Visually impaired researchers get their hands on quantum chemistry: application to a computational study on the isomerization of a sterol

NASA Astrophysics Data System (ADS)

Lounnas, Valère; Wedler, Henry B.; Newman, Timothy; Schaftenaar, Gijs; Harrison, Jason G.; Nepomuceno, Gabriella; Pemberton, Ryan; Tantillo, Dean J.; Vriend, Gert

2014-11-01

In molecular sciences, articles tend to revolve around 2D representations of 3D molecules, and sighted scientists often resort to 3D virtual reality software to study these molecules in detail. Blind and visually impaired (BVI) molecular scientists have access to a series of audio devices that can help them read the text in articles and work with computers. Reading articles published in this journal, though, is nearly impossible for them because they need to generate mental 3D images of molecules, but the article-reading software cannot do that for them. We have previously designed AsteriX, a web server that fully automatically decomposes articles, detects 2D plots of low molecular weight molecules, removes meta data and annotations from these plots, and converts them into 3D atomic coordinates. AsteriX-BVI goes one step further and converts the 3D representation into a 3D printable, haptic-enhanced format that includes Braille annotations. These Braille-annotated physical 3D models allow BVI scientists to generate a complete mental model of the molecule. AsteriX-BVI uses Molden to convert the meta data of quantum chemistry experiments into BVI friendly formats so that the entire line of scientific information that sighted people take for granted—from published articles, via printed results of computational chemistry experiments, to 3D models—is now available to BVI scientists too. The possibilities offered by AsteriX-BVI are illustrated by a project on the isomerization of a sterol, executed by the blind co-author of this article (HBW).

A Framework for the Design of Effective Graphics for Scientific Visualization

NASA Technical Reports Server (NTRS)

Miceli, Kristina D.

1992-01-01

This proposal presents a visualization framework, based on a data model, that supports the production of effective graphics for scientific visualization. Visual representations are effective only if they augment comprehension of the increasing amounts of data being generated by modern computer simulations. These representations are created by taking into account the goals and capabilities of the scientist, the type of data to be displayed, and software and hardware considerations. This framework is embodied in an assistant-based visualization system to guide the scientist in the visualization process. This will improve the quality of the visualizations and decrease the time the scientist is required to spend in generating the visualizations. I intend to prove that such a framework will create a more productive environment for tile analysis and interpretation of large, complex data sets.

Computer Models of Proteins

NASA Technical Reports Server (NTRS)

2000-01-01

Dr. Marc Pusey (seated) and Dr. Craig Kundrot use computers to analyze x-ray maps and generate three-dimensional models of protein structures. With this information, scientists at Marshall Space Flight Center can learn how proteins are made and how they work. The computer screen depicts a proten structure as a ball-and-stick model. Other models depict the actual volume occupied by the atoms, or the ribbon-like structures that are crucial to a protein's function.

Computer Aided Grid Interface: An Interactive CFD Pre-Processor

NASA Technical Reports Server (NTRS)

Soni, Bharat K.

1997-01-01

NASA maintains an applications oriented computational fluid dynamics (CFD) efforts complementary to and in support of the aerodynamic-propulsion design and test activities. This is especially true at NASA/MSFC where the goal is to advance and optimize present and future liquid-fueled rocket engines. Numerical grid generation plays a significant role in the fluid flow simulations utilizing CFD. An overall goal of the current project was to develop a geometry-grid generation tool that will help engineers, scientists and CFD practitioners to analyze design problems involving complex geometries in a timely fashion. This goal is accomplished by developing the CAGI: Computer Aided Grid Interface system. The CAGI system is developed by integrating CAD/CAM (Computer Aided Design/Computer Aided Manufacturing) geometric system output and/or Initial Graphics Exchange Specification (IGES) files (including all the NASA-IGES entities), geometry manipulations and generations associated with grid constructions, and robust grid generation methodologies. This report describes the development process of the CAGI system.

Computer Aided Grid Interface: An Interactive CFD Pre-Processor

NASA Technical Reports Server (NTRS)

Soni, Bharat K.

1996-01-01

NASA maintains an applications oriented computational fluid dynamics (CFD) efforts complementary to and in support of the aerodynamic-propulsion design and test activities. This is especially true at NASA/MSFC where the goal is to advance and optimize present and future liquid-fueled rocket engines. Numerical grid generation plays a significant role in the fluid flow simulations utilizing CFD. An overall goal of the current project was to develop a geometry-grid generation tool that will help engineers, scientists and CFD practitioners to analyze design problems involving complex geometries in a timely fashion. This goal is accomplished by developing the Computer Aided Grid Interface system (CAGI). The CAGI system is developed by integrating CAD/CAM (Computer Aided Design/Computer Aided Manufacturing) geometric system output and / or Initial Graphics Exchange Specification (IGES) files (including all the NASA-IGES entities), geometry manipulations and generations associated with grid constructions, and robust grid generation methodologies. This report describes the development process of the CAGI system.

Astro Data Science: The Next Generation

NASA Astrophysics Data System (ADS)

Mentzel, Chris

2018-01-01

Astronomers have been at the forefront of data-driven discovery since before the days of Kepler. Using data in the scientific inquiry into the workings of the the universe is the lifeblood of the field. This said, data science is considered a new thing, and researchers from every discipline are rushing to learn data science techniques, train themselves on data science tools, and even leaving academia to become data scientists. It is undeniable that our ability to harness new computational and statistical methods to make sense of today’s unprecedented size, complexity, and fast streaming data is helping scientists make new discoveries. The question now is how to ensure that researchers can employ these tools and use them appropriately. This talk will cover the state of data science as it relates to scientific research and the role astronomers play in its development, use, and training the next generation of astro-data scientists.

Implicit Theories of Creativity in Computer Science in the United States and China

ERIC Educational Resources Information Center

Tang, Chaoying; Baer, John; Kaufman, James C.

2015-01-01

To study implicit concepts of creativity in computer science in the United States and mainland China, we first asked 308 Chinese computer scientists for adjectives that would describe a creative computer scientist. Computer scientists and non-computer scientists from China (N = 1069) and the United States (N = 971) then rated how well those…

Dizziness Can Be a Drag: Coping with Balance Disorders

MedlinePlus

... now in clinical trials, scientists have created a “virtual reality” grocery store. It allows people with balance disorders to walk safely on a treadmill through computer-generated store aisles. While ... reach for items on virtual shelves. By doing this, they safely learn how ...

Current Developments in Machine Learning Techniques in Biological Data Mining.

PubMed

Dumancas, Gerard G; Adrianto, Indra; Bello, Ghalib; Dozmorov, Mikhail

2017-01-01

This supplement is intended to focus on the use of machine learning techniques to generate meaningful information on biological data. This supplement under Bioinformatics and Biology Insights aims to provide scientists and researchers working in this rapid and evolving field with online, open-access articles authored by leading international experts in this field. Advances in the field of biology have generated massive opportunities to allow the implementation of modern computational and statistical techniques. Machine learning methods in particular, a subfield of computer science, have evolved as an indispensable tool applied to a wide spectrum of bioinformatics applications. Thus, it is broadly used to investigate the underlying mechanisms leading to a specific disease, as well as the biomarker discovery process. With a growth in this specific area of science comes the need to access up-to-date, high-quality scholarly articles that will leverage the knowledge of scientists and researchers in the various applications of machine learning techniques in mining biological data.

An application of artificial intelligence to the interpretation of mass spectra.

NASA Technical Reports Server (NTRS)

Buchanan, B. G.; Duffield, A. M.; Robertson, A. V.

1971-01-01

Description of the DENDRAL (Dendritic Algorithm) project, the objectives of which were to base the computer program on an alogorithm that generates an exhaustive, nonredundant list of all the structural isomers of a given chemical composition, and to devise a computer program that would perform an organic structure determination, given a molecular formula and a mass spectrum. This program is called 'Heuristic DENDRAL' and it operates by using the known structure/spectrum correlations to constrain the DENDRAL isomer generator to produce a single isomer for that composition. The collaboration of chemists and computer scientists has produced a tool of some practical utility from the chemical viewpoint, and an interesting program from the viewpoint of artificial intelligence.

Microgravity

NASA Image and Video Library

2000-04-19

Dr. Marc Pusey (seated) and Dr. Craig Kundrot use computers to analyze x-ray maps and generate three-dimensional models of protein structures. With this information, scientists at Marshall Space Flight Center can learn how proteins are made and how they work. The computer screen depicts a proten structure as a ball-and-stick model. Other models depict the actual volume occupied by the atoms, or the ribbon-like structures that are crucial to a protein's function.

Towards Robot Scientists for autonomous scientific discovery

PubMed Central

2010-01-01

We review the main components of autonomous scientific discovery, and how they lead to the concept of a Robot Scientist. This is a system which uses techniques from artificial intelligence to automate all aspects of the scientific discovery process: it generates hypotheses from a computer model of the domain, designs experiments to test these hypotheses, runs the physical experiments using robotic systems, analyses and interprets the resulting data, and repeats the cycle. We describe our two prototype Robot Scientists: Adam and Eve. Adam has recently proven the potential of such systems by identifying twelve genes responsible for catalysing specific reactions in the metabolic pathways of the yeast Saccharomyces cerevisiae. This work has been formally recorded in great detail using logic. We argue that the reporting of science needs to become fully formalised and that Robot Scientists can help achieve this. This will make scientific information more reproducible and reusable, and promote the integration of computers in scientific reasoning. We believe the greater automation of both the physical and intellectual aspects of scientific investigations to be essential to the future of science. Greater automation improves the accuracy and reliability of experiments, increases the pace of discovery and, in common with conventional laboratory automation, removes tedious and repetitive tasks from the human scientist. PMID:20119518

Towards Robot Scientists for autonomous scientific discovery.

PubMed

Sparkes, Andrew; Aubrey, Wayne; Byrne, Emma; Clare, Amanda; Khan, Muhammed N; Liakata, Maria; Markham, Magdalena; Rowland, Jem; Soldatova, Larisa N; Whelan, Kenneth E; Young, Michael; King, Ross D

2010-01-04

We review the main components of autonomous scientific discovery, and how they lead to the concept of a Robot Scientist. This is a system which uses techniques from artificial intelligence to automate all aspects of the scientific discovery process: it generates hypotheses from a computer model of the domain, designs experiments to test these hypotheses, runs the physical experiments using robotic systems, analyses and interprets the resulting data, and repeats the cycle. We describe our two prototype Robot Scientists: Adam and Eve. Adam has recently proven the potential of such systems by identifying twelve genes responsible for catalysing specific reactions in the metabolic pathways of the yeast Saccharomyces cerevisiae. This work has been formally recorded in great detail using logic. We argue that the reporting of science needs to become fully formalised and that Robot Scientists can help achieve this. This will make scientific information more reproducible and reusable, and promote the integration of computers in scientific reasoning. We believe the greater automation of both the physical and intellectual aspects of scientific investigations to be essential to the future of science. Greater automation improves the accuracy and reliability of experiments, increases the pace of discovery and, in common with conventional laboratory automation, removes tedious and repetitive tasks from the human scientist.

Proteomics, lipidomics, metabolomics: a mass spectrometry tutorial from a computer scientist's point of view.

PubMed

Smith, Rob; Mathis, Andrew D; Ventura, Dan; Prince, John T

2014-01-01

For decades, mass spectrometry data has been analyzed to investigate a wide array of research interests, including disease diagnostics, biological and chemical theory, genomics, and drug development. Progress towards solving any of these disparate problems depends upon overcoming the common challenge of interpreting the large data sets generated. Despite interim successes, many data interpretation problems in mass spectrometry are still challenging. Further, though these challenges are inherently interdisciplinary in nature, the significant domain-specific knowledge gap between disciplines makes interdisciplinary contributions difficult. This paper provides an introduction to the burgeoning field of computational mass spectrometry. We illustrate key concepts, vocabulary, and open problems in MS-omics, as well as provide invaluable resources such as open data sets and key search terms and references. This paper will facilitate contributions from mathematicians, computer scientists, and statisticians to MS-omics that will fundamentally improve results over existing approaches and inform novel algorithmic solutions to open problems.

A characterization of workflow management systems for extreme-scale applications

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

Ferreira da Silva, Rafael; Filgueira, Rosa; Pietri, Ilia

We present that the automation of the execution of computational tasks is at the heart of improving scientific productivity. Over the last years, scientific workflows have been established as an important abstraction that captures data processing and computation of large and complex scientific applications. By allowing scientists to model and express entire data processing steps and their dependencies, workflow management systems relieve scientists from the details of an application and manage its execution on a computational infrastructure. As the resource requirements of today’s computational and data science applications that process vast amounts of data keep increasing, there is a compellingmore » case for a new generation of advances in high-performance computing, commonly termed as extreme-scale computing, which will bring forth multiple challenges for the design of workflow applications and management systems. This paper presents a novel characterization of workflow management systems using features commonly associated with extreme-scale computing applications. We classify 15 popular workflow management systems in terms of workflow execution models, heterogeneous computing environments, and data access methods. Finally, the paper also surveys workflow applications and identifies gaps for future research on the road to extreme-scale workflows and management systems.« less

A characterization of workflow management systems for extreme-scale applications

DOE PAGES

Ferreira da Silva, Rafael; Filgueira, Rosa; Pietri, Ilia; ...

2017-02-16

We present that the automation of the execution of computational tasks is at the heart of improving scientific productivity. Over the last years, scientific workflows have been established as an important abstraction that captures data processing and computation of large and complex scientific applications. By allowing scientists to model and express entire data processing steps and their dependencies, workflow management systems relieve scientists from the details of an application and manage its execution on a computational infrastructure. As the resource requirements of today’s computational and data science applications that process vast amounts of data keep increasing, there is a compellingmore » case for a new generation of advances in high-performance computing, commonly termed as extreme-scale computing, which will bring forth multiple challenges for the design of workflow applications and management systems. This paper presents a novel characterization of workflow management systems using features commonly associated with extreme-scale computing applications. We classify 15 popular workflow management systems in terms of workflow execution models, heterogeneous computing environments, and data access methods. Finally, the paper also surveys workflow applications and identifies gaps for future research on the road to extreme-scale workflows and management systems.« less

Perspectives on next-generation technology for environmental sensor networks

Treesearch

Barbara J. Benson; Barbara J. Bond; Michael P. Hamilton; Russell K. Monson; Richard Han

2009-01-01

Sensor networks promise to transform and expand environmental science. However, many technological difficulties must be overcome to achieve this potential. Partnerships of ecologists with computer scientists and engineers are critical in meeting these challenges. Technological issues include promoting innovation in new sensor design, incorporating power optimization...

EASI: An electronic assistant for scientific investigation

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

Schur, A.; Feller, D.; DeVaney, M.

1991-09-01

Although many automated tools support the productivity of professionals (engineers, managers, architects, secretaries, etc.), none specifically address the needs of the scientific researcher. The scientist's needs are complex and the primary activities are cognitive rather than physical. The individual scientist collects and manipulates large data sets, integrates, synthesizes, generates, and records information. The means to access and manipulate information are a critical determinant of the performance of the system as a whole. One hindrance in this process is the scientist's computer environment, which has changed little in the last two decades. Extensive time and effort is demanded from the scientistmore » to learn to use the computer system. This paper describes how chemists' activities and interactions with information were abstracted into a common paradigm that meets the critical requirement of facilitating information access and retrieval. This paradigm was embodied in EASI, a working prototype that increased the productivity of the individual scientific researcher. 4 refs., 2 figs., 1 tab.« less

Skel: Generative Software for Producing Skeletal I/O Applications

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

Logan, J.; Klasky, S.; Lofstead, J.

2011-01-01

Massively parallel computations consist of a mixture of computation, communication, and I/O. As part of the co-design for the inevitable progress towards exascale computing, we must apply lessons learned from past work to succeed in this new age of computing. Of the three components listed above, implementing an effective parallel I/O solution has often been overlooked by application scientists and was usually added to large scale simulations only when existing serial techniques had failed. As scientists teams scaled their codes to run on hundreds of processors, it was common to call on an I/O expert to implement a set ofmore » more scalable I/O routines. These routines were easily separated from the calculations and communication, and in many cases, an I/O kernel was derived from the application which could be used for testing I/O performance independent of the application. These I/O kernels developed a life of their own used as a broad measure for comparing different I/O techniques. Unfortunately, as years passed and computation and communication changes required changes to the I/O, the separate I/O kernel used for benchmarking remained static no longer providing an accurate indicator of the I/O performance of the simulation making I/O research less relevant for the application scientists. In this paper we describe a new approach to this problem where I/O kernels are replaced with skeletal I/O applications automatically generated from an abstract set of simulation I/O parameters. We realize this abstraction by leveraging the ADIOS middleware's XML I/O specification with additional runtime parameters. Skeletal applications offer all of the benefits of I/O kernels including allowing I/O optimizations to focus on useful I/O patterns. Moreover, since they are automatically generated, it is easy to produce an updated I/O skeleton whenever the simulation's I/O changes. In this paper we analyze the performance of automatically generated I/O skeletal applications for the S3D and GTS codes. We show that these skeletal applications achieve performance comparable to that of the production applications. We wrap up the paper with a discussion of future changes to make the skeletal application better approximate the actual I/O performed in the simulation.« less

Encouraging Greater Student Inquiry Engagement in Science through Motivational Support by Online Scientist-Mentors

ERIC Educational Resources Information Center

Scogin, Stephen C.; Stuessy, Carol L.

2015-01-01

Next Generation Science Standards (NGSS) call for integrating knowledge and practice in learning experiences in K-12 science education. "PlantingScience" (PS), an ideal curriculum for use as an NGSS model, is a computer-mediated collaborative learning environment intertwining scientific inquiry, classroom instruction, and online…

To the Cloud! A Grassroots Proposal to Accelerate Brain Science Discovery

PubMed Central

Vogelstein, Joshua T.; Mensh, Brett; Hausser, Michael; Spruston, Nelson; Evans, Alan; Kording, Konrad; Amunts, Katrin; Ebell, Christoph; Muller, Jeff; Telefont, Martin; Hill, Sean; Koushika, Sandhya P.; Cali, Corrado; Valdés-Sosa, Pedro Antonio; Littlewood, Peter; Koch, Christof; Saalfeld, Stephan; Kepecs, Adam; Peng, Hanchuan; Halchenko, Yaroslav O.; Kiar, Gregory; Poo, Mu-Ming; Poline, Jean-Baptiste; Milham, Michael P.; Schaffer, Alyssa Picchini; Gidron, Rafi; Okano, Hideyuki; Calhoun, Vince D; Chun, Miyoung; Kleissas, Dean M.; Vogelstein, R. Jacob; Perlman, Eric; Burns, Randal; Huganir, Richard; Miller, Michael I.

2018-01-01

The revolution in neuroscientific data acquisition is creating an analysis challenge. We propose leveraging cloud-computing technologies to enable large-scale neurodata storing, exploring, analyzing, and modeling. This utility will empower scientists globally to generate and test theories of brain function and dysfunction. PMID:27810005

Amplify scientific discovery with artificial intelligence

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

Gil, Yolanda; Greaves, Mark T.; Hendler, James

Computing innovations have fundamentally changed many aspects of scientific inquiry. For example, advances in robotics, high-end computing, networking, and databases now underlie much of what we do in science such as gene sequencing, general number crunching, sharing information between scientists, and analyzing large amounts of data. As computing has evolved at a rapid pace, so too has its impact in science, with the most recent computing innovations repeatedly being brought to bear to facilitate new forms of inquiry. Recently, advances in Artificial Intelligence (AI) have deeply penetrated many consumer sectors, including for example Apple’s Siri™ speech recognition system, real-time automatedmore » language translation services, and a new generation of self-driving cars and self-navigating drones. However, AI has yet to achieve comparable levels of penetration in scientific inquiry, despite its tremendous potential in aiding computers to help scientists tackle tasks that require scientific reasoning. We contend that advances in AI will transform the practice of science as we are increasingly able to effectively and jointly harness human and machine intelligence in the pursuit of major scientific challenges.« less

Surface Modeling, Grid Generation, and Related Issues in Computational Fluid Dynamic (CFD) Solutions

NASA Technical Reports Server (NTRS)

Choo, Yung K. (Compiler)

1995-01-01

The NASA Steering Committee for Surface Modeling and Grid Generation (SMAGG) sponsored a workshop on surface modeling, grid generation, and related issues in Computational Fluid Dynamics (CFD) solutions at Lewis Research Center, Cleveland, Ohio, May 9-11, 1995. The workshop provided a forum to identify industry needs, strengths, and weaknesses of the five grid technologies (patched structured, overset structured, Cartesian, unstructured, and hybrid), and to exchange thoughts about where each technology will be in 2 to 5 years. The workshop also provided opportunities for engineers and scientists to present new methods, approaches, and applications in SMAGG for CFD. This Conference Publication (CP) consists of papers on industry overview, NASA overview, five grid technologies, new methods/ approaches/applications, and software systems.

From Scoresby to Nansen to Wegener: The Role of Polar History in Producing the Next Generation of High-Latitude Hydrologic and Cryospheric Scientists

NASA Astrophysics Data System (ADS)

Sturm, M.

2009-05-01

Many scientists, like myself, were first attracted to the polar regions by tales of heroic explorers. These earlier explorers were also scientists, or more correctly, naturalists. They produced maps, sketches, and studies on atmospheric, cryospheric, biological, and sociological topics alike. For many of us, reading about polar history led directly to our interests in cryospheric and hydrological science. While the age of geographical exploration is long over, replaced by Google Earth, the stories from that by-gone era may still be one of the most powerful recruiting tools for producing passionate and committed polar scientists for the next generation. I would argue for an increased emphasis in teaching our students about the history of exploration and science. If we do so, at a minimum our students will better appreciate modern clothing, transportation, data loggers, communication equipment, and computers. More importantly, it will introduce to the next generation the idea of the naturalist, whose purview is all components of the natural system. Many of the high latitude issues facing us today require a system-science approach that can be difficult to learn or master in an era of disciplinary specialization. The early naturalist-explorers understood this approach and still have much to teach us if we take the time to listen to what went before.

Marketing and commercialization of computational research services.

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

Toevs, J. W.

Physical and computational scientists and mathematicians in Russia's nuclear cities are turning their work toward generating profits from Western markets. Successful ventures require an understanding of the marketing of contract research as well as Western expectations regarding contract execution, quality, and performance. This paper will address fundamentals in business structure, marketing, and contract performance for organizations engaging in the marketing and commercialization of research services. Considerable emphasis will be placed on developing adequate communication within the organization.

A Grid Infrastructure for Supporting Space-based Science Operations

NASA Technical Reports Server (NTRS)

Bradford, Robert N.; Redman, Sandra H.; McNair, Ann R. (Technical Monitor)

2002-01-01

Emerging technologies for computational grid infrastructures have the potential for revolutionizing the way computers are used in all aspects of our lives. Computational grids are currently being implemented to provide a large-scale, dynamic, and secure research and engineering environments based on standards and next-generation reusable software, enabling greater science and engineering productivity through shared resources and distributed computing for less cost than traditional architectures. Combined with the emerging technologies of high-performance networks, grids provide researchers, scientists and engineers the first real opportunity for an effective distributed collaborative environment with access to resources such as computational and storage systems, instruments, and software tools and services for the most computationally challenging applications.

Recruitment of Foreigners in the Market for Computer Scientists in the United States

PubMed Central

Bound, John; Braga, Breno; Golden, Joseph M.

2016-01-01

We present and calibrate a dynamic model that characterizes the labor market for computer scientists. In our model, firms can recruit computer scientists from recently graduated college students, from STEM workers working in other occupations or from a pool of foreign talent. Counterfactual simulations suggest that wages for computer scientists would have been 2.8–3.8% higher, and the number of Americans employed as computers scientists would have been 7.0–13.6% higher in 2004 if firms could not hire more foreigners than they could in 1994. In contrast, total CS employment would have been 3.8–9.0% lower, and consequently output smaller. PMID:27170827

P-MartCancer: A New Online Platform to Access CPTAC Datasets and Enable New Analyses | Office of Cancer Clinical Proteomics Research

Cancer.gov

The November 1, 2017 issue of Cancer Research is dedicated to a collection of computational resource papers in genomics, proteomics, animal models, imaging, and clinical subjects for non-bioinformaticists looking to incorporate computing tools into their work. Scientists at Pacific Northwest National Laboratory have developed P-MartCancer, an open, web-based interactive software tool that enables statistical analyses of peptide or protein data generated from mass-spectrometry (MS)-based global proteomics experiments.

Preparing the Next Generation of Environmental Scientists to Work at the Frontier of Data-Intensive Research

NASA Astrophysics Data System (ADS)

Hampton, S. E.

2015-12-01

The science necessary to unravel complex environmental problems confronts severe computational challenges - coping with huge volumes of heterogeneous data, spanning vast spatial scales at high resolution, and requiring integration of disparate measurements from multiple disciplines. But as cyberinfrastructure advances to support such work, scientists in many fields lack sufficient computational skills to participate in interdisciplinary, data-intensive research. In response, we developed innovative training workshops for early-career scientists, in order to explore both the needs and solutions for training next-generation scientists in skills for data-intensive environmental research. In 2013 and 2014 we ran intensive 3-week training workshops for early-career researchers. One of the workshops was run concurrently in California and North Carolina, connected by virtual technologies and coordinated schedules. We attracted applicants to the workshop with the opportunity to pursue data-intensive small-group research projects that they proposed. This approach presented a realistic possibility that publishable products could result from 3 weeks of focused hands-on classroom instruction combined with self-directed group research in which instructors were present to assist trainees. Instruction addressed 1) collaboration modes and technologies, 2) data management, preservation, and sharing, 3) preparing data for analysis using scripting, 4) reproducible research, 5) sustainable software practices, 6) data analysis and modeling, and 7) communicating results to broad communities. The most dramatic improvements in technical skills were in data management, version control, and working with spatial data outside of proprietary software. In addition, participants built strong networks and collaborative skills that later resulted in a successful student-led grant proposal, published manuscripts, and participants reported that the training was a highly influential experience.

Computational and Experimental Evaluation of a Complex Inlet Swirl Pattern Generation System (POSTPRINT)

DTIC Science & Technology

2016-08-01

Sanders, Chase A. Nessler, William W. Copenhaver, Michael G. List, and Timothy J. Janczewski Turbomachinery Branch Turbine Engine Division AUGUST...Branch Turbine Engine Division Turbine Engine Division Aerospace Systems Directorate //Signature// ROBERT D. HANCOCK Principal Scientist Turbine ...ORGANIZATION Turbomachinery Branch Turbine Engine Division Air Force Research Laboratory, Aerospace Systems Directorate Wright-Patterson Air Force

More of an art than a science: Using microbial DNA sequences to compose music

DOE PAGES

Larsen, Peter E.

2016-03-01

Bacteria are everywhere. Microbial ecology is emerging as a critical field for understanding the relationships between these ubiquitous bacterial communities, the environment, and human health. Next generation DNA sequencing technology provides us a powerful tool to indirectly observe the communities by sequencing and analyzing all of the bacterial DNA present in an environment. The results of the DNA sequencing experiments can generate gigabytes to terabytes of information however, making it difficult for the citizen scientist to grasp and the educator to convey this data. Here, we present a method for interpreting massive amounts of microbial ecology data as musical performances,more » easily generated on any computer and using only commonly available or freely available software and the ‘Microbial Bebop’ algorithm. Furthermore, using this approach citizen scientists and biology educators can sonify complex data in a fun and interactive format, making it easier to communicate both the importance and the excitement of exploring the planet earth’s largest ecosystem.« less

More of an art than a science: Using microbial DNA sequences to compose music

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

Larsen, Peter E.

Bacteria are everywhere. Microbial ecology is emerging as a critical field for understanding the relationships between these ubiquitous bacterial communities, the environment, and human health. Next generation DNA sequencing technology provides us a powerful tool to indirectly observe the communities by sequencing and analyzing all of the bacterial DNA present in an environment. The results of the DNA sequencing experiments can generate gigabytes to terabytes of information however, making it difficult for the citizen scientist to grasp and the educator to convey this data. Here, we present a method for interpreting massive amounts of microbial ecology data as musical performances,more » easily generated on any computer and using only commonly available or freely available software and the ‘Microbial Bebop’ algorithm. Furthermore, using this approach citizen scientists and biology educators can sonify complex data in a fun and interactive format, making it easier to communicate both the importance and the excitement of exploring the planet earth’s largest ecosystem.« less

Use of Emerging Grid Computing Technologies for the Analysis of LIGO Data

NASA Astrophysics Data System (ADS)

Koranda, Scott

2004-03-01

The LIGO Scientific Collaboration (LSC) today faces the challenge of enabling analysis of terabytes of LIGO data by hundreds of scientists from institutions all around the world. To meet this challenge the LSC is developing tools, infrastructure, applications, and expertise leveraging Grid Computing technologies available today, and making available to LSC scientists compute resources at sites across the United States and Europe. We use digital credentials for strong and secure authentication and authorization to compute resources and data. Building on top of products from the Globus project for high-speed data transfer and information discovery we have created the Lightweight Data Replicator (LDR) to securely and robustly replicate data to resource sites. We have deployed at our computing sites the Virtual Data Toolkit (VDT) Server and Client packages, developed in collaboration with our partners in the GriPhyN and iVDGL projects, providing uniform access to distributed resources for users and their applications. Taken together these Grid Computing technologies and infrastructure have formed the LSC DataGrid--a coherent and uniform environment across two continents for the analysis of gravitational-wave detector data. Much work, however, remains in order to scale current analyses and recent lessons learned need to be integrated into the next generation of Grid middleware.

High-performance integrated virtual environment (HIVE): a robust infrastructure for next-generation sequence data analysis

PubMed Central

Simonyan, Vahan; Chumakov, Konstantin; Dingerdissen, Hayley; Faison, William; Goldweber, Scott; Golikov, Anton; Gulzar, Naila; Karagiannis, Konstantinos; Vinh Nguyen Lam, Phuc; Maudru, Thomas; Muravitskaja, Olesja; Osipova, Ekaterina; Pan, Yang; Pschenichnov, Alexey; Rostovtsev, Alexandre; Santana-Quintero, Luis; Smith, Krista; Thompson, Elaine E.; Tkachenko, Valery; Torcivia-Rodriguez, John; Wan, Quan; Wang, Jing; Wu, Tsung-Jung; Wilson, Carolyn; Mazumder, Raja

2016-01-01

The High-performance Integrated Virtual Environment (HIVE) is a distributed storage and compute environment designed primarily to handle next-generation sequencing (NGS) data. This multicomponent cloud infrastructure provides secure web access for authorized users to deposit, retrieve, annotate and compute on NGS data, and to analyse the outcomes using web interface visual environments appropriately built in collaboration with research and regulatory scientists and other end users. Unlike many massively parallel computing environments, HIVE uses a cloud control server which virtualizes services, not processes. It is both very robust and flexible due to the abstraction layer introduced between computational requests and operating system processes. The novel paradigm of moving computations to the data, instead of moving data to computational nodes, has proven to be significantly less taxing for both hardware and network infrastructure. The honeycomb data model developed for HIVE integrates metadata into an object-oriented model. Its distinction from other object-oriented databases is in the additional implementation of a unified application program interface to search, view and manipulate data of all types. This model simplifies the introduction of new data types, thereby minimizing the need for database restructuring and streamlining the development of new integrated information systems. The honeycomb model employs a highly secure hierarchical access control and permission system, allowing determination of data access privileges in a finely granular manner without flooding the security subsystem with a multiplicity of rules. HIVE infrastructure will allow engineers and scientists to perform NGS analysis in a manner that is both efficient and secure. HIVE is actively supported in public and private domains, and project collaborations are welcomed. Database URL: https://hive.biochemistry.gwu.edu PMID:26989153

High-performance integrated virtual environment (HIVE): a robust infrastructure for next-generation sequence data analysis.

PubMed

Simonyan, Vahan; Chumakov, Konstantin; Dingerdissen, Hayley; Faison, William; Goldweber, Scott; Golikov, Anton; Gulzar, Naila; Karagiannis, Konstantinos; Vinh Nguyen Lam, Phuc; Maudru, Thomas; Muravitskaja, Olesja; Osipova, Ekaterina; Pan, Yang; Pschenichnov, Alexey; Rostovtsev, Alexandre; Santana-Quintero, Luis; Smith, Krista; Thompson, Elaine E; Tkachenko, Valery; Torcivia-Rodriguez, John; Voskanian, Alin; Wan, Quan; Wang, Jing; Wu, Tsung-Jung; Wilson, Carolyn; Mazumder, Raja

2016-01-01

The High-performance Integrated Virtual Environment (HIVE) is a distributed storage and compute environment designed primarily to handle next-generation sequencing (NGS) data. This multicomponent cloud infrastructure provides secure web access for authorized users to deposit, retrieve, annotate and compute on NGS data, and to analyse the outcomes using web interface visual environments appropriately built in collaboration with research and regulatory scientists and other end users. Unlike many massively parallel computing environments, HIVE uses a cloud control server which virtualizes services, not processes. It is both very robust and flexible due to the abstraction layer introduced between computational requests and operating system processes. The novel paradigm of moving computations to the data, instead of moving data to computational nodes, has proven to be significantly less taxing for both hardware and network infrastructure.The honeycomb data model developed for HIVE integrates metadata into an object-oriented model. Its distinction from other object-oriented databases is in the additional implementation of a unified application program interface to search, view and manipulate data of all types. This model simplifies the introduction of new data types, thereby minimizing the need for database restructuring and streamlining the development of new integrated information systems. The honeycomb model employs a highly secure hierarchical access control and permission system, allowing determination of data access privileges in a finely granular manner without flooding the security subsystem with a multiplicity of rules. HIVE infrastructure will allow engineers and scientists to perform NGS analysis in a manner that is both efficient and secure. HIVE is actively supported in public and private domains, and project collaborations are welcomed. Database URL: https://hive.biochemistry.gwu.edu. © The Author(s) 2016. Published by Oxford University Press.

