Sets, mainly those that are created by the LOFAR telescope. It goes through visibilities in time order and contains standard operations like averaging, phase-shifting and flagging bad stations. Between the steps in a pipeline, the data is not written to disk, making this tool suitable for operations where I/O dominates. More advanced procedures such as gain calibration are also included. Other computing steps can be provided by loading a shared library; currently supported external steps are the AOFlagger (ascl:1010.017) and a bridge that enables loading python steps.

The visual and radiological inspection of a pipeline using a teleoperated pipe crawler

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

Fogle, R.F.; Kuelske, K.; Kellner, R.A.

1996-07-01

In the 1950s the Savannah River Site built an open, unlined retention basin for temporary storage of potentially radionuclide-contaminated cooling water form a chemical separations process and storm water drainage from a nearby waste management facility which stored large quantities of nuclear fission by-products in carbon steel tanks. An underground process pipeline lead to the basin. Once the closure of the basin in 1972, further assessment has been required. A visual and radiological inspection of the pipeline was necessary to aid in the decision about further remediation. This article describes the inspection using a teleoperated pipe crawler. 5 figs.

Implementation of quality by design toward processing of food products.

PubMed

Rathore, Anurag S; Kapoor, Gautam

2017-05-28

Quality by design (QbD) is a systematic approach that begins with predefined objectives and emphasizes product and process understanding and process control. It is an approach based on principles of sound science and quality risk management. As the food processing industry continues to embrace the idea of in-line, online, and/or at-line sensors and real-time characterization for process monitoring and control, the existing gaps with regard to our ability to monitor multiple parameters/variables associated with the manufacturing process will be alleviated over time. Investments made for development of tools and approaches that facilitate high-throughput analytical and process development, process analytical technology, design of experiments, risk analysis, knowledge management, and enhancement of process/product understanding would pave way for operational and economic benefits later in the commercialization process and across other product pipelines. This article aims to achieve two major objectives. First, to review the progress that has been made in the recent years on the topic of QbD implementation in processing of food products and second, present a case study that illustrates benefits of such QbD implementation.

Virtual Instrumentation Corrosion Controller for Natural Gas Pipelines

NASA Astrophysics Data System (ADS)

Gopalakrishnan, J.; Agnihotri, G.; Deshpande, D. M.

2012-12-01

Corrosion is an electrochemical process. Corrosion in natural gas (methane) pipelines leads to leakages. Corrosion occurs when anode and cathode are connected through electrolyte. Rate of corrosion in metallic pipeline can be controlled by impressing current to it and thereby making it to act as cathode of corrosion cell. Technologically advanced and energy efficient corrosion controller is required to protect natural gas pipelines. Proposed virtual instrumentation (VI) based corrosion controller precisely controls the external corrosion in underground metallic pipelines, enhances its life and ensures safety. Designing and development of proportional-integral-differential (PID) corrosion controller using VI (LabVIEW) is carried out. When the designed controller is deployed at field, it maintains the pipe to soil potential (PSP) within safe operating limit and not entering into over/under protection zone. Horizontal deployment of this technique can be done to protect all metallic structure, oil pipelines, which need corrosion protection.

Weld Design, Testing, and Assessment Procedures for High Strength Pipelines

DOT National Transportation Integrated Search

2011-12-20

Long-distance high-strength pipelines are increasingly being constructed for the efficient transportation of energy products. While the high-strength linepipe steels and high productivity welding processes are being applied, the procedures employed f...

ORAC-DR -- SCUBA-2 Pipeline Data Reduction

NASA Astrophysics Data System (ADS)

Gibb, Andrew G.; Jenness, Tim

The ORAC-DR data reduction pipeline is designed to reduce data from many different instruments. This document describes how to use ORAC-DR to process data taken with the SCUBA-2 instrument on the James Clerk Maxwell Telescope.

NGSANE: a lightweight production informatics framework for high-throughput data analysis.

PubMed

Buske, Fabian A; French, Hugh J; Smith, Martin A; Clark, Susan J; Bauer, Denis C

2014-05-15

The initial steps in the analysis of next-generation sequencing data can be automated by way of software 'pipelines'. However, individual components depreciate rapidly because of the evolving technology and analysis methods, often rendering entire versions of production informatics pipelines obsolete. Constructing pipelines from Linux bash commands enables the use of hot swappable modular components as opposed to the more rigid program call wrapping by higher level languages, as implemented in comparable published pipelining systems. Here we present Next Generation Sequencing ANalysis for Enterprises (NGSANE), a Linux-based, high-performance-computing-enabled framework that minimizes overhead for set up and processing of new projects, yet maintains full flexibility of custom scripting when processing raw sequence data. Ngsane is implemented in bash and publicly available under BSD (3-Clause) licence via GitHub at https://github.com/BauerLab/ngsane. Denis.Bauer@csiro.au Supplementary data are available at Bioinformatics online.

Study on Failure of Third-Party Damage for Urban Gas Pipeline Based on Fuzzy Comprehensive Evaluation.

PubMed

Li, Jun; Zhang, Hong; Han, Yinshan; Wang, Baodong

2016-01-01

Focusing on the diversity, complexity and uncertainty of the third-party damage accident, the failure probability of third-party damage to urban gas pipeline was evaluated on the theory of analytic hierarchy process and fuzzy mathematics. The fault tree of third-party damage containing 56 basic events was built by hazard identification of third-party damage. The fuzzy evaluation of basic event probabilities were conducted by the expert judgment method and using membership function of fuzzy set. The determination of the weight of each expert and the modification of the evaluation opinions were accomplished using the improved analytic hierarchy process, and the failure possibility of the third-party to urban gas pipeline was calculated. Taking gas pipelines of a certain large provincial capital city as an example, the risk assessment structure of the method was proved to conform to the actual situation, which provides the basis for the safety risk prevention.

A Model for Oil-Gas Pipelines Cost Prediction Based on a Data Mining Process

NASA Astrophysics Data System (ADS)

Batzias, Fragiskos A.; Spanidis, Phillip-Mark P.

2009-08-01

This paper addresses the problems associated with the cost estimation of oil/gas pipelines during the elaboration of feasibility assessments. Techno-economic parameters, i.e., cost, length and diameter, are critical for such studies at the preliminary design stage. A methodology for the development of a cost prediction model based on Data Mining (DM) process is proposed. The design and implementation of a Knowledge Base (KB), maintaining data collected from various disciplines of the pipeline industry, are presented. The formulation of a cost prediction equation is demonstrated by applying multiple regression analysis using data sets extracted from the KB. Following the methodology proposed, a learning context is inductively developed as background pipeline data are acquired, grouped and stored in the KB, and through a linear regression model provide statistically substantial results, useful for project managers or decision makers.

Applying the vantage PDMS to jack-up drilling ships

NASA Astrophysics Data System (ADS)

Yin, Peng; Chen, Yuan-Ming; Cui, Tong-Kai; Wang, Zi-Shen; Gong, Li-Jiang; Yu, Xiang-Fen

2009-09-01

The plant design management system (PDMS) is an integrated application which includes a database and is useful when designing complex 3-D industrial projects. It could be used to simplify the most difficult part of a subsea oil extraction project—detailed pipeline design. It could also be used to integrate the design of equipment, structures, HVAC, E-ways as well as the detailed designs of other specialists. This article mainly examines the applicability of the Vantage PDMS database to pipeline projects involving jack-up drilling ships. It discusses the catalogue (CATA) of the pipeline, the spec-world (SPWL) of the pipeline, the bolt tables (BLTA) and so on. This article explains the main methods for CATA construction as well as problem in the process of construction. In this article, the authors point out matters needing attention when using the Vantage PDMS database in the design process and discuss partial solutions to these questions.

The application of Mike Urban model in drainage and waterlogging in Lincheng county, China

NASA Astrophysics Data System (ADS)

Luan, Qinghua; Zhang, Kun; Liu, Jiahong; Wang, Dong; Ma, Jun

2018-06-01

Recently, the water disaster in cities especially in Chinese mountainous cities is more serious, due to the coupling influences of waterlogging and regional floods. It is necessary to study the surface runoff process of mountainous cities and examine the regional drainage pipeline network. In this study, the runoff processes of Lincheng county (located in Hebei province, China) in different scenarios were simulated through Mike Urban model. The results show that all of the runoff process of the old town and the new residential area with larger slope, is significant and full flow of these above zones exists in the part of the drainage pipeline network; and the overflow exists in part of the drainage pipeline network when the return period is ten years or twenty years, which illuminates that the waterlogging risk in this zone of Lincheng is higher. Therefore, remodeling drainage pipeline network in the old town of Lincheng and adding water storage ponds in the new residential areas were suggested. This research provides both technical support and decision-making reference to local storm flood management, also give the experiences for the study on the runoff process of similar cities.

Heterogeneous Optimization Framework: Reproducible Preprocessing of Multi-Spectral Clinical MRI for Neuro-Oncology Imaging Research.

PubMed

Milchenko, Mikhail; Snyder, Abraham Z; LaMontagne, Pamela; Shimony, Joshua S; Benzinger, Tammie L; Fouke, Sarah Jost; Marcus, Daniel S

2016-07-01

Neuroimaging research often relies on clinically acquired magnetic resonance imaging (MRI) datasets that can originate from multiple institutions. Such datasets are characterized by high heterogeneity of modalities and variability of sequence parameters. This heterogeneity complicates the automation of image processing tasks such as spatial co-registration and physiological or functional image analysis. Given this heterogeneity, conventional processing workflows developed for research purposes are not optimal for clinical data. In this work, we describe an approach called Heterogeneous Optimization Framework (HOF) for developing image analysis pipelines that can handle the high degree of clinical data non-uniformity. HOF provides a set of guidelines for configuration, algorithm development, deployment, interpretation of results and quality control for such pipelines. At each step, we illustrate the HOF approach using the implementation of an automated pipeline for Multimodal Glioma Analysis (MGA) as an example. The MGA pipeline computes tissue diffusion characteristics of diffusion tensor imaging (DTI) acquisitions, hemodynamic characteristics using a perfusion model of susceptibility contrast (DSC) MRI, and spatial cross-modal co-registration of available anatomical, physiological and derived patient images. Developing MGA within HOF enabled the processing of neuro-oncology MR imaging studies to be fully automated. MGA has been successfully used to analyze over 160 clinical tumor studies to date within several research projects. Introduction of the MGA pipeline improved image processing throughput and, most importantly, effectively produced co-registered datasets that were suitable for advanced analysis despite high heterogeneity in acquisition protocols.

Designing Image Analysis Pipelines in Light Microscopy: A Rational Approach.