2017 ISCB Accomplishment by a Senior Scientist Award: Pavel Pevzner

PubMed Central

Fogg, Christiana N.; Kovats, Diane E.; Berger, Bonnie

2017-01-01

The International Society for Computational Biology ( ISCB) recognizes an established scientist each year with the Accomplishment by a Senior Scientist Award for significant contributions he or she has made to the field. This award honors scientists who have contributed to the advancement of computational biology and bioinformatics through their research, service, and education work. Pavel Pevzner, PhD, Ronald R. Taylor Professor of Computer Science and Director of the NIH Center for Computational Mass Spectrometry at University of California, San Diego, has been selected as the winner of the 2017 Accomplishment by a Senior Scientist Award. The ISCB awards committee, chaired by Dr. Bonnie Berger of the Massachusetts Institute of Technology, selected Pevzner as the 2017 winner. Pevzner will receive his award and deliver a keynote address at the 2017 Intelligent Systems for Molecular Biology-European Conference on Computational Biology joint meeting ( ISMB/ECCB 2017) held in Prague, Czech Republic from July 21-July 25, 2017. ISMB/ECCB is a biennial joint meeting that brings together leading scientists in computational biology and bioinformatics from around the globe. PMID:28713548

Buried deep: How data about subseafloor life becomes dark and why

NASA Astrophysics Data System (ADS)

Darch, P. T.; Cummings, R.

2013-12-01

Earth scientists increasingly work in distributed, multidisciplinary projects. To promote the sharing of data across such a project, it is vital to improve long-term preservation of data in formats accessible to scientists in multiple disciplines with diverse needs, tools and scientific practices. When developing data management plans and infrastructure, it is important to ask: - What data are generated? - Where are these data preserved and shared? - What are the processes by which these data become 'dark'? - What are the infrastructural and social factors that shape these processes? In response to these questions, we present findings from the first year of a case study of the Center for Dark Energy Biosphere Investigations (C-DEBI), an NSF Science and Technology Center studying microbial life in the deep subseafloor biosphere. Our case study is funded by the Sloan Foundation and the NSF. It involves observation in laboratories, interviews, attendance of scientific meetings, and document analysis. At the laboratory level, we observed scientists mainly working on individual projects, or in a team of two or three. There is infrequent sharing of laboratory-generated data across C-DEBI. Where it does happen, it often takes place following discovery of the data through informal networks or serendipitous encounters with the data's creator. Instead, most of the laboratory-generated data become dark data. These data are typically preserved on a scientist's personal computer in ways particular to the individual, frequently not in a form meaningful to others. Other scientists are often not even aware that these data exist. Furthermore, the scientist tends to take care to preserve these data only as long as they require them: data loss can occur over time. Some data - those which support findings in a paper - may be deposited in a disciplinary database. However, these data are the end result of extensive processing: earlier versions of datasets can be lost. Also, in some disciplines, scientists are not required to deposit these data. Hence the data deposited in these databases are only a fraction of the total laboratory-generated data. Thus, the vast majority of laboratory-generated data is not preserved long-term in a form discoverable or usable to other scientists. We found that the multidisciplinary, distributed nature of C-DEBI can exacerbate the factors that contribute to data staying dark. These include: - It can be hard for scientists to conceptualize how their data may be useful to scientists in other disciplines. This reduces scientists' willingness to perform the work of long-term data preservation; - Fewer opportunities for building of informal networks or serendipitous encounters for data discovery than if scientists were collocated; - Many scientists are part of C-DEBI for a short time only (1-3 years), getting involved through the awarding of C-DEBI grants and fellowships. After their involvement, they may no longer maintain contacts across disciplines within C-DEBI. This makes it harder for them to see how their data might be useful to others, and for others to discover these data through word-of-mouth; - Resistance to standardization of data practices. Multidisciplinary work involves bringing multiple perspectives to bear on research questions. Scientists are concerned that standardization could prematurely foreclose as-yet-unexplored scientific methods.

New Web-Based Tools Make Systems Pharmacology More Accessible Using Data from the NCI-60 | Center for Cancer Research

Cancer.gov

High-throughput biological techniques, like microarrays and drug screens, generate an enormous amount of data that may be critically important for cancer researchers and clinicians. Being able to manipulate the data to extract those pieces of interest, however, can require computational or bioinformatics skills beyond those of the average scientist.

Development of a PC-based diabetes simulator in collaboration with teenagers with type 1 diabetes.

PubMed

Nordfeldt, S; Hanberger, L; Malm, F; Ludvigsson, J

2007-02-01

The main aim of this study was to develop and test in a pilot study a PC-based interactive diabetes simulator prototype as a part of future Internet-based support systems for young teenagers and their families. A second aim was to gain experience in user-centered design (UCD) methods applied to such subjects. Using UCD methods, a computer scientist participated in iterative user group sessions involving teenagers with Type 1 diabetes 13-17 years old and parents. Input was transformed into a requirements specification by the computer scientist and advisors. This was followed by gradual prototype development based on a previously developed mathematical core. Individual test sessions were followed by a pilot study with five subjects testing a prototype. The process was evaluated by registration of flow and content of input and opinions from expert advisors. It was initially difficult to motivate teenagers to participate. User group discussion topics ranged from concrete to more academic matters. The issue of a simulator created active discussions among parents and teenagers. A large amount of input was generated from discussions among the teenagers. Individual test runs generated useful input. A pilot study suggested that the gradually elaborated software was functional. A PC-based diabetes simulator may create substantial interest among teenagers and parents, and the prototype seems worthy of further development and studies. UCD methods may generate significant input for computer support system design work and contribute to a functional design. Teenager involvement in design work may require time, patience, and flexibility.

Microgravity

NASA Image and Video Library

2001-06-06

X-rays diffracted from a well-ordered protein crystal create sharp patterns of scattered light on film. A computer can use these patterns to generate a model of a protein molecule. To analyze the selected crystal, an X-ray crystallographer shines X-rays through the crystal. Unlike a single dental X-ray, which produces a shadow image of a tooth, these X-rays have to be taken many times from different angles to produce a pattern from the scattered light, a map of the intensity of the X-rays after they diffract through the crystal. The X-rays bounce off the electron clouds that form the outer structure of each atom. A flawed crystal will yield a blurry pattern; a well-ordered protein crystal yields a series of sharp diffraction patterns. From these patterns, researchers build an electron density map. With powerful computers and a lot of calculations, scientists can use the electron density patterns to determine the structure of the protein and make a computer-generated model of the structure. The models let researchers improve their understanding of how the protein functions. They also allow scientists to look for receptor sites and active areas that control a protein's function and role in the progress of diseases. From there, pharmaceutical researchers can design molecules that fit the active site, much like a key and lock, so that the protein is locked without affecting the rest of the body. This is called structure-based drug design.

Mantle Convection on Modern Supercomputers

NASA Astrophysics Data System (ADS)

Weismüller, J.; Gmeiner, B.; Huber, M.; John, L.; Mohr, M.; Rüde, U.; Wohlmuth, B.; Bunge, H. P.

2015-12-01

Mantle convection is the cause for plate tectonics, the formation of mountains and oceans, and the main driving mechanism behind earthquakes. The convection process is modeled by a system of partial differential equations describing the conservation of mass, momentum and energy. Characteristic to mantle flow is the vast disparity of length scales from global to microscopic, turning mantle convection simulations into a challenging application for high-performance computing. As system size and technical complexity of the simulations continue to increase, design and implementation of simulation models for next generation large-scale architectures is handled successfully only in an interdisciplinary context. A new priority program - named SPPEXA - by the German Research Foundation (DFG) addresses this issue, and brings together computer scientists, mathematicians and application scientists around grand challenges in HPC. Here we report from the TERRA-NEO project, which is part of the high visibility SPPEXA program, and a joint effort of four research groups. TERRA-NEO develops algorithms for future HPC infrastructures, focusing on high computational efficiency and resilience in next generation mantle convection models. We present software that can resolve the Earth's mantle with up to 1012 grid points and scales efficiently to massively parallel hardware with more than 50,000 processors. We use our simulations to explore the dynamic regime of mantle convection and assess the impact of small scale processes on global mantle flow.

Representation of research hypotheses

PubMed Central

2011-01-01

Background Hypotheses are now being automatically produced on an industrial scale by computers in biology, e.g. the annotation of a genome is essentially a large set of hypotheses generated by sequence similarity programs; and robot scientists enable the full automation of a scientific investigation, including generation and testing of research hypotheses. Results This paper proposes a logically defined way for recording automatically generated hypotheses in machine amenable way. The proposed formalism allows the description of complete hypotheses sets as specified input and output for scientific investigations. The formalism supports the decomposition of research hypotheses into more specialised hypotheses if that is required by an application. Hypotheses are represented in an operational way – it is possible to design an experiment to test them. The explicit formal description of research hypotheses promotes the explicit formal description of the results and conclusions of an investigation. The paper also proposes a framework for automated hypotheses generation. We demonstrate how the key components of the proposed framework are implemented in the Robot Scientist “Adam”. Conclusions A formal representation of automatically generated research hypotheses can help to improve the way humans produce, record, and validate research hypotheses. Availability http://www.aber.ac.uk/en/cs/research/cb/projects/robotscientist/results/ PMID:21624164

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.

How Data Becomes Physics: Inside the RACF

ScienceCinema

Ernst, Michael; Rind, Ofer; Rajagopalan, Srini; Lauret, Jerome; Pinkenburg, Chris

2018-06-22

The RHIC & ATLAS Computing Facility (RACF) at the U.S. Department of Energy’s (DOE) Brookhaven National Laboratory sits at the center of a global computing network. It connects more than 2,500 researchers around the world with the data generated by millions of particle collisions taking place each second at Brookhaven Lab's Relativistic Heavy Ion Collider (RHIC, a DOE Office of Science User Facility for nuclear physics research), and the ATLAS experiment at the Large Hadron Collider in Europe. Watch this video to learn how the people and computing resources of the RACF serve these scientists to turn petabytes of raw data into physics discoveries.

Open-Phylo: a customizable crowd-computing platform for multiple sequence alignment

PubMed Central

2013-01-01

Citizen science games such as Galaxy Zoo, Foldit, and Phylo aim to harness the intelligence and processing power generated by crowds of online gamers to solve scientific problems. However, the selection of the data to be analyzed through these games is under the exclusive control of the game designers, and so are the results produced by gamers. Here, we introduce Open-Phylo, a freely accessible crowd-computing platform that enables any scientist to enter our system and use crowds of gamers to assist computer programs in solving one of the most fundamental problems in genomics: the multiple sequence alignment problem. PMID:24148814

The iPlant Collaborative: Cyberinfrastructure for Plant Biology.

PubMed

Goff, Stephen A; Vaughn, Matthew; McKay, Sheldon; Lyons, Eric; Stapleton, Ann E; Gessler, Damian; Matasci, Naim; Wang, Liya; Hanlon, Matthew; Lenards, Andrew; Muir, Andy; Merchant, Nirav; Lowry, Sonya; Mock, Stephen; Helmke, Matthew; Kubach, Adam; Narro, Martha; Hopkins, Nicole; Micklos, David; Hilgert, Uwe; Gonzales, Michael; Jordan, Chris; Skidmore, Edwin; Dooley, Rion; Cazes, John; McLay, Robert; Lu, Zhenyuan; Pasternak, Shiran; Koesterke, Lars; Piel, William H; Grene, Ruth; Noutsos, Christos; Gendler, Karla; Feng, Xin; Tang, Chunlao; Lent, Monica; Kim, Seung-Jin; Kvilekval, Kristian; Manjunath, B S; Tannen, Val; Stamatakis, Alexandros; Sanderson, Michael; Welch, Stephen M; Cranston, Karen A; Soltis, Pamela; Soltis, Doug; O'Meara, Brian; Ane, Cecile; Brutnell, Tom; Kleibenstein, Daniel J; White, Jeffery W; Leebens-Mack, James; Donoghue, Michael J; Spalding, Edgar P; Vision, Todd J; Myers, Christopher R; Lowenthal, David; Enquist, Brian J; Boyle, Brad; Akoglu, Ali; Andrews, Greg; Ram, Sudha; Ware, Doreen; Stein, Lincoln; Stanzione, Dan

2011-01-01

The iPlant Collaborative (iPlant) is a United States National Science Foundation (NSF) funded project that aims to create an innovative, comprehensive, and foundational cyberinfrastructure in support of plant biology research (PSCIC, 2006). iPlant is developing cyberinfrastructure that uniquely enables scientists throughout the diverse fields that comprise plant biology to address Grand Challenges in new ways, to stimulate and facilitate cross-disciplinary research, to promote biology and computer science research interactions, and to train the next generation of scientists on the use of cyberinfrastructure in research and education. Meeting humanity's projected demands for agricultural and forest products and the expectation that natural ecosystems be managed sustainably will require synergies from the application of information technologies. The iPlant cyberinfrastructure design is based on an unprecedented period of research community input, and leverages developments in high-performance computing, data storage, and cyberinfrastructure for the physical sciences. iPlant is an open-source project with application programming interfaces that allow the community to extend the infrastructure to meet its needs. iPlant is sponsoring community-driven workshops addressing specific scientific questions via analysis tool integration and hypothesis testing. These workshops teach researchers how to add bioinformatics tools and/or datasets into the iPlant cyberinfrastructure enabling plant scientists to perform complex analyses on large datasets without the need to master the command-line or high-performance computational services.

The iPlant Collaborative: Cyberinfrastructure for Plant Biology

PubMed Central

Goff, Stephen A.; Vaughn, Matthew; McKay, Sheldon; Lyons, Eric; Stapleton, Ann E.; Gessler, Damian; Matasci, Naim; Wang, Liya; Hanlon, Matthew; Lenards, Andrew; Muir, Andy; Merchant, Nirav; Lowry, Sonya; Mock, Stephen; Helmke, Matthew; Kubach, Adam; Narro, Martha; Hopkins, Nicole; Micklos, David; Hilgert, Uwe; Gonzales, Michael; Jordan, Chris; Skidmore, Edwin; Dooley, Rion; Cazes, John; McLay, Robert; Lu, Zhenyuan; Pasternak, Shiran; Koesterke, Lars; Piel, William H.; Grene, Ruth; Noutsos, Christos; Gendler, Karla; Feng, Xin; Tang, Chunlao; Lent, Monica; Kim, Seung-Jin; Kvilekval, Kristian; Manjunath, B. S.; Tannen, Val; Stamatakis, Alexandros; Sanderson, Michael; Welch, Stephen M.; Cranston, Karen A.; Soltis, Pamela; Soltis, Doug; O'Meara, Brian; Ane, Cecile; Brutnell, Tom; Kleibenstein, Daniel J.; White, Jeffery W.; Leebens-Mack, James; Donoghue, Michael J.; Spalding, Edgar P.; Vision, Todd J.; Myers, Christopher R.; Lowenthal, David; Enquist, Brian J.; Boyle, Brad; Akoglu, Ali; Andrews, Greg; Ram, Sudha; Ware, Doreen; Stein, Lincoln; Stanzione, Dan

2011-01-01

The iPlant Collaborative (iPlant) is a United States National Science Foundation (NSF) funded project that aims to create an innovative, comprehensive, and foundational cyberinfrastructure in support of plant biology research (PSCIC, 2006). iPlant is developing cyberinfrastructure that uniquely enables scientists throughout the diverse fields that comprise plant biology to address Grand Challenges in new ways, to stimulate and facilitate cross-disciplinary research, to promote biology and computer science research interactions, and to train the next generation of scientists on the use of cyberinfrastructure in research and education. Meeting humanity's projected demands for agricultural and forest products and the expectation that natural ecosystems be managed sustainably will require synergies from the application of information technologies. The iPlant cyberinfrastructure design is based on an unprecedented period of research community input, and leverages developments in high-performance computing, data storage, and cyberinfrastructure for the physical sciences. iPlant is an open-source project with application programming interfaces that allow the community to extend the infrastructure to meet its needs. iPlant is sponsoring community-driven workshops addressing specific scientific questions via analysis tool integration and hypothesis testing. These workshops teach researchers how to add bioinformatics tools and/or datasets into the iPlant cyberinfrastructure enabling plant scientists to perform complex analyses on large datasets without the need to master the command-line or high-performance computational services. PMID:22645531

Concept of a Cloud Service for Data Preparation and Computational Control on Custom HPC Systems in Application to Molecular Dynamics

NASA Astrophysics Data System (ADS)

Puzyrkov, Dmitry; Polyakov, Sergey; Podryga, Viktoriia; Markizov, Sergey

2018-02-01

At the present stage of computer technology development it is possible to study the properties and processes in complex systems at molecular and even atomic levels, for example, by means of molecular dynamics methods. The most interesting are problems related with the study of complex processes under real physical conditions. Solving such problems requires the use of high performance computing systems of various types, for example, GRID systems and HPC clusters. Considering the time consuming computational tasks, the need arises of software for automatic and unified monitoring of such computations. A complex computational task can be performed over different HPC systems. It requires output data synchronization between the storage chosen by a scientist and the HPC system used for computations. The design of the computational domain is also quite a problem. It requires complex software tools and algorithms for proper atomistic data generation on HPC systems. The paper describes the prototype of a cloud service, intended for design of atomistic systems of large volume for further detailed molecular dynamic calculations and computational management for this calculations, and presents the part of its concept aimed at initial data generation on the HPC systems.

A systematic identification and analysis of scientists on Twitter.

PubMed

Ke, Qing; Ahn, Yong-Yeol; Sugimoto, Cassidy R

2017-01-01

Metrics derived from Twitter and other social media-often referred to as altmetrics-are increasingly used to estimate the broader social impacts of scholarship. Such efforts, however, may produce highly misleading results, as the entities that participate in conversations about science on these platforms are largely unknown. For instance, if altmetric activities are generated mainly by scientists, does it really capture broader social impacts of science? Here we present a systematic approach to identifying and analyzing scientists on Twitter. Our method can identify scientists across many disciplines, without relying on external bibliographic data, and be easily adapted to identify other stakeholder groups in science. We investigate the demographics, sharing behaviors, and interconnectivity of the identified scientists. We find that Twitter has been employed by scholars across the disciplinary spectrum, with an over-representation of social and computer and information scientists; under-representation of mathematical, physical, and life scientists; and a better representation of women compared to scholarly publishing. Analysis of the sharing of URLs reveals a distinct imprint of scholarly sites, yet only a small fraction of shared URLs are science-related. We find an assortative mixing with respect to disciplines in the networks between scientists, suggesting the maintenance of disciplinary walls in social media. Our work contributes to the literature both methodologically and conceptually-we provide new methods for disambiguating and identifying particular actors on social media and describing the behaviors of scientists, thus providing foundational information for the construction and use of indicators on the basis of social media metrics.

A systematic identification and analysis of scientists on Twitter

PubMed Central

Ke, Qing; Ahn, Yong-Yeol; Sugimoto, Cassidy R.

2017-01-01

Metrics derived from Twitter and other social media—often referred to as altmetrics—are increasingly used to estimate the broader social impacts of scholarship. Such efforts, however, may produce highly misleading results, as the entities that participate in conversations about science on these platforms are largely unknown. For instance, if altmetric activities are generated mainly by scientists, does it really capture broader social impacts of science? Here we present a systematic approach to identifying and analyzing scientists on Twitter. Our method can identify scientists across many disciplines, without relying on external bibliographic data, and be easily adapted to identify other stakeholder groups in science. We investigate the demographics, sharing behaviors, and interconnectivity of the identified scientists. We find that Twitter has been employed by scholars across the disciplinary spectrum, with an over-representation of social and computer and information scientists; under-representation of mathematical, physical, and life scientists; and a better representation of women compared to scholarly publishing. Analysis of the sharing of URLs reveals a distinct imprint of scholarly sites, yet only a small fraction of shared URLs are science-related. We find an assortative mixing with respect to disciplines in the networks between scientists, suggesting the maintenance of disciplinary walls in social media. Our work contributes to the literature both methodologically and conceptually—we provide new methods for disambiguating and identifying particular actors on social media and describing the behaviors of scientists, thus providing foundational information for the construction and use of indicators on the basis of social media metrics. PMID:28399145

User's manual for the generalized computer program system. Open-channel flow and sedimentation, TABS-2. Main text

NASA Astrophysics Data System (ADS)

Thomas, W. A.; McAnally, W. H., Jr.

1985-07-01

TABS-2 is a generalized numerical modeling system for open-channel flows, sedimentation, and constituent transport. It consists of more than 40 computer programs to perform modeling and related tasks. The major modeling components--RMA-2V, STUDH, and RMA-4--calculate two-dimensional, depth-averaged flows, sedimentation, and dispersive transport, respectively. The other programs in the system perform digitizing, mesh generation, data management, graphical display, output analysis, and model interfacing tasks. Utilities include file management and automatic generation of computer job control instructions. TABS-2 has been applied to a variety of waterways, including rivers, estuaries, bays, and marshes. It is designed for use by engineers and scientists who may not have a rigorous computer background. Use of the various components is described in Appendices A-O. The bound version of the report does not include the appendices. A looseleaf form with Appendices A-O is distributed to system users.

Participatory Design of Human-Centered Cyberinfrastructure (Invited)

NASA Astrophysics Data System (ADS)

Pennington, D. D.; Gates, A. Q.

2010-12-01

Cyberinfrastructure, by definition, is about people sharing resources to achieve outcomes that cannot be reached independently. CI depends not just on creating discoverable resources, or tools that allow those resources to be processed, integrated, and visualized -- but on human activation of flows of information across those resources. CI must be centered on human activities. Yet for those CI projects that are directed towards observational science, there are few models for organizing collaborative research in ways that align individual research interests into a collective vision of CI-enabled science. Given that the emerging technologies are themselves expected to change the way science is conducted, it is not simply a matter of conducting requirements analysis on how scientists currently work, or building consensus among the scientists on what is needed. Developing effective CI depends on generating a new, creative vision of problem solving within a community based on computational concepts that are, in some cases, still very abstract and theoretical. The computer science theory may (or may not) be well formalized, but the potential for impact on any particular domain is typically ill-defined. In this presentation we will describe approaches being developed and tested at the CyberShARE Center of Excellence at University of Texas in El Paso for ill-structured problem solving within cross-disciplinary teams of scientists and computer scientists working on data intensive environmental and geoscience. These approaches deal with the challenges associated with sharing and integrating knowledge across disciplines; the challenges of developing effective teamwork skills in a culture that favors independent effort; and the challenges of evolving shared, focused research goals from ill-structured, vague starting points - all issues that must be confronted by every interdisciplinary CI project. We will introduce visual and semantic-based tools that can enable the collaborative research design process and illustrate their application in designing and developing useful end-to-end data solutions for scientists. Lastly, we will outline areas of future investigation within CyberShARE that we believe have the potential for high impact.

Interactive visualization of Earth and Space Science computations

NASA Technical Reports Server (NTRS)

Hibbard, William L.; Paul, Brian E.; Santek, David A.; Dyer, Charles R.; Battaiola, Andre L.; Voidrot-Martinez, Marie-Francoise

1994-01-01

Computers have become essential tools for scientists simulating and observing nature. Simulations are formulated as mathematical models but are implemented as computer algorithms to simulate complex events. Observations are also analyzed and understood in terms of mathematical models, but the number of these observations usually dictates that we automate analyses with computer algorithms. In spite of their essential role, computers are also barriers to scientific understanding. Unlike hand calculations, automated computations are invisible and, because of the enormous numbers of individual operations in automated computations, the relation between an algorithm's input and output is often not intuitive. This problem is illustrated by the behavior of meteorologists responsible for forecasting weather. Even in this age of computers, many meteorologists manually plot weather observations on maps, then draw isolines of temperature, pressure, and other fields by hand (special pads of maps are printed for just this purpose). Similarly, radiologists use computers to collect medical data but are notoriously reluctant to apply image-processing algorithms to that data. To these scientists with life-and-death responsibilities, computer algorithms are black boxes that increase rather than reduce risk. The barrier between scientists and their computations can be bridged by techniques that make the internal workings of algorithms visible and that allow scientists to experiment with their computations. Here we describe two interactive systems developed at the University of Wisconsin-Madison Space Science and Engineering Center (SSEC) that provide these capabilities to Earth and space scientists.

An Agro-Climatological Early Warning Tool Based on the Google Earth Engine to Support Regional Food Security Analysis

NASA Astrophysics Data System (ADS)

Landsfeld, M. F.; Daudert, B.; Friedrichs, M.; Morton, C.; Hegewisch, K.; Husak, G. J.; Funk, C. C.; Peterson, P.; Huntington, J. L.; Abatzoglou, J. T.; Verdin, J. P.; Williams, E. L.

2015-12-01

The Famine Early Warning Systems Network (FEWS NET) focuses on food insecurity in developing nations and provides objective, evidence based analysis to help government decision-makers and relief agencies plan for and respond to humanitarian emergencies. The Google Earth Engine (GEE) is a platform provided by Google Inc. to support scientific research and analysis of environmental data in their cloud environment. The intent is to allow scientists and independent researchers to mine massive collections of environmental data and leverage Google's vast computational resources to detect changes and monitor the Earth's surface and climate. GEE hosts an enormous amount of satellite imagery and climate archives, one of which is the Climate Hazards Group Infrared Precipitation with Stations dataset (CHIRPS). The CHIRPS dataset is land based, quasi-global (latitude 50N-50S), 0.05 degree resolution, and has a relatively long term period of record (1981-present). CHIRPS is on a continuous monthly feed into the GEE as new data fields are generated each month. This precipitation dataset is a key input for FEWS NET monitoring and forecasting efforts. FEWS NET intends to leverage the GEE in order to provide analysts and scientists with flexible, interactive tools to aid in their monitoring and research efforts. These scientists often work in bandwidth limited regions, so lightweight Internet tools and services that bypass the need for downloading massive datasets to analyze them, are preferred for their work. The GEE provides just this type of service. We present a tool designed specifically for FEWS NET scientists to be utilized interactively for investigating and monitoring for agro-climatological issues. We are able to utilize the enormous GEE computing power to generate on-the-fly statistics to calculate precipitation anomalies, z-scores, percentiles and band ratios, and allow the user to interactively select custom areas for statistical time series comparisons and predictions.

X-ray crystallography

NASA Technical Reports Server (NTRS)

2001-01-01

X-rays diffracted from a well-ordered protein crystal create sharp patterns of scattered light on film. A computer can use these patterns to generate a model of a protein molecule. To analyze the selected crystal, an X-ray crystallographer shines X-rays through the crystal. Unlike a single dental X-ray, which produces a shadow image of a tooth, these X-rays have to be taken many times from different angles to produce a pattern from the scattered light, a map of the intensity of the X-rays after they diffract through the crystal. The X-rays bounce off the electron clouds that form the outer structure of each atom. A flawed crystal will yield a blurry pattern; a well-ordered protein crystal yields a series of sharp diffraction patterns. From these patterns, researchers build an electron density map. With powerful computers and a lot of calculations, scientists can use the electron density patterns to determine the structure of the protein and make a computer-generated model of the structure. The models let researchers improve their understanding of how the protein functions. They also allow scientists to look for receptor sites and active areas that control a protein's function and role in the progress of diseases. From there, pharmaceutical researchers can design molecules that fit the active site, much like a key and lock, so that the protein is locked without affecting the rest of the body. This is called structure-based drug design.

Telescience Support Center Data System Software

NASA Technical Reports Server (NTRS)

Rahman, Hasan

2010-01-01

The Telescience Support Center (TSC) team has developed a databasedriven, increment-specific Data Require - ment Document (DRD) generation tool that automates much of the work required for generating and formatting the DRD. It creates a database to load the required changes to configure the TSC data system, thus eliminating a substantial amount of labor in database entry and formatting. The TSC database contains the TSC systems configuration, along with the experimental data, in which human physiological data must be de-commutated in real time. The data for each experiment also must be cataloged and archived for future retrieval. TSC software provides tools and resources for ground operation and data distribution to remote users consisting of PIs (principal investigators), bio-medical engineers, scientists, engineers, payload specialists, and computer scientists. Operations support is provided for computer systems access, detailed networking, and mathematical and computational problems of the International Space Station telemetry data. User training is provided for on-site staff and biomedical researchers and other remote personnel in the usage of the space-bound services via the Internet, which enables significant resource savings for the physical facility along with the time savings versus traveling to NASA sites. The software used in support of the TSC could easily be adapted to other Control Center applications. This would include not only other NASA payload monitoring facilities, but also other types of control activities, such as monitoring and control of the electric grid, chemical, or nuclear plant processes, air traffic control, and the like.

Short-Pulse Laser-Matter Computational Workshop Proceedings

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

Town, R; Tabak, M

For three days at the end of August 2004, 55 plasma scientists met at the Four Points by Sheraton in Pleasanton to discuss some of the critical issues associated with the computational aspects of the interaction of short-pulse high-intensity lasers with matter. The workshop was organized around the following six key areas: (1) Laser propagation/interaction through various density plasmas: micro scale; (2) Anomalous electron transport effects: From micro to meso scale; (3) Electron transport through plasmas: From meso to macro scale; (4) Ion beam generation, transport, and focusing; (5) ''Atomic-scale'' electron and proton stopping powers; and (6) K{alpha} diagnostics.

Applications of Deep Learning and Reinforcement Learning to Biological Data.

PubMed

Mahmud, Mufti; Kaiser, Mohammed Shamim; Hussain, Amir; Vassanelli, Stefano

2018-06-01

Rapid advances in hardware-based technologies during the past decades have opened up new possibilities for life scientists to gather multimodal data in various application domains, such as omics, bioimaging, medical imaging, and (brain/body)-machine interfaces. These have generated novel opportunities for development of dedicated data-intensive machine learning techniques. In particular, recent research in deep learning (DL), reinforcement learning (RL), and their combination (deep RL) promise to revolutionize the future of artificial intelligence. The growth in computational power accompanied by faster and increased data storage, and declining computing costs have already allowed scientists in various fields to apply these techniques on data sets that were previously intractable owing to their size and complexity. This paper provides a comprehensive survey on the application of DL, RL, and deep RL techniques in mining biological data. In addition, we compare the performances of DL techniques when applied to different data sets across various application domains. Finally, we outline open issues in this challenging research area and discuss future development perspectives.

Adapting bioinformatics curricula for big data.

PubMed

Greene, Anna C; Giffin, Kristine A; Greene, Casey S; Moore, Jason H

2016-01-01

Modern technologies are capable of generating enormous amounts of data that measure complex biological systems. Computational biologists and bioinformatics scientists are increasingly being asked to use these data to reveal key systems-level properties. We review the extent to which curricula are changing in the era of big data. We identify key competencies that scientists dealing with big data are expected to possess across fields, and we use this information to propose courses to meet these growing needs. While bioinformatics programs have traditionally trained students in data-intensive science, we identify areas of particular biological, computational and statistical emphasis important for this era that can be incorporated into existing curricula. For each area, we propose a course structured around these topics, which can be adapted in whole or in parts into existing curricula. In summary, specific challenges associated with big data provide an important opportunity to update existing curricula, but we do not foresee a wholesale redesign of bioinformatics training programs. © The Author 2015. Published by Oxford University Press.

Adapting bioinformatics curricula for big data

PubMed Central

Greene, Anna C.; Giffin, Kristine A.; Greene, Casey S.

2016-01-01

Modern technologies are capable of generating enormous amounts of data that measure complex biological systems. Computational biologists and bioinformatics scientists are increasingly being asked to use these data to reveal key systems-level properties. We review the extent to which curricula are changing in the era of big data. We identify key competencies that scientists dealing with big data are expected to possess across fields, and we use this information to propose courses to meet these growing needs. While bioinformatics programs have traditionally trained students in data-intensive science, we identify areas of particular biological, computational and statistical emphasis important for this era that can be incorporated into existing curricula. For each area, we propose a course structured around these topics, which can be adapted in whole or in parts into existing curricula. In summary, specific challenges associated with big data provide an important opportunity to update existing curricula, but we do not foresee a wholesale redesign of bioinformatics training programs. PMID:25829469

Software Innovations Speed Scientific Computing

NASA Technical Reports Server (NTRS)

2012-01-01

To help reduce the time needed to analyze data from missions like those studying the Sun, Goddard Space Flight Center awarded SBIR funding to Tech-X Corporation of Boulder, Colorado. That work led to commercial technologies that help scientists accelerate their data analysis tasks. Thanks to its NASA work, the company doubled its number of headquarters employees to 70 and generated about $190,000 in revenue from its NASA-derived products.

A novel paradigm for cell and molecule interaction ontology: from the CMM model to IMGT-ONTOLOGY

PubMed Central

2010-01-01

Background Biology is moving fast toward the virtuous circle of other disciplines: from data to quantitative modeling and back to data. Models are usually developed by mathematicians, physicists, and computer scientists to translate qualitative or semi-quantitative biological knowledge into a quantitative approach. To eliminate semantic confusion between biology and other disciplines, it is necessary to have a list of the most important and frequently used concepts coherently defined. Results We propose a novel paradigm for generating new concepts for an ontology, starting from model rather than developing a database. We apply that approach to generate concepts for cell and molecule interaction starting from an agent based model. This effort provides a solid infrastructure that is useful to overcome the semantic ambiguities that arise between biologists and mathematicians, physicists, and computer scientists, when they interact in a multidisciplinary field. Conclusions This effort represents the first attempt at linking molecule ontology with cell ontology, in IMGT-ONTOLOGY, the well established ontology in immunogenetics and immunoinformatics, and a paradigm for life science biology. With the increasing use of models in biology and medicine, the need to link different levels, from molecules to cells to tissues and organs, is increasingly important. PMID:20167082

Integrating High-Throughput Parallel Processing Framework and Storage Area Network Concepts Into a Prototype Interactive Scientific Visualization Environment for Hyperspectral Data

NASA Astrophysics Data System (ADS)

Smuga-Otto, M. J.; Garcia, R. K.; Knuteson, R. O.; Martin, G. D.; Flynn, B. M.; Hackel, D.

2006-12-01

The University of Wisconsin-Madison Space Science and Engineering Center (UW-SSEC) is developing tools to help scientists realize the potential of high spectral resolution instruments for atmospheric science. Upcoming satellite spectrometers like the Cross-track Infrared Sounder (CrIS), experimental instruments like the Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) and proposed instruments like the Hyperspectral Environmental Suite (HES) within the GOES-R project will present a challenge in the form of the overwhelmingly large amounts of continuously generated data. Current and near-future workstations will have neither the storage space nor computational capacity to cope with raw spectral data spanning more than a few minutes of observations from these instruments. Schemes exist for processing raw data from hyperspectral instruments currently in testing, that involve distributed computation across clusters. Data, which for an instrument like GIFTS can amount to over 1.5 Terabytes per day, is carefully managed on Storage Area Networks (SANs), with attention paid to proper maintenance of associated metadata. The UW-SSEC is preparing a demonstration integrating these back-end capabilities as part of a larger visualization framework, to assist scientists in developing new products from high spectral data, sourcing data volumes they could not otherwise manage. This demonstration focuses on managing storage so that only the data specifically needed for the desired product are pulled from the SAN, and on running computationally expensive intermediate processing on a back-end cluster, with the final product being sent to a visualization system on the scientist's workstation. Where possible, existing software and solutions are used to reduce cost of development. The heart of the computing component is the GIFTS Information Processing System (GIPS), developed at the UW- SSEC to allow distribution of processing tasks such as conversion of raw GIFTS interferograms into calibrated radiance spectra, and retrieving temperature and water vapor content atmospheric profiles from these spectra. The hope is that by demonstrating the capabilities afforded by a composite system like the one described here, scientists can be convinced to contribute further algorithms in support of this model of computing and visualization.

Climate@Home: Crowdsourcing Climate Change Research

NASA Astrophysics Data System (ADS)

Xu, C.; Yang, C.; Li, J.; Sun, M.; Bambacus, M.

2011-12-01

Climate change deeply impacts human wellbeing. Significant amounts of resources have been invested in building super-computers that are capable of running advanced climate models, which help scientists understand climate change mechanisms, and predict its trend. Although climate change influences all human beings, the general public is largely excluded from the research. On the other hand, scientists are eagerly seeking communication mediums for effectively enlightening the public on climate change and its consequences. The Climate@Home project is devoted to connect the two ends with an innovative solution: crowdsourcing climate computing to the general public by harvesting volunteered computing resources from the participants. A distributed web-based computing platform will be built to support climate computing, and the general public can 'plug-in' their personal computers to participate in the research. People contribute the spare computing power of their computers to run a computer model, which is used by scientists to predict climate change. Traditionally, only super-computers could handle such a large computing processing load. By orchestrating massive amounts of personal computers to perform atomized data processing tasks, investments on new super-computers, energy consumed by super-computers, and carbon release from super-computers are reduced. Meanwhile, the platform forms a social network of climate researchers and the general public, which may be leveraged to raise climate awareness among the participants. A portal is to be built as the gateway to the climate@home project. Three types of roles and the corresponding functionalities are designed and supported. The end users include the citizen participants, climate scientists, and project managers. Citizen participants connect their computing resources to the platform by downloading and installing a computing engine on their personal computers. Computer climate models are defined at the server side. Climate scientists configure computer model parameters through the portal user interface. After model configuration, scientists then launch the computing task. Next, data is atomized and distributed to computing engines that are running on citizen participants' computers. Scientists will receive notifications on the completion of computing tasks, and examine modeling results via visualization modules of the portal. Computing tasks, computing resources, and participants are managed by project managers via portal tools. A portal prototype has been built for proof of concept. Three forums have been setup for different groups of users to share information on science aspect, technology aspect, and educational outreach aspect. A facebook account has been setup to distribute messages via the most popular social networking platform. New treads are synchronized from the forums to facebook. A mapping tool displays geographic locations of the participants and the status of tasks on each client node. A group of users have been invited to test functions such as forums, blogs, and computing resource monitoring.

Basic instincts

NASA Astrophysics Data System (ADS)

Hutson, Matthew

2018-05-01

In their adaptability, young children demonstrate common sense, a kind of intelligence that, so far, computer scientists have struggled to reproduce. Gary Marcus, a developmental cognitive scientist at New York University in New York City, believes the field of artificial intelligence (AI) would do well to learn lessons from young thinkers. Researchers in machine learning argue that computers trained on mountains of data can learn just about anything—including common sense—with few, if any, programmed rules. But Marcus says computer scientists are ignoring decades of work in the cognitive sciences and developmental psychology showing that humans have innate abilities—programmed instincts that appear at birth or in early childhood—that help us think abstractly and flexibly. He believes AI researchers ought to include such instincts in their programs. Yet many computer scientists, riding high on the successes of machine learning, are eagerly exploring the limits of what a naïve AI can do. Computer scientists appreciate simplicity and have an aversion to debugging complex code. Furthermore, big companies such as Facebook and Google are pushing AI in this direction. These companies are most interested in narrowly defined, near-term problems, such as web search and facial recognition, in which blank-slate AI systems can be trained on vast data sets and work remarkably well. But in the longer term, computer scientists expect AIs to take on much tougher tasks that require flexibility and common sense. They want to create chatbots that explain the news, autonomous taxis that can handle chaotic city traffic, and robots that nurse the elderly. Some computer scientists are already trying. Such efforts, researchers hope, will result in AIs that sit somewhere between pure machine learning and pure instinct. They will boot up following some embedded rules, but will also learn as they go.

Computer graphics and the graphic artist

NASA Technical Reports Server (NTRS)

Taylor, N. L.; Fedors, E. G.; Pinelli, T. E.

1985-01-01

A centralized computer graphics system is being developed at the NASA Langley Research Center. This system was required to satisfy multiuser needs, ranging from presentation quality graphics prepared by a graphic artist to 16-mm movie simulations generated by engineers and scientists. While the major thrust of the central graphics system was directed toward engineering and scientific applications, hardware and software capabilities to support the graphic artists were integrated into the design. This paper briefly discusses the importance of computer graphics in research; the central graphics system in terms of systems, software, and hardware requirements; the application of computer graphics to graphic arts, discussed in terms of the requirements for a graphic arts workstation; and the problems encountered in applying computer graphics to the graphic arts. The paper concludes by presenting the status of the central graphics system.

Facilities | Computational Science | NREL

Science.gov Websites

technology innovation by providing scientists and engineers the ability to tackle energy challenges that scientists and engineers to take full advantage of advanced computing hardware and software resources

AIRSLUG: A fortran program for the computation of type curves to estimate transmissivity and storativity from prematurely terminated air-pressurized slug tests

USGS Publications Warehouse

Greene, E.A.; Shapiro, A.M.

1998-01-01

The Fortran code AIRSLUG can be used to generate the type curves needed to analyze the recovery data from prematurely terminated air-pressurized slug tests. These type curves, when used with a graphical software package, enable the engineer or scientist to analyze field tests to estimate transmissivity and storativity. Prematurely terminating the slug test can significantly reduce the overall time needed to conduct the test, especially at low-permeability sites, thus saving time and money.The Fortran code AIRSLUG can be used to generate the type curves needed to analyze the recovery data from prematurely terminated air-pressurized slug tests. These type curves, when used with a graphical software package, enable the engineer or scientist to analyze field tests to estimate transmissivity and storativity. Prematurely terminating the slug test can significantly reduce the overall time needed to conduct the test, especially at low-permeability sites, thus saving time and money.

Computer models and the evidence of anthropogenic climate change: An epistemology of variety-of-evidence inferences and robustness analysis.

PubMed

Vezér, Martin A

2016-04-01

To study climate change, scientists employ computer models, which approximate target systems with various levels of skill. Given the imperfection of climate models, how do scientists use simulations to generate knowledge about the causes of observed climate change? Addressing a similar question in the context of biological modelling, Levins (1966) proposed an account grounded in robustness analysis. Recent philosophical discussions dispute the confirmatory power of robustness, raising the question of how the results of computer modelling studies contribute to the body of evidence supporting hypotheses about climate change. Expanding on Staley's (2004) distinction between evidential strength and security, and Lloyd's (2015) argument connecting variety-of-evidence inferences and robustness analysis, I address this question with respect to recent challenges to the epistemology robustness analysis. Applying this epistemology to case studies of climate change, I argue that, despite imperfections in climate models, and epistemic constraints on variety-of-evidence reasoning and robustness analysis, this framework accounts for the strength and security of evidence supporting climatological inferences, including the finding that global warming is occurring and its primary causes are anthropogenic. Copyright © 2016 Elsevier Ltd. All rights reserved.

Do the Brain Networks of Scientists Account for Their Superiority in Hypothesis-Generating?

ERIC Educational Resources Information Center

Lee, Jun-Ki

2012-01-01

Where do scientists' superior abilities originate from when generating a creative idea? What different brain functions are activated between scientists and i) general academic high school students and ii) science high school students when generating a biological hypothesis? To reveal brain level explanations for these questions, this paper…

An Analysis of Computer-Mediated Communication between Middle School Students and Scientist Role Models: A Pilot Study.

ERIC Educational Resources Information Center

Murfin, Brian

1994-01-01

Reports on a study of the effectiveness of computer-mediated communication (CMC) in providing African American and female middle school students with scientist role models. Quantitative and qualitative data gathered by analyzing messages students and scientists posted on a shared electronic bulletin board showed that CMC could be an effective…

Cloud computing approaches to accelerate drug discovery value chain.

PubMed

Garg, Vibhav; Arora, Suchir; Gupta, Chitra

2011-12-01

Continued advancements in the area of technology have helped high throughput screening (HTS) evolve from a linear to parallel approach by performing system level screening. Advanced experimental methods used for HTS at various steps of drug discovery (i.e. target identification, target validation, lead identification and lead validation) can generate data of the order of terabytes. As a consequence, there is pressing need to store, manage, mine and analyze this data to identify informational tags. This need is again posing challenges to computer scientists to offer the matching hardware and software infrastructure, while managing the varying degree of desired computational power. Therefore, the potential of "On-Demand Hardware" and "Software as a Service (SAAS)" delivery mechanisms cannot be denied. This on-demand computing, largely referred to as Cloud Computing, is now transforming the drug discovery research. Also, integration of Cloud computing with parallel computing is certainly expanding its footprint in the life sciences community. The speed, efficiency and cost effectiveness have made cloud computing a 'good to have tool' for researchers, providing them significant flexibility, allowing them to focus on the 'what' of science and not the 'how'. Once reached to its maturity, Discovery-Cloud would fit best to manage drug discovery and clinical development data, generated using advanced HTS techniques, hence supporting the vision of personalized medicine.

NASA's Pleiades Supercomputer Crunches Data For Groundbreaking Analysis and Visualizations

NASA Image and Video Library

2016-11-23

The Pleiades supercomputer at NASA's Ames Research Center, recently named the 13th fastest computer in the world, provides scientists and researchers high-fidelity numerical modeling of complex systems and processes. By using detailed analyses and visualizations of large-scale data, Pleiades is helping to advance human knowledge and technology, from designing the next generation of aircraft and spacecraft to understanding the Earth's climate and the mysteries of our galaxy.

SPAGHETTILENS: A software stack for modeling gravitational lenses by citizen scientists

NASA Astrophysics Data System (ADS)

Küng, R.

2018-04-01

The 2020s are expected to see tens of thousands of lens discoveries. Mass reconstruction or modeling of these lenses will be needed, but current modeling methods are time intensive for specialists and expert human resources do not scale. SpaghettiLens approaches this challenge with the help of experienced citizen scientist volunteers who have already been involved in finding lenses. A top level description is as follows. Citizen scientists look at data and provide a graphical input based on Fermat's principle which we call a Spaghetti Diagram. This input works as a model configuration. It is followed by the generation of the model, which is a compute intensive task done server side though a task distribution system. Model results are returned in graphical form to the citizen scientist, who examines and then either forwards them for forum discussion or rejects the model and retries. As well as configuring models, citizen scientists can also modify existing model configurations, which results in a version tree of models and makes the modeling process collaborative. SpaghettiLens is designed to be scalable and could be adopted to problems with similar characteristics. It is licensed under the MIT license, released at http://labs.spacewarps.org and the source code is available at https://github.com/RafiKueng/SpaghettiLens.

Reinforced Adversarial Neural Computer for de Novo Molecular Design.

PubMed

Putin, Evgeny; Asadulaev, Arip; Ivanenkov, Yan; Aladinskiy, Vladimir; Sanchez-Lengeling, Benjamin; Aspuru-Guzik, Alán; Zhavoronkov, Alex

2018-06-12

In silico modeling is a crucial milestone in modern drug design and development. Although computer-aided approaches in this field are well-studied, the application of deep learning methods in this research area is at the beginning. In this work, we present an original deep neural network (DNN) architecture named RANC (Reinforced Adversarial Neural Computer) for the de novo design of novel small-molecule organic structures based on the generative adversarial network (GAN) paradigm and reinforcement learning (RL). As a generator RANC uses a differentiable neural computer (DNC), a category of neural networks, with increased generation capabilities due to the addition of an explicit memory bank, which can mitigate common problems found in adversarial settings. The comparative results have shown that RANC trained on the SMILES string representation of the molecules outperforms its first DNN-based counterpart ORGANIC by several metrics relevant to drug discovery: the number of unique structures, passing medicinal chemistry filters (MCFs), Muegge criteria, and high QED scores. RANC is able to generate structures that match the distributions of the key chemical features/descriptors (e.g., MW, logP, TPSA) and lengths of the SMILES strings in the training data set. Therefore, RANC can be reasonably regarded as a promising starting point to develop novel molecules with activity against different biological targets or pathways. In addition, this approach allows scientists to save time and covers a broad chemical space populated with novel and diverse compounds.

Multiuser Collaboration with Networked Mobile Devices

NASA Technical Reports Server (NTRS)

Tso, Kam S.; Tai, Ann T.; Deng, Yong M.; Becks, Paul G.

2006-01-01

In this paper we describe a multiuser collaboration infrastructure that enables multiple mission scientists to remotely and collaboratively interact with visualization and planning software, using wireless networked personal digital assistants(PDAs) and other mobile devices. During ground operations of planetary rover and lander missions, scientists need to meet daily to review downlinked data and plan science activities. For example, scientists use the Science Activity Planner (SAP) in the Mars Exploration Rover (MER) mission to visualize downlinked data and plan rover activities during the science meetings [1]. Computer displays are projected onto large screens in the meeting room to enable the scientists to view and discuss downlinked images and data displayed by SAP and other software applications. However, only one person can interact with the software applications because input to the computer is limited to a single mouse and keyboard. As a result, the scientists have to verbally express their intentions, such as selecting a target at a particular location on the Mars terrain image, to that person in order to interact with the applications. This constrains communication and limits the returns of science planning. Furthermore, ground operations for Mars missions are fundamentally constrained by the short turnaround time for science and engineering teams to process and analyze data, plan the next uplink, generate command sequences, and transmit the uplink to the vehicle [2]. Therefore, improving ground operations is crucial to the success of Mars missions. The multiuser collaboration infrastructure enables users to control software applications remotely and collaboratively using mobile devices. The infrastructure includes (1) human-computer interaction techniques to provide natural, fast, and accurate inputs, (2) a communications protocol to ensure reliable and efficient coordination of the input devices and host computers, (3) an application-independent middleware that maintains the states, sessions, and interactions of individual users of the software applications, (4) an application programming interface to enable tight integration of applications and the middleware. The infrastructure is able to support any software applications running under the Windows or Unix platforms. The resulting technologies not only are applicable to NASA mission operations, but also useful in other situations such as design reviews, brainstorming sessions, and business meetings, as they can benefit from having the participants concurrently interact with the software applications (e.g., presentation applications and CAD design tools) to illustrate their ideas and provide inputs.

From Both Sides, Now: Librarians Team up with Computer Scientist to Deliver Virtual Computer-Information Literacy Instruction

ERIC Educational Resources Information Center

Loesch, Martha Fallahay

2011-01-01

Two members of the library faculty at Seton Hall University teamed up with a respected professor of mathematics and computer science, in order to create an online course that introduces information literacy both from the perspectives of the computer scientist and from the instruction librarian. This collaboration is unique in that it addresses the…

Diamond Thin-Film Thermionic Generator

NASA Astrophysics Data System (ADS)

Clewell, J. M.; Ordonez, C. A.; Perez, J. M.

1997-03-01

Since the eighteen-hundreds scientists have sought to develop the highest thermal efficiency in heat engines such as thermionic generators. Modern research in the emerging diamond film industry has indicated the work functions of diamond thin-films can be much less than one electron volt, compelling fresh investigation into their capacity as thermionic generators and inviting new methodology for determining that efficiency. Our objective is to predict the efficiency of a low-work-function, degenerate semiconductor (diamond film) thermionic generator operated as a heat engine between two constant-temperature thermal reservoirs. Our presentation will focus on a theoretical model which predicts the efficiency of the system by employing a Monte Carlo computational technique from which we report results for the thermal efficiency and the thermionic current densities of diamond thin-films.

Enabling drug discovery project decisions with integrated computational chemistry and informatics

NASA Astrophysics Data System (ADS)

Tsui, Vickie; Ortwine, Daniel F.; Blaney, Jeffrey M.

2017-03-01

Computational chemistry/informatics scientists and software engineers in Genentech Small Molecule Drug Discovery collaborate with experimental scientists in a therapeutic project-centric environment. Our mission is to enable and improve pre-clinical drug discovery design and decisions. Our goal is to deliver timely data, analysis, and modeling to our therapeutic project teams using best-in-class software tools. We describe our strategy, the organization of our group, and our approaches to reach this goal. We conclude with a summary of the interdisciplinary skills required for computational scientists and recommendations for their training.

"Women in Astronomy: an Essay Review"

NASA Astrophysics Data System (ADS)

Cox, M.

2006-12-01

Interest in the history of women in astronomy has increased dramatically in the last 30 years. This interest has come from the growing number of professional scientists, historians and feminists researching the lives and work of earlier generations, as well as from amateur astronomers. It is reflected in the vast amount of literature on the subject, both in books and journals, and on the internet. This Essay Review will focus on monographs published in the last 10 years (1996-2006), and will be restricted mainly to pre-20th century women. The scope includes researchers, translators, computers and astronomical assistants as well as observers. Where appropriate, it includes books that discuss the role of women scientists, as well as pure astronomy books. Part 2, to be published later, will consider encyclopaedias and large works of reference .

Advanced Scientific Computing Research Exascale Requirements Review. An Office of Science review sponsored by Advanced Scientific Computing Research, September 27-29, 2016, Rockville, Maryland

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

Almgren, Ann; DeMar, Phil; Vetter, Jeffrey

The widespread use of computing in the American economy would not be possible without a thoughtful, exploratory research and development (R&D) community pushing the performance edge of operating systems, computer languages, and software libraries. These are the tools and building blocks — the hammers, chisels, bricks, and mortar — of the smartphone, the cloud, and the computing services on which we rely. Engineers and scientists need ever-more specialized computing tools to discover new material properties for manufacturing, make energy generation safer and more efficient, and provide insight into the fundamentals of the universe, for example. The research division of themore » U.S. Department of Energy’s (DOE’s) Office of Advanced Scientific Computing and Research (ASCR Research) ensures that these tools and building blocks are being developed and honed to meet the extreme needs of modern science. See also http://exascaleage.org/ascr/ for additional information.« less

Preface: SciDAC 2005

NASA Astrophysics Data System (ADS)

Mezzacappa, Anthony

2005-01-01

On 26-30 June 2005 at the Grand Hyatt on Union Square in San Francisco several hundred computational scientists from around the world came together for what can certainly be described as a celebration of computational science. Scientists from the SciDAC Program and scientists from other agencies and nations were joined by applied mathematicians and computer scientists to highlight the many successes in the past year where computation has led to scientific discovery in a variety of fields: lattice quantum chromodynamics, accelerator modeling, chemistry, biology, materials science, Earth and climate science, astrophysics, and combustion and fusion energy science. Also highlighted were the advances in numerical methods and computer science, and the multidisciplinary collaboration cutting across science, mathematics, and computer science that enabled these discoveries. The SciDAC Program was conceived and funded by the US Department of Energy Office of Science. It is the Office of Science's premier computational science program founded on what is arguably the perfect formula: the priority and focus is science and scientific discovery, with the understanding that the full arsenal of `enabling technologies' in applied mathematics and computer science must be brought to bear if we are to have any hope of attacking and ultimately solving today's computational Grand Challenge problems. The SciDAC Program has been in existence for four years, and many of the computational scientists funded by this program will tell you that the program has given them the hope of addressing their scientific problems in full realism for the very first time. Many of these scientists will also tell you that SciDAC has also fundamentally changed the way they do computational science. We begin this volume with one of DOE's great traditions, and core missions: energy research. As we will see, computation has been seminal to the critical advances that have been made in this arena. Of course, to understand our world, whether it is to understand its very nature or to understand it so as to control it for practical application, will require explorations on all of its scales. Computational science has been no less an important tool in this arena than it has been in the arena of energy research. From explorations of quantum chromodynamics, the fundamental theory that describes how quarks make up the protons and neutrons of which we are composed, to explorations of the complex biomolecules that are the building blocks of life, to explorations of some of the most violent phenomena in our universe and of the Universe itself, computation has provided not only significant insight, but often the only means by which we have been able to explore these complex, multicomponent systems and by which we have been able to achieve scientific discovery and understanding. While our ultimate target remains scientific discovery, it certainly can be said that at a fundamental level the world is mathematical. Equations ultimately govern the evolution of the systems of interest to us, be they physical, chemical, or biological systems. The development and choice of discretizations of these underlying equations is often a critical deciding factor in whether or not one is able to model such systems stably, faithfully, and practically, and in turn, the algorithms to solve the resultant discrete equations are the complementary, critical ingredient in the recipe to model the natural world. The use of parallel computing platforms, especially at the TeraScale, and the trend toward even larger numbers of processors, continue to present significant challenges in the development and implementation of these algorithms. Computational scientists often speak of their `workflows'. A workflow, as the name suggests, is the sum total of all complex and interlocking tasks, from simulation set up, execution, and I/O, to visualization and scientific discovery, through which the advancement in our understanding of the natural world is realized. For the computational scientist, enabling such workflows presents myriad, signiflcant challenges, and it is computer scientists that are called upon at such times to address these challenges. Simulations are currently generating data at the staggering rate of tens of TeraBytes per simulation, over the course of days. In the next few years, these data generation rates are expected to climb exponentially to hundreds of TeraBytes per simulation, performed over the course of months. The output, management, movement, analysis, and visualization of these data will be our key to unlocking the scientific discoveries buried within the data. And there is no hope of generating such data to begin with, or of scientific discovery, without stable computing platforms and a sufficiently high and sustained performance of scientific applications codes on them. Thus, scientific discovery in the realm of computational science at the TeraScale and beyond will occur at the intersection of science, applied mathematics, and computer science. The SciDAC Program was constructed to mirror this reality, and the pages that follow are a testament to the efficacy of such an approach. We would like to acknowledge the individuals on whose talents and efforts the success of SciDAC 2005 was based. Special thanks go to Betsy Riley for her work on the SciDAC 2005 Web site and meeting agenda, for lining up our corporate sponsors, for coordinating all media communications, and for her efforts in processing the proceedings contributions, to Sherry Hempfling for coordinating the overall SciDAC 2005 meeting planning, for handling a significant share of its associated communications, and for coordinating with the ORNL Conference Center and Grand Hyatt, to Angela Harris for producing many of the documents and records on which our meeting planning was based and for her efforts in coordinating with ORNL Graphics Services, to Angie Beach of the ORNL Conference Center for her efforts in procurement and setting up and executing the contracts with the hotel, and to John Bui and John Smith for their superb wireless networking and A/V set up and support. We are grateful for the relentless efforts of all of these individuals, their remarkable talents, and for the joy of working with them during this past year. They were the cornerstones of SciDAC 2005. Thanks also go to Kymba A'Hearn and Patty Boyd for on-site registration, Brittany Hagen for administrative support, Bruce Johnston for netcast support, Tim Jones for help with the proceedings and Web site, Sherry Lamb for housing and registration, Cindy Lathum for Web site design, Carolyn Peters for on-site registration, and Dami Rich for graphic design. And we would like to express our appreciation to the Oak Ridge National Laboratory, especially Jeff Nichols, the Argonne National Laboratory, the Lawrence Berkeley National Laboratory, and to our corporate sponsors, Cray, IBM, Intel, and SGI, for their support. We would like to extend special thanks also to our plenary speakers, technical speakers, poster presenters, and panelists for all of their efforts on behalf of SciDAC 2005 and for their remarkable achievements and contributions. We would like to express our deep appreciation to Lali Chatterjee, Graham Douglas and Margaret Smith of Institute of Physics Publishing, who worked tirelessly in order to provide us with this finished volume within two months, which is nothing short of miraculous. Finally, we wish to express our heartfelt thanks to Michael Strayer, SciDAC Director, whose vision it was to focus SciDAC 2005 on scientific discovery, around which all of the excitement we experienced revolved, and to our DOE SciDAC program managers, especially Fred Johnson, for their support, input, and help throughout.

Center for computation and visualization of geometric structures. Final report, 1992 - 1995

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

NONE

1995-11-01

This report describes the overall goals and the accomplishments of the Geometry Center of the University of Minnesota, whose mission is to develop, support, and promote computational tools for visualizing geometric structures, for facilitating communication among mathematical and computer scientists and between these scientists and the public at large, and for stimulating research in geometry.

Educating the Next Generation of Agricultural Scientists.

ERIC Educational Resources Information Center

National Academy of Sciences - National Research Council, Washington, DC. Board on Agriculture.

The Committee on Evaluation of Trends in Agricultural Research at the Doctoral and Postdoctoral Level was established to analyze issues related to the next generation of agricultural scientists. This report contains the findings, conclusions, and recommendations regarding the status and future needs of agricultural scientists. This report focuses…

What do computer scientists tweet? Analyzing the link-sharing practice on Twitter.

PubMed

Schmitt, Marco; Jäschke, Robert

2017-01-01

Twitter communication has permeated every sphere of society. To highlight and share small pieces of information with possibly vast audiences or small circles of the interested has some value in almost any aspect of social life. But what is the value exactly for a scientific field? We perform a comprehensive study of computer scientists using Twitter and their tweeting behavior concerning the sharing of web links. Discerning the domains, hosts and individual web pages being tweeted and the differences between computer scientists and a Twitter sample enables us to look in depth at the Twitter-based information sharing practices of a scientific community. Additionally, we aim at providing a deeper understanding of the role and impact of altmetrics in computer science and give a glance at the publications mentioned on Twitter that are most relevant for the computer science community. Our results show a link sharing culture that concentrates more heavily on public and professional quality information than the Twitter sample does. The results also show a broad variety in linked sources and especially in linked publications with some publications clearly related to community-specific interests of computer scientists, while others with a strong relation to attention mechanisms in social media. This refers to the observation that Twitter is a hybrid form of social media between an information service and a social network service. Overall the computer scientists' style of usage seems to be more on the information-oriented side and to some degree also on professional usage. Therefore, altmetrics are of considerable use in analyzing computer science.

New Frontiers in Analyzing Dynamic Group Interactions: Bridging Social and Computer Science

PubMed Central

Lehmann-Willenbrock, Nale; Hung, Hayley; Keyton, Joann

2017-01-01

This special issue on advancing interdisciplinary collaboration between computer scientists and social scientists documents the joint results of the international Lorentz workshop, “Interdisciplinary Insights into Group and Team Dynamics,” which took place in Leiden, The Netherlands, July 2016. An equal number of scholars from social and computer science participated in the workshop and contributed to the papers included in this special issue. In this introduction, we first identify interaction dynamics as the core of group and team models and review how scholars in social and computer science have typically approached behavioral interactions in groups and teams. Next, we identify key challenges for interdisciplinary collaboration between social and computer scientists, and we provide an overview of the different articles in this special issue aimed at addressing these challenges. PMID:29249891

Human computers: the first pioneers of the information age.

PubMed

Grier, D A

2001-03-01

Before computers were machines, they were people. They were men and women, young and old, well educated and common. They were the workers who convinced scientists that large-scale calculation had value. Long before Presper Eckert and John Mauchly built the ENIAC at the Moore School of Electronics, Philadelphia, or Maurice Wilkes designed the EDSAC for Manchester University, human computers had created the discipline of computation. They developed numerical methodologies and proved them on practical problems. These human computers were not savants or calculating geniuses. Some knew little more than basic arithmetic. A few were near equals of the scientists they served and, in a different time or place, might have become practicing scientists had they not been barred from a scientific career by their class, education, gender or ethnicity.

New Frontiers in Analyzing Dynamic Group Interactions: Bridging Social and Computer Science.

PubMed

Lehmann-Willenbrock, Nale; Hung, Hayley; Keyton, Joann

2017-10-01

This special issue on advancing interdisciplinary collaboration between computer scientists and social scientists documents the joint results of the international Lorentz workshop, "Interdisciplinary Insights into Group and Team Dynamics," which took place in Leiden, The Netherlands, July 2016. An equal number of scholars from social and computer science participated in the workshop and contributed to the papers included in this special issue. In this introduction, we first identify interaction dynamics as the core of group and team models and review how scholars in social and computer science have typically approached behavioral interactions in groups and teams. Next, we identify key challenges for interdisciplinary collaboration between social and computer scientists, and we provide an overview of the different articles in this special issue aimed at addressing these challenges.

Building place-based collaborations to develop high school students' groundwater systems knowledge and decision-making capacity

NASA Astrophysics Data System (ADS)

Podrasky, A.; Covitt, B. A.; Woessner, W.

2017-12-01

The availability of clean water to support human uses and ecological integrity has become an urgent interest for many scientists, decision makers and citizens. Likewise, as computational capabilities increasingly revolutionize and become integral to the practice of science, technology, engineering and math (STEM) disciplines, the STEM+ Computing (STEM+C) Partnerships program seeks to integrate the use of computational approaches in K-12 STEM teaching and learning. The Comp Hydro project, funded by a STEM+C grant from the National Science Foundation, brings together a diverse team of scientists, educators, professionals and citizens at sites in Arizona, Colorado, Maryland and Montana to foster water literacy, as well as computational science literacy, by integrating authentic, place- and data- based learning using physical, mathematical, computational and conceptual models. This multi-state project is currently engaging four teams of six teachers who work during two academic years with educators and scientists at each site. Teams work to develop instructional units specific to their region that integrate hydrologic science and computational modeling. The units, currently being piloted in high school earth and environmental science classes, provide a classroom context to investigate student understanding of how computation is used in Earth systems science. To develop effective science instruction that is rich in place- and data- based learning, effective collaborations between researchers, educators, scientists, professionals and citizens are crucial. In this poster, we focus on project implementation in Montana, where an instructional unit has been developed and is being tested through collaboration among University scientists, researchers and educators, high school teachers and agency and industry scientists and engineers. In particular, we discuss three characteristics of effective collaborative science education design for developing and implementing place- and data- based science education to support students in developing socio-scientific and computational literacy sufficient for making decisions about real world issues such as groundwater contamination. These characteristics include that science education experiences are real, responsive/accessible and rigorous.

Deep Unsupervised Learning on a Desktop PC: A Primer for Cognitive Scientists.