PubMed

Arganda-Carreras, Ignacio; Andrey, Philippe

2017-01-01

With the progress of microscopy techniques and the rapidly growing amounts of acquired imaging data, there is an increased need for automated image processing and analysis solutions in biological studies. Each new application requires the design of a specific image analysis pipeline, by assembling a series of image processing operations. Many commercial or free bioimage analysis software are now available and several textbooks and reviews have presented the mathematical and computational fundamentals of image processing and analysis. Tens, if not hundreds, of algorithms and methods have been developed and integrated into image analysis software, resulting in a combinatorial explosion of possible image processing sequences. This paper presents a general guideline methodology to rationally address the design of image processing and analysis pipelines. The originality of the proposed approach is to follow an iterative, backwards procedure from the target objectives of analysis. The proposed goal-oriented strategy should help biologists to better apprehend image analysis in the context of their research and should allow them to efficiently interact with image processing specialists.

Enabling Velocity-Resolved Science with Advanced Processing of Herschel/HIFI Observations

NASA Astrophysics Data System (ADS)

Morris, Patrick

The Herschel/HIFI instrument was a heterodyne spectrometer with technology demonstrating and flight components built by NASA/JPL, and acquired over 9000 astronomical observations at velocity resolutions of better than 1 km/s between 480 -1910 GHz (157 - 612 microns). Its performances designed around the scientific goals of exploring the cyclical interrelation of stars and the ISM in diverse environments unified by copious amounts molecular and atomic gas and dust have resulted in over 350 refereed scientific publications, providing a successful foundation and inspiration for current and future science with terahertz instrumentation above the Earth's atmosphere. Nonetheless, almost 60% of the valid observations in the Herschel Science Archive (HSA) are unpublished. This is in largest part due to the limitations of the automated pipeline, and the complexities of interactive treatment the data to bring them to science-ready quality. New users of the archive lacking knowledge of the nuances of heterodyne instrumentation and/or experience with the data processing system are particularly challenged to optimize the data around their science interests or goals with ultra-high resolution spectra. Similarly, the effort to remove quality-degrading instrument artifacts and apply noise performance enhancements is a challenge at this stage even for more experienced users and original program observers who have not yet exploited their observations, either in part or in full as many published observations may also be further harvested for new science results. Recognizing that this situation will likely not improve over time, the HIFI instrument team put substantial effort during the funded post-cryo phase into interactively creating Highly Processed Data Products (HPDPs) from a set of observations in need of corrections and enhancements, in order to promote user accessibility and HIFI's scientific legacy. A set HPDPs created from 350 spectral mapping observations were created in an effort lead at the NASA Herschel Science Center, and delivered in November 2016 to the NASA InfraRed Science Archive (IRSA) and the HSA where they are available to the community. Due to limited resources, this effort could not cover the full list of observations in need of interactive treatments. We are proposing to cover that final set observations (spectral maps and a selection of spectral scans and point observations) in a project spread over 2 years with 0.5 FTE funding, for a guaranteed set of phased deliverables produced with optimized quality at high efficiency using expert processing and delivery procedures already in place. This effort will tackle the quality-degrading artifacts which could not be corrected in the automatic pipeline -- and becoming more and more remote for potential users to correct on their own even with scripted guidance. The expectation is that the huge investments by the funding agencies, and the successful operations of the observatory meeting and often exceeding performance requirements, can be returned to the maximum scientific extent possible. We can guarantee some of that scientific return, in a study of fundamental carbon chemistry in energetic star forming regions, using the proposed HPDPs from unpublished and partially unexploited HIFI data to probe UV- and shockdriven chemistries to explain an unexpected deficiency of C+ in the Orion KL eruptive outflow. We will test a hypothesis that C+ is depleted by production of CO rather than CH+, through a chain of reactions involving intermediate products suited to the molecular environment.

Photometric Calibration of the Gemini South Adaptive Optics Imager

NASA Astrophysics Data System (ADS)

Stevenson, Sarah Anne; Rodrigo Carrasco Damele, Eleazar; Thomas-Osip, Joanna

2017-01-01

The Gemini South Adaptive Optics Imager (GSAOI) is an instrument available on the Gemini South telescope at Cerro Pachon, Chile, utilizing the Gemini Multi-Conjugate Adaptive Optics System (GeMS). In order to allow users to easily perform photometry with this instrument and to monitor any changes in the instrument in the future, we seek to set up a process for performing photometric calibration with standard star observations taken across the time of the instrument’s operation. We construct a Python-based pipeline that includes IRAF wrappers for reduction and combines the AstroPy photutils package and original Python scripts with the IRAF apphot and photcal packages to carry out photometry and linear regression fitting. Using the pipeline, we examine standard star observations made with GSAOI on 68 nights between 2013 and 2015 in order to determine the nightly photometric zero points in the J, H, Kshort, and K bands. This work is based on observations obtained at the Gemini Observatory, processed using the Gemini IRAF and gemini_python packages, which is operated by the Association of Universities for Research in Astronomy, Inc., under a cooperative agreement with the NSF on behalf of the Gemini partnership: the National Science Foundation (United States), the National Research Council (Canada), CONICYT (Chile), Ministerio de Ciencia, Tecnología e Innovación Productiva (Argentina), and Ministério da Ciência, Tecnologia e Inovação (Brazil).

Update on the SDSS-III MARVELS data pipeline development

NASA Astrophysics Data System (ADS)

Li, Rui; Ge, J.; Thomas, N. B.; Petersen, E.; Wang, J.; Ma, B.; Sithajan, S.; Shi, J.; Ouyang, Y.; Chen, Y.

2014-01-01

MARVELS (Multi-object APO Radial Velocity Exoplanet Large-area Survey), as one of the four surveys in the SDSS-III program, has monitored over 3,300 stars during 2008-2012, with each being visited an average of 26 times over a 2-year window. Although the early data pipeline was able to detect over 20 brown dwarf candidates and several hundreds of binaries, no giant planet candidates have been reliably identified due to its large systematic errors. Learning from past data pipeline lessons, we re-designed the entire pipeline to handle various types of systematic effects caused by the instrument (such as trace, slant, distortion, drifts and dispersion) and observation condition changes (such as illumination profile and continuum). We also introduced several advanced methods to precisely extract the RV signals. To date, we have achieved a long term RMS RV measurement error of 14 m/s for HIP-14810 (one of our reference stars) after removal of the known planet signal based on previous HIRES RV measurement. This new 1-D data pipeline has been used to robustly identify four giant planet candidates within the small fraction of the survey data that has been processed (Thomas et al. this meeting). The team is currently working hard to optimize the pipeline, especially the 2-D interference-fringe RV extraction, where early results show a 1.5 times improvement over the 1-D data pipeline. We are quickly approaching the survey baseline performance requirement of 10-35 m/s RMS for 8-12 solar type stars. With this fine-tuned pipeline and the soon to be processed plates of data, we expect to discover many more giant planet candidates and make a large statistical impact to the exoplanet study.

Image processing pipeline for synchrotron-radiation-based tomographic microscopy.

PubMed

Hintermüller, C; Marone, F; Isenegger, A; Stampanoni, M

2010-07-01

With synchrotron-radiation-based tomographic microscopy, three-dimensional structures down to the micrometer level can be visualized. Tomographic data sets typically consist of 1000 to 1500 projections of 1024 x 1024 to 2048 x 2048 pixels and are acquired in 5-15 min. A processing pipeline has been developed to handle this large amount of data efficiently and to reconstruct the tomographic volume within a few minutes after the end of a scan. Just a few seconds after the raw data have been acquired, a selection of reconstructed slices is accessible through a web interface for preview and to fine tune the reconstruction parameters. The same interface allows initiation and control of the reconstruction process on the computer cluster. By integrating all programs and tools, required for tomographic reconstruction into the pipeline, the necessary user interaction is reduced to a minimum. The modularity of the pipeline allows functionality for new scan protocols to be added, such as an extended field of view, or new physical signals such as phase-contrast or dark-field imaging etc.

Synergy with HST and JWST Data Management Systems

NASA Astrophysics Data System (ADS)

Greene, Gretchen; Space Telescope Data Management Team

2014-01-01

The data processing and archive systems for the JWST will contain a petabyte of science data and the best news is that users will have fast access to the latest calibrations through a variety of new services. With a synergistic approach currently underway with the STScI science operations between the Hubble Space Telescope and James Webb Space Telescope data management subsystems (DMS), operational verification is right around the corner. Next year the HST archive will provide scientists on-demand fully calibrated data products via the Mikulski Archive for Space Telescopes (MAST), which takes advantage of an upgraded DMS. This enhanced system, developed jointly with the JWST DMS is based on a new CONDOR distributed processing system capable of reprocessing data using a prioritization queue which runs in the background. A Calibration Reference Data System manages the latest optimal configuration for each scientific instrument pipeline. Science users will be able to search and discover the growing MAST archive calibrated datasets from these missions along with the other multiple mission holdings both local to MAST and available through the Virtual Observatory. JWST data systems will build upon the successes and lessons learned from the HST legacy and move us forward into the next generation of multi-wavelength archive research.

Teaching Planetary Science as Part of the Search for Extraterrestrial Intelligence (SETI)

NASA Astrophysics Data System (ADS)

Margot, Jean-Luc; Greenberg, Adam H.

2017-10-01

In Spring 2016 and 2017, UCLA offered a course titled "EPSS C179/279 - Search for Extraterrestrial Intelligence: Theory and Applications". The course is designed for advanced undergraduate students and graduate students in the science, technical, engineering, and mathematical fields. Each year, students designed an observing sequence for the Green Bank telescope, observed known planetary systems remotely, wrote a sophisticated and modular data processing pipeline, analyzed the data, and presented their results. In 2016, 15 students participated in the course (9U, 5G; 11M, 3F) and observed 14 planetary systems in the Kepler field. In 2017, 17 students participated (15U, 2G; 10M, 7F) and observed 10 planetary systems in the Kepler field, TRAPPIST-1, and LHS 1140. In order to select suitable targets, students learned about planetary systems, planetary habitability, and planetary dynamics. In addition to planetary science fundamentals, students learned radio astronomy fundamentals, collaborative software development, signal processing techniques, and statistics. Evaluations indicate that the course is challenging but that students are eager to learn because of the engrossing nature of SETI. Students particularly value the teamwork approach, the observing experience, and working with their own data. The next offering of the course will be in Spring 2018. Additional information about our SETI work is available at seti.ucla.edu.

Supply Support of Air Force 463L Equipment: An Analysis of the 463L equipment Spare Parts Pipeline

DTIC Science & Technology

1989-09-01

service; and 4) the order processing system created inherent delays in the pipeline because of outdated and indirect information systems and technology. Keywords: Materials handling equipment, Theses. (AW)

Lessons Learned while Exploring Cloud-Native Architectures for NASA EOSDIS Applications and Systems

NASA Astrophysics Data System (ADS)

Pilone, D.