PubMed

Testolin, Alberto; Stoianov, Ivilin; De Filippo De Grazia, Michele; Zorzi, Marco

2013-01-01

Deep belief networks hold great promise for the simulation of human cognition because they show how structured and abstract representations may emerge from probabilistic unsupervised learning. These networks build a hierarchy of progressively more complex distributed representations of the sensory data by fitting a hierarchical generative model. However, learning in deep networks typically requires big datasets and it can involve millions of connection weights, which implies that simulations on standard computers are unfeasible. Developing realistic, medium-to-large-scale learning models of cognition would therefore seem to require expertise in programing parallel-computing hardware, and this might explain why the use of this promising approach is still largely confined to the machine learning community. Here we show how simulations of deep unsupervised learning can be easily performed on a desktop PC by exploiting the processors of low cost graphic cards (graphic processor units) without any specific programing effort, thanks to the use of high-level programming routines (available in MATLAB or Python). We also show that even an entry-level graphic card can outperform a small high-performance computing cluster in terms of learning time and with no loss of learning quality. We therefore conclude that graphic card implementations pave the way for a widespread use of deep learning among cognitive scientists for modeling cognition and behavior.

Deep Unsupervised Learning on a Desktop PC: A Primer for Cognitive Scientists

PubMed Central

Testolin, Alberto; Stoianov, Ivilin; De Filippo De Grazia, Michele; Zorzi, Marco

2013-01-01

Deep belief networks hold great promise for the simulation of human cognition because they show how structured and abstract representations may emerge from probabilistic unsupervised learning. These networks build a hierarchy of progressively more complex distributed representations of the sensory data by fitting a hierarchical generative model. However, learning in deep networks typically requires big datasets and it can involve millions of connection weights, which implies that simulations on standard computers are unfeasible. Developing realistic, medium-to-large-scale learning models of cognition would therefore seem to require expertise in programing parallel-computing hardware, and this might explain why the use of this promising approach is still largely confined to the machine learning community. Here we show how simulations of deep unsupervised learning can be easily performed on a desktop PC by exploiting the processors of low cost graphic cards (graphic processor units) without any specific programing effort, thanks to the use of high-level programming routines (available in MATLAB or Python). We also show that even an entry-level graphic card can outperform a small high-performance computing cluster in terms of learning time and with no loss of learning quality. We therefore conclude that graphic card implementations pave the way for a widespread use of deep learning among cognitive scientists for modeling cognition and behavior. PMID:23653617

A case study of tuning MapReduce for efficient Bioinformatics in the cloud

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

Shi, Lizhen; Wang, Zhong; Yu, Weikuan

The combination of the Hadoop MapReduce programming model and cloud computing allows biological scientists to analyze next-generation sequencing (NGS) data in a timely and cost-effective manner. Cloud computing platforms remove the burden of IT facility procurement and management from end users and provide ease of access to Hadoop clusters. However, biological scientists are still expected to choose appropriate Hadoop parameters for running their jobs. More importantly, the available Hadoop tuning guidelines are either obsolete or too general to capture the particular characteristics of bioinformatics applications. In this paper, we aim to minimize the cloud computing cost spent on bioinformatics datamore » analysis by optimizing the extracted significant Hadoop parameters. When using MapReduce-based bioinformatics tools in the cloud, the default settings often lead to resource underutilization and wasteful expenses. We choose k-mer counting, a representative application used in a large number of NGS data analysis tools, as our study case. Experimental results show that, with the fine-tuned parameters, we achieve a total of 4× speedup compared with the original performance (using the default settings). Finally, this paper presents an exemplary case for tuning MapReduce-based bioinformatics applications in the cloud, and documents the key parameters that could lead to significant performance benefits.« less

Scientific Computing Paradigm

NASA Technical Reports Server (NTRS)

VanZandt, John

1994-01-01

The usage model of supercomputers for scientific applications, such as computational fluid dynamics (CFD), has changed over the years. Scientific visualization has moved scientists away from looking at numbers to looking at three-dimensional images, which capture the meaning of the data. This change has impacted the system models for computing. This report details the model which is used by scientists at NASA's research centers.

Message from the ISCB: 2015 ISCB Accomplishment by a Senior Scientist Award: Cyrus Chothia.

PubMed

Fogg, Christiana N; Kovats, Diane E

2015-07-01

The International Society for Computational Biology (ISCB; http://www.iscb.org) honors a senior scientist annually for his or her outstanding achievements with the ISCB Accomplishment by a Senior Scientist Award. This award recognizes a leader in the field of computational biology for his or her significant contributions to the community through research, service and education. Cyrus Chothia, an emeritus scientist at the Medical Research Council Laboratory of Molecular Biology and emeritus fellow of Wolfson College at Cambridge University, England, is the 2015 ISCB Accomplishment by a Senior Scientist Award winner.Chothia was selected by the Awards Committee, which is chaired by Dr Bonnie Berger of the Massachusetts Institute of Technology. He will receive his award and deliver a keynote presentation at 2015 Intelligent Systems for Molecular Biology/European Conference on Computational Biology in Dublin, Ireland, in July 2015. dkovats@iscb.org. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

CSBB: synthetic biology research at Newcastle University.

PubMed

Goñi-Moreno, Angel; Wipat, Anil; Krasnogor, Natalio

2017-06-15

The Centre for Synthetic Biology and the Bioeconomy (CSBB) brings together a far-reaching multidisciplinary community across all Newcastle University's faculties - Medical Sciences, Science, Agriculture and Engineering, and Humanities, Arts and Social Sciences. The CSBB focuses on many different areas of Synthetic Biology, including bioprocessing, computational design and in vivo computation, as well as improving understanding of basic molecular machinery. Such breadth is supported by major national and international research funding, a range of industrial partners in the North East of England and beyond, as well as a large number of doctoral and post-doctoral researchers. The CSBB trains the next generation of scientists through a 1-year MSc in Synthetic Biology. © 2017 The Author(s).

Template Interfaces for Agile Parallel Data-Intensive Science

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

Ramakrishnan, Lavanya; Gunter, Daniel; Pastorello, Gilerto Z.

Tigres provides a programming library to compose and execute large-scale data-intensive scientific workflows from desktops to supercomputers. DOE User Facilities and large science collaborations are increasingly generating large enough data sets that it is no longer practical to download them to a desktop to operate on them. They are instead stored at centralized compute and storage resources such as high performance computing (HPC) centers. Analysis of this data requires an ability to run on these facilities, but with current technologies, scaling an analysis to an HPC center and to a large data set is difficult even for experts. Tigres ismore » addressing the challenge of enabling collaborative analysis of DOE Science data through a new concept of reusable "templates" that enable scientists to easily compose, run and manage collaborative computational tasks. These templates define common computation patterns used in analyzing a data set.« less

CREASE 6.0 Catalog of Resources for Education in Ada and Software Engineering

DTIC Science & Technology

1992-02-01

Programming Software Engineering Strong Typing Tasking Audene . Computer Scientists Terbook(s): Barnes, J. Programming in Ada, 3rd ed. Addison-Wesley...Ada. Concept: Abstract Data Types Management Overview Package Real-Time Programming Tasking Audene Computer Scientists Textbook(s): Barnes, J

Parallel computing in genomic research: advances and applications

PubMed Central

Ocaña, Kary; de Oliveira, Daniel

2015-01-01

Today’s genomic experiments have to process the so-called “biological big data” that is now reaching the size of Terabytes and Petabytes. To process this huge amount of data, scientists may require weeks or months if they use their own workstations. Parallelism techniques and high-performance computing (HPC) environments can be applied for reducing the total processing time and to ease the management, treatment, and analyses of this data. However, running bioinformatics experiments in HPC environments such as clouds, grids, clusters, and graphics processing unit requires the expertise from scientists to integrate computational, biological, and mathematical techniques and technologies. Several solutions have already been proposed to allow scientists for processing their genomic experiments using HPC capabilities and parallelism techniques. This article brings a systematic review of literature that surveys the most recently published research involving genomics and parallel computing. Our objective is to gather the main characteristics, benefits, and challenges that can be considered by scientists when running their genomic experiments to benefit from parallelism techniques and HPC capabilities. PMID:26604801

Parallel computing in genomic research: advances and applications.

PubMed

Ocaña, Kary; de Oliveira, Daniel

2015-01-01

Today's genomic experiments have to process the so-called "biological big data" that is now reaching the size of Terabytes and Petabytes. To process this huge amount of data, scientists may require weeks or months if they use their own workstations. Parallelism techniques and high-performance computing (HPC) environments can be applied for reducing the total processing time and to ease the management, treatment, and analyses of this data. However, running bioinformatics experiments in HPC environments such as clouds, grids, clusters, and graphics processing unit requires the expertise from scientists to integrate computational, biological, and mathematical techniques and technologies. Several solutions have already been proposed to allow scientists for processing their genomic experiments using HPC capabilities and parallelism techniques. This article brings a systematic review of literature that surveys the most recently published research involving genomics and parallel computing. Our objective is to gather the main characteristics, benefits, and challenges that can be considered by scientists when running their genomic experiments to benefit from parallelism techniques and HPC capabilities.

Just-in-time Time Data Analytics and Visualization of Climate Simulations using the Bellerophon Framework

NASA Astrophysics Data System (ADS)

Anantharaj, V. G.; Venzke, J.; Lingerfelt, E.; Messer, B.

2015-12-01

Climate model simulations are used to understand the evolution and variability of earth's climate. Unfortunately, high-resolution multi-decadal climate simulations can take days to weeks to complete. Typically, the simulation results are not analyzed until the model runs have ended. During the course of the simulation, the output may be processed periodically to ensure that the model is preforming as expected. However, most of the data analytics and visualization are not performed until the simulation is finished. The lengthy time period needed for the completion of the simulation constrains the productivity of climate scientists. Our implementation of near real-time data visualization analytics capabilities allows scientists to monitor the progress of their simulations while the model is running. Our analytics software executes concurrently in a co-scheduling mode, monitoring data production. When new data are generated by the simulation, a co-scheduled data analytics job is submitted to render visualization artifacts of the latest results. These visualization output are automatically transferred to Bellerophon's data server located at ORNL's Compute and Data Environment for Science (CADES) where they are processed and archived into Bellerophon's database. During the course of the experiment, climate scientists can then use Bellerophon's graphical user interface to view animated plots and their associated metadata. The quick turnaround from the start of the simulation until the data are analyzed permits research decisions and projections to be made days or sometimes even weeks sooner than otherwise possible! The supercomputer resources used to run the simulation are unaffected by co-scheduling the data visualization jobs, so the model runs continuously while the data are visualized. Our just-in-time data visualization software looks to increase climate scientists' productivity as climate modeling moves into exascale era of computing.

BAID: The Barrow Area Information Database - an interactive web mapping portal and cyberinfrastructure for scientific activities in the vicinity of Barrow, Alaska

NASA Astrophysics Data System (ADS)

Cody, R. P.; Kassin, A.; Gaylord, A.; Brown, J.; Tweedie, C. E.

2012-12-01

The Barrow area of northern Alaska is one of the most intensely researched locations in the Arctic. The Barrow Area Information Database (BAID, www.baidims.org) is a cyberinfrastructure (CI) that details much of the historic and extant research undertaken within in the Barrow region in a suite of interactive web-based mapping and information portals (geobrowsers). The BAID user community and target audience for BAID is diverse and includes research scientists, science logisticians, land managers, educators, students, and the general public. BAID contains information on more than 9,600 Barrow area research sites that extend back to the 1940's and more than 640 remote sensing images and geospatial datasets. In a web-based setting, users can zoom, pan, query, measure distance, and save or print maps and query results. Data are described with metadata that meet Federal Geographic Data Committee standards and are archived at the University Corporation for Atmospheric Research Earth Observing Laboratory (EOL) where non-proprietary BAID data can be freely downloaded. BAID has been used to: Optimize research site choice; Reduce duplication of science effort; Discover complementary and potentially detrimental research activities in an area of scientific interest; Re-establish historical research sites for resampling efforts assessing change in ecosystem structure and function over time; Exchange knowledge across disciplines and generations; Facilitate communication between western science and traditional ecological knowledge; Provide local residents access to science data that facilitates adaptation to arctic change; (and) Educate the next generation of environmental and computer scientists. This poster describes key activities that will be undertaken over the next three years to provide BAID users with novel software tools to interact with a current and diverse selection of information and data about the Barrow area. Key activities include: 1. Collecting data on research activities, generating geospatial data, and providing mapping support. 2. Maintaining, updating and innovating the existing suite of BAID geobrowsers. 3. Maintaining and updating aging server hardware supporting BAID. 4. Adding interoperability with other CI using workflows, controlled vocabularies and web services. 5. Linking BAID to data archives at the National Snow and Ice Data Center (NSIDC). 6. Developing a wireless sensor network that provides web based interaction with near-real time climate and other data. 7. Training next generation of environmental and computer scientists and conducting outreach.

THE TRAINING OF NEXT GENERATION DATA SCIENTISTS IN BIOMEDICINE.

PubMed

Garmire, Lana X; Gliske, Stephen; Nguyen, Quynh C; Chen, Jonathan H; Nemati, Shamim; VAN Horn, John D; Moore, Jason H; Shreffler, Carol; Dunn, Michelle

2017-01-01

With the booming of new technologies, biomedical science has transformed into digitalized, data intensive science. Massive amount of data need to be analyzed and interpreted, demand a complete pipeline to train next generation data scientists. To meet this need, the transinstitutional Big Data to Knowledge (BD2K) Initiative has been implemented since 2014, complementing other NIH institutional efforts. In this report, we give an overview the BD2K K01 mentored scientist career awards, which have demonstrated early success. We address the specific trainings needed in representative data science areas, in order to make the next generation of data scientists in biomedicine.

An economic and financial exploratory

NASA Astrophysics Data System (ADS)

Cincotti, S.; Sornette, D.; Treleaven, P.; Battiston, S.; Caldarelli, G.; Hommes, C.; Kirman, A.

2012-11-01

This paper describes the vision of a European Exploratory for economics and finance using an interdisciplinary consortium of economists, natural scientists, computer scientists and engineers, who will combine their expertise to address the enormous challenges of the 21st century. This Academic Public facility is intended for economic modelling, investigating all aspects of risk and stability, improving financial technology, and evaluating proposed regulatory and taxation changes. The European Exploratory for economics and finance will be constituted as a network of infrastructure, observatories, data repositories, services and facilities and will foster the creation of a new cross-disciplinary research community of social scientists, complexity scientists and computing (ICT) scientists to collaborate in investigating major issues in economics and finance. It is also considered a cradle for training and collaboration with the private sector to spur spin-offs and job creations in Europe in the finance and economic sectors. The Exploratory will allow Social Scientists and Regulators as well as Policy Makers and the private sector to conduct realistic investigations with real economic, financial and social data. The Exploratory will (i) continuously monitor and evaluate the status of the economies of countries in their various components, (ii) use, extend and develop a large variety of methods including data mining, process mining, computational and artificial intelligence and every other computer and complex science techniques coupled with economic theory and econometric, and (iii) provide the framework and infrastructure to perform what-if analysis, scenario evaluations and computational, laboratory, field and web experiments to inform decision makers and help develop innovative policy, market and regulation designs.

From Years of Work in Psychology and Computer Science, Scientists Build Theories of Thinking and Learning.

ERIC Educational Resources Information Center

Wheeler, David L.

1988-01-01

Scientists feel that progress in artificial intelligence and the availability of thousands of experimental results make this the right time to build and test theories on how people think and learn, using the computer to model minds. (MSE)

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

McCaskey, Alexander J.

Hybrid programming models for beyond-CMOS technologies will prove critical for integrating new computing technologies alongside our existing infrastructure. Unfortunately the software infrastructure required to enable this is lacking or not available. XACC is a programming framework for extreme-scale, post-exascale accelerator architectures that integrates alongside existing conventional applications. It is a pluggable framework for programming languages developed for next-gen computing hardware architectures like quantum and neuromorphic computing. It lets computational scientists efficiently off-load classically intractable work to attached accelerators through user-friendly Kernel definitions. XACC makes post-exascale hybrid programming approachable for domain computational scientists.

20th International Conference for Students and Young Scientists: Modern Techniques and Technologies (MTT'2014)

NASA Astrophysics Data System (ADS)

2014-10-01

The active involvement of young researchers in scientific processes and the acquisition of scientific experience by gifted youth currently have a great value for the development of science. One of the research activities of National Research Tomsk Polytechnic University, aimed at the preparing and formation of the next generation of scientists, is the International Conference of Students and Young Scientists ''Modern Techniques and Technologies'', which was held in 2014 for the twentieth time. Great experience in the organization of scientific events has been acquired through years of carrying the conference. There are all the necessary resources for this: a team of organizers - employees of Tomsk Polytechnic University, premises provided with modern office equipment and equipment for demonstration, and leading scientists - professors of TPU, as well as the status of the university as a leading research university in Russia. This way the conference is able to attract world leading scientists for the collaboration. For the previous years the conference proved itself as a major scientific event at international level, which attracts more than 600 students and young scientists from Russia, CIS and other countries. The conference provides oral plenary and section reports. The conference is organized around lectures, where leading Russian and foreign scientists deliver plenary presentations to young audiences. An important indicator of this scientific event is the magnitude of the coverage of scientific fields: energy, heat and power, instrument making, engineering, systems and devices for medical purposes, electromechanics, material science, computer science and control in technical systems, nanotechnologies and nanomaterials, physical methods in science and technology, control and quality management, design and technology of artistic materials processing. The main issues considered by young researchers at the conference were related to the analysis of contemporary problems using new techniques and application of new technologies.

Executable research compendia in geoscience research infrastructures

NASA Astrophysics Data System (ADS)

Nüst, Daniel

2017-04-01

From generation through analysis and collaboration to communication, scientific research requires the right tools. Scientists create their own software using third party libraries and platforms. Cloud computing, Open Science, public data infrastructures, and Open Source enable scientists with unprecedented opportunites, nowadays often in a field "Computational X" (e.g. computational seismology) or X-informatics (e.g. geoinformatics) [0]. This increases complexity and generates more innovation, e.g. Environmental Research Infrastructures (environmental RIs [1]). Researchers in Computational X write their software relying on both source code (e.g. from https://github.com) and binary libraries (e.g. from package managers such as APT, https://wiki.debian.org/Apt, or CRAN, https://cran.r-project.org/). They download data from domain specific (cf. https://re3data.org) or generic (e.g. https://zenodo.org) data repositories, and deploy computations remotely (e.g. European Open Science Cloud). The results themselves are archived, given persistent identifiers, connected to other works (e.g. using https://orcid.org/), and listed in metadata catalogues. A single researcher, intentionally or not, interacts with all sub-systems of RIs: data acquisition, data access, data processing, data curation, and community support [3]. To preserve computational research [3] proposes the Executable Research Compendium (ERC), a container format closing the gap of dependency preservation by encapsulating the runtime environment. ERCs and RIs can be integrated for different uses: (i) Coherence: ERC services validate completeness, integrity and results (ii) Metadata: ERCs connect the different parts of a piece of research and faciliate discovery (iii) Exchange and Preservation: ERC as usable building blocks are the shared and archived entity (iv) Self-consistency: ERCs remove dependence on ephemeral sources (v) Execution: ERC services create and execute a packaged analysis but integrate with existing platforms for display and control These integrations are vital for capturing workflows in RIs and connect key stakeholders (scientists, publishers, librarians). They are demonstrated using developments by the DFG-funded project Opening Reproducible Research (http://o2r.info). Semi-automatic creation of ERCs based on research workflows is a core goal of the project. References [0] Tony Hey, Stewart Tansley, Kristin Tolle (eds), 2009. The Fourth Paradigm: Data-Intensive Scientific Discovery. Microsoft Research. [1] P. Martin et al., Open Information Linking for Environmental Research Infrastructures, 2015 IEEE 11th International Conference on e-Science, Munich, 2015, pp. 513-520. doi: 10.1109/eScience.2015.66 [2] Y. Chen et al., Analysis of Common Requirements for Environmental Science Research Infrastructures, The International Symposium on Grids and Clouds (ISGC) 2013, Taipei, 2013, http://pos.sissa.it/archive/conferences/179/032/ISGC [3] Opening Reproducible Research, Geophysical Research Abstracts Vol. 18, EGU2016-7396, 2016, http://meetingorganizer.copernicus.org/EGU2016/EGU2016-7396.pdf

"Ask Argonne" - Charlie Catlett, Computer Scientist, Part 2

ScienceCinema

Catlett, Charlie

2018-02-14

A few weeks back, computer scientist Charlie Catlett talked a bit about the work he does and invited questions from the public during Part 1 of his "Ask Argonne" video set (http://bit.ly/1joBtzk). In Part 2, he answers some of the questions that were submitted. Enjoy!

"Ask Argonne" - Charlie Catlett, Computer Scientist, Part 2

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

Catlett, Charlie

2014-06-17

A few weeks back, computer scientist Charlie Catlett talked a bit about the work he does and invited questions from the public during Part 1 of his "Ask Argonne" video set (http://bit.ly/1joBtzk). In Part 2, he answers some of the questions that were submitted. Enjoy!

The International Symposium on Grids and Clouds

NASA Astrophysics Data System (ADS)

The International Symposium on Grids and Clouds (ISGC) 2012 will be held at Academia Sinica in Taipei from 26 February to 2 March 2012, with co-located events and workshops. The conference is hosted by the Academia Sinica Grid Computing Centre (ASGC). 2012 is the decennium anniversary of the ISGC which over the last decade has tracked the convergence, collaboration and innovation of individual researchers across the Asia Pacific region to a coherent community. With the continuous support and dedication from the delegates, ISGC has provided the primary international distributed computing platform where distinguished researchers and collaboration partners from around the world share their knowledge and experiences. The last decade has seen the wide-scale emergence of e-Infrastructure as a critical asset for the modern e-Scientist. The emergence of large-scale research infrastructures and instruments that has produced a torrent of electronic data is forcing a generational change in the scientific process and the mechanisms used to analyse the resulting data deluge. No longer can the processing of these vast amounts of data and production of relevant scientific results be undertaken by a single scientist. Virtual Research Communities that span organisations around the world, through an integrated digital infrastructure that connects the trust and administrative domains of multiple resource providers, have become critical in supporting these analyses. Topics covered in ISGC 2012 include: High Energy Physics, Biomedicine & Life Sciences, Earth Science, Environmental Changes and Natural Disaster Mitigation, Humanities & Social Sciences, Operations & Management, Middleware & Interoperability, Security and Networking, Infrastructure Clouds & Virtualisation, Business Models & Sustainability, Data Management, Distributed Volunteer & Desktop Grid Computing, High Throughput Computing, and High Performance, Manycore & GPU Computing.

On-the-Job Evidence-Based Medicine Training for Clinician-Scientists of the Next Generation

PubMed Central

Leung, Elaine YL; Malick, Sadia M; Khan, Khalid S

2013-01-01

Clinical scientists are at the unique interface between laboratory science and frontline clinical practice for supporting clinical partnerships for evidence-based practice. In an era of molecular diagnostics and personalised medicine, evidence-based laboratory practice (EBLP) is also crucial in aiding clinical scientists to keep up-to-date with this expanding knowledge base. However, there are recognised barriers to the implementation of EBLP and its training. The aim of this review is to provide a practical summary of potential strategies for training clinician-scientists of the next generation. Current evidence suggests that clinically integrated evidence-based medicine (EBM) training is effective. Tailored e-learning EBM packages and evidence-based journal clubs have been shown to improve knowledge and skills of EBM. Moreover, e-learning is no longer restricted to computer-assisted learning packages. For example, social media platforms such as Twitter have been used to complement existing journal clubs and provide additional post-publication appraisal information for journals. In addition, the delivery of an EBLP curriculum has influence on its success. Although e-learning of EBM skills is effective, having EBM trained teachers available locally promotes the implementation of EBM training. Training courses, such as Training the Trainers, are now available to help trainers identify and make use of EBM training opportunities in clinical practice. On the other hand, peer-assisted learning and trainee-led support networks can strengthen self-directed learning of EBM and research participation among clinical scientists in training. Finally, we emphasise the need to evaluate any EBLP training programme using validated assessment tools to help identify the most crucial ingredients of effective EBLP training. In summary, we recommend on-the-job training of EBM with additional focus on overcoming barriers to its implementation. In addition, future studies evaluating the effectiveness of EBM training should use validated outcome tools, endeavour to achieve adequate power and consider the effects of EBM training on learning environment and patient outcomes. PMID:24151345

On-the-Job Evidence-Based Medicine Training for Clinician-Scientists of the Next Generation.

PubMed

Leung, Elaine Yl; Malick, Sadia M; Khan, Khalid S

2013-08-01

Clinical scientists are at the unique interface between laboratory science and frontline clinical practice for supporting clinical partnerships for evidence-based practice. In an era of molecular diagnostics and personalised medicine, evidence-based laboratory practice (EBLP) is also crucial in aiding clinical scientists to keep up-to-date with this expanding knowledge base. However, there are recognised barriers to the implementation of EBLP and its training. The aim of this review is to provide a practical summary of potential strategies for training clinician-scientists of the next generation. Current evidence suggests that clinically integrated evidence-based medicine (EBM) training is effective. Tailored e-learning EBM packages and evidence-based journal clubs have been shown to improve knowledge and skills of EBM. Moreover, e-learning is no longer restricted to computer-assisted learning packages. For example, social media platforms such as Twitter have been used to complement existing journal clubs and provide additional post-publication appraisal information for journals. In addition, the delivery of an EBLP curriculum has influence on its success. Although e-learning of EBM skills is effective, having EBM trained teachers available locally promotes the implementation of EBM training. Training courses, such as Training the Trainers, are now available to help trainers identify and make use of EBM training opportunities in clinical practice. On the other hand, peer-assisted learning and trainee-led support networks can strengthen self-directed learning of EBM and research participation among clinical scientists in training. Finally, we emphasise the need to evaluate any EBLP training programme using validated assessment tools to help identify the most crucial ingredients of effective EBLP training. In summary, we recommend on-the-job training of EBM with additional focus on overcoming barriers to its implementation. In addition, future studies evaluating the effectiveness of EBM training should use validated outcome tools, endeavour to achieve adequate power and consider the effects of EBM training on learning environment and patient outcomes.

Opening Remarks: SciDAC 2007

NASA Astrophysics Data System (ADS)

Strayer, Michael

2007-09-01

Good morning. Welcome to Boston, the home of the Red Sox, Celtics and Bruins, baked beans, tea parties, Robert Parker, and SciDAC 2007. A year ago I stood before you to share the legacy of the first SciDAC program and identify the challenges that we must address on the road to petascale computing—a road E E Cummins described as `. . . never traveled, gladly beyond any experience.' Today, I want to explore the preparations for the rapidly approaching extreme scale (X-scale) generation. These preparations are the first step propelling us along the road of burgeoning scientific discovery enabled by the application of X- scale computing. We look to petascale computing and beyond to open up a world of discovery that cuts across scientific fields and leads us to a greater understanding of not only our world, but our universe. As part of the President's America Competitiveness Initiative, the ASCR Office has been preparing a ten year vision for computing. As part of this planning the LBNL together with ORNL and ANL hosted three town hall meetings on Simulation and Modeling at the Exascale for Energy, Ecological Sustainability and Global Security (E3). The proposed E3 initiative is organized around four programmatic themes: Engaging our top scientists, engineers, computer scientists and applied mathematicians; investing in pioneering large-scale science; developing scalable analysis algorithms, and storage architectures to accelerate discovery; and accelerating the build-out and future development of the DOE open computing facilities. It is clear that we have only just started down the path to extreme scale computing. Plan to attend Thursday's session on the out-briefing and discussion of these meetings. The road to the petascale has been at best rocky. In FY07, the continuing resolution provided 12% less money for Advanced Scientific Computing than either the President, the Senate, or the House. As a consequence, many of you had to absorb a no cost extension for your SciDAC work. I am pleased that the President's FY08 budget restores the funding for SciDAC. Quoting from Advanced Scientific Computing Research description in the House Energy and Water Development Appropriations Bill for FY08, "Perhaps no other area of research at the Department is so critical to sustaining U.S. leadership in science and technology, revolutionizing the way science is done and improving research productivity." As a society we need to revolutionize our approaches to energy, environmental and global security challenges. As we go forward along the road to the X-scale generation, the use of computation will continue to be a critical tool along with theory and experiment in understanding the behavior of the fundamental components of nature as well as for fundamental discovery and exploration of the behavior of complex systems. The foundation to overcome these societal challenges will build from the experiences and knowledge gained as you, members of our SciDAC research teams, work together to attack problems at the tera- and peta- scale. If SciDAC is viewed as an experiment for revolutionizing scientific methodology, then a strategic goal of ASCR program must be to broaden the intellectual base prepared to address the challenges of the new X-scale generation of computing. We must focus our computational science experiences gained over the past five years on the opportunities introduced with extreme scale computing. Our facilities are on a path to provide the resources needed to undertake the first part of our journey. Using the newly upgraded 119 teraflop Cray XT system at the Leadership Computing Facility, SciDAC research teams have in three days performed a 100-year study of the time evolution of the atmospheric CO2 concentration originating from the land surface. The simulation of the El Nino/Southern Oscillation which was part of this study has been characterized as `the most impressive new result in ten years' gained new insight into the behavior of superheated ionic gas in the ITER reactor as a result of an AORSA run on 22,500 processors that achieved over 87 trillion calculations per second (87 teraflops) which is 74% of the system's theoretical peak. Tomorrow, Argonne and IBM will announce that the first IBM Blue Gene/P, a 100 teraflop system, will be shipped to the Argonne Leadership Computing Facility later this fiscal year. By the end of FY2007 ASCR high performance and leadership computing resources will include the 114 teraflop IBM Blue Gene/P; a 102 teraflop Cray XT4 at NERSC and a 119 teraflop Cray XT system at Oak Ridge. Before ringing in the New Year, Oak Ridge will upgrade to 250 teraflops with the replacement of the dual core processors with quad core processors and Argonne will upgrade to between 250-500 teraflops, and next year, a petascale Cray Baker system is scheduled for delivery at Oak Ridge. The multidisciplinary teams in our SciDAC Centers for Enabling Technologies and our SciDAC Institutes must continue to work with our Scientific Application teams to overcome the barriers that prevent effective use of these new systems. These challenges include: the need for new algorithms as well as operating system and runtime software and tools which scale to parallel systems composed of hundreds of thousands processors; program development environments and tools which scale effectively and provide ease of use for developers and scientific end users; and visualization and data management systems that support moving, storing, analyzing, manipulating and visualizing multi-petabytes of scientific data and objects. The SciDAC Centers, located primarily at our DOE national laboratories will take the lead in ensuring that critical computer science and applied mathematics issues are addressed in a timely and comprehensive fashion and to address issues associated with research software lifecycle. In contrast, the SciDAC Institutes, which are university-led centers of excellence, will have more flexibility to pursue new research topics through a range of research collaborations. The Institutes will also work to broaden the intellectual and researcher base—conducting short courses and summer schools to take advantage of new high performance computing capabilities. The SciDAC Outreach Center at Lawrence Berkeley National Laboratory complements the outreach efforts of the SciDAC Institutes. The Outreach Center is our clearinghouse for SciDAC activities and resources and will communicate with the high performance computing community in part to understand their needs for workshops, summer schools and institutes. SciDAC is not ASCR's only effort to broaden the computational science community needed to meet the challenges of the new X-scale generation. I hope that you were able to attend the Computational Science Graduate Fellowship poster session last night. ASCR developed the fellowship in 1991 to meet the nation's growing need for scientists and technology professionals with advanced computer skills. CSGF, now jointly funded between ASCR and NNSA, is more than a traditional academic fellowship. It has provided more than 200 of the best and brightest graduate students with guidance, support and community in preparing them as computational scientists. Today CSGF alumni are bringing their diverse top-level skills and knowledge to research teams at DOE laboratories and in industries such as Proctor and Gamble, Lockheed Martin and Intel. At universities they are working to train the next generation of computational scientists. To build on this success, we intend to develop a wholly new Early Career Principal Investigator's (ECPI) program. Our objective is to stimulate academic research in scientific areas within ASCR's purview especially among faculty in early stages of their academic careers. Last February, we lost Ken Kennedy, one of the leading lights of our community. As we move forward into the extreme computing generation, his vision and insight will be greatly missed. In memorial to Ken Kennedy, we shall designate the ECPI grants to beginning faculty in Computer Science as the Ken Kennedy Fellowship. Watch the ASCR website for more information about ECPI and other early career programs in the computational sciences. We look to you, our scientists, researchers, and visionaries to take X-scale computing and use it to explode scientific discovery in your fields. We at SciDAC will work to ensure that this tool is the sharpest and most precise and efficient instrument to carve away the unknown and reveal the most exciting secrets and stimulating scientific discoveries of our time. The partnership between research and computing is the marriage that will spur greater discovery, and as Spencer said to Susan in Robert Parker's novel, `Sudden Mischief', `We stick together long enough, and we may get as smart as hell'. Michael Strayer

Big Data, Big Solutions

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

Pike, Bill

Data—lots of data—generated in seconds and piling up on the internet, streaming and stored in countless databases. Big data is important for commerce, society and our nation’s security. Yet the volume, velocity, variety and veracity of data is simply too great for any single analyst to make sense of alone. It requires advanced, data-intensive computing. Simply put, data-intensive computing is the use of sophisticated computers to sort through mounds of information and present analysts with solutions in the form of graphics, scenarios, formulas, new hypotheses and more. This scientific capability is foundational to PNNL’s energy, environment and security missions. Seniormore » Scientist and Division Director Bill Pike and his team are developing analytic tools that are used to solve important national challenges, including cyber systems defense, power grid control systems, intelligence analysis, climate change and scientific exploration.« less

Computational Astrophysics Consortium, University of Minnesota, Final Report

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

Heger, Alexander

During its six year duration the Computational Astrophysics consortium helped to train the next generation of scientists in computational and nuclear astrophysics. A total of five graduate students were supported by the grant at UMN. The major advances at UMN were in the use, testing, and contribution to development of the CASTRO that efficiently scales on over 100,000 CPUs. At UMN it was used for modeling of thermonuclear supernovae (pair instability and supermassive stars) and core-collapse supernovae as well as the final phases of their progenitors, as well as for x-ray bursts from accreting neutron stars. Important secondary advances inmore » the field of nuclear astrophysics included a better understanding of the evolution of massive stars and the origin of the elements. The research resulted in more than 50 publications.« less

From Lived Experiences to Game Creation: How Scaffolding Supports Elementary School Students Learning Computer Science Principles in an After School Setting

ERIC Educational Resources Information Center

Her Many Horses, Ian

2016-01-01

The world, and especially our own country, is in dire need of a larger and more diverse population of computer scientists. While many organizations have approached this problem of too few computer scientists in various ways, a promising, and I believe necessary, path is to expose elementary students to authentic practices of the discipline.…

Southern California Earthquake Center/Undergraduate Studies in Earthquake Information Technology (SCEC/UseIT): Towards the Next Generation of Internship

NASA Astrophysics Data System (ADS)

Perry, S.; Benthien, M.; Jordan, T. H.

2005-12-01

The SCEC/UseIT internship program is training the next generation of earthquake scientist, with methods that can be adapted to other disciplines. UseIT interns work collaboratively, in multi-disciplinary teams, conducting computer science research that is needed by earthquake scientists. Since 2002, the UseIT program has welcomed 64 students, in some two dozen majors, at all class levels, from schools around the nation. Each summer''s work is posed as a ``Grand Challenge.'' The students then organize themselves into project teams, decide how to proceed, and pool their diverse talents and backgrounds. They have traditional mentors, who provide advice and encouragement, but they also mentor one another, and this has proved to be a powerful relationship. Most begin with fear that their Grand Challenge is impossible, and end with excitement and pride about what they have accomplished. The 22 UseIT interns in summer, 2005, were primarily computer science and engineering majors, with others in geology, mathematics, English, digital media design, physics, history, and cinema. The 2005 Grand Challenge was to "build an earthquake monitoring system" to aid scientists who must visualize rapidly evolving earthquake sequences and convey information to emergency personnel and the public. Most UseIT interns were engaged in software engineering, bringing new datasets and functionality to SCEC-VDO (Virtual Display of Objects), a 3D visualization software that was prototyped by interns last year, using Java3D and an extensible, plug-in architecture based on the Eclipse Integrated Development Environment. Other UseIT interns used SCEC-VDO to make animated movies, and experimented with imagery in order to communicate concepts and events in earthquake science. One movie-making project included the creation of an assessment to test the effectiveness of the movie''s educational message. Finally, one intern created an interactive, multimedia presentation of the UseIT program.

Making Scientific Data Usable and Useful

NASA Astrophysics Data System (ADS)

Satwicz, T.; Bharadwaj, A.; Evans, J.; Dirks, J.; Clark Cole, K.

2017-12-01

Transforming geological data into information that has broad scientific and societal impact is a process fraught with barriers. Data sets and tools are often reported to have poor user experiences (UX) that make scientific work more challenging than it needs be. While many other technical fields have benefited from ongoing improvements to the UX of their tools (e.g., healthcare and financial services) scientists are faced with using tools that are labor intensive and not intuitive. Our research team has been involved in a multi-year effort to understand and improve the UX of scientific tools and data sets. We use a User-Centered Design (UCD) process that involves naturalistic behavioral observation and other qualitative research methods adopted from Human-Computer Interaction (HCI) and related fields. Behavioral observation involves having users complete common tasks on data sets, tools, and websites to identify usability issues and understand the severity of the issues. We measure how successfully they complete tasks and diagnosis the cause of any failures. Behavioral observation is paired with in-depth interviews where users describe their process for generating results (from initial inquiry to final results). By asking detailed questions we unpack common patterns and challenges scientists experience while working with data. We've found that tools built using the UCD process can have a large impact on scientist work flows and greatly reduce the time it takes to process data before analysis. It is often challenging to understand the organization and nuances of data across scientific fields. By better understanding how scientists work we can create tools that make routine tasks less-labor intensive, data easier to find, and solve common issues with discovering new data sets and engaging in interdisciplinary research. There is a tremendous opportunity for advancing scientific knowledge and helping the public benefit from that work by creating intuitive, interactive, and powerful tools and resources for generating knowledge. The pathway to achieving that is through building a detailed understanding of users and their needs, then using this knowledge to inform the design of the data products, tools, and services scientists and non-scientists use to do their work.

SciFlo: Semantically-Enabled Grid Workflow for Collaborative Science

NASA Astrophysics Data System (ADS)

Yunck, T.; Wilson, B. D.; Raskin, R.; Manipon, G.

2005-12-01

SciFlo is a system for Scientific Knowledge Creation on the Grid using a Semantically-Enabled Dataflow Execution Environment. SciFlo leverages Simple Object Access Protocol (SOAP) Web Services and the Grid Computing standards (WS-* standards and the Globus Alliance toolkits), and enables scientists to do multi-instrument Earth Science by assembling reusable SOAP Services, native executables, local command-line scripts, and python codes into a distributed computing flow (a graph of operators). SciFlo's XML dataflow documents can be a mixture of concrete operators (fully bound operations) and abstract template operators (late binding via semantic lookup). All data objects and operators can be both simply typed (simple and complex types in XML schema) and semantically typed using controlled vocabularies (linked to OWL ontologies such as SWEET). By exploiting ontology-enhanced search and inference, one can discover (and automatically invoke) Web Services and operators that have been semantically labeled as performing the desired transformation, and adapt a particular invocation to the proper interface (number, types, and meaning of inputs and outputs). The SciFlo client & server engines optimize the execution of such distributed data flows and allow the user to transparently find and use datasets and operators without worrying about the actual location of the Grid resources. The scientist injects a distributed computation into the Grid by simply filling out an HTML form or directly authoring the underlying XML dataflow document, and results are returned directly to the scientist's desktop. A Visual Programming tool is also being developed, but it is not required. Once an analysis has been specified for a granule or day of data, it can be easily repeated with different control parameters and over months or years of data. SciFlo uses and preserves semantics, and also generates and infers new semantic annotations. Specifically, the SciFlo engine uses semantic metadata to understand (infer) what it is doing and potentially improve the data flow; preserves semantics by saving links to the semantics of (metadata describing) the input datasets, related datasets, and the data transformations (algorithms) used to generate downstream products; generates new metadata by allowing the user to add semantic annotations to the generated data products (or simply accept automatically generated provenance annotations); and infers new semantic metadata by understanding and applying logic to the semantics of the data and the transformations performed. Much ontology development still needs to be done but, nevertheless, SciFlo documents provide a substrate for using and preserving more semantics as ontologies develop. We will give a live demonstration of the growing SciFlo network using an example dataflow in which atmospheric temperature and water vapor profiles from three Earth Observing System (EOS) instruments are retrieved using SOAP (geo-location query & data access) services, co-registered, and visually & statistically compared on demand (see http://sciflo.jpl.nasa.gov for more information).

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

Ayer, Vidya M.; Miguez, Sheila; Toby, Brian H.

Scientists have been central to the historical development of the computer industry, but the importance of software only continues to grow for all areas of scientific research and in particular for powder diffraction. Knowing how to program a computer is a basic and useful skill for scientists. The article introduces the three types of programming languages and why scripting languages are now preferred for scientists. Of them, the authors assert Python is the most useful and easiest to learn. Python is introduced. Also presented is an overview to a few of the many add-on packages available to extend the capabilitiesmore » of Python, for example, for numerical computations, scientific graphics and graphical user interface programming.« less

Long live the Data Scientist, but can he/she persist?

NASA Astrophysics Data System (ADS)

Wyborn, L. A.

2011-12-01

In recent years the fourth paradigm of data intensive science has slowly taken hold as the increased capacity of instruments and an increasing number of instruments (in particular sensor networks) have changed how fundamental research is undertaken. Most modern scientific research is about digital capture of data direct from instruments, processing it by computers, storing the results on computers and only publishing a small fraction of data in hard copy publications. At the same time, the rapid increase in capacity of supercomputers, particularly at petascale, means that far larger data sets can be analysed and to greater resolution than previously possible. The new cloud computing paradigm which allows distributed data, software and compute resources to be linked by seamless workflows, is creating new opportunities in processing of high volumes of data to an increasingly larger number of researchers. However, to take full advantage of these compute resources, data sets for analysis have to be aggregated from multiple sources to create high performance data sets. These new technology developments require that scientists must become more skilled in data management and/or have a higher degree of computer literacy. In almost every science discipline there is now an X-informatics branch and a computational X branch (eg, Geoinformatics and Computational Geoscience): both require a new breed of researcher that has skills in both the science fundamentals and also knowledge of some ICT aspects (computer programming, data base design and development, data curation, software engineering). People that can operate in both science and ICT are increasingly known as 'data scientists'. Data scientists are a critical element of many large scale earth and space science informatics projects, particularly those that are tackling current grand challenges at an international level on issues such as climate change, hazard prediction and sustainable development of our natural resources. These projects by their very nature require the integration of multiple digital data sets from multiple sources. Often the preparation of the data for computational analysis can take months and requires painstaking attention to detail to ensure that anomalies identified are real and are not just artefacts of the data preparation and/or the computational analysis. Although data scientists are increasingly vital to successful data intensive earth and space science projects, unless they are recognised for their capabilities in both the science and the computational domains they are likely to migrate to either a science role or an ICT role as their career advances. Most reward and recognition systems do not recognise those with skills in both, hence, getting trained data scientists to persist beyond one or two projects can be challenge. Those data scientists that persist in the profession are characteristically committed and enthusiastic people who have the support of their organisations to take on this role. They also tend to be people who share developments and are critical to the success of the open source software movement. However, the fact remains that survival of the data scientist as a species is being threatened unless something is done to recognise their invaluable contributions to the new fourth paradigm of science.

How to Cloud for Earth Scientists: An Introduction

NASA Technical Reports Server (NTRS)

Lynnes, Chris

2018-01-01

This presentation is a tutorial on getting started with cloud computing for the purposes of Earth Observation datasets. We first discuss some of the main advantages that cloud computing can provide for the Earth scientist: copious processing power, immense and affordable data storage, and rapid startup time. We also talk about some of the challenges of getting the most out of cloud computing: re-organizing the way data are analyzed, handling node failures and attending.

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

Eric A. Wernert; William R. Sherman; Patrick O'Leary

Immersive visualization makes use of the medium of virtual reality (VR) - it is a subset of virtual reality focused on the application of VR technologies to scientific and information visualization. As the name implies, there is a particular focus on the physically immersive aspect of VR that more fully engages the perceptual and kinesthetic capabilities of the scientist with the goal of producing greater insight. The immersive visualization community is uniquely positioned to address the analysis needs of the wide spectrum of domain scientists who are becoming increasingly overwhelmed by data. The outputs of computational science simulations and high-resolutionmore » sensors are creating a data deluge. Data is coming in faster than it can be analyzed, and there are countless opportunities for discovery that are missed as the data speeds by. By more fully utilizing the scientists visual and other sensory systems, and by offering a more natural user interface with which to interact with computer-generated representations, immersive visualization offers great promise in taming this data torrent. However, increasing the adoption of immersive visualization in scientific research communities can only happen by simultaneously lowering the engagement threshold while raising the measurable benefits of adoption. Scientists time spent immersed with their data will thus be rewarded with higher productivity, deeper insight, and improved creativity. Immersive visualization ties together technologies and methodologies from a variety of related but frequently disjoint areas, including hardware, software and human-computer interaction (HCI) disciplines. In many ways, hardware is a solved problem. There are well established technologies including large walk-in systems such as the CAVE{trademark} and head-based systems such as the Wide-5{trademark}. The advent of new consumer-level technologies now enable an entirely new generation of immersive displays, with smaller footprints and costs, widening the potential consumer base. While one would be hard-pressed to call software a solved problem, we now understand considerably more about best practices for designing and developing sustainable, scalable software systems, and we have useful software examples that illuminate the way to even better implementations. As with any research endeavour, HCI will always be exploring new topics in interface design, but we now have a sizable knowledge base of the strengths and weaknesses of the human perceptual systems and we know how to design effective interfaces for immersive systems. So, in a research landscape with a clear need for better visualization and analysis tools, a methodology in immersive visualization that has been shown to effectively address some of those needs, and vastly improved supporting technologies and knowledge of hardware, software, and HCI, why hasn't immersive visualization 'caught on' more with scientists? What can we do as a community of immersive visualization researchers and practitioners to facilitate greater adoption by scientific communities so as to make the transition from 'the promise of virtual reality' to 'the reality of virtual reality'.« less

Wasatch: An architecture-proof multiphysics development environment using a Domain Specific Language and graph theory

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

Saad, Tony; Sutherland, James C.

To address the coding and software challenges of modern hybrid architectures, we propose an approach to multiphysics code development for high-performance computing. This approach is based on using a Domain Specific Language (DSL) in tandem with a directed acyclic graph (DAG) representation of the problem to be solved that allows runtime algorithm generation. When coupled with a large-scale parallel framework, the result is a portable development framework capable of executing on hybrid platforms and handling the challenges of multiphysics applications. In addition, we share our experience developing a code in such an environment – an effort that spans an interdisciplinarymore » team of engineers and computer scientists.« less

Wasatch: An architecture-proof multiphysics development environment using a Domain Specific Language and graph theory

DOE PAGES

Saad, Tony; Sutherland, James C.

2016-05-04

To address the coding and software challenges of modern hybrid architectures, we propose an approach to multiphysics code development for high-performance computing. This approach is based on using a Domain Specific Language (DSL) in tandem with a directed acyclic graph (DAG) representation of the problem to be solved that allows runtime algorithm generation. When coupled with a large-scale parallel framework, the result is a portable development framework capable of executing on hybrid platforms and handling the challenges of multiphysics applications. In addition, we share our experience developing a code in such an environment – an effort that spans an interdisciplinarymore » team of engineers and computer scientists.« less

2009 ALCF annual report.

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

Beckman, P.; Martin, D.; Drugan, C.

2010-11-23

This year the Argonne Leadership Computing Facility (ALCF) delivered nearly 900 million core hours of science. The research conducted at their leadership class facility touched our lives in both minute and massive ways - whether it was studying the catalytic properties of gold nanoparticles, predicting protein structures, or unearthing the secrets of exploding stars. The authors remained true to their vision to act as the forefront computational center in extending science frontiers by solving pressing problems for our nation. Our success in this endeavor was due mainly to the Department of Energy's (DOE) INCITE (Innovative and Novel Computational Impact onmore » Theory and Experiment) program. The program awards significant amounts of computing time to computationally intensive, unclassified research projects that can make high-impact scientific advances. This year, DOE allocated 400 million hours of time to 28 research projects at the ALCF. Scientists from around the world conducted the research, representing such esteemed institutions as the Princeton Plasma Physics Laboratory, National Institute of Standards and Technology, and European Center for Research and Advanced Training in Scientific Computation. Argonne also provided Director's Discretionary allocations for research challenges, addressing such issues as reducing aerodynamic noise, critical for next-generation 'green' energy systems. Intrepid - the ALCF's 557-teraflops IBM Blue/Gene P supercomputer - enabled astounding scientific solutions and discoveries. Intrepid went into full production five months ahead of schedule. As a result, the ALCF nearly doubled the days of production computing available to the DOE Office of Science, INCITE awardees, and Argonne projects. One of the fastest supercomputers in the world for open science, the energy-efficient system uses about one-third as much electricity as a machine of comparable size built with more conventional parts. In October 2009, President Barack Obama recognized the excellence of the entire Blue Gene series by awarding it to the National Medal of Technology and Innovation. Other noteworthy achievements included the ALCF's collaboration with the National Energy Research Scientific Computing Center (NERSC) to examine cloud computing as a potential new computing paradigm for scientists. Named Magellan, the DOE-funded initiative will explore which science application programming models work well within the cloud, as well as evaluate the challenges that come with this new paradigm. The ALCF obtained approval for its next-generation machine, a 10-petaflops system to be delivered in 2012. This system will allow us to resolve ever more pressing problems, even more expeditiously through breakthrough science in the years to come.« less

The 3D widgets for exploratory scientific visualization

NASA Technical Reports Server (NTRS)

Herndon, Kenneth P.; Meyer, Tom

1995-01-01

Computational fluid dynamics (CFD) techniques are used to simulate flows of fluids like air or water around such objects as airplanes and automobiles. These techniques usually generate very large amounts of numerical data which are difficult to understand without using graphical scientific visualization techniques. There are a number of commercial scientific visualization applications available today which allow scientists to control visualization tools via textual and/or 2D user interfaces. However, these user interfaces are often difficult to use. We believe that 3D direct-manipulation techniques for interactively controlling visualization tools will provide opportunities for powerful and useful interfaces with which scientists can more effectively explore their datasets. A few systems have been developed which use these techniques. In this paper, we will present a variety of 3D interaction techniques for manipulating parameters of visualization tools used to explore CFD datasets, and discuss in detail various techniques for positioning tools in a 3D scene.

Skills and Knowledge for Data-Intensive Environmental Research

PubMed Central

Hampton, Stephanie E.; Jones, Matthew B.; Wasser, Leah A.; Schildhauer, Mark P.; Supp, Sarah R.; Brun, Julien; Hernandez, Rebecca R.; Boettiger, Carl; Collins, Scott L.; Gross, Louis J.; Fernández, Denny S.; Budden, Amber; White, Ethan P.; Teal, Tracy K.; Aukema, Juliann E.

2017-01-01

Abstract The scale and magnitude of complex and pressing environmental issues lend urgency to the need for integrative and reproducible analysis and synthesis, facilitated by data-intensive research approaches. However, the recent pace of technological change has been such that appropriate skills to accomplish data-intensive research are lacking among environmental scientists, who more than ever need greater access to training and mentorship in computational skills. Here, we provide a roadmap for raising data competencies of current and next-generation environmental researchers by describing the concepts and skills needed for effectively engaging with the heterogeneous, distributed, and rapidly growing volumes of available data. We articulate five key skills: (1) data management and processing, (2) analysis, (3) software skills for science, (4) visualization, and (5) communication methods for collaboration and dissemination. We provide an overview of the current suite of training initiatives available to environmental scientists and models for closing the skill-transfer gap. PMID:28584342

Skills and Knowledge for Data-Intensive Environmental Research.

PubMed

Hampton, Stephanie E; Jones, Matthew B; Wasser, Leah A; Schildhauer, Mark P; Supp, Sarah R; Brun, Julien; Hernandez, Rebecca R; Boettiger, Carl; Collins, Scott L; Gross, Louis J; Fernández, Denny S; Budden, Amber; White, Ethan P; Teal, Tracy K; Labou, Stephanie G; Aukema, Juliann E

2017-06-01

The scale and magnitude of complex and pressing environmental issues lend urgency to the need for integrative and reproducible analysis and synthesis, facilitated by data-intensive research approaches. However, the recent pace of technological change has been such that appropriate skills to accomplish data-intensive research are lacking among environmental scientists, who more than ever need greater access to training and mentorship in computational skills. Here, we provide a roadmap for raising data competencies of current and next-generation environmental researchers by describing the concepts and skills needed for effectively engaging with the heterogeneous, distributed, and rapidly growing volumes of available data. We articulate five key skills: (1) data management and processing, (2) analysis, (3) software skills for science, (4) visualization, and (5) communication methods for collaboration and dissemination. We provide an overview of the current suite of training initiatives available to environmental scientists and models for closing the skill-transfer gap.

Watering Down Barriers to Using Hydropower through Fisheries Research

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

Ham, Ken

Much of our work on clean energy is targeted at improving performance of hydropower, the largest source of renewable energy in the Pacific Northwest and the nation. PNNL experts in hydropower—from computer scientists to biologists and engineers—are helping to optimize the efficiency and environmental performance of hydroelectric plants. The Columbia River is the nation’s most important hydropower resource, producing 40 percent of the nation’s hydroelectric generation and up to 70 percent of the region’s power. At PNNL, Fisheries Biologist Ken Ham and others are working with stakeholders in the Pacific Northwest, the Army Corps of Engineers and DOE to ensuremore » that this resource continues to provide its many benefits while setting a new standard for environmental sustainability. As aging turbines are replaced in existing hydropower dams, computational modeling and state-of-the-art fisheries research combine to aid the design of a next-generation hydro turbine that meets or exceeds current biological performance standards and produces more power.« less

Enabling the transition towards Earth Observation Science 2.0

NASA Astrophysics Data System (ADS)

Mathieu, Pierre-Philippe; Desnos, Yves-Louis

2015-04-01

Science 2.0 refers to the rapid and systematic changes in doing Research and organising Science driven by the rapid advances in ICT and digital technologies combined with a growing demand to do Science for Society (actionable research) and in Society (co-design of knowledge). Nowadays, teams of researchers around the world can easily access a wide range of open data across disciplines and remotely process them on the Cloud, combining them with their own data to generate knowledge, develop information products for societal applications, and tackle complex integrative complex problems that could not be addressed a few years ago. Such rapid exchange of digital data is fostering a new world of data-intensive research, characterized by openness, transparency, and scrutiny and traceability of results, access to large volume of complex data, availability of community open tools, unprecedented level of computing power, and new collaboration among researchers and new actors such as citizen scientists. The EO scientific community is now facing the challenge of responding to this new paradigm in science 2.0 in order to make the most of the large volume of complex and diverse data delivered by the new generation of EO missions, and in particular the Sentinels. In this context, ESA - in particular within the framework of the Scientific Exploitation of Operational Missions (SEOM) element - is supporting a variety of activities in partnership with research communities to ease the transition and make the most of the data. These include the generation of new open tools and exploitation platforms, exploring new ways to exploit data on cloud-based platforms, dissiminate data, building new partnership with citizen scientists, and training the new generation of data scientists. The paper will give a brief overview of some of ESA activities aiming to facilitate the exploitation of large amount of data from EO missions in a collaborative, cross-disciplinary, and open way, from science to applications and education.

The IT in Secondary Science Book. A Compendium of Ideas for Using Computers and Teaching Science.

ERIC Educational Resources Information Center

Frost, Roger

Scientists need to measure and communicate, to handle information, and model ideas. In essence, they need to process information. Young scientists have the same needs. Computers have become a tremendously important addition to the processing of information through database use, graphing and modeling and also in the collection of information…

75 FR 64996 - Takes of Marine Mammals Incidental to Specified Activities; Marine Geophysical Survey in the...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-21

... cruises. A laptop computer is located on the observer platform for ease of data entry. The computer is... lines, the receiving systems will receive the returning acoustic signals. The study (e.g., equipment...-board assistance by the scientists who have proposed the study. The Chief Scientist is Dr. Franco...

Real Science, Real Learning: Bridging the Gap Between Scientists, Educators and Students

NASA Astrophysics Data System (ADS)

Lewis, Y.

2006-05-01

Today as never before, America needs its citizens to be literate in science and technology. Not only must we only inspire a new generation of scientists and engineers and technologists, we must foster a society capable of meeting complex, 21st-century challenges. Unfortunately, the need for creative, flexible thinkers is growing at a time when our young students are lagging in science interest and performance. Over the past 17 years, the JASON Project has worked to link real science and scientists to the classroom. This link provide viable pipeline to creating the next generation scientists and researchers. Ultimately, JASON's mission is to improve the way science is taught by enabling students to learn directly from leading scientists. Through partnerships with agencies such as NOAA and NASA, JASON creates multimedia classroom products based on current scientific research. Broadcasts of science expeditions, hosted by leading researchers, are coupled with classroom materials that include interactive computer-based simulations, video- on-demand, inquiry-based experiments and activities, and print materials for students and teachers. A "gated" Web site hosts online resources and provides a secure platform to network with scientists and other classrooms in a nationwide community of learners. Each curriculum is organized around a specific theme for a comprehensive learning experience. It may be taught as a complete package, or individual components can be selected to teach specific, standards-based concepts. Such thematic units include: Disappearing Wetlands, Mysteries of Earth and Mars, and Monster Storms. All JASON curriculum units are grounded in "inquiry-based learning." The highly interactive curriculum will enable students to access current, real-world scientific research and employ the scientific method through reflection, investigation, identification of problems, sharing of data, and forming and testing hypotheses. JASON specializes in effectively applying technology in science education by designing animated interactive visualizations that promote student understanding of complex scientific concepts and systems (Rieber, 1990, 1996). JASON's experience in utilizing the power of simulation technology has been widely recognized for its effectiveness in exciting and engaging students in science learning by independent evaluations of JASON's multimedia science curriculum (Ba et al., 2001; Goldenberg et al., 2003). The data collected indicates that JASON's science products have had a positive impact on students' science learning, have positively influenced their perceptions of scientists and of becoming scientists, and have helped diverse students grasp a deeper understanding of complex scientific content, concepts and technologies.

NASA Scientists Push the Limits of Computer Technology

NASA Technical Reports Server (NTRS)

1998-01-01

Dr. Donald Frazier,NASA researcher, uses a blue laser shining through a quarts window into a special mix of chemicals to generate a polymer film on the inside quartz surface. As the chemicals respond to the laser light, they adhere to the glass surface, forming optical films. Dr. Frazier and Dr. Mark S. Paley developed the process in the Space Sciences Laboratory at NASA's Marshall Space Flight Center in Huntsville, AL. Working aboard the Space Shuttle, a science team led by Dr. Frazier formed thin films potentially useful in optical computers with fewer impurities than those formed on Earth. Patterns of these films can be traced onto the quartz surface. In the optical computers of the future, these films could replace electronic circuits and wires, making the systems more efficient and cost-effective, as well as lighter and more compact. Photo credit: NASA/Marshall Space Flight Center.

NASA Scientists Push the Limits of Computer Technology

NASA Technical Reports Server (NTRS)

1998-01-01

NASA research Dr. Donald Frazier uses a blue laser shining through a quartz window into a special mix of chemicals to generate a polymer film on the inside quartz surface. As the chemicals respond to the laser light, they adhere to the glass surface, forming opticl films. Dr. Frazier and Dr. Mark S. Paley developed the process in the Space Sciences Laboratory at NASA's Marshall Space Flight Center in Huntsville, AL. Working aboard the Space Shuttle, a science team led by Dr. Frazier formed thin-films potentially useful in optical computers with fewer impurities than those formed on Earth. Patterns of these films can be traced onto the quartz surface. In the optical computers on the future, these films could replace electronic circuits and wires, making the systems more efficient and cost-effective, as well as lighter and more compact. Photo credit: NASA/Marshall Space Flight Center

NASA Scientists Push the Limits of Computer Technology

NASA Technical Reports Server (NTRS)

1999-01-01

NASA researcher Dr. Donald Frazier uses a blue laser shining through a quartz window into a special mix of chemicals to generate a polymer film on the inside quartz surface. As the chemicals respond to the laser light, they adhere to the glass surface, forming optical films. Dr. Frazier and Dr. Mark S. Paley developed the process in the Space Sciences Laboratory at NASA's Marshall Space Flight Center in Huntsville, AL. Working aboard the Space Shuttle, a science team led by Dr. Frazier formed thin-films potentially useful in optical computers with fewer impurities than those formed on Earth. Patterns of these films can be traced onto the quartz surface. In the optical computers of the future, thee films could replace electronic circuits and wires, making the systems more efficient and cost-effective, as well as lighter and more compact. Photo credit: NASA/Marshall Space Flight Center

Technologies for Large Data Management in Scientific Computing

NASA Astrophysics Data System (ADS)

Pace, Alberto

2014-01-01

In recent years, intense usage of computing has been the main strategy of investigations in several scientific research projects. The progress in computing technology has opened unprecedented opportunities for systematic collection of experimental data and the associated analysis that were considered impossible only few years ago. This paper focuses on the strategies in use: it reviews the various components that are necessary for an effective solution that ensures the storage, the long term preservation, and the worldwide distribution of large quantities of data that are necessary in a large scientific research project. The paper also mentions several examples of data management solutions used in High Energy Physics for the CERN Large Hadron Collider (LHC) experiments in Geneva, Switzerland which generate more than 30,000 terabytes of data every year that need to be preserved, analyzed, and made available to a community of several tenth of thousands scientists worldwide.

What do computer scientists tweet? Analyzing the link-sharing practice on Twitter

PubMed Central

Schmitt, Marco

2017-01-01

Twitter communication has permeated every sphere of society. To highlight and share small pieces of information with possibly vast audiences or small circles of the interested has some value in almost any aspect of social life. But what is the value exactly for a scientific field? We perform a comprehensive study of computer scientists using Twitter and their tweeting behavior concerning the sharing of web links. Discerning the domains, hosts and individual web pages being tweeted and the differences between computer scientists and a Twitter sample enables us to look in depth at the Twitter-based information sharing practices of a scientific community. Additionally, we aim at providing a deeper understanding of the role and impact of altmetrics in computer science and give a glance at the publications mentioned on Twitter that are most relevant for the computer science community. Our results show a link sharing culture that concentrates more heavily on public and professional quality information than the Twitter sample does. The results also show a broad variety in linked sources and especially in linked publications with some publications clearly related to community-specific interests of computer scientists, while others with a strong relation to attention mechanisms in social media. This refers to the observation that Twitter is a hybrid form of social media between an information service and a social network service. Overall the computer scientists’ style of usage seems to be more on the information-oriented side and to some degree also on professional usage. Therefore, altmetrics are of considerable use in analyzing computer science. PMID:28636619

Analysis of severe storm data

NASA Technical Reports Server (NTRS)

Hickey, J. S.

1983-01-01

The Mesoscale Analysis and Space Sensor (MASS) Data Management and Analysis System developed by Atsuko Computing International (ACI) on the MASS HP-1000 Computer System within the Systems Dynamics Laboratory of the Marshall Space Flight Center is described. The MASS Data Management and Analysis System was successfully implemented and utilized daily by atmospheric scientists to graphically display and analyze large volumes of conventional and satellite derived meteorological data. The scientists can process interactively various atmospheric data (Sounding, Single Level, Gird, and Image) by utilizing the MASS (AVE80) share common data and user inputs, thereby reducing overhead, optimizing execution time, and thus enhancing user flexibility, useability, and understandability of the total system/software capabilities. In addition ACI installed eight APPLE III graphics/imaging computer terminals in individual scientist offices and integrated them into the MASS HP-1000 Computer System thus providing significant enhancement to the overall research environment.

NASA/DOD Aerospace Knowledge Diffusion Research Project. Paper 19: Computer and information technology and aerospace knowledge diffusion

NASA Technical Reports Server (NTRS)

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

1992-01-01

To remain a world leader in aerospace, the US must improve and maintain the professional competency of its engineers and scientists, increase the research and development (R&D) knowledge base, improve productivity, and maximize the integration of recent technological developments into the R&D process. How well these objectives are met, and at what cost, depends on a variety of factors, but largely on the ability of US aerospace engineers and scientists to acquire and process the results of federally funded R&D. The Federal Government's commitment to high speed computing and networking systems presupposes that computer and information technology will play a major role in the aerospace knowledge diffusion process. However, we know little about information technology needs, uses, and problems within the aerospace knowledge diffusion process. The use of computer and information technology by US aerospace engineers and scientists in academia, government, and industry is reported.

Introduction to the Space Physics Analysis Network (SPAN)

NASA Technical Reports Server (NTRS)

Green, J. L. (Editor); Peters, D. J. (Editor)

1985-01-01

The Space Physics Analysis Network or SPAN is emerging as a viable method for solving an immediate communication problem for the space scientist. SPAN provides low-rate communication capability with co-investigators and colleagues, and access to space science data bases and computational facilities. The SPAN utilizes up-to-date hardware and software for computer-to-computer communications allowing binary file transfer and remote log-on capability to over 25 nationwide space science computer systems. SPAN is not discipline or mission dependent with participation from scientists in such fields as magnetospheric, ionospheric, planetary, and solar physics. Basic information on the network and its use are provided. It is anticipated that SPAN will grow rapidly over the next few years, not only from the standpoint of more network nodes, but as scientists become more proficient in the use of telescience, more capability will be needed to satisfy the demands.

Streaming support for data intensive cloud-based sequence analysis.

PubMed

Issa, Shadi A; Kienzler, Romeo; El-Kalioby, Mohamed; Tonellato, Peter J; Wall, Dennis; Bruggmann, Rémy; Abouelhoda, Mohamed

2013-01-01

Cloud computing provides a promising solution to the genomics data deluge problem resulting from the advent of next-generation sequencing (NGS) technology. Based on the concepts of "resources-on-demand" and "pay-as-you-go", scientists with no or limited infrastructure can have access to scalable and cost-effective computational resources. However, the large size of NGS data causes a significant data transfer latency from the client's site to the cloud, which presents a bottleneck for using cloud computing services. In this paper, we provide a streaming-based scheme to overcome this problem, where the NGS data is processed while being transferred to the cloud. Our scheme targets the wide class of NGS data analysis tasks, where the NGS sequences can be processed independently from one another. We also provide the elastream package that supports the use of this scheme with individual analysis programs or with workflow systems. Experiments presented in this paper show that our solution mitigates the effect of data transfer latency and saves both time and cost of computation.