2016-12-01

As new, high data rate missions begin collecting data, the NASA's Earth Observing System Data and Information System (EOSDIS) archive is projected to grow roughly 20x to over 300PBs by 2025. To prepare for the dramatic increase in data and enable broad scientific inquiry into larger time series and datasets, NASA has been exploring the impact of applying cloud technologies throughout EOSDIS. In this talk we will provide an overview of NASA's prototyping and lessons learned in applying cloud architectures to: Highly scalable and extensible ingest and archive of EOSDIS data Going "all-in" on cloud based application architectures including "serverless" data processing pipelines and evaluating approaches to vendor-lock in Rethinking data distribution and approaches to analysis in a cloud environment Incorporating and enforcing security controls while minimizing the barrier for research efforts to deploy to NASA compliant, operational environments. NASA's Earth Observing System (EOS) is a coordinated series of satellites for long term global observations. NASA's Earth Observing System Data and Information System (EOSDIS) is a multi-petabyte-scale archive of environmental data that supports global climate change research by providing end-to-end services from EOS instrument data collection to science data processing to full access to EOS and other earth science data. On a daily basis, the EOSDIS ingests, processes, archives and distributes over 3 terabytes of data from NASA's Earth Science missions representing over 6000 data products ranging from various types of science disciplines. EOSDIS has continually evolved to improve the discoverability, accessibility, and usability of high-impact NASA data spanning the multi-petabyte-scale archive of Earth science data products.

Extraction of UMLS® Concepts Using Apache cTAKES™ for German Language.

PubMed

Becker, Matthias; Böckmann, Britta

2016-01-01

Automatic information extraction of medical concepts and classification with semantic standards from medical reports is useful for standardization and for clinical research. This paper presents an approach for an UMLS concept extraction with a customized natural language processing pipeline for German clinical notes using Apache cTAKES. The objectives are, to test the natural language processing tool for German language if it is suitable to identify UMLS concepts and map these with SNOMED-CT. The German UMLS database and German OpenNLP models extended the natural language processing pipeline, so the pipeline can normalize to domain ontologies such as SNOMED-CT using the German concepts. For testing, the ShARe/CLEF eHealth 2013 training dataset translated into German was used. The implemented algorithms are tested with a set of 199 German reports, obtaining a result of average 0.36 F1 measure without German stemming, pre- and post-processing of the reports.

Pipeline transport and simultaneous saccharification of corn stover.

PubMed

Kumar, Amit; Cameron, Jay B; Flynn, Peter C

2005-05-01

Pipeline transport of corn stover delivered by truck from the field is evaluated against a range of truck transport costs. Corn stover transported by pipeline at 20% solids concentration (wet basis) or higher could directly enter an ethanol fermentation plant, and hence the investment in the pipeline inlet end processing facilities displaces comparable investment in the plant. At 20% solids, pipeline transport of corn stover costs less than trucking at capacities in excess of 1.4 M drytonnes/yr when compared to a mid range of truck transport cost (excluding any credit for economies of scale achieved in the ethanol fermentation plant from larger scale due to multiple pipelines). Pipelining of corn stover gives the opportunity to conduct simultaneous transport and saccharification (STS). If current enzymes are used, this would require elevated temperature. Heating of the slurry for STS, which in a fermentation plant is achieved from waste heat, is a significant cost element (more than 5 cents/l of ethanol) if done at the pipeline inlet unless waste heat is available, for example from an electric power plant located adjacent to the pipeline inlet. Heat loss in a 1.26 m pipeline carrying 2 M drytonnes/yr is about 5 degrees C at a distance of 400 km in typical prairie clay soils, and would not likely require insulation; smaller pipelines or different soil conditions might require insulation for STS. Saccharification in the pipeline would reduce the need for investment in the fermentation plant, saving about 0.2 cents/l of ethanol. Transport of corn stover in multiple pipelines offers the opportunity to develop a large ethanol fermentation plant, avoiding some of the diseconomies of scale that arise from smaller plants whose capacities are limited by issues of truck congestion.

"Actually, I 'May' Be Clever Enough to Do It". Using Identity as a Lens to Investigate Students' Trajectories towards Science and University

ERIC Educational Resources Information Center

Krogh, Lars Brian; Andersen, Hanne Moeller

2013-01-01

We have followed a group of students in the potential pipeline for science through their last years of upper secondary school and in the context of a university mentorship program. The student group is defined by their choice of Mathematics at A-level which is mandatory for admission to tertiary STEM education in Denmark. Rich data (repeated…

Students Leaving the STEM Pipeline: An Investigation of Their Attitudes and the Influence of Significant Others on Their Study Choice

ERIC Educational Resources Information Center

Korpershoek, Hanke; Kuyper, Hans; Bosker, Roel; van der Werf, Greetje

2013-01-01

The main aim of the present study was to investigate why some students do not continue in science-oriented studies in higher education despite that their previous career in secondary education proved that they were interested and suitably qualified to do so. We introduced a new approach to deal with these students' attitudes towards science,…

49 CFR 192.937 - What is a continual process of evaluation and assessment to maintain a pipeline's integrity?

Code of Federal Regulations, 2012 CFR

2012-10-01

...: MINIMUM FEDERAL SAFETY STANDARDS Gas Transmission Pipeline Integrity Management § 192.937 What is a..., or stress corrosion cracking. An operator must conduct the direct assessment in accordance with the...

49 CFR 192.937 - What is a continual process of evaluation and assessment to maintain a pipeline's integrity?

Code of Federal Regulations, 2011 CFR

2011-10-01

...: MINIMUM FEDERAL SAFETY STANDARDS Gas Transmission Pipeline Integrity Management § 192.937 What is a..., or stress corrosion cracking. An operator must conduct the direct assessment in accordance with the...

49 CFR 192.937 - What is a continual process of evaluation and assessment to maintain a pipeline's integrity?

Code of Federal Regulations, 2013 CFR

2013-10-01

...: MINIMUM FEDERAL SAFETY STANDARDS Gas Transmission Pipeline Integrity Management § 192.937 What is a..., or stress corrosion cracking. An operator must conduct the direct assessment in accordance with the...

49 CFR 192.937 - What is a continual process of evaluation and assessment to maintain a pipeline's integrity?

Code of Federal Regulations, 2014 CFR

2014-10-01

...: MINIMUM FEDERAL SAFETY STANDARDS Gas Transmission Pipeline Integrity Management § 192.937 What is a..., or stress corrosion cracking. An operator must conduct the direct assessment in accordance with the...

Rolling Band Artifact Flagging in the Kepler Data Pipeline

NASA Astrophysics Data System (ADS)

Clarke, Bruce; Kolodziejczak, Jeffery J; Caldwell, Douglas A.

2014-06-01

Instrument-induced artifacts in the raw Kepler pixel data include time-varying crosstalk from the fine guidance sensor (FGS) clock signals, manifestations of drifting moiré pattern as locally correlated nonstationary noise and rolling bands in the images. These systematics find their way into the calibrated pixel time series and ultimately into the target flux time series. The Kepler pipeline module Dynablack models the FGS crosstalk artifacts using a combination of raw science pixel data, full frame images, reverse-clocked pixel data and ancillary temperature data. The calibration module (CAL) uses the fitted Dynablack models to remove FGS crosstalk artifacts in the calibrated pixels by adjusting the black level correction per cadence. Dynablack also detects and flags spatial regions and time intervals of strong time-varying black-level. These rolling band artifact (RBA) flags are produced on a per row per cadence basis by searching for transit signatures in the Dynablack fit residuals. The Photometric Analysis module (PA) generates per target per cadence data quality flags based on the Dynablack RBA flags. Proposed future work includes using the target data quality flags as a basis for de-weighting in the Presearch Data Conditioning (PDC), Transiting Planet Search (TPS) and Data Validation (DV) pipeline modules. We discuss the effectiveness of RBA flagging for downstream users and illustrate with some affected light curves. We also discuss the implementation of Dynablack in the Kepler data pipeline and present results regarding the improvement in calibrated pixels and the expected improvement in cotrending performance as a result of including FGS corrections in the calibration. Funding for the Kepler Mission has been provided by the NASA Science Mission Directorate.

The Relationship Between Cognitive and Non-Cognitive Variables and Academic Performance of Students in the Science Enrichment Preparation (S.E.P.) Program

NASA Astrophysics Data System (ADS)

Borden, Paula D.

This dissertation study concerned the lack of underrepresented minority students matriculating through the health professions pipeline. The term pipeline is "the educational avenue by which one must travel to successfully enter a profession" (Sullivan Alliance, 2004). There are a significant number of health professional pipeline programs based across the United States and, for the purposes of this study, a focus was placed on the Science Enrichment Preparation (S.E.P.) Program which is based at The University of North Carolina at Chapel Hill. The S.E.P. Program, is an eight-week residential summer experience, designed to support underrepresented minority pre-health students develop the competitive edge for successful admission into health professional school programs. The bedrock of this dissertation study concerned itself with the relationships between cognitive variables and non-cognitive variables and academic performance of students in the S.E.P. Program from 2005-2013. The study was undertaken to provide a clearer understanding for the NC Health Careers Access Program's (NC-HCAP) leadership with regard to variables associated with the students' academic performance in the S.E.P. Program. The data outcomes were informative for NC-HCAP in identifying cognitive and non-cognitive variables associated with student academic performance. Additionally, these findings provided direction as to what infrastructures may be put into place to more effectively support the S.E.P. participants. It is the researcher's hope this study may serve as an educational model and resource to pipeline programs and others with similar educational missions. The consequences and implications of a non-diverse healthcare workforce are high and far reaching. Without parity representation in the healthcare workforce, health disparities between racial and economic groups will likely continue to grow.

Providing Situational Awareness for Pipeline Control Operations

NASA Astrophysics Data System (ADS)

Butts, Jonathan; Kleinhans, Hugo; Chandia, Rodrigo; Papa, Mauricio; Shenoi, Sujeet

A SCADA system for a single 3,000-mile-long strand of oil or gas pipeline may employ several thousand field devices to measure process parameters and operate equipment. Because of the vital tasks performed by these sensors and actuators, pipeline operators need accurate and timely information about their status and integrity. This paper describes a realtime scanner that provides situational awareness about SCADA devices and control operations. The scanner, with the assistance of lightweight, distributed sensors, analyzes SCADA network traffic, verifies the operational status and integrity of field devices, and identifies anomalous activity. Experimental results obtained using real pipeline control traffic demonstrate the utility of the scanner in industrial settings.

"Actually, I May be Clever Enough to do it". Using Identity as a Lens to Investigate Students' Trajectories Towards Science and University

NASA Astrophysics Data System (ADS)

Krogh, Lars Brian; Andersen, Hanne Moeller

2013-04-01

We have followed a group of students in the potential pipeline for science through their last years of upper secondary school and in the context of a university mentorship program. The student group is defined by their choice of Mathematics at A-level which is mandatory for admission to tertiary STEM education in Denmark. Rich data (repeated interviews, questionnaires (pre-and post-) and observations) from 14 target students have been collected. Using Late Modern identity theory as a lens, we have analysed students' identity narratives in order to establish their trajectories in relation to university in general, and towards science studies and science careers in particular. We find that the diversity of students' educational identity narratives can be characterized and their trajectories understood in terms of a Four Factor Framework comprising: general identity process orientations (reflecting, committing, exploring), personal values, subject self-concepts and subject interests. In various ways these constructs interact and set the range and direction of the students' searches for future education and careers. Our longitudinal study suggests that they have enough permanence to enable us to hypothesize more or less secured paths of individual students to tertiary science (or other areas of academia).