Automated Generation of Message-Passing Programs: An Evaluation Using CAPTools

NASA Technical Reports Server (NTRS)

Hribar, Michelle R.; Jin, Haoqiang; Yan, Jerry C.; Saini, Subhash (Technical Monitor)

1998-01-01

Scientists at NASA Ames Research Center have been developing computational aeroscience applications on highly parallel architectures over the past ten years. During that same time period, a steady transition of hardware and system software also occurred, forcing us to expend great efforts into migrating and re-coding our applications. As applications and machine architectures become increasingly complex, the cost and time required for this process will become prohibitive. In this paper, we present the first set of results in our evaluation of interactive parallelization tools. In particular, we evaluate CAPTool's ability to parallelize computational aeroscience applications. CAPTools was tested on serial versions of the NAS Parallel Benchmarks and ARC3D, a computational fluid dynamics application, on two platforms: the SGI Origin 2000 and the Cray T3E. This evaluation includes performance, amount of user interaction required, limitations and portability. Based on these results, a discussion on the feasibility of computer aided parallelization of aerospace applications is presented along with suggestions for future work.

Montage Version 3.0

NASA Technical Reports Server (NTRS)

Jacob, Joseph; Katz, Daniel; Prince, Thomas; Berriman, Graham; Good, John; Laity, Anastasia

2006-01-01

The final version (3.0) of the Montage software has been released. To recapitulate from previous NASA Tech Briefs articles about Montage: This software generates custom, science-grade mosaics of astronomical images on demand from input files that comply with the Flexible Image Transport System (FITS) standard and contain image data registered on projections that comply with the World Coordinate System (WCS) standards. This software can be executed on single-processor computers, multi-processor computers, and such networks of geographically dispersed computers as the National Science Foundation s TeraGrid or NASA s Information Power Grid. The primary advantage of running Montage in a grid environment is that computations can be done on a remote supercomputer for efficiency. Multiple computers at different sites can be used for different parts of a computation a significant advantage in cases of computations for large mosaics that demand more processor time than is available at any one site. Version 3.0 incorporates several improvements over prior versions. The most significant improvement is that this version is accessible to scientists located anywhere, through operational Web services that provide access to data from several large astronomical surveys and construct mosaics on either local workstations or remote computational grids as needed.

Jade: using on-demand cloud analysis to give scientists back their flow

NASA Astrophysics Data System (ADS)

Robinson, N.; Tomlinson, J.; Hilson, A. J.; Arribas, A.; Powell, T.

2017-12-01

The UK's Met Office generates 400 TB weather and climate data every day by running physical models on its Top 20 supercomputer. As data volumes explode, there is a danger that analysis workflows become dominated by watching progress bars, and not thinking about science. We have been researching how we can use distributed computing to allow analysts to process these large volumes of high velocity data in a way that's easy, effective and cheap.Our prototype analysis stack, Jade, tries to encapsulate this. Functionality includes: An under-the-hood Dask engine which parallelises and distributes computations, without the need to retrain analysts Hybrid compute clusters (AWS, Alibaba, and local compute) comprising many thousands of cores Clusters which autoscale up/down in response to calculation load using Kubernetes, and balances the cluster across providers based on the current price of compute Lazy data access from cloud storage via containerised OpenDAP This technology stack allows us to perform calculations many orders of magnitude faster than is possible on local workstations. It is also possible to outperform dedicated local compute clusters, as cloud compute can, in principle, scale to much larger scales. The use of ephemeral compute resources also makes this implementation cost efficient.

Defining Computational Thinking for Mathematics and Science Classrooms

NASA Astrophysics Data System (ADS)

Weintrop, David; Beheshti, Elham; Horn, Michael; Orton, Kai; Jona, Kemi; Trouille, Laura; Wilensky, Uri

2016-02-01

Science and mathematics are becoming computational endeavors. This fact is reflected in the recently released Next Generation Science Standards and the decision to include "computational thinking" as a core scientific practice. With this addition, and the increased presence of computation in mathematics and scientific contexts, a new urgency has come to the challenge of defining computational thinking and providing a theoretical grounding for what form it should take in school science and mathematics classrooms. This paper presents a response to this challenge by proposing a definition of computational thinking for mathematics and science in the form of a taxonomy consisting of four main categories: data practices, modeling and simulation practices, computational problem solving practices, and systems thinking practices. In formulating this taxonomy, we draw on the existing computational thinking literature, interviews with mathematicians and scientists, and exemplary computational thinking instructional materials. This work was undertaken as part of a larger effort to infuse computational thinking into high school science and mathematics curricular materials. In this paper, we argue for the approach of embedding computational thinking in mathematics and science contexts, present the taxonomy, and discuss how we envision the taxonomy being used to bring current educational efforts in line with the increasingly computational nature of modern science and mathematics.

Most Social Scientists Shun Free Use of Supercomputers.

ERIC Educational Resources Information Center

Kiernan, Vincent

1998-01-01

Social scientists, who frequently complain that the federal government spends too little on them, are passing up what scholars in the physical and natural sciences see as the government's best give-aways: free access to supercomputers. Some social scientists say the supercomputers are difficult to use; others find desktop computers provide…

The Unified English Braille Code: Examination by Science, Mathematics, and Computer Science Technical Expert Braille Readers

ERIC Educational Resources Information Center

Holbrook, M. Cay; MacCuspie, P. Ann

2010-01-01

Braille-reading mathematicians, scientists, and computer scientists were asked to examine the usability of the Unified English Braille Code (UEB) for technical materials. They had little knowledge of the code prior to the study. The research included two reading tasks, a short tutorial about UEB, and a focus group. The results indicated that the…

Meet EPA Scientist Valerie Zartarian, Ph.D.

EPA Pesticide Factsheets

Senior exposure scientist and research environmental engineer Valerie Zartarian, Ph.D. helps build computer models and other tools that advance our understanding of how people interact with chemicals.

Hot, Hot, Hot Computer Careers.

ERIC Educational Resources Information Center

Basta, Nicholas

1988-01-01

Discusses the increasing need for electrical, electronic, and computer engineers; and scientists. Provides current status of the computer industry and average salaries. Considers computer chip manufacture and the current chip shortage. (MVL)

Smagglce: Surface Modeling and Grid Generation for Iced Airfoils: Phase 1 Results

NASA Technical Reports Server (NTRS)

Vickerman, Mary B.; Choo, Yung K.; Braun, Donald C.; Baez, Marivell; Gnepp, Steven

1999-01-01

SmaggIce (Surface Modeling and Grid Generation for Iced Airfoils) is a software toolkit used in the process of aerodynamic performance prediction of iced airfoils with grid-based Computational Fluid Dynamics (CFD). It includes tools for data probing, boundary smoothing, domain decomposition, and structured grid generation and refinement. SmaggIce provides the underlying computations to perform these functions, a GUI (Graphical User Interface) to control and interact with those functions, and graphical displays of results, it is being developed at NASA Glenn Research Center. This paper discusses the overall design of SmaggIce as well as what has been implemented in Phase 1. Phase 1 results provide two types of software tools: interactive ice shape probing and interactive ice shape control. The ice shape probing tools will provide aircraft icing engineers and scientists with an interactive means to measure the physical characteristics of ice shapes. On the other hand, the ice shape control features of SmaggIce will allow engineers to examine input geometry data, correct or modify any deficiencies in the geometry, and perform controlled systematic smoothing to a level that will make the CFD process manageable.

Towards data warehousing and mining of protein unfolding simulation data.

PubMed

Berrar, Daniel; Stahl, Frederic; Silva, Candida; Rodrigues, J Rui; Brito, Rui M M; Dubitzky, Werner

2005-10-01

The prediction of protein structure and the precise understanding of protein folding and unfolding processes remains one of the greatest challenges in structural biology and bioinformatics. Computer simulations based on molecular dynamics (MD) are at the forefront of the effort to gain a deeper understanding of these complex processes. Currently, these MD simulations are usually on the order of tens of nanoseconds, generate a large amount of conformational data and are computationally expensive. More and more groups run such simulations and generate a myriad of data, which raises new challenges in managing and analyzing these data. Because the vast range of proteins researchers want to study and simulate, the computational effort needed to generate data, the large data volumes involved, and the different types of analyses scientists need to perform, it is desirable to provide a public repository allowing researchers to pool and share protein unfolding data. To adequately organize, manage, and analyze the data generated by unfolding simulation studies, we designed a data warehouse system that is embedded in a grid environment to facilitate the seamless sharing of available computer resources and thus enable many groups to share complex molecular dynamics simulations on a more regular basis. To gain insight into the conformational fluctuations and stability of the monomeric forms of the amyloidogenic protein transthyretin (TTR), molecular dynamics unfolding simulations of the monomer of human TTR have been conducted. Trajectory data and meta-data of the wild-type (WT) protein and the highly amyloidogenic variant L55P-TTR represent the test case for the data warehouse. Web and grid services, especially pre-defined data mining services that can run on or 'near' the data repository of the data warehouse, are likely to play a pivotal role in the analysis of molecular dynamics unfolding data.

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

Shankar, Arjun

Computer scientist Arjun Shankar is director of the Compute and Data Environment for Science (CADES), ORNL’s multidisciplinary big data computing center. CADES offers computing, networking and data analytics to facilitate workflows for both ORNL and external research projects.

Jungle Computing: Distributed Supercomputing Beyond Clusters, Grids, and Clouds

NASA Astrophysics Data System (ADS)

Seinstra, Frank J.; Maassen, Jason; van Nieuwpoort, Rob V.; Drost, Niels; van Kessel, Timo; van Werkhoven, Ben; Urbani, Jacopo; Jacobs, Ceriel; Kielmann, Thilo; Bal, Henri E.

In recent years, the application of high-performance and distributed computing in scientific practice has become increasingly wide spread. Among the most widely available platforms to scientists are clusters, grids, and cloud systems. Such infrastructures currently are undergoing revolutionary change due to the integration of many-core technologies, providing orders-of-magnitude speed improvements for selected compute kernels. With high-performance and distributed computing systems thus becoming more heterogeneous and hierarchical, programming complexity is vastly increased. Further complexities arise because urgent desire for scalability and issues including data distribution, software heterogeneity, and ad hoc hardware availability commonly force scientists into simultaneous use of multiple platforms (e.g., clusters, grids, and clouds used concurrently). A true computing jungle.

Modeling Natural Selection

ERIC Educational Resources Information Center

Bogiages, Christopher A.; Lotter, Christine

2011-01-01

In their research, scientists generate, test, and modify scientific models. These models can be shared with others and demonstrate a scientist's understanding of how the natural world works. Similarly, students can generate and modify models to gain a better understanding of the content, process, and nature of science (Kenyon, Schwarz, and Hug…

Space station Simulation Computer System (SCS) study for NASA/MSFC. Volume 4: Conceptual design report

NASA Technical Reports Server (NTRS)

1989-01-01

The Simulation Computer System (SCS) is the computer hardware, software, and workstations that will support the Payload Training Complex (PTC) at Marshall Space Flight Center (MSFC). The PTC will train the space station payload scientists, station scientists, and ground controllers to operate the wide variety of experiments that will be onboard the Space Station Freedom. In the first step of this task, a methodology was developed to ensure that all relevant design dimensions were addressed, and that all feasible designs could be considered. The development effort yielded the following method for generating and comparing designs in task 4: (1) Extract SCS system requirements (functions) from the system specification; (2) Develop design evaluation criteria; (3) Identify system architectural dimensions relevant to SCS system designs; (4) Develop conceptual designs based on the system requirements and architectural dimensions identified in step 1 and step 3 above; (5) Evaluate the designs with respect to the design evaluation criteria developed in step 2 above. The results of the method detailed in the above 5 steps are discussed. The results of the task 4 work provide the set of designs which two or three candidate designs are to be selected by MSFC as input to task 5-refine SCS conceptual designs. The designs selected for refinement will be developed to a lower level of detail, and further analyses will be done to begin to determine the size and speed of the components required to implement these designs.

CICT Computing, Information, and Communications Technology Program

NASA Technical Reports Server (NTRS)

Laufenberg, Lawrence; Tu, Eugene (Technical Monitor)

2002-01-01

The CICT Program is part of the NASA Aerospace Technology Enterprise's fundamental technology thrust to develop tools. processes, and technologies that enable new aerospace system capabilities and missions. The CICT Program's four key objectives are: Provide seamless access to NASA resources- including ground-, air-, and space-based distributed information technology resources-so that NASA scientists and engineers can more easily control missions, make new scientific discoveries, and design the next-generation space vehicles, provide high-data delivery from these assets directly to users for missions, develop goal-oriented human-centered systems, and research, develop and evaluate revolutionary technology.

Developing a strategy for computational lab skills training through Software and Data Carpentry: Experiences from the ELIXIR Pilot action

PubMed Central

Pawlik, Aleksandra; van Gelder, Celia W.G.; Nenadic, Aleksandra; Palagi, Patricia M.; Korpelainen, Eija; Lijnzaad, Philip; Marek, Diana; Sansone, Susanna-Assunta; Hancock, John; Goble, Carole

2017-01-01

Quality training in computational skills for life scientists is essential to allow them to deliver robust, reproducible and cutting-edge research. A pan-European bioinformatics programme, ELIXIR, has adopted a well-established and progressive programme of computational lab and data skills training from Software and Data Carpentry, aimed at increasing the number of skilled life scientists and building a sustainable training community in this field. This article describes the Pilot action, which introduced the Carpentry training model to the ELIXIR community. PMID:28781745

Developing a strategy for computational lab skills training through Software and Data Carpentry: Experiences from the ELIXIR Pilot action.

PubMed

Pawlik, Aleksandra; van Gelder, Celia W G; Nenadic, Aleksandra; Palagi, Patricia M; Korpelainen, Eija; Lijnzaad, Philip; Marek, Diana; Sansone, Susanna-Assunta; Hancock, John; Goble, Carole

2017-01-01

Quality training in computational skills for life scientists is essential to allow them to deliver robust, reproducible and cutting-edge research. A pan-European bioinformatics programme, ELIXIR, has adopted a well-established and progressive programme of computational lab and data skills training from Software and Data Carpentry, aimed at increasing the number of skilled life scientists and building a sustainable training community in this field. This article describes the Pilot action, which introduced the Carpentry training model to the ELIXIR community.

Computer user's manual for a generalized curve fit and plotting program

NASA Technical Reports Server (NTRS)

Schlagheck, R. A.; Beadle, B. D., II; Dolerhie, B. D., Jr.; Owen, J. W.

1973-01-01

A FORTRAN coded program has been developed for generating plotted output graphs on 8-1/2 by 11-inch paper. The program is designed to be used by engineers, scientists, and non-programming personnel on any IBM 1130 system that includes a 1627 plotter. The program has been written to provide a fast and efficient method of displaying plotted data without having to generate any additions. Various output options are available to the program user for displaying data in four different types of formatted plots. These options include discrete linear, continuous, and histogram graphical outputs. The manual contains information about the use and operation of this program. A mathematical description of the least squares goodness of fit test is presented. A program listing is also included.

Expert System Approach For Generating And Evaluating Engine Design Alternatives

NASA Astrophysics Data System (ADS)

Shen, Stewart N. T.; Chew, Meng-Sang; Issa, Ghassan F.

1989-03-01

Artificial intelligence is becoming an increasingly important subject of study for computer scientists, engineering designers, as well as professionals in other fields. Even though AI technology is a relatively new discipline, many of its concepts have already found practical applications. Expert systems, in particular, have made significant contributions to technologies in such fields as business, medicine, engineering design, chemistry, and particle physics. This paper describes an expert system developed to aid the mechanical designer with the preliminary design of variable-stroke internal-combustion engines. The expert system accomplished its task by generating and evaluating a large number of design alternatives represented in the form of graphs. Through the application of structural and design rules directly to the graphs, optimal and near optimal preliminary design configurations of engines are deduced.

Communicating Ocean Sciences to Informal Audiences: A Scientist-Educator Partnership to Prepare the Next Generation of Scientists

ERIC Educational Resources Information Center

Halversen, Catherine; Tran, Lynn Uyen

2010-01-01

Communicating Ocean Sciences to Informal Audiences (COSIA) is a college course that creates and develops partnerships between science educators in informal science education institutions, such as museums, science centers and aquariums, and ocean scientists in colleges and universities. For the course, a scientist and educator team-teach…

An Examination of Climate Scientists' Participation in Education: Implications for Supporting the Teaching and Learning of Socially Controversial Science

ERIC Educational Resources Information Center

Walsh, Elizabeth M.

2012-01-01

Preparing a generation of citizens to respond to the impacts of climate change will require collaborative interactions between natural scientists, learning scientists, educators and learners. Promoting effective involvement of scientists in climate change education is especially important as climate change science and climate impacts are…

The Terra Data Fusion Project: An Update

NASA Astrophysics Data System (ADS)

Di Girolamo, L.; Bansal, S.; Butler, M.; Fu, D.; Gao, Y.; Lee, H. J.; Liu, Y.; Lo, Y. L.; Raila, D.; Turner, K.; Towns, J.; Wang, S. W.; Yang, K.; Zhao, G.

2017-12-01

Terra is the flagship of NASA's Earth Observing System. Launched in 1999, Terra's five instruments continue to gather data that enable scientists to address fundamental Earth science questions. By design, the strength of the Terra mission has always been rooted in its five instruments and the ability to fuse the instrument data together for obtaining greater quality of information for Earth Science compared to individual instruments alone. As the data volume grows and the central Earth Science questions move towards problems requiring decadal-scale data records, the need for data fusion and the ability for scientists to perform large-scale analytics with long records have never been greater. The challenge is particularly acute for Terra, given its growing volume of data (> 1 petabyte), the storage of different instrument data at different archive centers, the different file formats and projection systems employed for different instrument data, and the inadequate cyberinfrastructure for scientists to access and process whole-mission fusion data (including Level 1 data). Sharing newly derived Terra products with the rest of the world also poses challenges. As such, the Terra Data Fusion Project aims to resolve two long-standing problems: 1) How do we efficiently generate and deliver Terra data fusion products? 2) How do we facilitate the use of Terra data fusion products by the community in generating new products and knowledge through national computing facilities, and disseminate these new products and knowledge through national data sharing services? Here, we will provide an update on significant progress made in addressing these problems by working with NASA and leveraging national facilities managed by the National Center for Supercomputing Applications (NCSA). The problems that we faced in deriving and delivering Terra L1B2 basic, reprojected and cloud-element fusion products, such as data transfer, data fusion, processing on different computer architectures, science, and sharing, will be presented with quantitative specifics. Results from several science-specific drivers for Terra fusion products will also be presented. We demonstrate that the Terra Data Fusion Project itself provides an excellent use-case for the community addressing Big Data and cyberinfrastructure problems.

Model Diagnostics for the Department of Energy's Accelerated Climate Modeling for Energy (ACME) Project

NASA Astrophysics Data System (ADS)

Smith, B.

2015-12-01

In 2014, eight Department of Energy (DOE) national laboratories, four academic institutions, one company, and the National Centre for Atmospheric Research combined forces in a project called Accelerated Climate Modeling for Energy (ACME) with the goal to speed Earth system model development for climate and energy. Over the planned 10-year span, the project will conduct simulations and modeling on DOE's most powerful high-performance computing systems at Oak Ridge, Argonne, and Lawrence Berkeley Leadership Compute Facilities. A key component of the ACME project is the development of an interactive test bed for the advanced Earth system model. Its execution infrastructure will accelerate model development and testing cycles. The ACME Workflow Group is leading the efforts to automate labor-intensive tasks, provide intelligent support for complex tasks and reduce duplication of effort through collaboration support. As part of this new workflow environment, we have created a diagnostic, metric, and intercomparison Python framework, called UVCMetrics, to aid in the testing-to-production execution of the ACME model. The framework exploits similarities among different diagnostics to compactly support diagnosis of new models. It presently focuses on atmosphere and land but is designed to support ocean and sea ice model components as well. This framework is built on top of the existing open-source software framework known as the Ultrascale Visualization Climate Data Analysis Tools (UV-CDAT). Because of its flexible framework design, scientists and modelers now can generate thousands of possible diagnostic outputs. These diagnostics can compare model runs, compare model vs. observation, or simply verify a model is physically realistic. Additional diagnostics are easily integrated into the framework, and our users have already added several. Diagnostics can be generated, viewed, and manipulated from the UV-CDAT graphical user interface, Python command line scripts and programs, and web browsers. The framework is designed to be scalable to large datasets, yet easy to use and familiar to scientists using previous tools. Integration in the ACME overall user interface facilitates data publication, further analysis, and quick feedback to model developers and scientists making component or coupled model runs.

Inertial Motion-Tracking Technology for Virtual 3-D

NASA Technical Reports Server (NTRS)

2005-01-01

In the 1990s, NASA pioneered virtual reality research. The concept was present long before, but, prior to this, the technology did not exist to make a viable virtual reality system. Scientists had theories and ideas they knew that the concept had potential, but the computers of the 1970s and 1980s were not fast enough, sensors were heavy and cumbersome, and people had difficulty blending fluidly with the machines. Scientists at Ames Research Center built upon the research of previous decades and put the necessary technology behind them, making the theories of virtual reality a reality. Virtual reality systems depend on complex motion-tracking sensors to convey information between the user and the computer to give the user the feeling that he is operating in the real world. These motion-tracking sensors measure and report an object s position and orientation as it changes. A simple example of motion tracking would be the cursor on a computer screen moving in correspondence to the shifting of the mouse. Tracking in 3-D, necessary to create virtual reality, however, is much more complex. To be successful, the perspective of the virtual image seen on the computer must be an accurate representation of what is seen in the real world. As the user s head or camera moves, turns, or tilts, the computer-generated environment must change accordingly with no noticeable lag, jitter, or distortion. Historically, the lack of smooth and rapid tracking of the user s motion has thwarted the widespread use of immersive 3-D computer graphics. NASA uses virtual reality technology for a variety of purposes, mostly training of astronauts. The actual missions are costly and dangerous, so any opportunity the crews have to practice their maneuvering in accurate situations before the mission is valuable and instructive. For that purpose, NASA has funded a great deal of virtual reality research, and benefited from the results.

NUCLEAR ESPIONAGE: Report Details Spying on Touring Scientists.

PubMed

Malakoff, D

2000-06-30

A congressional report released this week details dozens of sometimes clumsy attempts by foreign agents to obtain nuclear secrets from U.S. nuclear scientists traveling abroad, ranging from offering scientists prostitutes to prying off the backs of their laptop computers. The report highlights the need to better prepare traveling researchers to safeguard secrets and resist such temptations, say the two lawmakers who requested the report and officials at the Department of Energy, which employs the scientists.

Keeping an Eye on the Prize

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

Hazi, A U

2007-02-06

Setting performance goals is part of the business plan for almost every company. The same is true in the world of supercomputers. Ten years ago, the Department of Energy (DOE) launched the Accelerated Strategic Computing Initiative (ASCI) to help ensure the safety and reliability of the nation's nuclear weapons stockpile without nuclear testing. ASCI, which is now called the Advanced Simulation and Computing (ASC) Program and is managed by DOE's National Nuclear Security Administration (NNSA), set an initial 10-year goal to obtain computers that could process up to 100 trillion floating-point operations per second (teraflops). Many computer experts thought themore » goal was overly ambitious, but the program's results have proved them wrong. Last November, a Livermore-IBM team received the 2005 Gordon Bell Prize for achieving more than 100 teraflops while modeling the pressure-induced solidification of molten metal. The prestigious prize, which is named for a founding father of supercomputing, is awarded each year at the Supercomputing Conference to innovators who advance high-performance computing. Recipients for the 2005 prize included six Livermore scientists--physicists Fred Streitz, James Glosli, and Mehul Patel and computer scientists Bor Chan, Robert Yates, and Bronis de Supinski--as well as IBM researchers James Sexton and John Gunnels. This team produced the first atomic-scale model of metal solidification from the liquid phase with results that were independent of system size. The record-setting calculation used Livermore's domain decomposition molecular-dynamics (ddcMD) code running on BlueGene/L, a supercomputer developed by IBM in partnership with the ASC Program. BlueGene/L reached 280.6 teraflops on the Linpack benchmark, the industry standard used to measure computing speed. As a result, it ranks first on the list of Top500 Supercomputer Sites released in November 2005. To evaluate the performance of nuclear weapons systems, scientists must understand how materials behave under extreme conditions. Because experiments at high pressures and temperatures are often difficult or impossible to conduct, scientists rely on computer models that have been validated with obtainable data. Of particular interest to weapons scientists is the solidification of metals. ''To predict the performance of aging nuclear weapons, we need detailed information on a material's phase transitions'', says Streitz, who leads the Livermore-IBM team. For example, scientists want to know what happens to a metal as it changes from molten liquid to a solid and how that transition affects the material's characteristics, such as its strength.« less

Assessment of USAFs Hiring Potential of Civilian Scientists and Engineers of the Millennial Generation

DTIC Science & Technology

2016-02-12

AIR WAR COLLEGE AIR UNIVERSITY ASSESSMENT OF USAF’S HIRING POTENTIAL OF CIVILIAN SCIENTISTS AND ENGINEERS OF THE MILLENNIAL GENERATION...government organizations. iv Abstract The Millennial Generation (individuals born 1981-2000) is entering the workforce in large numbers and...of Millennials and what they view as important in their work and social lives revealed policy approaches that could ensure the USAF maximizes it

IVAG: An Integrative Visualization Application for Various Types of Genomic Data Based on R-Shiny and the Docker Platform.

PubMed

Lee, Tae-Rim; Ahn, Jin Mo; Kim, Gyuhee; Kim, Sangsoo

2017-12-01

Next-generation sequencing (NGS) technology has become a trend in the genomics research area. There are many software programs and automated pipelines to analyze NGS data, which can ease the pain for traditional scientists who are not familiar with computer programming. However, downstream analyses, such as finding differentially expressed genes or visualizing linkage disequilibrium maps and genome-wide association study (GWAS) data, still remain a challenge. Here, we introduce a dockerized web application written in R using the Shiny platform to visualize pre-analyzed RNA sequencing and GWAS data. In addition, we have integrated a genome browser based on the JBrowse platform and an automated intermediate parsing process required for custom track construction, so that users can easily build and navigate their personal genome tracks with in-house datasets. This application will help scientists perform series of downstream analyses and obtain a more integrative understanding about various types of genomic data by interactively visualizing them with customizable options.

Final Report. Center for Scalable Application Development Software

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

Mellor-Crummey, John

2014-10-26

The Center for Scalable Application Development Software (CScADS) was established as a part- nership between Rice University, Argonne National Laboratory, University of California Berkeley, University of Tennessee – Knoxville, and University of Wisconsin – Madison. CScADS pursued an integrated set of activities with the aim of increasing the productivity of DOE computational scientists by catalyzing the development of systems software, libraries, compilers, and tools for leadership computing platforms. Principal Center activities were workshops to engage the research community in the challenges of leadership computing, research and development of open-source software, and work with computational scientists to help them develop codesmore » for leadership computing platforms. This final report summarizes CScADS activities at Rice University in these areas.« less

Characterization of real-time computers

NASA Technical Reports Server (NTRS)

Shin, K. G.; Krishna, C. M.

1984-01-01

A real-time system consists of a computer controller and controlled processes. Despite the synergistic relationship between these two components, they have been traditionally designed and analyzed independently of and separately from each other; namely, computer controllers by computer scientists/engineers and controlled processes by control scientists. As a remedy for this problem, in this report real-time computers are characterized by performance measures based on computer controller response time that are: (1) congruent to the real-time applications, (2) able to offer an objective comparison of rival computer systems, and (3) experimentally measurable/determinable. These measures, unlike others, provide the real-time computer controller with a natural link to controlled processes. In order to demonstrate their utility and power, these measures are first determined for example controlled processes on the basis of control performance functionals. They are then used for two important real-time multiprocessor design applications - the number-power tradeoff and fault-masking and synchronization.

IDEAL: Images Across Domains, Experiments, Algorithms and Learning

NASA Astrophysics Data System (ADS)

Ushizima, Daniela M.; Bale, Hrishikesh A.; Bethel, E. Wes; Ercius, Peter; Helms, Brett A.; Krishnan, Harinarayan; Grinberg, Lea T.; Haranczyk, Maciej; Macdowell, Alastair A.; Odziomek, Katarzyna; Parkinson, Dilworth Y.; Perciano, Talita; Ritchie, Robert O.; Yang, Chao

2016-11-01

Research across science domains is increasingly reliant on image-centric data. Software tools are in high demand to uncover relevant, but hidden, information in digital images, such as those coming from faster next generation high-throughput imaging platforms. The challenge is to analyze the data torrent generated by the advanced instruments efficiently, and provide insights such as measurements for decision-making. In this paper, we overview work performed by an interdisciplinary team of computational and materials scientists, aimed at designing software applications and coordinating research efforts connecting (1) emerging algorithms for dealing with large and complex datasets; (2) data analysis methods with emphasis in pattern recognition and machine learning; and (3) advances in evolving computer architectures. Engineering tools around these efforts accelerate the analyses of image-based recordings, improve reusability and reproducibility, scale scientific procedures by reducing time between experiments, increase efficiency, and open opportunities for more users of the imaging facilities. This paper describes our algorithms and software tools, showing results across image scales, demonstrating how our framework plays a role in improving image understanding for quality control of existent materials and discovery of new compounds.

RNA-Seq Analysis to Measure the Expression of SINE Retroelements.

PubMed

Román, Ángel Carlos; Morales-Hernández, Antonio; Fernández-Salguero, Pedro M

2016-01-01

The intrinsic features of retroelements, like their repetitive nature and disseminated presence in their host genomes, demand the use of advanced methodologies for their bioinformatic and functional study. The short length of SINE (short interspersed elements) retrotransposons makes such analyses even more complex. Next-generation sequencing (NGS) technologies are currently one of the most widely used tools to characterize the whole repertoire of gene expression in a specific tissue. In this chapter, we will review the molecular and computational methods needed to perform NGS analyses on SINE elements. We will also describe new methods of potential interest for researchers studying repetitive elements. We intend to outline the general ideas behind the computational analyses of NGS data obtained from SINE elements, and to stimulate other scientists to expand our current knowledge on SINE biology using RNA-seq and other NGS tools.

Active Storage with Analytics Capabilities and I/O Runtime System for Petascale Systems

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

Choudhary, Alok

Computational scientists must understand results from experimental, observational and computational simulation generated data to gain insights and perform knowledge discovery. As systems approach the petascale range, problems that were unimaginable a few years ago are within reach. With the increasing volume and complexity of data produced by ultra-scale simulations and high-throughput experiments, understanding the science is largely hampered by the lack of comprehensive I/O, storage, acceleration of data manipulation, analysis, and mining tools. Scientists require techniques, tools and infrastructure to facilitate better understanding of their data, in particular the ability to effectively perform complex data analysis, statistical analysis and knowledgemore » discovery. The goal of this work is to enable more effective analysis of scientific datasets through the integration of enhancements in the I/O stack, from active storage support at the file system layer to MPI-IO and high-level I/O library layers. We propose to provide software components to accelerate data analytics, mining, I/O, and knowledge discovery for large-scale scientific applications, thereby increasing productivity of both scientists and the systems. Our approaches include 1) design the interfaces in high-level I/O libraries, such as parallel netCDF, for applications to activate data mining operations at the lower I/O layers; 2) Enhance MPI-IO runtime systems to incorporate the functionality developed as a part of the runtime system design; 3) Develop parallel data mining programs as part of runtime library for server-side file system in PVFS file system; and 4) Prototype an active storage cluster, which will utilize multicore CPUs, GPUs, and FPGAs to carry out the data mining workload.« less

Computer analysis of digital sky surveys using citizen science and manual classification

NASA Astrophysics Data System (ADS)

Kuminski, Evan; Shamir, Lior

2015-01-01

As current and future digital sky surveys such as SDSS, LSST, DES, Pan-STARRS and Gaia create increasingly massive databases containing millions of galaxies, there is a growing need to be able to efficiently analyze these data. An effective way to do this is through manual analysis, however, this may be insufficient considering the extremely vast pipelines of astronomical images generated by the present and future surveys. Some efforts have been made to use citizen science to classify galaxies by their morphology on a larger scale than individual or small groups of scientists can. While these citizen science efforts such as Zooniverse have helped obtain reasonably accurate morphological information about large numbers of galaxies, they cannot scale to provide complete analysis of billions of galaxy images that will be collected by future ventures such as LSST. Since current forms of manual classification cannot scale to the masses of data collected by digital sky surveys, it is clear that in order to keep up with the growing databases some form of automation of the data analysis will be required, and will work either independently or in combination with human analysis such as citizen science. Here we describe a computer vision method that can automatically analyze galaxy images and deduce galaxy morphology. Experiments using Galaxy Zoo 2 data show that the performance of the method increases as the degree of agreement between the citizen scientists gets higher, providing a cleaner dataset. For several morphological features, such as the spirality of the galaxy, the algorithm agreed with the citizen scientists on around 95% of the samples. However, the method failed to analyze some of the morphological features such as the number of spiral arms, and provided accuracy of just ~36%.