From sequencer to supercomputer: an automatic pipeline for managing and processing next generation sequencing data.

PubMed

Camerlengo, Terry; Ozer, Hatice Gulcin; Onti-Srinivasan, Raghuram; Yan, Pearlly; Huang, Tim; Parvin, Jeffrey; Huang, Kun

2012-01-01

Next Generation Sequencing is highly resource intensive. NGS Tasks related to data processing, management and analysis require high-end computing servers or even clusters. Additionally, processing NGS experiments requires suitable storage space and significant manual interaction. At The Ohio State University's Biomedical Informatics Shared Resource, we designed and implemented a scalable architecture to address the challenges associated with the resource intensive nature of NGS secondary analysis built around Illumina Genome Analyzer II sequencers and Illumina's Gerald data processing pipeline. The software infrastructure includes a distributed computing platform consisting of a LIMS called QUEST (http://bisr.osumc.edu), an Automation Server, a computer cluster for processing NGS pipelines, and a network attached storage device expandable up to 40TB. The system has been architected to scale to multiple sequencers without requiring additional computing or labor resources. This platform provides demonstrates how to manage and automate NGS experiments in an institutional or core facility setting.

DKIST visible broadband imager data processing pipeline

NASA Astrophysics Data System (ADS)

Beard, Andrew; Cowan, Bruce; Ferayorni, Andrew

2014-07-01

The Daniel K. Inouye Solar Telescope (DKIST) Data Handling System (DHS) provides the technical framework and building blocks for developing on-summit instrument quality assurance and data reduction pipelines. The DKIST Visible Broadband Imager (VBI) is a first light instrument that alone will create two data streams with a bandwidth of 960 MB/s each. The high data rate and data volume of the VBI require near-real time processing capability for quality assurance and data reduction, and will be performed on-summit using Graphics Processing Unit (GPU) technology. The VBI data processing pipeline (DPP) is the first designed and developed using the DKIST DHS components, and therefore provides insight into the strengths and weaknesses of the framework. In this paper we lay out the design of the VBI DPP, examine how the underlying DKIST DHS components are utilized, and discuss how integration of the DHS framework with GPUs was accomplished. We present our results of the VBI DPP alpha release implementation of the calibration, frame selection reduction, and quality assurance display processing nodes.

Tumor image signatures and habitats: a processing pipeline of multimodality metabolic and physiological images.

PubMed

You, Daekeun; Kim, Michelle M; Aryal, Madhava P; Parmar, Hemant; Piert, Morand; Lawrence, Theodore S; Cao, Yue

2018-01-01

To create tumor "habitats" from the "signatures" discovered from multimodality metabolic and physiological images, we developed a framework of a processing pipeline. The processing pipeline consists of six major steps: (1) creating superpixels as a spatial unit in a tumor volume; (2) forming a data matrix [Formula: see text] containing all multimodality image parameters at superpixels; (3) forming and clustering a covariance or correlation matrix [Formula: see text] of the image parameters to discover major image "signatures;" (4) clustering the superpixels and organizing the parameter order of the [Formula: see text] matrix according to the one found in step 3; (5) creating "habitats" in the image space from the superpixels associated with the "signatures;" and (6) pooling and clustering a matrix consisting of correlation coefficients of each pair of image parameters from all patients to discover subgroup patterns of the tumors. The pipeline was applied to a dataset of multimodality images in glioblastoma (GBM) first, which consisted of 10 image parameters. Three major image "signatures" were identified. The three major "habitats" plus their overlaps were created. To test generalizability of the processing pipeline, a second image dataset from GBM, acquired on the scanners different from the first one, was processed. Also, to demonstrate the clinical association of image-defined "signatures" and "habitats," the patterns of recurrence of the patients were analyzed together with image parameters acquired prechemoradiation therapy. An association of the recurrence patterns with image-defined "signatures" and "habitats" was revealed. These image-defined "signatures" and "habitats" can be used to guide stereotactic tissue biopsy for genetic and mutation status analysis and to analyze for prediction of treatment outcomes, e.g., patterns of failure.

Astro-H/Hitomi data analysis, processing, and archive

NASA Astrophysics Data System (ADS)

Angelini, Lorella; Terada, Yukikatsu; Dutka, Michael; Eggen, Joseph; Harrus, Ilana; Hill, Robert S.; Krimm, Hans; Loewenstein, Michael; Miller, Eric D.; Nobukawa, Masayoshi; Rutkowski, Kristin; Sargent, Andrew; Sawada, Makoto; Takahashi, Hiromitsu; Yamaguchi, Hiroya; Yaqoob, Tahir; Witthoeft, Michael

2018-01-01

Astro-H is the x-ray/gamma-ray mission led by Japan with international participation, launched on February 17, 2016. Soon after launch, Astro-H was renamed Hitomi. The payload consists of four different instruments (SXS, SXI, HXI, and SGD) that operate simultaneously to cover the energy range from 0.3 keV up to 600 keV. On March 27, 2016, JAXA lost contact with the satellite and, on April 28, they announced the cessation of the efforts to restore mission operations. Hitomi collected about one month's worth of data with its instruments. This paper presents the analysis software and the data processing pipeline created to calibrate and analyze the Hitomi science data, along with the plan for the archive. These activities have been a collaborative effort shared between scientists and software engineers working in several institutes in Japan and United States.

Susceptibility-weighted imaging using inter-echo-variance channel combination for improved contrast at 7 tesla.

PubMed

Hosseini, Zahra; Liu, Junmin; Solovey, Igor; Menon, Ravi S; Drangova, Maria

2017-04-01

To implement and optimize a new approach for susceptibility-weighted image (SWI) generation from multi-echo multi-channel image data and compare its performance against optimized traditional SWI pipelines. Five healthy volunteers were imaged at 7 Tesla. The inter-echo-variance (IEV) channel combination, which uses the variance of the local frequency shift at multiple echo times as a weighting factor during channel combination, was used to calculate multi-echo local phase shift maps. Linear phase masks were combined with the magnitude to generate IEV-SWI. The performance of the IEV-SWI pipeline was compared with that of two accepted SWI pipelines-channel combination followed by (i) Homodyne filtering (HPH-SWI) and (ii) unwrapping and high-pass filtering (SVD-SWI). The filtering steps of each pipeline were optimized. Contrast-to-noise ratio was used as the comparison metric. Qualitative assessment of artifact and vessel conspicuity was performed and processing time of pipelines was evaluated. The optimized IEV-SWI pipeline (σ = 7 mm) resulted in continuous vessel visibility throughout the brain. IEV-SWI had significantly higher contrast compared with HPH-SWI and SVD-SWI (P < 0.001, Friedman nonparametric test). Residual background fields and phase wraps in HPH-SWI and SVD-SWI corrupted the vessel signal and/or generated vessel-mimicking artifact. Optimized implementation of the IEV-SWI pipeline processed a six-echo 16-channel dataset in under 10 min. IEV-SWI benefits from channel-by-channel processing of phase data and results in high contrast images with an optimal balance between contrast and background noise removal, thereby presenting evidence of importance of the order in which postprocessing techniques are applied for multi-channel SWI generation. 2 J. Magn. Reson. Imaging 2017;45:1113-1124. © 2016 International Society for Magnetic Resonance in Medicine.

Processing Shotgun Proteomics Data on the Amazon Cloud with the Trans-Proteomic Pipeline*

PubMed Central

Slagel, Joseph; Mendoza, Luis; Shteynberg, David; Deutsch, Eric W.; Moritz, Robert L.

2015-01-01

Cloud computing, where scalable, on-demand compute cycles and storage are available as a service, has the potential to accelerate mass spectrometry-based proteomics research by providing simple, expandable, and affordable large-scale computing to all laboratories regardless of location or information technology expertise. We present new cloud computing functionality for the Trans-Proteomic Pipeline, a free and open-source suite of tools for the processing and analysis of tandem mass spectrometry datasets. Enabled with Amazon Web Services cloud computing, the Trans-Proteomic Pipeline now accesses large scale computing resources, limited only by the available Amazon Web Services infrastructure, for all users. The Trans-Proteomic Pipeline runs in an environment fully hosted on Amazon Web Services, where all software and data reside on cloud resources to tackle large search studies. In addition, it can also be run on a local computer with computationally intensive tasks launched onto the Amazon Elastic Compute Cloud service to greatly decrease analysis times. We describe the new Trans-Proteomic Pipeline cloud service components, compare the relative performance and costs of various Elastic Compute Cloud service instance types, and present on-line tutorials that enable users to learn how to deploy cloud computing technology rapidly with the Trans-Proteomic Pipeline. We provide tools for estimating the necessary computing resources and costs given the scale of a job and demonstrate the use of cloud enabled Trans-Proteomic Pipeline by performing over 1100 tandem mass spectrometry files through four proteomic search engines in 9 h and at a very low cost. PMID:25418363

Processing shotgun proteomics data on the Amazon cloud with the trans-proteomic pipeline.

PubMed

Slagel, Joseph; Mendoza, Luis; Shteynberg, David; Deutsch, Eric W; Moritz, Robert L

2015-02-01

Cloud computing, where scalable, on-demand compute cycles and storage are available as a service, has the potential to accelerate mass spectrometry-based proteomics research by providing simple, expandable, and affordable large-scale computing to all laboratories regardless of location or information technology expertise. We present new cloud computing functionality for the Trans-Proteomic Pipeline, a free and open-source suite of tools for the processing and analysis of tandem mass spectrometry datasets. Enabled with Amazon Web Services cloud computing, the Trans-Proteomic Pipeline now accesses large scale computing resources, limited only by the available Amazon Web Services infrastructure, for all users. The Trans-Proteomic Pipeline runs in an environment fully hosted on Amazon Web Services, where all software and data reside on cloud resources to tackle large search studies. In addition, it can also be run on a local computer with computationally intensive tasks launched onto the Amazon Elastic Compute Cloud service to greatly decrease analysis times. We describe the new Trans-Proteomic Pipeline cloud service components, compare the relative performance and costs of various Elastic Compute Cloud service instance types, and present on-line tutorials that enable users to learn how to deploy cloud computing technology rapidly with the Trans-Proteomic Pipeline. We provide tools for estimating the necessary computing resources and costs given the scale of a job and demonstrate the use of cloud enabled Trans-Proteomic Pipeline by performing over 1100 tandem mass spectrometry files through four proteomic search engines in 9 h and at a very low cost. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Image Registration to Compensate for EPI Distortion in Patients with Brain Tumors: An Evaluation of Tract-Specific Effects.

PubMed

Albi, Angela; Meola, Antonio; Zhang, Fan; Kahali, Pegah; Rigolo, Laura; Tax, Chantal M W; Ciris, Pelin Aksit; Essayed, Walid I; Unadkat, Prashin; Norton, Isaiah; Rathi, Yogesh; Olubiyi, Olutayo; Golby, Alexandra J; O'Donnell, Lauren J

2018-03-01

Diffusion magnetic resonance imaging (dMRI) provides preoperative maps of neurosurgical patients' white matter tracts, but these maps suffer from echo-planar imaging (EPI) distortions caused by magnetic field inhomogeneities. In clinical neurosurgical planning, these distortions are generally not corrected and thus contribute to the uncertainty of fiber tracking. Multiple image processing pipelines have been proposed for image-registration-based EPI distortion correction in healthy subjects. In this article, we perform the first comparison of such pipelines in neurosurgical patient data. Five pipelines were tested in a retrospective clinical dMRI dataset of 9 patients with brain tumors. Pipelines differed in the choice of fixed and moving images and the similarity metric for image registration. Distortions were measured in two important tracts for neurosurgery, the arcuate fasciculus and corticospinal tracts. Significant differences in distortion estimates were found across processing pipelines. The most successful pipeline used dMRI baseline and T2-weighted images as inputs for distortion correction. This pipeline gave the most consistent distortion estimates across image resolutions and brain hemispheres. Quantitative results of mean tract distortions on the order of 1-2 mm are in line with other recent studies, supporting the potential need for distortion correction in neurosurgical planning. Novel results include significantly higher distortion estimates in the tumor hemisphere and greater effect of image resolution choice on results in the tumor hemisphere. Overall, this study demonstrates possible pitfalls and indicates that care should be taken when implementing EPI distortion correction in clinical settings. Copyright © 2018 by the American Society of Neuroimaging.

SIRTF Science Operations System Design

NASA Technical Reports Server (NTRS)

Green, William

1999-01-01

SIRTF Science Operations System Design William B. Green Manager, SIRTF Science Center California Institute of Technology M/S 310-6 1200 E. California Blvd., Pasadena CA 91125 (626) 395 8572 Fax (626) 568 0673 bgreen@ipac.caltech.edu. The Space Infrared Telescope Facility (SIRTF) will be launched in December 2001, and perform an extended series of science observations at wavelengths ranging from 20 to 160 microns for five years or more. The California Institute of Technology has been selected as the home for the SIRTF Science Center (SSC). The SSC will be responsible for evaluating and selecting observation proposals, providing technical support to the science community, performing mission planning and science observation scheduling activities, instrument calibration during operations and instrument health monitoring, production of archival quality data products, and management of science research grants. The science payload consists of three instruments delivered by instrument Principal Investigators located at University of Arizona, Cornell, and Harvard Smithsonian Astrophysical Observatory. The SSC is responsible for design, development, and operation of the Science Operations System (SOS) which will support the functions assigned to the SSC by NASA. The SIRTF spacecraft, mission profile, and science instrument design have undergone almost ten years of refinement. SIRTF development and operations activities are highly cost constrained. The cost constraints have impacted the design of the SOS in several ways. The Science Operations System has been designed to incorporate a set of efficient, easy to use tools which will make it possible for scientists to propose observation sequences in a rapid and automated manner. The use of highly automated tools for requesting observations will simplify the long range observatory scheduling process, and the short term scheduling of science observations. Pipeline data processing will be highly automated and data-driven, utilizing a variety of tools developed at JPL, the instrument development teams, and Space Telescope Science Institute to automate processing. An incremental ground data system development approach has been adopted, featuring periodic deliveries that are validated with the flight hardware throughout the various phases of system level development and testing. This approach minimizes development time and decreases operations risk. This paper will describe the top level architecture of the SOS and the basic design concepts. A summary of the incremental development approach will be presented. Examples of the unique science user tools now under final development prior to the first proposal call scheduled for mid-2000 will be shown.

Determine new design and construction techniques for transportation of ethanol and ethanol/gasoline blends in new pipelines.

DOT National Transportation Integrated Search

2013-02-15

The technical tasks in this study included activities to characterize the impact of selected : metallurgical processing and fabrication variables on ethanol stress corrosion cracking (ethanol : SCC) of new pipeline steels, develop a better understand...

Guidelines for Constructing Natural Gas and Liquid Hydrocarbon Pipelines Through Areas Prone to Landslide and Subsidence Hazards

DOT National Transportation Integrated Search

2009-01-01

These guidelines provide recommendations for the assessment of new and existing natural gas and liquid hydrocarbon pipelines subjected to potential ground displacements resulting from landslides and subsidence. The process of defining landslide and s...

Bio-Docklets: virtualization containers for single-step execution of NGS pipelines.

PubMed

Kim, Baekdoo; Ali, Thahmina; Lijeron, Carlos; Afgan, Enis; Krampis, Konstantinos

2017-08-01

Processing of next-generation sequencing (NGS) data requires significant technical skills, involving installation, configuration, and execution of bioinformatics data pipelines, in addition to specialized postanalysis visualization and data mining software. In order to address some of these challenges, developers have leveraged virtualization containers toward seamless deployment of preconfigured bioinformatics software and pipelines on any computational platform. We present an approach for abstracting the complex data operations of multistep, bioinformatics pipelines for NGS data analysis. As examples, we have deployed 2 pipelines for RNA sequencing and chromatin immunoprecipitation sequencing, preconfigured within Docker virtualization containers we call Bio-Docklets. Each Bio-Docklet exposes a single data input and output endpoint and from a user perspective, running the pipelines as simply as running a single bioinformatics tool. This is achieved using a "meta-script" that automatically starts the Bio-Docklets and controls the pipeline execution through the BioBlend software library and the Galaxy Application Programming Interface. The pipeline output is postprocessed by integration with the Visual Omics Explorer framework, providing interactive data visualizations that users can access through a web browser. Our goal is to enable easy access to NGS data analysis pipelines for nonbioinformatics experts on any computing environment, whether a laboratory workstation, university computer cluster, or a cloud service provider. Beyond end users, the Bio-Docklets also enables developers to programmatically deploy and run a large number of pipeline instances for concurrent analysis of multiple datasets. © The Authors 2017. Published by Oxford University Press.

Bio-Docklets: virtualization containers for single-step execution of NGS pipelines

PubMed Central

Kim, Baekdoo; Ali, Thahmina; Lijeron, Carlos; Afgan, Enis

2017-01-01

Abstract Processing of next-generation sequencing (NGS) data requires significant technical skills, involving installation, configuration, and execution of bioinformatics data pipelines, in addition to specialized postanalysis visualization and data mining software. In order to address some of these challenges, developers have leveraged virtualization containers toward seamless deployment of preconfigured bioinformatics software and pipelines on any computational platform. We present an approach for abstracting the complex data operations of multistep, bioinformatics pipelines for NGS data analysis. As examples, we have deployed 2 pipelines for RNA sequencing and chromatin immunoprecipitation sequencing, preconfigured within Docker virtualization containers we call Bio-Docklets. Each Bio-Docklet exposes a single data input and output endpoint and from a user perspective, running the pipelines as simply as running a single bioinformatics tool. This is achieved using a “meta-script” that automatically starts the Bio-Docklets and controls the pipeline execution through the BioBlend software library and the Galaxy Application Programming Interface. The pipeline output is postprocessed by integration with the Visual Omics Explorer framework, providing interactive data visualizations that users can access through a web browser. Our goal is to enable easy access to NGS data analysis pipelines for nonbioinformatics experts on any computing environment, whether a laboratory workstation, university computer cluster, or a cloud service provider. Beyond end users, the Bio-Docklets also enables developers to programmatically deploy and run a large number of pipeline instances for concurrent analysis of multiple datasets. PMID:28854616

The National Ocean Sciences Bowl: An Effective Model for Engaging High School Students in Ocean Science

NASA Astrophysics Data System (ADS)

Holloway, A. E.

2016-02-01

The National Ocean Sciences Bowl (NOSB) is an informal high school education program that engages students in ocean and environmental science and exposes them to the breadth of ocean-related careers. The NOSB strives to train the next generation of interdisciplinary capable scientists and build a STEM-literate society that harnesses the power of ocean and climate science to address environmental, economic, and societal issues. Through the NOSB, students not only learn scientific principles, but also apply them to compelling real-world problems. The NOSB provides a richer STEM education and exposes students to ocean science topics they may not otherwise study through classroom curriculum. A longitudinal study that began in 2007 has shown that NOSB participants have an enhanced interest in ocean-related hobbies and environmental stewardship and an increasing number of these students have remained in the STEM pipeline and workforce.While the NOSB is primarily an academic competition, it has evolved since its creation in 1998 to include a variety of practical and professional development components. One of the program enhancements, the Scientific Expert Briefing (SEB), gives students the opportunity to apply what they have studied and think critically about current and ongoing ocean science challenges. The SEB helps students connect their knowledge of ocean science with current and proposed policy initiatives. Students gain significant research, writing, and presentation skills, while enhancing their ability for collaboration and consensus building, all vital workforce skills. Ultimately, the SEB teaches students how to communicate complex scientific research into digestible information for decision-makers and the general public.This poster will examine the impact of the NOSB and its role in strengthening the workforce pipeline through a combination of independent learning, competition, and opportunities for communication skills development.

PyEmir: Data Reduction Pipeline for EMIR, the GTC Near-IR Multi-Object Spectrograph

NASA Astrophysics Data System (ADS)

Pascual, S.; Gallego, J.; Cardiel, N.; Eliche-Moral, M. C.

2010-12-01

EMIR is the near-infrared wide-field camera and multi-slit spectrograph being built for Gran Telescopio Canarias. We present here the work being done on its data processing pipeline. PyEmir is based on Python and it will process automatically data taken in both imaging and spectroscopy mode. PyEmir is begin developed by the UCM Group of Extragalactic Astrophysics and Astronomical Instrumentation.

High-throughput Analysis of Large Microscopy Image Datasets on CPU-GPU Cluster Platforms

PubMed Central

Teodoro, George; Pan, Tony; Kurc, Tahsin M.; Kong, Jun; Cooper, Lee A. D.; Podhorszki, Norbert; Klasky, Scott; Saltz, Joel H.