The Fermilab Connection

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

Fermilab

More than 4,000 scientists in 53 countries use Fermilab and its particle accelerators, detectors and computers for their research. That includes about 2,500 scientists from 223 U.S. institutions in 42 states, plus the District of Columbia and Puerto Rico.

EarthCube: A Community-Driven Cyberinfrastructure for the Geosciences

NASA Astrophysics Data System (ADS)

Koskela, Rebecca; Ramamurthy, Mohan; Pearlman, Jay; Lehnert, Kerstin; Ahern, Tim; Fredericks, Janet; Goring, Simon; Peckham, Scott; Powers, Lindsay; Kamalabdi, Farzad; Rubin, Ken; Yarmey, Lynn

2017-04-01

EarthCube is creating a dynamic, System of Systems (SoS) infrastructure and data tools to collect, access, analyze, share, and visualize all forms of geoscience data and resources, using advanced collaboration, technological, and computational capabilities. EarthCube, as a joint effort between the U.S. National Science Foundation Directorate for Geosciences and the Division of Advanced Cyberinfrastructure, is a quickly growing community of scientists across all geoscience domains, as well as geoinformatics researchers and data scientists. EarthCube has attracted an evolving, dynamic virtual community of more than 2,500 contributors, including earth, ocean, polar, planetary, atmospheric, geospace, computer and social scientists, educators, and data and information professionals. During 2017, EarthCube will transition to the implementation phase. The implementation will balance "innovation" and "production" to advance cross-disciplinary science goals as well as the development of future data scientists. This presentation will describe the current architecture design for the EarthCube cyberinfrastructure and implementation plan.

A Collaborative Extensible User Environment for Simulation and Knowledge Management

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

Freedman, Vicky L.; Lansing, Carina S.; Porter, Ellen A.

2015-06-01

In scientific simulation, scientists use measured data to create numerical models, execute simulations and analyze results from advanced simulators executing on high performance computing platforms. This process usually requires a team of scientists collaborating on data collection, model creation and analysis, and on authorship of publications and data. This paper shows that scientific teams can benefit from a user environment called Akuna that permits subsurface scientists in disparate locations to collaborate on numerical modeling and analysis projects. The Akuna user environment is built on the Velo framework that provides both a rich client environment for conducting and analyzing simulations andmore » a Web environment for data sharing and annotation. Akuna is an extensible toolset that integrates with Velo, and is designed to support any type of simulator. This is achieved through data-driven user interface generation, use of a customizable knowledge management platform, and an extensible framework for simulation execution, monitoring and analysis. This paper describes how the customized Velo content management system and the Akuna toolset are used to integrate and enhance an effective collaborative research and application environment. The extensible architecture of Akuna is also described and demonstrates its usage for creation and execution of a 3D subsurface simulation.« less

Instrumentino: An Open-Source Software for Scientific Instruments.

PubMed

Koenka, Israel Joel; Sáiz, Jorge; Hauser, Peter C

2015-01-01

Scientists often need to build dedicated computer-controlled experimental systems. For this purpose, it is becoming common to employ open-source microcontroller platforms, such as the Arduino. These boards and associated integrated software development environments provide affordable yet powerful solutions for the implementation of hardware control of transducers and acquisition of signals from detectors and sensors. It is, however, a challenge to write programs that allow interactive use of such arrangements from a personal computer. This task is particularly complex if some of the included hardware components are connected directly to the computer and not via the microcontroller. A graphical user interface framework, Instrumentino, was therefore developed to allow the creation of control programs for complex systems with minimal programming effort. By writing a single code file, a powerful custom user interface is generated, which enables the automatic running of elaborate operation sequences and observation of acquired experimental data in real time. The framework, which is written in Python, allows extension by users, and is made available as an open source project.

Streaming Support for Data Intensive Cloud-Based Sequence Analysis

PubMed Central

Issa, Shadi A.; Kienzler, Romeo; El-Kalioby, Mohamed; Tonellato, Peter J.; Wall, Dennis; Bruggmann, Rémy; Abouelhoda, Mohamed

2013-01-01

Cloud computing provides a promising solution to the genomics data deluge problem resulting from the advent of next-generation sequencing (NGS) technology. Based on the concepts of “resources-on-demand” and “pay-as-you-go”, scientists with no or limited infrastructure can have access to scalable and cost-effective computational resources. However, the large size of NGS data causes a significant data transfer latency from the client's site to the cloud, which presents a bottleneck for using cloud computing services. In this paper, we provide a streaming-based scheme to overcome this problem, where the NGS data is processed while being transferred to the cloud. Our scheme targets the wide class of NGS data analysis tasks, where the NGS sequences can be processed independently from one another. We also provide the elastream package that supports the use of this scheme with individual analysis programs or with workflow systems. Experiments presented in this paper show that our solution mitigates the effect of data transfer latency and saves both time and cost of computation. PMID:23710461

Computational biology and bioinformatics in Nigeria.

PubMed

Fatumo, Segun A; Adoga, Moses P; Ojo, Opeolu O; Oluwagbemi, Olugbenga; Adeoye, Tolulope; Ewejobi, Itunuoluwa; Adebiyi, Marion; Adebiyi, Ezekiel; Bewaji, Clement; Nashiru, Oyekanmi

2014-04-01

Over the past few decades, major advances in the field of molecular biology, coupled with advances in genomic technologies, have led to an explosive growth in the biological data generated by the scientific community. The critical need to process and analyze such a deluge of data and turn it into useful knowledge has caused bioinformatics to gain prominence and importance. Bioinformatics is an interdisciplinary research area that applies techniques, methodologies, and tools in computer and information science to solve biological problems. In Nigeria, bioinformatics has recently played a vital role in the advancement of biological sciences. As a developing country, the importance of bioinformatics is rapidly gaining acceptance, and bioinformatics groups comprised of biologists, computer scientists, and computer engineers are being constituted at Nigerian universities and research institutes. In this article, we present an overview of bioinformatics education and research in Nigeria. We also discuss professional societies and academic and research institutions that play central roles in advancing the discipline in Nigeria. Finally, we propose strategies that can bolster bioinformatics education and support from policy makers in Nigeria, with potential positive implications for other developing countries.

Computational Biology and Bioinformatics in Nigeria

PubMed Central

Fatumo, Segun A.; Adoga, Moses P.; Ojo, Opeolu O.; Oluwagbemi, Olugbenga; Adeoye, Tolulope; Ewejobi, Itunuoluwa; Adebiyi, Marion; Adebiyi, Ezekiel; Bewaji, Clement; Nashiru, Oyekanmi

2014-01-01

Over the past few decades, major advances in the field of molecular biology, coupled with advances in genomic technologies, have led to an explosive growth in the biological data generated by the scientific community. The critical need to process and analyze such a deluge of data and turn it into useful knowledge has caused bioinformatics to gain prominence and importance. Bioinformatics is an interdisciplinary research area that applies techniques, methodologies, and tools in computer and information science to solve biological problems. In Nigeria, bioinformatics has recently played a vital role in the advancement of biological sciences. As a developing country, the importance of bioinformatics is rapidly gaining acceptance, and bioinformatics groups comprised of biologists, computer scientists, and computer engineers are being constituted at Nigerian universities and research institutes. In this article, we present an overview of bioinformatics education and research in Nigeria. We also discuss professional societies and academic and research institutions that play central roles in advancing the discipline in Nigeria. Finally, we propose strategies that can bolster bioinformatics education and support from policy makers in Nigeria, with potential positive implications for other developing countries. PMID:24763310

Volunteer Clouds and Citizen Cyberscience for LHC Physics

NASA Astrophysics Data System (ADS)

Aguado Sanchez, Carlos; Blomer, Jakob; Buncic, Predrag; Chen, Gang; Ellis, John; Garcia Quintas, David; Harutyunyan, Artem; Grey, Francois; Lombrana Gonzalez, Daniel; Marquina, Miguel; Mato, Pere; Rantala, Jarno; Schulz, Holger; Segal, Ben; Sharma, Archana; Skands, Peter; Weir, David; Wu, Jie; Wu, Wenjing; Yadav, Rohit

2011-12-01

Computing for the LHC, and for HEP more generally, is traditionally viewed as requiring specialized infrastructure and software environments, and therefore not compatible with the recent trend in "volunteer computing", where volunteers supply free processing time on ordinary PCs and laptops via standard Internet connections. In this paper, we demonstrate that with the use of virtual machine technology, at least some standard LHC computing tasks can be tackled with volunteer computing resources. Specifically, by presenting volunteer computing resources to HEP scientists as a "volunteer cloud", essentially identical to a Grid or dedicated cluster from a job submission perspective, LHC simulations can be processed effectively. This article outlines both the technical steps required for such a solution and the implications for LHC computing as well as for LHC public outreach and for participation by scientists from developing regions in LHC research.

Computer-based communication in support of scientific and technical work. [conferences on management information systems used by scientists of NASA programs

NASA Technical Reports Server (NTRS)

Vallee, J.; Wilson, T.

1976-01-01

Results are reported of the first experiments for a computer conference management information system at the National Aeronautics and Space Administration. Between August 1975 and March 1976, two NASA projects with geographically separated participants (NASA scientists) used the PLANET computer conferencing system for portions of their work. The first project was a technology assessment of future transportation systems. The second project involved experiments with the Communication Technology Satellite. As part of this project, pre- and postlaunch operations were discussed in a computer conference. These conferences also provided the context for an analysis of the cost of computer conferencing. In particular, six cost components were identified: (1) terminal equipment, (2) communication with a network port, (3) network connection, (4) computer utilization, (5) data storage and (6) administrative overhead.

Know Your Discipline: Teaching the Philosophy of Computer Science

ERIC Educational Resources Information Center

Tedre, Matti

2007-01-01

The diversity and interdisciplinarity of computer science and the multiplicity of its uses in other sciences make it hard to define computer science and to prescribe how computer science should be carried out. The diversity of computer science also causes friction between computer scientists from different branches. Computer science curricula, as…

Field Instrumentation With Bricks: Wireless Networks Built From Tough, Cheap, Reliable Field Computers

NASA Astrophysics Data System (ADS)

Fatland, D. R.; Anandakrishnan, S.; Heavner, M.

2004-12-01

We describe tough, cheap, reliable field computers configured as wireless networks for distributed high-volume data acquisition and low-cost data recovery. Running under the GNU/Linux open source model these network nodes ('Bricks') are intended for either autonomous or managed deployment for many months in harsh Arctic conditions. We present here results from Generation-1 Bricks used in 2004 for glacier seismology research in Alaska and Antarctica and describe future generation Bricks in terms of core capabilities and a growing list of field applications. Subsequent generations of Bricks will feature low-power embedded architecture, large data storage capacity (GB), long range telemetry (15 km+ up from 3 km currently), and robust operational software. The list of Brick applications is growing to include Geodetic GPS, Bioacoustics (bats to whales), volcano seismicity, tracking marine fauna, ice sounding via distributed microwave receivers and more. This NASA-supported STTR project capitalizes on advancing computer/wireless technology to get scientists more data per research budget dollar, solving system integration problems and thereby getting researchers out of the hardware lab and into the field. One exemplary scenario: An investigator can install a Brick network in a remote polar environment to collect data for several months and then fly over the site to recover the data via wireless telemetry. In the past year Brick networks have moved beyond proof-of-concept to the full-bore development and testing stage; they will be a mature and powerful tool available for IPY 2007-8.

Boom. Bust. Build.

ERIC Educational Resources Information Center

Kite, Vance; Park, Soonhye

2018-01-01

In 2006 Jeanette Wing, a professor of computer science at Carnegie Mellon University, proposed computational thinking (CT) as a literacy just as important as reading, writing, and mathematics. Wing defined CT as a set of skills and strategies computer scientists use to solve complex, computational problems (Wing 2006). The computer science and…

Workforce Retention Study in Support of the U.S. Army Aberdeen Test Center Human Capital Management Strategy

DTIC Science & Technology

2016-09-01

Sciences Group 6% 1550s Computer Scientists Group 5% Other 1500s ORSAa, Mathematics, & Statistics Group 3% 1600s Equipment & Facilities Group 4...Employee removal based on misconduct, delinquency , suitability, unsatisfactory performance, or failure to qualify for conversion to a career appointment...average of 10.4% in many areas, but over double the average for the 1550s (Computer Scientists) and other 1500s (ORSA, Mathematics, and Statistics ). Also

Research Institute for Advanced Computer Science: Annual Report October 1998 through September 1999

NASA Technical Reports Server (NTRS)

Leiner, Barry M.; Gross, Anthony R. (Technical Monitor)

1999-01-01

The Research Institute for Advanced Computer Science (RIACS) carries out basic research and technology development in computer science, in support of the National Aeronautics and Space Administration's missions. RIACS is located at the NASA Ames Research Center (ARC). It currently operates under a multiple year grant/cooperative agreement that began on October 1, 1997 and is up for renewal in the year 2002. ARC has been designated NASA's Center of Excellence in Information Technology. In this capacity, ARC is charged with the responsibility to build an Information Technology Research Program that is preeminent within NASA. RIACS serves as a bridge between NASA ARC and the academic community, and RIACS scientists and visitors work in close collaboration with NASA scientists. RIACS has the additional goal of broadening the base of researchers in these areas of importance to the nation's space and aeronautics enterprises. RIACS research focuses on the three cornerstones of information technology research necessary to meet the future challenges of NASA missions: (1) Automated Reasoning for Autonomous Systems. Techniques are being developed enabling spacecraft that will be self-guiding and self-correcting to the extent that they will require little or no human intervention. Such craft will be equipped to independently solve problems as they arise, and fulfill their missions with minimum direction from Earth. (2) Human-Centered Computing. Many NASA missions require synergy between humans and computers, with sophisticated computational aids amplifying human cognitive and perceptual abilities; (3) High Performance Computing and Networking Advances in the performance of computing and networking continue to have major impact on a variety of NASA endeavors, ranging from modeling and simulation to data analysis of large datasets to collaborative engineering, planning and execution. In addition, RIACS collaborates with NASA scientists to apply information technology research to a variety of NASA application domains. RIACS also engages in other activities, such as workshops, seminars, and visiting scientist programs, designed to encourage and facilitate collaboration between the university and NASA information technology research communities.

Research Institute for Advanced Computer Science

NASA Technical Reports Server (NTRS)

Gross, Anthony R. (Technical Monitor); Leiner, Barry M.

2000-01-01

The Research Institute for Advanced Computer Science (RIACS) carries out basic research and technology development in computer science, in support of the National Aeronautics and Space Administration's missions. RIACS is located at the NASA Ames Research Center. It currently operates under a multiple year grant/cooperative agreement that began on October 1, 1997 and is up for renewal in the year 2002. Ames has been designated NASA's Center of Excellence in Information Technology. In this capacity, Ames is charged with the responsibility to build an Information Technology Research Program that is preeminent within NASA. RIACS serves as a bridge between NASA Ames and the academic community, and RIACS scientists and visitors work in close collaboration with NASA scientists. RIACS has the additional goal of broadening the base of researchers in these areas of importance to the nation's space and aeronautics enterprises. RIACS research focuses on the three cornerstones of information technology research necessary to meet the future challenges of NASA missions: (1) Automated Reasoning for Autonomous Systems. Techniques are being developed enabling spacecraft that will be self-guiding and self-correcting to the extent that they will require little or no human intervention. Such craft will be equipped to independently solve problems as they arise, and fulfill their missions with minimum direction from Earth; (2) Human-Centered Computing. Many NASA missions require synergy between humans and computers, with sophisticated computational aids amplifying human cognitive and perceptual abilities; (3) High Performance Computing and Networking. Advances in the performance of computing and networking continue to have major impact on a variety of NASA endeavors, ranging from modeling and simulation to data analysis of large datasets to collaborative engineering, planning and execution. In addition, RIACS collaborates with NASA scientists to apply information technology research to a variety of NASA application domains. RIACS also engages in other activities, such as workshops, seminars, and visiting scientist programs, designed to encourage and facilitate collaboration between the university and NASA information technology research communities.

Public Outreach at RAL: Engaging the Next Generation of Scientists and Engineers

NASA Astrophysics Data System (ADS)

Corbett, G.; Ryall, G.; Palmer, S.; Collier, I. P.; Adams, J.; Appleyard, R.

2015-12-01

The Rutherford Appleton Laboratory (RAL) is part of the UK's Science and Technology Facilities Council (STFC). As part of the Royal Charter that established the STFC, the organisation is required to generate public awareness and encourage public engagement and dialogue in relation to the science undertaken. The staff at RAL firmly support this activity as it is important to encourage the next generation of students to consider studying Science, Technology, Engineering, and Mathematics (STEM) subjects, providing the UK with a highly skilled work-force in the future. To this end, the STFC undertakes a variety of outreach activities. This paper will describe the outreach activities undertaken by RAL, particularly focussing on those of the Scientific Computing Department (SCD). These activities include: an Arduino based activity day for 12-14 year-olds to celebrate Ada Lovelace day; running a centre as part of the Young Rewired State - encouraging 11-18 year-olds to create web applications with open data; sponsoring a team in the Engineering Education Scheme - supporting a small team of 16-17 year-olds to solve a real world engineering problem; as well as the more traditional tours of facilities. These activities could serve as an example for other sites involved in scientific computing around the globe.

I'm a Scientist, Get Me out of Here! (Australia)

ERIC Educational Resources Information Center

Teaching Science, 2012

2012-01-01

The May event of I'm a Scientist, Get Me Out of Here! harnessed fifteen scientists in three general zones, engaging almost 800 students from twenty two schools across the country, generating 624 answered questions, 406 comments and fifty three live-chat sessions. (Contains 4 photos.)

GeoBrain Computational Cyber-laboratory for Earth Science Studies

NASA Astrophysics Data System (ADS)

Deng, M.; di, L.

2009-12-01

Computational approaches (e.g., computer-based data visualization, analysis and modeling) are critical for conducting increasingly data-intensive Earth science (ES) studies to understand functions and changes of the Earth system. However, currently Earth scientists, educators, and students have met two major barriers that prevent them from being effectively using computational approaches in their learning, research and application activities. The two barriers are: 1) difficulties in finding, obtaining, and using multi-source ES data; and 2) lack of analytic functions and computing resources (e.g., analysis software, computing models, and high performance computing systems) to analyze the data. Taking advantages of recent advances in cyberinfrastructure, Web service, and geospatial interoperability technologies, GeoBrain, a project funded by NASA, has developed a prototype computational cyber-laboratory to effectively remove the two barriers. The cyber-laboratory makes ES data and computational resources at large organizations in distributed locations available to and easily usable by the Earth science community through 1) enabling seamless discovery, access and retrieval of distributed data, 2) federating and enhancing data discovery with a catalogue federation service and a semantically-augmented catalogue service, 3) customizing data access and retrieval at user request with interoperable, personalized, and on-demand data access and services, 4) automating or semi-automating multi-source geospatial data integration, 5) developing a large number of analytic functions as value-added, interoperable, and dynamically chainable geospatial Web services and deploying them in high-performance computing facilities, 6) enabling the online geospatial process modeling and execution, and 7) building a user-friendly extensible web portal for users to access the cyber-laboratory resources. Users can interactively discover the needed data and perform on-demand data analysis and modeling through the web portal. The GeoBrain cyber-laboratory provides solutions to meet common needs of ES research and education, such as, distributed data access and analysis services, easy access to and use of ES data, and enhanced geoprocessing and geospatial modeling capability. It greatly facilitates ES research, education, and applications. The development of the cyber-laboratory provides insights, lessons-learned, and technology readiness to build more capable computing infrastructure for ES studies, which can meet wide-range needs of current and future generations of scientists, researchers, educators, and students for their formal or informal educational training, research projects, career development, and lifelong learning.

Integrated Hardware and Software for No-Loss Computing

NASA Technical Reports Server (NTRS)

James, Mark

2007-01-01

When an algorithm is distributed across multiple threads executing on many distinct processors, a loss of one of those threads or processors can potentially result in the total loss of all the incremental results up to that point. When implementation is massively hardware distributed, then the probability of a hardware failure during the course of a long execution is potentially high. Traditionally, this problem has been addressed by establishing checkpoints where the current state of some or part of the execution is saved. Then in the event of a failure, this state information can be used to recompute that point in the execution and resume the computation from that point. A serious problem arises when one distributes a problem across multiple threads and physical processors is that one increases the likelihood of the algorithm failing due to no fault of the scientist but as a result of hardware faults coupled with operating system problems. With good reason, scientists expect their computing tools to serve them and not the other way around. What is novel here is a unique combination of hardware and software that reformulates an application into monolithic structure that can be monitored in real-time and dynamically reconfigured in the event of a failure. This unique reformulation of hardware and software will provide advanced aeronautical technologies to meet the challenges of next-generation systems in aviation, for civilian and scientific purposes, in our atmosphere and in atmospheres of other worlds. In particular, with respect to NASA s manned flight to Mars, this technology addresses the critical requirements for improving safety and increasing reliability of manned spacecraft.

Simulation Data as Data Streams

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

Abdulla, G; Arrighi, W; Critchlow, T

2003-11-18

Computational or scientific simulations are increasingly being applied to solve a variety of scientific problems. Domains such as astrophysics, engineering, chemistry, biology, and environmental studies are benefiting from this important capability. Simulations, however, produce enormous amounts of data that need to be analyzed and understood. In this overview paper, we describe scientific simulation data, its characteristics, and the way scientists generate and use the data. We then compare and contrast simulation data to data streams. Finally, we describe our approach to analyzing simulation data, present the AQSim (Ad-hoc Queries for Simulation data) system, and discuss some of the challenges thatmore » result from handling this kind of data.« less

Recent Advances and Issues in Computers. Oryx Frontiers of Science Series.

ERIC Educational Resources Information Center

Gay, Martin K.

Discussing recent issues in computer science, this book contains 11 chapters covering: (1) developments that have the potential for changing the way computers operate, including microprocessors, mass storage systems, and computing environments; (2) the national computational grid for high-bandwidth, high-speed collaboration among scientists, and…

Developing the Next Generation of Science Data System Engineers

NASA Technical Reports Server (NTRS)

Moses, John F.; Behnke, Jeanne; Durachka, Christopher D.

2016-01-01

At Goddard, engineers and scientists with a range of experience in science data systems are needed to employ new technologies and develop advances in capabilities for supporting new Earth and Space science research. Engineers with extensive experience in science data, software engineering and computer-information architectures are needed to lead and perform these activities. The increasing types and complexity of instrument data and emerging computer technologies coupled with the current shortage of computer engineers with backgrounds in science has led the need to develop a career path for science data systems engineers and architects.The current career path, in which undergraduate students studying various disciplines such as Computer Engineering or Physical Scientist, generally begins with serving on a development team in any of the disciplines where they can work in depth on existing Goddard data systems or serve with a specific NASA science team. There they begin to understand the data, infuse technologies, and begin to know the architectures of science data systems. From here the typical career involves peermentoring, on-the-job training or graduate level studies in analytics, computational science and applied science and mathematics. At the most senior level, engineers become subject matter experts and system architect experts, leading discipline-specific data centers and large software development projects. They are recognized as a subject matter expert in a science domain, they have project management expertise, lead standards efforts and lead international projects. A long career development remains necessary not only because of the breadth of knowledge required across physical sciences and engineering disciplines, but also because of the diversity of instrument data being developed today both by NASA and international partner agencies and because multidiscipline science and practitioner communities expect to have access to all types of observational data.This paper describes an approach to defining career-path guidance for college-bound high school and undergraduate engineering students, junior and senior engineers from various disciplines.

Developing the Next Generation of Science Data System Engineers

NASA Astrophysics Data System (ADS)

Moses, J. F.; Durachka, C. D.; Behnke, J.

2015-12-01

At Goddard, engineers and scientists with a range of experience in science data systems are needed to employ new technologies and develop advances in capabilities for supporting new Earth and Space science research. Engineers with extensive experience in science data, software engineering and computer-information architectures are needed to lead and perform these activities. The increasing types and complexity of instrument data and emerging computer technologies coupled with the current shortage of computer engineers with backgrounds in science has led the need to develop a career path for science data systems engineers and architects. The current career path, in which undergraduate students studying various disciplines such as Computer Engineering or Physical Scientist, generally begins with serving on a development team in any of the disciplines where they can work in depth on existing Goddard data systems or serve with a specific NASA science team. There they begin to understand the data, infuse technologies, and begin to know the architectures of science data systems. From here the typical career involves peer mentoring, on-the-job training or graduate level studies in analytics, computational science and applied science and mathematics. At the most senior level, engineers become subject matter experts and system architect experts, leading discipline-specific data centers and large software development projects. They are recognized as a subject matter expert in a science domain, they have project management expertise, lead standards efforts and lead international projects. A long career development remains necessary not only because of the breath of knowledge required across physical sciences and engineering disciplines, but also because of the diversity of instrument data being developed today both by NASA and international partner agencies and because multi-discipline science and practitioner communities expect to have access to all types of observational data. This paper describes an approach to defining career-path guidance for college-bound high school and undergraduate engineering students, junior and senior engineers from various disciplines.

Electronic Ecosystem.

ERIC Educational Resources Information Center

Travis, John

1991-01-01

A discipline in which scientists seek to simulate and synthesize lifelike behaviors within computers, chemical mixtures, and other media is discussed. A computer program with self-replicating digital "organisms" that evolve as they compete for computer time and memory is described. (KR)

Developing an online programme in computational biology.

PubMed

Vincent, Heather M; Page, Christopher

2013-11-01

Much has been written about the need for continuing education and training to enable life scientists and computer scientists to manage and exploit the different types of biological data now becoming available. Here we describe the development of an online programme that combines short training courses, so that those who require an educational programme can progress to complete a formal qualification. Although this flexible approach fits the needs of course participants, it does not fit easily within the organizational structures of a campus-based university.

Cloud-Scale Genomic Signals Processing for Robust Large-Scale Cancer Genomic Microarray Data Analysis.

PubMed

Harvey, Benjamin Simeon; Ji, Soo-Yeon

2017-01-01

As microarray data available to scientists continues to increase in size and complexity, it has become overwhelmingly important to find multiple ways to bring forth oncological inference to the bioinformatics community through the analysis of large-scale cancer genomic (LSCG) DNA and mRNA microarray data that is useful to scientists. Though there have been many attempts to elucidate the issue of bringing forth biological interpretation by means of wavelet preprocessing and classification, there has not been a research effort that focuses on a cloud-scale distributed parallel (CSDP) separable 1-D wavelet decomposition technique for denoising through differential expression thresholding and classification of LSCG microarray data. This research presents a novel methodology that utilizes a CSDP separable 1-D method for wavelet-based transformation in order to initialize a threshold which will retain significantly expressed genes through the denoising process for robust classification of cancer patients. Additionally, the overall study was implemented and encompassed within CSDP environment. The utilization of cloud computing and wavelet-based thresholding for denoising was used for the classification of samples within the Global Cancer Map, Cancer Cell Line Encyclopedia, and The Cancer Genome Atlas. The results proved that separable 1-D parallel distributed wavelet denoising in the cloud and differential expression thresholding increased the computational performance and enabled the generation of higher quality LSCG microarray datasets, which led to more accurate classification results.

System biology of gene regulation.

PubMed

Baitaluk, Michael

2009-01-01

A famous joke story that exhibits the traditionally awkward alliance between theory and experiment and showing the differences between experimental biologists and theoretical modelers is when a University sends a biologist, a mathematician, a physicist, and a computer scientist to a walking trip in an attempt to stimulate interdisciplinary research. During a break, they watch a cow in a field nearby and the leader of the group asks, "I wonder how one could decide on the size of a cow?" Since a cow is a biological object, the biologist responded first: "I have seen many cows in this area and know it is a big cow." The mathematician argued, "The true volume is determined by integrating the mathematical function that describes the outer surface of the cow's body." The physicist suggested: "Let's assume the cow is a sphere...." Finally the computer scientist became nervous and said that he didn't bring his computer because there is no Internet connection up there on the hill. In this humorous but explanatory story suggestions proposed by theorists can be taken to reflect the view of many experimental biologists that computer scientists and theorists are too far removed from biological reality and therefore their theories and approaches are not of much immediate usefulness. Conversely, the statement of the biologist mirrors the view of many traditional theoretical and computational scientists that biological experiments are for the most part simply descriptive, lack rigor, and that much of the resulting biological data are of questionable functional relevance. One of the goals of current biology as a multidisciplinary science is to bring people from different scientific areas together on the same "hill" and teach them to speak the same "language." In fact, of course, when presenting their data, most experimentalist biologists do provide an interpretation and explanation for the results, and many theorists/computer scientists aim to answer (or at least to fully describe) questions of biological relevance. Thus systems biology could be treated as such a socioscientific phenomenon and a new approach to both experiments and theory that is defined by the strategy of pursuing integration of complex data about the interactions in biological systems from diverse experimental sources using interdisciplinary tools and personnel.

Science & Technology Review June 2012

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

Poyneer, L A

2012-04-20

This month's issue has the following articles: (1) A New Era in Climate System Analysis - Commentary by William H. Goldstein; (2) Seeking Clues to Climate Change - By comparing past climate records with results from computer simulations, Livermore scientists can better understand why Earth's climate has changed and how it might change in the future; (3) Finding and Fixing a Supercomputer's Faults - Livermore experts have developed innovative methods to detect hardware faults in supercomputers and help applications recover from errors that do occur; (4) Targeting Ignition - Enhancements to the cryogenic targets for National Ignition Facility experiments aremore » furthering work to achieve fusion ignition with energy gain; (5) Neural Implants Come of Age - A new generation of fully implantable, biocompatible neural prosthetics offers hope to patients with neurological impairment; and (6) Incubator Busy Growing Energy Technologies - Six collaborations with industrial partners are using the Laboratory's high-performance computing resources to find solutions to urgent energy-related problems.« less

Airborne laser scanning for high-resolution mapping of Antarctica

NASA Astrophysics Data System (ADS)

Csatho, Bea; Schenk, Toni; Krabill, William; Wilson, Terry; Lyons, William; McKenzie, Garry; Hallam, Cheryl; Manizade, Serdar; Paulsen, Timothy

In order to evaluate the potential of airborne laser scanning for topographic mapping in Antarctica and to establish calibration/validation sites for NASA's Ice, Cloud and land Elevation Satellite (ICESat) altimeter mission, NASA, the U.S. National Science Foundation (NSF), and the U.S. Geological Survey (USGS) joined forces to collect high-resolution airborne laser scanning data.In a two-week campaign during the 2001-2002 austral summer, NASA's Airborne Topographic Mapper (ATM) system was used to collect data over several sites in the McMurdo Sound area of Antarctica (Figure 1a). From the recorded signals, NASA computed laser points and The Ohio State University (OSU) completed the elaborate computation/verification of high-resolution Digital Elevation Models (DEMs) in 2003. This article reports about the DEM generation and some exemplary results from scientists using the geomorphologic information from the DEMs during the 2003-2004 field season.

Drawing the PDB: Protein-Ligand Complexes in Two Dimensions.

PubMed

Stierand, Katrin; Rarey, Matthias

2010-12-09

The two-dimensional representation of molecules is a popular communication medium in chemistry and the associated scientific fields. Computational methods for drawing small molecules with and without manual investigation are well-established and widely spread in terms of numerous software tools. Concerning the planar depiction of molecular complexes, there is considerably less choice. We developed the software PoseView, which automatically generates two-dimensional diagrams of macromolecular complexes, showing the ligand, the interactions, and the interacting residues. All depicted molecules are drawn on an atomic level as structure diagrams; thus, the output plots are clearly structured and easily readable for the scientist. We tested the performance of PoseView in a large-scale application on nearly all druglike complexes of the PDB (approximately 200000 complexes); for more than 92% of the complexes considered for drawing, a layout could be computed. In the following, we will present the results of this application study.

The Virtual Pelvic Floor, a tele-immersive educational environment.

PubMed Central

Pearl, R. K.; Evenhouse, R.; Rasmussen, M.; Dech, F.; Silverstein, J. C.; Prokasy, S.; Panko, W. B.

1999-01-01

This paper describes the development of the Virtual Pelvic Floor, a new method of teaching the complex anatomy of the pelvic region utilizing virtual reality and advanced networking technology. Virtual reality technology allows improved visualization of three-dimensional structures over conventional media because it supports stereo vision, viewer-centered perspective, large angles of view, and interactivity. Two or more ImmersaDesk systems, drafting table format virtual reality displays, are networked together providing an environment where teacher and students share a high quality three-dimensional anatomical model, and are able to converse, see each other, and to point in three dimensions to indicate areas of interest. This project was realized by the teamwork of surgeons, medical artists and sculptors, computer scientists, and computer visualization experts. It demonstrates the future of virtual reality for surgical education and applications for the Next Generation Internet. Images Figure 1 Figure 2 Figure 3 PMID:10566378

The next scientific revolution.