2014-01-01

Analysis of large pathology image datasets offers significant opportunities for the investigation of disease morphology, but the resource requirements of analysis pipelines limit the scale of such studies. Motivated by a brain cancer study, we propose and evaluate a parallel image analysis application pipeline for high throughput computation of large datasets of high resolution pathology tissue images on distributed CPU-GPU platforms. To achieve efficient execution on these hybrid systems, we have built runtime support that allows us to express the cancer image analysis application as a hierarchical data processing pipeline. The application is implemented as a coarse-grain pipeline of stages, where each stage may be further partitioned into another pipeline of fine-grain operations. The fine-grain operations are efficiently managed and scheduled for computation on CPUs and GPUs using performance aware scheduling techniques along with several optimizations, including architecture aware process placement, data locality conscious task assignment, data prefetching, and asynchronous data copy. These optimizations are employed to maximize the utilization of the aggregate computing power of CPUs and GPUs and minimize data copy overheads. Our experimental evaluation shows that the cooperative use of CPUs and GPUs achieves significant improvements on top of GPU-only versions (up to 1.6×) and that the execution of the application as a set of fine-grain operations provides more opportunities for runtime optimizations and attains better performance than coarser-grain, monolithic implementations used in other works. An implementation of the cancer image analysis pipeline using the runtime support was able to process an image dataset consisting of 36,848 4Kx4K-pixel image tiles (about 1.8TB uncompressed) in less than 4 minutes (150 tiles/second) on 100 nodes of a state-of-the-art hybrid cluster system. PMID:25419546

MetaDB a Data Processing Workflow in Untargeted MS-Based Metabolomics Experiments.

PubMed

Franceschi, Pietro; Mylonas, Roman; Shahaf, Nir; Scholz, Matthias; Arapitsas, Panagiotis; Masuero, Domenico; Weingart, Georg; Carlin, Silvia; Vrhovsek, Urska; Mattivi, Fulvio; Wehrens, Ron

2014-01-01

Due to their sensitivity and speed, mass-spectrometry based analytical technologies are widely used to in metabolomics to characterize biological phenomena. To address issues like metadata organization, quality assessment, data processing, data storage, and, finally, submission to public repositories, bioinformatic pipelines of a non-interactive nature are often employed, complementing the interactive software used for initial inspection and visualization of the data. These pipelines often are created as open-source software allowing the complete and exhaustive documentation of each step, ensuring the reproducibility of the analysis of extensive and often expensive experiments. In this paper, we will review the major steps which constitute such a data processing pipeline, discussing them in the context of an open-source software for untargeted MS-based metabolomics experiments recently developed at our institute. The software has been developed by integrating our metaMS R package with a user-friendly web-based application written in Grails. MetaMS takes care of data pre-processing and annotation, while the interface deals with the creation of the sample lists, the organization of the data storage, and the generation of survey plots for quality assessment. Experimental and biological metadata are stored in the ISA-Tab format making the proposed pipeline fully integrated with the Metabolights framework.

The Underbelly of Economy versus Environment Conflicts: Detangling Sources of Tension in Contentious Natural Resource Decisions

NASA Astrophysics Data System (ADS)

Clermont, Holly J. K.

It is well-established that biodiversity confers resilience to social-ecological systems, and also that humans are collectively and routinely degrading and destroying ecosystems and driving species to extinction through development and other avenues. In the decade preceding this research, biodiversity loss at local and globally-aggregated scales persistently and substantially exceeded the safe operating space for biosphere integrity, contributing to assertions that the stability of Earth's systems could no longer be relied upon. The propensity to protect biodiversity, or contribute to its demise, arises from a variety of tangled motivations. I investigated five of these influences, including values, sense of place, networks of relationships, media frames, and perceptions of science, for two contentious proposed energy projects in western Canada. I first conducted a frame analysis of online media regarding an oil pipeline expansion from Alberta to British Columbia (BC), and a run-of-river hydroelectric project on the BC coast. I then surveyed and interviewed participants, mapped their place connections, analyzed social networks and social media networks, and examined text and oral submissions to regulatory agencies. These findings were systematically integrated to explore how the five influences contributed to each conflict and decisions affecting biodiversity. Support and opposition for the pipeline were found to be proxies for the prioritization of self-enhancement and self-transcendence (nature) values, respectively, while self-transcendence (nature) values were found on both sides of the run-of-river conflict. For the pipeline conflict, disparities in senses of place underscored a clash of regions. In both cases, well-intentioned but polarizing leaders contributed to online media frames that emphasized conflict and buttressed extreme positions, while helping shape or reinforce siloed networks and the diffusion, uptake, and understanding of scientific and other information. Environmental review processes were mostly unresponsive to these influences. Leverage points to better reduce environmental conflict and protect biodiversity were identified for environmental assessment and similar processes.

Failure modes for pipelines in landslide areas

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

Bruschi, R.; Spinazze, M.; Tomassini, D.

1995-12-31

In recent years a number of incidences of pipelines affected by slow soil movements have been reported in the relevant literature. Further related issues such as soil-pipe interaction have been studied both theoretically and through experimental surveys, along with the environmental conditions which are responsible for hazard to the pipeline integrity. A suitable design criteria under these circumstances has been discussed by several authors, in particular in relation to a limit state approach and hence a strain based criteria. The scope of this paper is to describe the failure mechanisms which may affect the pipeline in the presence of slowmore » soil movements impacting on the pipeline, both in the longitudinal and transverse direction. Particular attention is paid to environmental, geometric and structural parameters which steer the process towards one or other failure mechanism. Criteria for deciding upon remedial measures required to guarantee the structural integrity of the pipeline, both in the short and in the long term, are discussed.« less

The Careers in Health and Medical Professions Program (CHAMPS): An Impact Study of a University-Based STEM+H Outreach Program

NASA Astrophysics Data System (ADS)

Wallace, Eric W.; Perry, Justin C.; Ferguson, Robert L.; Jackson, Debbie K.

2015-08-01

The present study investigated the impact of a Science, Technology, Engineering, Mathematics and Health (STEM+H) university-based pipeline program, the Careers in Health and Medical Professions Program, over the course of two summers among predominantly African-American high school students recruited from urban school districts ( N = 155). Based on a mixed methods approach, results indicated that youth made significant gains in both academic and career knowledge. Furthermore, youth generally rated the program's sessions favorably, but also rated sessions with varying levels of satisfaction. The limitations and implications for program delivery and evaluation methods among pipeline programs are discussed.

Demonstrating the Effects of Shop Flow Process Variability on the Air Force Depot Level Reparable Item Pipeline

DTIC Science & Technology

1992-09-01

Crawford found that pipeline contents are extremely variable about their mean (10:24) and Kettner and Wheatley said that "a statistical analysis of data...write the results from this replication "* to the ANOVA files for later analysis . The first set outputs points "* for overall pipeline contents . The...families and friends for their unselfishness and support. Marvin A. Arostegui and Jon A. Larvick ii Table of Contents Page Preface

Study on Failure of Third-Party Damage for Urban Gas Pipeline Based on Fuzzy Comprehensive Evaluation

PubMed Central

Li, Jun; Zhang, Hong; Han, Yinshan; Wang, Baodong

2016-01-01

Focusing on the diversity, complexity and uncertainty of the third-party damage accident, the failure probability of third-party damage to urban gas pipeline was evaluated on the theory of analytic hierarchy process and fuzzy mathematics. The fault tree of third-party damage containing 56 basic events was built by hazard identification of third-party damage. The fuzzy evaluation of basic event probabilities were conducted by the expert judgment method and using membership function of fuzzy set. The determination of the weight of each expert and the modification of the evaluation opinions were accomplished using the improved analytic hierarchy process, and the failure possibility of the third-party to urban gas pipeline was calculated. Taking gas pipelines of a certain large provincial capital city as an example, the risk assessment structure of the method was proved to conform to the actual situation, which provides the basis for the safety risk prevention. PMID:27875545

Examination of Longitudinal Invariance on a Framework for Observing and Categorizing Instructional Strategies

NASA Astrophysics Data System (ADS)

Ryoo, Ji Hoon; Tai, Robert H.; Skeeles-Worley, Angela D.

2018-02-01

In longitudinal studies, measurement invariance is required to conduct substantive comparisons over time or across groups. In this study, we examined measurement invariance on a recently developed instrument capturing student preferences for seven instructional strategies related to science learning and career interest. We have labeled these seven instructional strategies as Collaborating, Competing, Caretaking, Creating/Making, Discovering, Performing, and Teaching. A better understanding of student preferences for particular instructional strategies can help educators, researchers, and policy makers deliberately tailor programmatic instructional structure to increase student persistence in the STEM pipeline. However, simply confirming the relationship between student preferences for science instructional strategies and their future career choices at a single time point is not sufficient to clarify our understanding of the relationship between instructional strategies and student persistence in the STEM pipeline, especially since preferences for instructional strategies are understood to vary over time. As such, we sought to develop a measure that invariantly captures student preference over a period of time: the Framework for Observing and Categorizing Instructional Strategies (FOCIS). We administered the FOCIS instrument over four semesters over two middle school grades to 1009 6th graders and 1021 7th graders and confirmed the longitudinal invariance of the FOCIS measure. This confirmation of longitudinal invariance will allow researchers to examine the relationship between student preference for certain instructional strategies and student persistence in the STEM pipeline.

Microarray Data Processing Techniques for Genome-Scale Network Inference from Large Public Repositories.

PubMed

Chockalingam, Sriram; Aluru, Maneesha; Aluru, Srinivas

2016-09-19

Pre-processing of microarray data is a well-studied problem. Furthermore, all popular platforms come with their own recommended best practices for differential analysis of genes. However, for genome-scale network inference using microarray data collected from large public repositories, these methods filter out a considerable number of genes. This is primarily due to the effects of aggregating a diverse array of experiments with different technical and biological scenarios. Here we introduce a pre-processing pipeline suitable for inferring genome-scale gene networks from large microarray datasets. We show that partitioning of the available microarray datasets according to biological relevance into tissue- and process-specific categories significantly extends the limits of downstream network construction. We demonstrate the effectiveness of our pre-processing pipeline by inferring genome-scale networks for the model plant Arabidopsis thaliana using two different construction methods and a collection of 11,760 Affymetrix ATH1 microarray chips. Our pre-processing pipeline and the datasets used in this paper are made available at http://alurulab.cc.gatech.edu/microarray-pp.

NASA Sounding Rocket Program Educational Outreach

NASA Technical Reports Server (NTRS)

Rosanova, G.

2013-01-01

Educational and public outreach is a major focus area for the National Aeronautics and Space Administration (NASA). The NASA Sounding Rocket Program (NSRP) shares in the belief that NASA plays a unique and vital role in inspiring future generations to pursue careers in science, mathematics, and technology. To fulfill this vision, the NSRP engages in a variety of educator training workshops and student flight projects that provide unique and exciting hands-on rocketry and space flight experiences. Specifically, the Wallops Rocket Academy for Teachers and Students (WRATS) is a one-week tutorial laboratory experience for high school teachers to learn the basics of rocketry, as well as build an instrumented model rocket for launch and data processing. The teachers are thus armed with the knowledge and experience to subsequently inspire the students at their home institution. Additionally, the NSRP has partnered with the Colorado Space Grant Consortium (COSGC) to provide a "pipeline" of space flight opportunities to university students and professors. Participants begin by enrolling in the RockOn! Workshop, which guides fledgling rocketeers through the construction and functional testing of an instrumentation kit. This is then integrated into a sealed canister and flown on a sounding rocket payload, which is recovered for the students to retrieve and process their data post flight. The next step in the "pipeline" involves unique, user-defined RockSat-C experiments in a sealed canister that allow participants more independence in developing, constructing, and testing spaceflight hardware. These experiments are flown and recovered on the same payload as the RockOn! Workshop kits. Ultimately, the "pipeline" culminates in the development of an advanced, user-defined RockSat-X experiment that is flown on a payload which provides full exposure to the space environment (not in a sealed canister), and includes telemetry and attitude control capability. The RockOn! and RockSat-C elements of the "pipeline" have been successfully demonstrated by five annual flights thus far from Wallops Flight Facility. RockSat-X has successfully flown twice, also from Wallops. The NSRP utilizes launch vehicles comprised of military surplus rocket motors (Terrier-Improved Orion and Terrier-Improved Malemute) to execute these missions. The NASA Sounding Rocket Program is proud of its role in inspiring the "next generation of explorers" and is working to expand its reach to all regions of the United States and the international community as well.

Barriers in the Physics Pipeline from K-12 to Tenure

NASA Astrophysics Data System (ADS)

Kilburn, Micha

2016-09-01

The lack of diversity in physics is a known problem, and yet efforts to change our demographics have only had minor effects during the last decade. I will explain some of the hidden barriers that dissuade underrepresented minorities in becoming physicists using a framework borrowed from sociology, Maslow's hierarchy of needs. I will draw from current research at the undergraduate to faculty levels over a variety of STEM fields that are also addressing a lack of diversity. I will also provide analysis from the Joint Institute for Nuclear Astrophysics Center for the Evolution of Elements (JINA-CEE) outreach programs to understand the likelihood of current K-12 students in becoming physicists. Specifically, I will present results from the pre-surveys from our Art 2 Science Camps (ages 8-14) about their attitudes towards science as well as results from analysis of teacher recommendations for our high school summer program. I will conclude with a positive outlook describing the pipeline created by JINA-CEE to retain students from middle school through college. This work was supported in part by the National Science Foundation under Grant No. PHY-1430152 (JINA Center for the Evolution of the Elements).

Theory and Application of Magnetic Flux Leakage Pipeline Detection.

PubMed

Shi, Yan; Zhang, Chao; Li, Rui; Cai, Maolin; Jia, Guanwei

2015-12-10

Magnetic flux leakage (MFL) detection is one of the most popular methods of pipeline inspection. It is a nondestructive testing technique which uses magnetic sensitive sensors to detect the magnetic leakage field of defects on both the internal and external surfaces of pipelines. This paper introduces the main principles, measurement and processing of MFL data. As the key point of a quantitative analysis of MFL detection, the identification of the leakage magnetic signal is also discussed. In addition, the advantages and disadvantages of different identification methods are analyzed. Then the paper briefly introduces the expert systems used. At the end of this paper, future developments in pipeline MFL detection are predicted.

Theory and Application of Magnetic Flux Leakage Pipeline Detection

PubMed Central

Shi, Yan; Zhang, Chao; Li, Rui; Cai, Maolin; Jia, Guanwei

2015-01-01

Magnetic flux leakage (MFL) detection is one of the most popular methods of pipeline inspection. It is a nondestructive testing technique which uses magnetic sensitive sensors to detect the magnetic leakage field of defects on both the internal and external surfaces of pipelines. This paper introduces the main principles, measurement and processing of MFL data. As the key point of a quantitative analysis of MFL detection, the identification of the leakage magnetic signal is also discussed. In addition, the advantages and disadvantages of different identification methods are analyzed. Then the paper briefly introduces the expert systems used. At the end of this paper, future developments in pipeline MFL detection are predicted. PMID:26690435

Simulation of pipeline in the area of the underwater crossing

NASA Astrophysics Data System (ADS)

Burkov, P.; Chernyavskiy, D.; Burkova, S.; Konan, E. C.

2014-08-01

The article studies stress-strain behavior of the main oil-pipeline section Alexandrovskoye-Anzhero-Sudzhensk using software system Ansys. This method of examination and assessment of technical conditions of objects of pipeline transport studies the objects and the processes that affect the technical condition of these facilities, including the research on the basis of computer simulation. Such approach allows to develop the theory, methods of calculations and designing of objects of pipeline transport, units and parts of machines, regardless of their industry and destination with a view to improve the existing constructions and create new structures, machines of high performance, durability and reliability, maintainability, low material capacity and cost, which have competitiveness on the world market.

CLAMP - a toolkit for efficiently building customized clinical natural language processing pipelines.

PubMed

Soysal, Ergin; Wang, Jingqi; Jiang, Min; Wu, Yonghui; Pakhomov, Serguei; Liu, Hongfang; Xu, Hua

2017-11-24

Existing general clinical natural language processing (NLP) systems such as MetaMap and Clinical Text Analysis and Knowledge Extraction System have been successfully applied to information extraction from clinical text. However, end users often have to customize existing systems for their individual tasks, which can require substantial NLP skills. Here we present CLAMP (Clinical Language Annotation, Modeling, and Processing), a newly developed clinical NLP toolkit that provides not only state-of-the-art NLP components, but also a user-friendly graphic user interface that can help users quickly build customized NLP pipelines for their individual applications. Our evaluation shows that the CLAMP default pipeline achieved good performance on named entity recognition and concept encoding. We also demonstrate the efficiency of the CLAMP graphic user interface in building customized, high-performance NLP pipelines with 2 use cases, extracting smoking status and lab test values. CLAMP is publicly available for research use, and we believe it is a unique asset for the clinical NLP community. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Parallel processing considerations for image recognition tasks

NASA Astrophysics Data System (ADS)

Simske, Steven J.

2011-01-01

Many image recognition tasks are well-suited to parallel processing. The most obvious example is that many imaging tasks require the analysis of multiple images. From this standpoint, then, parallel processing need be no more complicated than assigning individual images to individual processors. However, there are three less trivial categories of parallel processing that will be considered in this paper: parallel processing (1) by task; (2) by image region; and (3) by meta-algorithm. Parallel processing by task allows the assignment of multiple workflows-as diverse as optical character recognition [OCR], document classification and barcode reading-to parallel pipelines. This can substantially decrease time to completion for the document tasks. For this approach, each parallel pipeline is generally performing a different task. Parallel processing by image region allows a larger imaging task to be sub-divided into a set of parallel pipelines, each performing the same task but on a different data set. This type of image analysis is readily addressed by a map-reduce approach. Examples include document skew detection and multiple face detection and tracking. Finally, parallel processing by meta-algorithm allows different algorithms to be deployed on the same image simultaneously. This approach may result in improved accuracy.

Scaling-up NLP Pipelines to Process Large Corpora of Clinical Notes.

PubMed

Divita, G; Carter, M; Redd, A; Zeng, Q; Gupta, K; Trautner, B; Samore, M; Gundlapalli, A

2015-01-01

This article is part of the Focus Theme of Methods of Information in Medicine on "Big Data and Analytics in Healthcare". This paper describes the scale-up efforts at the VA Salt Lake City Health Care System to address processing large corpora of clinical notes through a natural language processing (NLP) pipeline. The use case described is a current project focused on detecting the presence of an indwelling urinary catheter in hospitalized patients and subsequent catheter-associated urinary tract infections. An NLP algorithm using v3NLP was developed to detect the presence of an indwelling urinary catheter in hospitalized patients. The algorithm was tested on a small corpus of notes on patients for whom the presence or absence of a catheter was already known (reference standard). In planning for a scale-up, we estimated that the original algorithm would have taken 2.4 days to run on a larger corpus of notes for this project (550,000 notes), and 27 days for a corpus of 6 million records representative of a national sample of notes. We approached scaling-up NLP pipelines through three techniques: pipeline replication via multi-threading, intra-annotator threading for tasks that can be further decomposed, and remote annotator services which enable annotator scale-out. The scale-up resulted in reducing the average time to process a record from 206 milliseconds to 17 milliseconds or a 12- fold increase in performance when applied to a corpus of 550,000 notes. Purposely simplistic in nature, these scale-up efforts are the straight forward evolution from small scale NLP processing to larger scale extraction without incurring associated complexities that are inherited by the use of the underlying UIMA framework. These efforts represent generalizable and widely applicable techniques that will aid other computationally complex NLP pipelines that are of need to be scaled out for processing and analyzing big data.

49 CFR 192.243 - Nondestructive testing.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 3 2010-10-01 2010-10-01 false Nondestructive testing. 192.243 Section 192.243... BY PIPELINE: MINIMUM FEDERAL SAFETY STANDARDS Welding of Steel in Pipelines § 192.243 Nondestructive testing. (a) Nondestructive testing of welds must be performed by any process, other than trepanning, that...

State Regulators Promote Consumer Choice in Retail Gas Markets

EIA Publications

1996-01-01

Restructuring of interstate pipeline companies has created new choices and challenges for local distribution companies (LDCs), their regulators, and their customers. The process of separating interstate pipeline gas sales from transportation service has been completed and has resulted in greater gas procurement options for LDCs.

Building a Snow Data Management System using Open Source Software (and IDL)

NASA Astrophysics Data System (ADS)

Goodale, C. E.; Mattmann, C. A.; Ramirez, P.; Hart, A. F.; Painter, T.; Zimdars, P. A.; Bryant, A.; Brodzik, M.; Skiles, M.; Seidel, F. C.; Rittger, K. E.

2012-12-01

At NASA's Jet Propulsion Laboratory free and open source software is used everyday to support a wide range of projects, from planetary to climate to research and development. In this abstract I will discuss the key role that open source software has played in building a robust science data processing pipeline for snow hydrology research, and how the system is also able to leverage programs written in IDL, making JPL's Snow Data System a hybrid of open source and proprietary software. Main Points: - The Design of the Snow Data System (illustrate how the collection of sub-systems are combined to create a complete data processing pipeline) - Discuss the Challenges of moving from a single algorithm on a laptop, to running 100's of parallel algorithms on a cluster of servers (lesson's learned) - Code changes - Software license related challenges - Storage Requirements - System Evolution (from data archiving, to data processing, to data on a map, to near-real-time products and maps) - Road map for the next 6 months (including how easily we re-used the snowDS code base to support the Airborne Snow Observatory Mission) Software in Use and their Software Licenses: IDL - Used for pre and post processing of data. Licensed under a proprietary software license held by Excelis. Apache OODT - Used for data management and workflow processing. Licensed under the Apache License Version 2. GDAL - Geospatial Data processing library used for data re-projection currently. Licensed under the X/MIT license. GeoServer - WMS Server. Licensed under the General Public License Version 2.0 Leaflet.js - Javascript web mapping library. Licensed under the Berkeley Software Distribution License. Python - Glue code and miscellaneous data processing support. Licensed under the Python Software Foundation License. Perl - Script wrapper for running the SCAG algorithm. Licensed under the General Public License Version 3. PHP - Front-end web application programming. Licensed under the PHP License Version 3.01

Women in science.

PubMed

Dean, Caroline; Osborn, Mary; Oshlack, Alicia; Thornton, Janet

2012-01-01

To coincide with International Women's Day, Genome Biology asked several female scientists about their experience of an academic career, how they managed to balance an active research career with family life, and what should be done to encourage more women to pursue research careers to stop the 'leaky' pipeline.

Gathering pipeline methane emissions in Fayetteville shale pipelines and scoping guidelines for future pipeline measurement campaigns

DOE PAGES

Zimmerle, Daniel J.; Pickering, Cody K.; Bell, Clay S.; ...

2017-11-24

Gathering pipelines, which transport gas from well pads to downstream processing, are a sector of the natural gas supply chain for which little measured methane emissions data are available. This study performed leak detection and measurement on 96 km of gathering pipeline and the associated 56 pigging facilities and 39 block valves. The study found one underground leak accounting for 83% (4.0 kg CH 4/hr) of total measured emissions. Methane emissions for the 4684 km of gathering pipeline in the study area were estimated at 402 kg CH 4/hr [95 to 1065 kg CH 4/hr, 95% CI], or 1% [0.2%more » to 2.6%] of all methane emissions measured during a prior aircraft study of the same area. Emissions estimated by this study fall within the uncertainty range of emissions estimated using emission factors from EPA's 2015 Greenhouse Inventory and study activity estimates. While EPA's current inventory is based upon emission factors from distribution mains measured in the 1990s, this study indicates that using emission factors from more recent distribution studies could significantly underestimate emissions from gathering pipelines. To guide broader studies of pipeline emissions, we also estimate the fraction of the pipeline length within a basin that must be measured to constrain uncertainty of pipeline emissions estimates to within 1% of total basin emissions. The study provides both substantial insight into the mix of emission sources and guidance for future gathering pipeline studies, but since measurements were made in a single basin, the results are not sufficiently representative to provide methane emission factors at the regional or national level.« less

Gathering pipeline methane emissions in Fayetteville shale pipelines and scoping guidelines for future pipeline measurement campaigns

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

Zimmerle, Daniel J.; Pickering, Cody K.; Bell, Clay S.

Gathering pipelines, which transport gas from well pads to downstream processing, are a sector of the natural gas supply chain for which little measured methane emissions data are available. This study performed leak detection and measurement on 96 km of gathering pipeline and the associated 56 pigging facilities and 39 block valves. The study found one underground leak accounting for 83% (4.0 kg CH 4/hr) of total measured emissions. Methane emissions for the 4684 km of gathering pipeline in the study area were estimated at 402 kg CH 4/hr [95 to 1065 kg CH 4/hr, 95% CI], or 1% [0.2%more » to 2.6%] of all methane emissions measured during a prior aircraft study of the same area. Emissions estimated by this study fall within the uncertainty range of emissions estimated using emission factors from EPA's 2015 Greenhouse Inventory and study activity estimates. While EPA's current inventory is based upon emission factors from distribution mains measured in the 1990s, this study indicates that using emission factors from more recent distribution studies could significantly underestimate emissions from gathering pipelines. To guide broader studies of pipeline emissions, we also estimate the fraction of the pipeline length within a basin that must be measured to constrain uncertainty of pipeline emissions estimates to within 1% of total basin emissions. The study provides both substantial insight into the mix of emission sources and guidance for future gathering pipeline studies, but since measurements were made in a single basin, the results are not sufficiently representative to provide methane emission factors at the regional or national level.« less

A method for simulating the release of natural gas from the rupture of high-pressure pipelines in any terrain.

PubMed

Deng, Yajun; Hu, Hongbing; Yu, Bo; Sun, Dongliang; Hou, Lei; Liang, Yongtu

2018-01-15

The rupture of a high-pressure natural gas pipeline can pose a serious threat to human life and environment. In this research, a method has been proposed to simulate the release of natural gas from the rupture of high-pressure pipelines in any terrain. The process of gas releases from the rupture of a high-pressure pipeline is divided into three stages, namely the discharge, jet, and dispersion stages. Firstly, a discharge model is established to calculate the release rate of the orifice. Secondly, an improved jet model is proposed to obtain the parameters of the pseudo source. Thirdly, a fast-modeling method applicable to any terrain is introduced. Finally, based upon these three steps, a dispersion model, which can take any terrain into account, is established. Then, the dispersion scenarios of released gas in four different terrains are studied. Moreover, the effects of pipeline pressure, pipeline diameter, wind speed and concentration of hydrogen sulfide on the dispersion scenario in real terrain are systematically analyzed. The results provide significant guidance for risk assessment and contingency planning of a ruptured natural gas pipeline. Copyright © 2017. Published by Elsevier B.V.

Fully automated processing of fMRI data in SPM: from MRI scanner to PACS.

PubMed

Maldjian, Joseph A; Baer, Aaron H; Kraft, Robert A; Laurienti, Paul J; Burdette, Jonathan H

2009-01-01

Here we describe the Wake Forest University Pipeline, a fully automated method for the processing of fMRI data using SPM. The method includes fully automated data transfer and archiving from the point of acquisition, real-time batch script generation, distributed grid processing, interface to SPM in MATLAB, error recovery and data provenance, DICOM conversion and PACS insertion. It has been used for automated processing of fMRI experiments, as well as for the clinical implementation of fMRI and spin-tag perfusion imaging. The pipeline requires no manual intervention, and can be extended to any studies requiring offline processing.

Space Science Cloud: a Virtual Space Science Research Platform Based on Cloud Model

NASA Astrophysics Data System (ADS)

Hu, Xiaoyan; Tong, Jizhou; Zou, Ziming

Through independent and co-operational science missions, Strategic Pioneer Program (SPP) on Space Science, the new initiative of space science program in China which was approved by CAS and implemented by National Space Science Center (NSSC), dedicates to seek new discoveries and new breakthroughs in space science, thus deepen the understanding of universe and planet earth. In the framework of this program, in order to support the operations of space science missions and satisfy the demand of related research activities for e-Science, NSSC is developing a virtual space science research platform based on cloud model, namely the Space Science Cloud (SSC). In order to support mission demonstration, SSC integrates interactive satellite orbit design tool, satellite structure and payloads layout design tool, payload observation coverage analysis tool, etc., to help scientists analyze and verify space science mission designs. Another important function of SSC is supporting the mission operations, which runs through the space satellite data pipelines. Mission operators can acquire and process observation data, then distribute the data products to other systems or issue the data and archives with the services of SSC. In addition, SSC provides useful data, tools and models for space researchers. Several databases in the field of space science are integrated and an efficient retrieve system is developing. Common tools for data visualization, deep processing (e.g., smoothing and filtering tools), analysis (e.g., FFT analysis tool and minimum variance analysis tool) and mining (e.g., proton event correlation analysis tool) are also integrated to help the researchers to better utilize the data. The space weather models on SSC include magnetic storm forecast model, multi-station middle and upper atmospheric climate model, solar energetic particle propagation model and so on. All the services above-mentioned are based on the e-Science infrastructures of CAS e.g. cloud storage and cloud computing. SSC provides its users with self-service storage and computing resources at the same time.At present, the prototyping of SSC is underway and the platform is expected to be put into trial operation in August 2014. We hope that as SSC develops, our vision of Digital Space may come true someday.

Natural gas and CO2 price variation: impact on the relative cost-efficiency of LNG and pipelines.

PubMed

Ulvestad, Marte; Overland, Indra

2012-06-01

THIS ARTICLE DEVELOPS A FORMAL MODEL FOR COMPARING THE COST STRUCTURE OF THE TWO MAIN TRANSPORT OPTIONS FOR NATURAL GAS: liquefied natural gas (LNG) and pipelines. In particular, it evaluates how variations in the prices of natural gas and greenhouse gas emissions affect the relative cost-efficiency of these two options. Natural gas is often promoted as the most environmentally friendly of all fossil fuels, and LNG as a modern and efficient way of transporting it. Some research has been carried out into the local environmental impact of LNG facilities, but almost none into aspects related to climate change. This paper concludes that at current price levels for natural gas and CO 2 emissions the distance from field to consumer and the volume of natural gas transported are the main determinants of transport costs. The pricing of natural gas and greenhouse emissions influence the relative cost-efficiency of LNG and pipeline transport, but only to a limited degree at current price levels. Because more energy is required for the LNG process (especially for fuelling the liquefaction process) than for pipelines at distances below 9100 km, LNG is more exposed to variability in the price of natural gas and greenhouse gas emissions up to this distance. If the prices of natural gas and/or greenhouse gas emission rise dramatically in the future, this will affect the choice between pipelines and LNG. Such a price increase will be favourable for pipelines relative to LNG.

Natural gas and CO2 price variation: impact on the relative cost-efficiency of LNG and pipelines

PubMed Central

Ulvestad, Marte; Overland, Indra

2012-01-01

This article develops a formal model for comparing the cost structure of the two main transport options for natural gas: liquefied natural gas (LNG) and pipelines. In particular, it evaluates how variations in the prices of natural gas and greenhouse gas emissions affect the relative cost-efficiency of these two options. Natural gas is often promoted as the most environmentally friendly of all fossil fuels, and LNG as a modern and efficient way of transporting it. Some research has been carried out into the local environmental impact of LNG facilities, but almost none into aspects related to climate change. This paper concludes that at current price levels for natural gas and CO2 emissions the distance from field to consumer and the volume of natural gas transported are the main determinants of transport costs. The pricing of natural gas and greenhouse emissions influence the relative cost-efficiency of LNG and pipeline transport, but only to a limited degree at current price levels. Because more energy is required for the LNG process (especially for fuelling the liquefaction process) than for pipelines at distances below 9100 km, LNG is more exposed to variability in the price of natural gas and greenhouse gas emissions up to this distance. If the prices of natural gas and/or greenhouse gas emission rise dramatically in the future, this will affect the choice between pipelines and LNG. Such a price increase will be favourable for pipelines relative to LNG. PMID:24683269

A novel joint-processing adaptive nonlinear equalizer using a modular recurrent neural network for chaotic communication systems.

PubMed

Zhao, Haiquan; Zeng, Xiangping; Zhang, Jiashu; Liu, Yangguang; Wang, Xiaomin; Li, Tianrui

2011-01-01

To eliminate nonlinear channel distortion in chaotic communication systems, a novel joint-processing adaptive nonlinear equalizer based on a pipelined recurrent neural network (JPRNN) is proposed, using a modified real-time recurrent learning (RTRL) algorithm. Furthermore, an adaptive amplitude RTRL algorithm is adopted to overcome the deteriorating effect introduced by the nesting process. Computer simulations illustrate that the proposed equalizer outperforms the pipelined recurrent neural network (PRNN) and recurrent neural network (RNN) equalizers. Copyright © 2010 Elsevier Ltd. All rights reserved.