PubMed

Hey, Tony

2010-11-01

For decades, computer scientists have tried to teach computers to think like human experts. Until recently, most of those efforts have failed to come close to generating the creative insights and solutions that seem to come naturally to the best researchers, doctors, and engineers. But now, Tony Hey, a VP of Microsoft Research, says we're witnessing the dawn of a new generation of powerful computer tools that can "mash up" vast quantities of data from many sources, analyze them, and help produce revolutionary scientific discoveries. Hey and his colleagues call this new method of scientific exploration "machine learning." At Microsoft, a team has already used it to innovate a method of predicting with impressive accuracy whether a patient with congestive heart failure who is released from the hospital will be readmitted within 30 days. It was developed by directing a computer program to pore through hundreds of thousands of data points on 300,000 patients and "learn" the profiles of patients most likely to be rehospitalized. The economic impact of this prediction tool could be huge: If a hospital understands the likelihood that a patient will "bounce back," it can design programs to keep him stable and save thousands of dollars in health care costs. Similar efforts to uncover important correlations that could lead to scientific breakthroughs are under way in oceanography, conservation, and AIDS research. And in business, deep data exploration has the potential to unearth critical insights about customers, supply chains, advertising effectiveness, and more.

Argonne Out Loud: Computation, Big Data, and the Future of Cities

ScienceCinema

Catlett, Charlie

2018-01-16

Charlie Catlett, a Senior Computer Scientist at Argonne and Director of the Urban Center for Computation and Data at the Computation Institute of the University of Chicago and Argonne, talks about how he and his colleagues are using high-performance computing, data analytics, and embedded systems to better understand and design cities.

Landsat Science: 40 Years of Innovation and Opportunity

NASA Technical Reports Server (NTRS)

Cook, Bruce D.; Irons, James R.; Masek, Jeffrey G.; Loveland, Thomas R.

2012-01-01

Landsat satellites have provided unparalleled Earth-observing data for nearly 40 years, allowing scientists to describe, monitor and model the global environment during a period of time that has seen dramatic changes in population growth, land use, and climate. The success of the Landsat program can be attributed to well-designed instrument specifications, astute engineering, comprehensive global acquisition and calibration strategies, and innovative scientists who have developed analytical techniques and applications to address a wide range of needs at local to global scales (e.g., crop production, water resource management, human health and environmental quality, urbanization, deforestation and biodiversity). Early Landsat contributions included inventories of natural resources and land cover classification maps, which were initially prepared by a visual interpretation of Landsat imagery. Over time, advances in computer technology facilitated the development of sophisticated image processing algorithms and complex ecosystem modeling, enabling scientists to create accurate, reproducible, and more realistic simulations of biogeochemical processes (e.g., plant production and ecosystem dynamics). Today, the Landsat data archive is freely available for download through the USGS, creating new opportunities for scientists to generate global image datasets, develop new change detection algorithms, and provide products in support of operational programs such as Reducing Emissions from Deforestation and Forest Degradation in Developing Countries (REDD). In particular, the use of dense (approximately annual) time series to characterize both rapid and progressive landscape change has yielded new insights into how the land environment is responding to anthropogenic and natural pressures. The launch of the Landsat Data Continuity Mission (LDCM) satellite in 2012 will continue to propel innovative Landsat science.

Issues in undergraduate education in computational science and high performance computing

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

Marchioro, T.L. II; Martin, D.

1994-12-31

The ever increasing need for mathematical and computational literacy within their society and among members of the work force has generated enormous pressure to revise and improve the teaching of related subjects throughout the curriculum, particularly at the undergraduate level. The Calculus Reform movement is perhaps the best known example of an organized initiative in this regard. The UCES (Undergraduate Computational Engineering and Science) project, an effort funded by the Department of Energy and administered through the Ames Laboratory, is sponsoring an informal and open discussion of the salient issues confronting efforts to improve and expand the teaching of computationalmore » science as a problem oriented, interdisciplinary approach to scientific investigation. Although the format is open, the authors hope to consider pertinent questions such as: (1) How can faculty and research scientists obtain the recognition necessary to further excellence in teaching the mathematical and computational sciences? (2) What sort of educational resources--both hardware and software--are needed to teach computational science at the undergraduate level? Are traditional procedural languages sufficient? Are PCs enough? Are massively parallel platforms needed? (3) How can electronic educational materials be distributed in an efficient way? Can they be made interactive in nature? How should such materials be tied to the World Wide Web and the growing ``Information Superhighway``?« less

Personalized medical education: Reappraising clinician-scientist training.

PubMed

DeLuca, Gabriele C; Ovseiko, Pavel V; Buchan, Alastair M

2016-01-13

Revitalizing the Oslerian ideal of the clinician-scientist-teacher may help in the training of the next generation of translational researchers. Copyright © 2016, American Association for the Advancement of Science.

PoPLAR: Portal for Petascale Lifescience Applications and Research

PubMed Central

2013-01-01

Background We are focusing specifically on fast data analysis and retrieval in bioinformatics that will have a direct impact on the quality of human health and the environment. The exponential growth of data generated in biology research, from small atoms to big ecosystems, necessitates an increasingly large computational component to perform analyses. Novel DNA sequencing technologies and complementary high-throughput approaches--such as proteomics, genomics, metabolomics, and meta-genomics--drive data-intensive bioinformatics. While individual research centers or universities could once provide for these applications, this is no longer the case. Today, only specialized national centers can deliver the level of computing resources required to meet the challenges posed by rapid data growth and the resulting computational demand. Consequently, we are developing massively parallel applications to analyze the growing flood of biological data and contribute to the rapid discovery of novel knowledge. Methods The efforts of previous National Science Foundation (NSF) projects provided for the generation of parallel modules for widely used bioinformatics applications on the Kraken supercomputer. We have profiled and optimized the code of some of the scientific community's most widely used desktop and small-cluster-based applications, including BLAST from the National Center for Biotechnology Information (NCBI), HMMER, and MUSCLE; scaled them to tens of thousands of cores on high-performance computing (HPC) architectures; made them robust and portable to next-generation architectures; and incorporated these parallel applications in science gateways with a web-based portal. Results This paper will discuss the various developmental stages, challenges, and solutions involved in taking bioinformatics applications from the desktop to petascale with a front-end portal for very-large-scale data analysis in the life sciences. Conclusions This research will help to bridge the gap between the rate of data generation and the speed at which scientists can study this data. The ability to rapidly analyze data at such a large scale is having a significant, direct impact on science achieved by collaborators who are currently using these tools on supercomputers. PMID:23902523

RIACS FY2002 Annual Report

NASA Technical Reports Server (NTRS)

Leiner, Barry M.; Gross, Anthony R. (Technical Monitor)

2002-01-01

The Research Institute for Advanced Computer Science (RIACS) carries out basic research and technology development in computer science, in support of the National Aeronautics and Space Administration's missions. Operated by the Universities Space Research Association (a non-profit university consortium), RIACS is located at the NASA Ames Research Center, Moffett Field, California. It currently operates under a multiple year grant/cooperative agreement that began on October 1, 1997 and is up for renewal in September 2003. Ames has been designated NASA's Center of Excellence in Information Technology. In this capacity, Ames is charged with the responsibility to build an Information Technology (IT) Research Program that is preeminent within NASA. RIACS serves as a bridge between NASA Ames and the academic community, and RIACS scientists and visitors work in close collaboration with NASA scientists. RIACS has the additional goal of broadening the base of researchers in these areas of importance to the nation's space and aeronautics enterprises. RIACS research focuses on the three cornerstones of IT research necessary to meet the future challenges of NASA missions: 1) Automated Reasoning for Autonomous Systems; 2) Human-Centered Computing; and 3) High Performance Computing and Networking. In addition, RIACS collaborates with NASA scientists to apply IT research to a variety of NASA application domains including aerospace technology, earth science, life sciences, and astrobiology. RIACS also engages in other activities, such as workshops, seminars, visiting scientist programs and student summer programs, designed to encourage and facilitate collaboration between the university and NASA IT research communities.

Exascale computing and what it means for shock physics

NASA Astrophysics Data System (ADS)

Germann, Timothy

2015-06-01

The U.S. Department of Energy is preparing to launch an Exascale Computing Initiative, to address the myriad challenges required to deploy and effectively utilize an exascale-class supercomputer (i.e., one capable of performing 1018 operations per second) in the 2023 timeframe. Since physical (power dissipation) requirements limit clock rates to at most a few GHz, this will necessitate the coordination of on the order of a billion concurrent operations, requiring sophisticated system and application software, and underlying mathematical algorithms, that may differ radically from traditional approaches. Even at the smaller workstation or cluster level of computation, the massive concurrency and heterogeneity within each processor will impact computational scientists. Through the multi-institutional, multi-disciplinary Exascale Co-design Center for Materials in Extreme Environments (ExMatEx), we have initiated an early and deep collaboration between domain (computational materials) scientists, applied mathematicians, computer scientists, and hardware architects, in order to establish the relationships between algorithms, software stacks, and architectures needed to enable exascale-ready materials science application codes within the next decade. In my talk, I will discuss these challenges, and what it will mean for exascale-era electronic structure, molecular dynamics, and engineering-scale simulations of shock-compressed condensed matter. In particular, we anticipate that the emerging hierarchical, heterogeneous architectures can be exploited to achieve higher physical fidelity simulations using adaptive physics refinement. This work is supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research.

CESDIS

NASA Technical Reports Server (NTRS)

1994-01-01

CESDIS, the Center of Excellence in Space Data and Information Sciences was developed jointly by NASA, Universities Space Research Association (USRA), and the University of Maryland in 1988 to focus on the design of advanced computing techniques and data systems to support NASA Earth and space science research programs. CESDIS is operated by USRA under contract to NASA. The Director, Associate Director, Staff Scientists, and administrative staff are located on-site at NASA's Goddard Space Flight Center in Greenbelt, Maryland. The primary CESDIS mission is to increase the connection between computer science and engineering research programs at colleges and universities and NASA groups working with computer applications in Earth and space science. Research areas of primary interest at CESDIS include: 1) High performance computing, especially software design and performance evaluation for massively parallel machines; 2) Parallel input/output and data storage systems for high performance parallel computers; 3) Data base and intelligent data management systems for parallel computers; 4) Image processing; 5) Digital libraries; and 6) Data compression. CESDIS funds multiyear projects at U. S. universities and colleges. Proposals are accepted in response to calls for proposals and are selected on the basis of peer reviews. Funds are provided to support faculty and graduate students working at their home institutions. Project personnel visit Goddard during academic recess periods to attend workshops, present seminars, and collaborate with NASA scientists on research projects. Additionally, CESDIS takes on specific research tasks of shorter duration for computer science research requested by NASA Goddard scientists.

Graduating College Students' Orientations toward Scientific Research Activity

ERIC Educational Resources Information Center

Zubova, L. G.; Andreeva, O. N.; Antropova, O. A.

2009-01-01

The population of scientists in Russia is aging, and it is difficult to attract young graduates to enter the profession. Greater efforts need to be made to change the condition of work for scientists in order to make it attractive to those who will become the next generation of Russian scientists. Creating the conditions favorable to the…

Computational Thinking: A Digital Age Skill for Everyone

ERIC Educational Resources Information Center

Barr, David; Harrison, John; Conery, Leslie

2011-01-01

In a seminal article published in 2006, Jeanette Wing described computational thinking (CT) as a way of "solving problems, designing systems, and understanding human behavior by drawing on the concepts fundamental to computer science." Wing's article gave rise to an often controversial discussion and debate among computer scientists,…

Big Computing in Astronomy: Perspectives and Challenges

NASA Astrophysics Data System (ADS)

Pankratius, Victor

2014-06-01

Hardware progress in recent years has led to astronomical instruments gathering large volumes of data. In radio astronomy for instance, the current generation of antenna arrays produces data at Tbits per second, and forthcoming instruments will expand these rates much further. As instruments are increasingly becoming software-based, astronomers will get more exposed to computer science. This talk therefore outlines key challenges that arise at the intersection of computer science and astronomy and presents perspectives on how both communities can collaborate to overcome these challenges.Major problems are emerging due to increases in data rates that are much larger than in storage and transmission capacity, as well as humans being cognitively overwhelmed when attempting to opportunistically scan through Big Data. As a consequence, the generation of scientific insight will become more dependent on automation and algorithmic instrument control. Intelligent data reduction will have to be considered across the entire acquisition pipeline. In this context, the presentation will outline the enabling role of machine learning and parallel computing.BioVictor Pankratius is a computer scientist who joined MIT Haystack Observatory following his passion for astronomy. He is currently leading efforts to advance astronomy through cutting-edge computer science and parallel computing. Victor is also involved in projects such as ALMA Phasing to enhance the ALMA Observatory with Very-Long Baseline Interferometry capabilities, the Event Horizon Telescope, as well as in the Radio Array of Portable Interferometric Detectors (RAPID) to create an analysis environment using parallel computing in the cloud. He has an extensive track record of research in parallel multicore systems and software engineering, with contributions to auto-tuning, debugging, and empirical experiments studying programmers. Victor has worked with major industry partners such as Intel, Sun Labs, and Oracle. He holds a distinguished doctorate and a Habilitation degree in Computer Science from the University of Karlsruhe. Contact him at pankrat@mit.edu, victorpankratius.com, or Twitter @vpankratius.

50 Years of renal physiology from one man and the perfused tubule: Maurice B. Burg.

PubMed

Hamilton, Kirk L; Moore, Antoni B

2016-08-01

Technical advancements in research techniques in science are made in slow increments. Even so, large advances from insight and hard work of an individual with a single technique can have astonishing ramifications. Here, we examine the impact of Dr. Maurice B. Burg and the isolated perfused renal tubule technique and celebrate the 50th anniversary of the publication by Dr. Burg and his colleagues of their landmark paper in the American Journal of Physiology in 1966. In this study, we have taken a scientific visualization approach to study the scientific contributions of Dr. Burg and the isolated perfused tubule preparation as determining research impact by the number of research students, postdoctoral fellows, visiting scientists, and national and international collaborators. Additionally, we have examined the research collaborations (first and second generation scientists), established the migrational visualization of the first generation scientists who worked directly with Dr. Burg, quantified the metrics indices, identified and quantified the network of coauthorship of the first generation scientists with their second generation links, and determined the citations analyses of outputs of Dr. Burg and/or his first generation collaborators as coauthors. We also review the major advances in kidney physiology that have been made with the isolated perfused tubule technique. Finally, we are all waiting for the discoveries that the isolated perfused preparation technique will bring during the next 50 years. Copyright © 2016 the American Physiological Society.

Information processing, computation, and cognition.

PubMed

Piccinini, Gualtiero; Scarantino, Andrea

2011-01-01

Computation and information processing are among the most fundamental notions in cognitive science. They are also among the most imprecisely discussed. Many cognitive scientists take it for granted that cognition involves computation, information processing, or both - although others disagree vehemently. Yet different cognitive scientists use 'computation' and 'information processing' to mean different things, sometimes without realizing that they do. In addition, computation and information processing are surrounded by several myths; first and foremost, that they are the same thing. In this paper, we address this unsatisfactory state of affairs by presenting a general and theory-neutral account of computation and information processing. We also apply our framework by analyzing the relations between computation and information processing on one hand and classicism, connectionism, and computational neuroscience on the other. We defend the relevance to cognitive science of both computation, at least in a generic sense, and information processing, in three important senses of the term. Our account advances several foundational debates in cognitive science by untangling some of their conceptual knots in a theory-neutral way. By leveling the playing field, we pave the way for the future resolution of the debates' empirical aspects.

RDNAnalyzer: A tool for DNA secondary structure prediction and sequence analysis.

PubMed

Afzal, Muhammad; Shahid, Ahmad Ali; Shehzadi, Abida; Nadeem, Shahid; Husnain, Tayyab

2012-01-01

RDNAnalyzer is an innovative computer based tool designed for DNA secondary structure prediction and sequence analysis. It can randomly generate the DNA sequence or user can upload the sequences of their own interest in RAW format. It uses and extends the Nussinov dynamic programming algorithm and has various application for the sequence analysis. It predicts the DNA secondary structure and base pairings. It also provides the tools for routinely performed sequence analysis by the biological scientists such as DNA replication, reverse compliment generation, transcription, translation, sequence specific information as total number of nucleotide bases, ATGC base contents along with their respective percentages and sequence cleaner. RDNAnalyzer is a unique tool developed in Microsoft Visual Studio 2008 using Microsoft Visual C# and Windows Presentation Foundation and provides user friendly environment for sequence analysis. It is freely available. http://www.cemb.edu.pk/sw.html RDNAnalyzer - Random DNA Analyser, GUI - Graphical user interface, XAML - Extensible Application Markup Language.

Engineering the next generation of clinical deep brain stimulation technology.

PubMed

McIntyre, Cameron C; Chaturvedi, Ashutosh; Shamir, Reuben R; Lempka, Scott F

2015-01-01

Deep brain stimulation (DBS) has evolved into a powerful clinical therapy for a range of neurological disorders, but even with impressive clinical growth, DBS technology has been relatively stagnant over its history. However, enhanced collaborations between neural engineers, neuroscientists, physicists, neurologists, and neurosurgeons are beginning to address some of the limitations of current DBS technology. These interactions have helped to develop novel ideas for the next generation of clinical DBS systems. This review attempts collate some of that progress with two goals in mind. First, provide a general description of current clinical DBS practices, geared toward educating biomedical engineers and computer scientists on a field that needs their expertise and attention. Second, describe some of the technological developments that are currently underway in surgical targeting, stimulation parameter selection, stimulation protocols, and stimulation hardware that are being directly evaluated for near term clinical application. Copyright © 2015 Elsevier Inc. All rights reserved.

Scientists at Work. Final Report.

ERIC Educational Resources Information Center

Education Turnkey Systems, Inc., Falls Church, VA.

This report summarizes activities related to the development, field testing, evaluation, and marketing of the "Scientists at Work" program which combines computer assisted instruction with database tools to aid cognitively impaired middle and early high school children in learning and applying thinking skills to science. The brief report reviews…

Artificial grammar learning meets formal language theory: an overview

PubMed Central

Fitch, W. Tecumseh; Friederici, Angela D.

2012-01-01

Formal language theory (FLT), part of the broader mathematical theory of computation, provides a systematic terminology and set of conventions for describing rules and the structures they generate, along with a rich body of discoveries and theorems concerning generative rule systems. Despite its name, FLT is not limited to human language, but is equally applicable to computer programs, music, visual patterns, animal vocalizations, RNA structure and even dance. In the last decade, this theory has been profitably used to frame hypotheses and to design brain imaging and animal-learning experiments, mostly using the ‘artificial grammar-learning’ paradigm. We offer a brief, non-technical introduction to FLT and then a more detailed analysis of empirical research based on this theory. We suggest that progress has been hampered by a pervasive conflation of distinct issues, including hierarchy, dependency, complexity and recursion. We offer clarifications of several relevant hypotheses and the experimental designs necessary to test them. We finally review the recent brain imaging literature, using formal languages, identifying areas of convergence and outstanding debates. We conclude that FLT has much to offer scientists who are interested in rigorous empirical investigations of human cognition from a neuroscientific and comparative perspective. PMID:22688631

A policy for science.

PubMed

Lauer, Michael S

2012-06-12

Policy and science often interact. Typically, we think of policymakers looking to scientists for advice on issues informed by science. We may appreciate less the opposite look: where people outside science inform policies that affect the conduct of science. In clinical medicine, we are forced to make decisions about practices for which there is insufficient, inadequate evidence to know whether they improve clinical outcomes, yet the health care system may not be structured to rapidly generate needed evidence. For example, when the Centers for Medicare and Medicaid Services noted insufficient evidence to support routine use of computed tomography angiography and they called for a national commitment to completion of randomized trials, their call ran into substantial opposition. I use the computed tomography angiography story to illustrate how we might consider a "policy for science" in which stakeholders would band together to identify evidence gaps and to use their influence to promote the efficient design, implementation, and completion of high-quality randomized trials. Such a policy for science could create a culture that incentivizes and invigorates the rapid generation of evidence, ultimately engaging all clinicians, all patients, and indeed all stakeholders into the scientific enterprise. Copyright © 2012 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Bridging Social and Semantic Computing - Design and Evaluation of User Interfaces for Hybrid Systems

ERIC Educational Resources Information Center

Bostandjiev, Svetlin Alex I.

2012-01-01

The evolution of the Web brought new interesting problems to computer scientists that we loosely classify in the fields of social and semantic computing. Social computing is related to two major paradigms: computations carried out by a large amount of people in a collective intelligence fashion (i.e. wikis), and performing computations on social…

Australian sea-floor survey data, with images and expert annotations.

PubMed

Bewley, Michael; Friedman, Ariell; Ferrari, Renata; Hill, Nicole; Hovey, Renae; Barrett, Neville; Marzinelli, Ezequiel M; Pizarro, Oscar; Figueira, Will; Meyer, Lisa; Babcock, Russ; Bellchambers, Lynda; Byrne, Maria; Williams, Stefan B

2015-01-01

This Australian benthic data set (BENTHOZ-2015) consists of an expert-annotated set of georeferenced benthic images and associated sensor data, captured by an autonomous underwater vehicle (AUV) around Australia. This type of data is of interest to marine scientists studying benthic habitats and organisms. AUVs collect georeferenced images over an area with consistent illumination and altitude, and make it possible to generate broad scale, photo-realistic 3D maps. Marine scientists then typically spend several minutes on each of thousands of images, labeling substratum type and biota at a subset of points. Labels from four Australian research groups were combined using the CATAMI classification scheme, a hierarchical classification scheme based on taxonomy and morphology for scoring marine imagery. This data set consists of 407,968 expert labeled points from around the Australian coast, with associated images, geolocation and other sensor data. The robotic surveys that collected this data form part of Australia's Integrated Marine Observing System (IMOS) ongoing benthic monitoring program. There is reuse potential in marine science, robotics, and computer vision research.

Australian sea-floor survey data, with images and expert annotations

PubMed Central

Bewley, Michael; Friedman, Ariell; Ferrari, Renata; Hill, Nicole; Hovey, Renae; Barrett, Neville; Pizarro, Oscar; Figueira, Will; Meyer, Lisa; Babcock, Russ; Bellchambers, Lynda; Byrne, Maria; Williams, Stefan B.

2015-01-01

This Australian benthic data set (BENTHOZ-2015) consists of an expert-annotated set of georeferenced benthic images and associated sensor data, captured by an autonomous underwater vehicle (AUV) around Australia. This type of data is of interest to marine scientists studying benthic habitats and organisms. AUVs collect georeferenced images over an area with consistent illumination and altitude, and make it possible to generate broad scale, photo-realistic 3D maps. Marine scientists then typically spend several minutes on each of thousands of images, labeling substratum type and biota at a subset of points. Labels from four Australian research groups were combined using the CATAMI classification scheme, a hierarchical classification scheme based on taxonomy and morphology for scoring marine imagery. This data set consists of 407,968 expert labeled points from around the Australian coast, with associated images, geolocation and other sensor data. The robotic surveys that collected this data form part of Australia's Integrated Marine Observing System (IMOS) ongoing benthic monitoring program. There is reuse potential in marine science, robotics, and computer vision research. PMID:26528396

Australian sea-floor survey data, with images and expert annotations

NASA Astrophysics Data System (ADS)

Bewley, Michael; Friedman, Ariell; Ferrari, Renata; Hill, Nicole; Hovey, Renae; Barrett, Neville; Pizarro, Oscar; Figueira, Will; Meyer, Lisa; Babcock, Russ; Bellchambers, Lynda; Byrne, Maria; Williams, Stefan B.

2015-10-01

This Australian benthic data set (BENTHOZ-2015) consists of an expert-annotated set of georeferenced benthic images and associated sensor data, captured by an autonomous underwater vehicle (AUV) around Australia. This type of data is of interest to marine scientists studying benthic habitats and organisms. AUVs collect georeferenced images over an area with consistent illumination and altitude, and make it possible to generate broad scale, photo-realistic 3D maps. Marine scientists then typically spend several minutes on each of thousands of images, labeling substratum type and biota at a subset of points. Labels from four Australian research groups were combined using the CATAMI classification scheme, a hierarchical classification scheme based on taxonomy and morphology for scoring marine imagery. This data set consists of 407,968 expert labeled points from around the Australian coast, with associated images, geolocation and other sensor data. The robotic surveys that collected this data form part of Australia's Integrated Marine Observing System (IMOS) ongoing benthic monitoring program. There is reuse potential in marine science, robotics, and computer vision research.

Profugus

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

Evans, Thomas; Hamilton, Steven; Slattery, Stuart

Profugus is an open-source mini-application (mini-app) for radiation transport and reactor applications. It contains the fundamental computational kernels used in the Exnihilo code suite from Oak Ridge National Laboratory. However, Exnihilo is production code with a substantial user base. Furthermore, Exnihilo is export controlled. This makes collaboration with computer scientists and computer engineers difficult. Profugus is designed to bridge that gap. By encapsulating the core numerical algorithms in an abbreviated code base that is open-source, computer scientists can analyze the algorithms and easily make code-architectural changes to test performance without compromising the production code values of Exnihilo. Profugus is notmore » meant to be production software with respect to problem analysis. The computational kernels in Profugus are designed to analyze performance, not correctness. Nonetheless, users of Profugus can setup and run problems with enough real-world features to be useful as proof-of-concept for actual production work.« less

Combinatorial Algorithms to Enable Computational Science and Engineering: Work from the CSCAPES Institute

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

Boman, Erik G.; Catalyurek, Umit V.; Chevalier, Cedric

2015-01-16

This final progress report summarizes the work accomplished at the Combinatorial Scientific Computing and Petascale Simulations Institute. We developed Zoltan, a parallel mesh partitioning library that made use of accurate hypergraph models to provide load balancing in mesh-based computations. We developed several graph coloring algorithms for computing Jacobian and Hessian matrices and organized them into a software package called ColPack. We developed parallel algorithms for graph coloring and graph matching problems, and also designed multi-scale graph algorithms. Three PhD students graduated, six more are continuing their PhD studies, and four postdoctoral scholars were advised. Six of these students and Fellowsmore » have joined DOE Labs (Sandia, Berkeley), as staff scientists or as postdoctoral scientists. We also organized the SIAM Workshop on Combinatorial Scientific Computing (CSC) in 2007, 2009, and 2011 to continue to foster the CSC community.« less

Perspectives on an education in computational biology and medicine.

PubMed

Rubinstein, Jill C

2012-09-01

The mainstream application of massively parallel, high-throughput assays in biomedical research has created a demand for scientists educated in Computational Biology and Bioinformatics (CBB). In response, formalized graduate programs have rapidly evolved over the past decade. Concurrently, there is increasing need for clinicians trained to oversee the responsible translation of CBB research into clinical tools. Physician-scientists with dedicated CBB training can facilitate such translation, positioning themselves at the intersection between computational biomedical research and medicine. This perspective explores key elements of the educational path to such a position, specifically addressing: 1) evolving perceptions of the role of the computational biologist and the impact on training and career opportunities; 2) challenges in and strategies for obtaining the core skill set required of a biomedical researcher in a computational world; and 3) how the combination of CBB with medical training provides a logical foundation for a career in academic medicine and/or biomedical research.

The 2008 Lindau Nobel Laureate Meeting: Robert Huber, Chemistry 1988. Interview by Klaus J. Korak.

PubMed

Huber, Robert

2008-11-25

Robert Huber and his colleagues, Johann Deisenhofer and Hartmut Michel, elucidated the three-dimensional structure of the Rhodopseudomonas viridis photosynthetic reaction center. This membrane protein complex is a basic component of photosynthesis - a process fundamental to life on Earth - and for their work, Huber and his colleagues received the 1988 Nobel Prize in Chemistry. Because structural information is central to understanding virtually any biological process, Huber likens their discovery to "switching on the light" for scientists trying to understand photosynthesis. Huber marvels at the growth of structural biology since the time he entered the field, when crystallographers worked with hand-made instruments and primitive computers, and only "a handful" of crystallographers would meet annually in the Bavarian Alps. In the "explosion" of structural biology since his early days of research, Huber looks to the rising generation of scientists to solve the remaining mysteries in the field - such as the mechanisms that underlie protein folding. A strong proponent of science mentorship, Huber delights in meeting young researchers at the annual Nobel Laureate Meetings in Lindau, Germany. He hopes that among these young scientists is an "Einstein of biology" who, he says with a twinkle in his eye, "doesn't know it yet." The interview was conducted by JoVE co-founder Klaus J. Korak at the Lindau Nobel Laureate Meeting 2008 in Lindau, Germany.

The 2008 Lindau Nobel Laureate Meeting: Robert Huber, Chemistry 1988

PubMed Central

Huber, Robert

2008-01-01

Robert Huber and his colleagues, Johann Deisenhofer and Hartmut Michel, elucidated the three-dimensional structure of the Rhodopseudomonas viridis photosynthetic reaction center. This membrane protein complex is a basic component of photosynthesis – a process fundamental to life on Earth – and for their work, Huber and his colleagues received the 1988 Nobel Prize in Chemistry. Because structural information is central to understanding virtually any biological process, Huber likens their discovery to “switching on the light” for scientists trying to understand photosynthesis. Huber marvels at the growth of structural biology since the time he entered the field, when crystallographers worked with hand-made instruments and primitive computers, and only “a handful” of crystallographers would meet annually in the Bavarian Alps. In the “explosion” of structural biology since his early days of research, Huber looks to the rising generation of scientists to solve the remaining mysteries in the field – such as the mechanisms that underlie protein folding. A strong proponent of science mentorship, Huber delights in meeting young researchers at the annual Nobel Laureate Meetings in Lindau, Germany. He hopes that among these young scientists is an “Einstein of biology” who, he says with a twinkle in his eye, “doesn’t know it yet.” The interview was conducted by JoVE co-founder Klaus J. Korak at the Lindau Nobel Laureate Meeting 2008 in Lindau, Germany. PMID:19066525

A need for a code of ethics in science communication?

NASA Astrophysics Data System (ADS)

Benestad, R. E.

2009-09-01

The modern western civilization and high standard of living are to a large extent the 'fruits' of scientific endeavor over generations. Some examples include the longer life expectancy due to progress in medical sciences, and changes in infrastructure associated with the utilization of electromagnetism. Modern meteorology is not possible without the state-of-the-art digital computers, satellites, remote sensing, and communications. Science also is of relevance for policy making, e.g. the present hot topic of climate change. Climate scientists have recently become much exposed to media focus and mass communications, a task for which many are not trained. Furthermore, science, communication, and politics have different objectives, and do not necessarily mix. Scientists have an obligation to provide unbiased information, and a code of ethics is needed to give a guidance for acceptable and unacceptable conduct. Some examples of questionable conduct in Norway include using the title 'Ph.D' to imply scientific authority when the person never had obtained such an academic degree, or writing biased and one-sided articles in Norwegian encyclopedia that do not reflect the scientific consensus. It is proposed here that a set of guide lines (for the scientists and journalists) and a code of conduct could provide recommendation for regarding how to act in media - similar to a code of conduct with respect to carrying out research - to which everyone could agree, even when disagreeing on specific scientific questions.

Integrated Circuits/Segregated Labor: Women in Three Computer-Related Occupations. Project Report No. 84-A27.

ERIC Educational Resources Information Center

Strober, Myra H.; Arnold, Carolyn L.

This discussion of the impact of new computer occupations on women's employment patterns is divided into four major sections. The first section describes the six computer-related occupations to be analyzed: (1) engineers; (2) computer scientists and systems analysts; (3) programmers; (4) electronic technicians; (5) computer operators; and (6) data…

Enduring Influence of Stereotypical Computer Science Role Models on Women's Academic Aspirations

ERIC Educational Resources Information Center

Cheryan, Sapna; Drury, Benjamin J.; Vichayapai, Marissa

2013-01-01

The current work examines whether a brief exposure to a computer science role model who fits stereotypes of computer scientists has a lasting influence on women's interest in the field. One-hundred undergraduate women who were not computer science majors met a female or male peer role model who embodied computer science stereotypes in appearance…

Collective Computation of Neural Network

DTIC Science & Technology

1990-03-15

Sciences, Beijing ABSTRACT Computational neuroscience is a new branch of neuroscience originating from current research on the theory of computer...scientists working in artificial intelligence engineering and neuroscience . The paper introduces the collective computational properties of model neural...vision research. On this basis, the authors analyzed the significance of the Hopfield model. Key phrases: Computational Neuroscience , Neural Network, Model

Text processing for technical reports (direct computer-assisted origination, editing, and output of text)

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

De Volpi, A.; Fenrick, M. R.; Stanford, G. S.

1980-10-01

Documentation often is a primary residual of research and development. Because of this important role and because of the large amount of time consumed in generating technical reports, particularly those containing formulas and graphics, an existing data-processing computer system has been adapted so as to provide text-processing of technical documents. Emphasis has been on accuracy, turnaround time, and time savings for staff and secretaries, for the types of reports normally produced in the reactor development program. The computer-assisted text-processing system, called TXT, has been implemented to benefit primarily the originator of technical reports. The system is of particular value tomore » professional staff, such as scientists and engineers, who have responsibility for generating much correspondence or lengthy, complex reports or manuscripts - especially if prompt turnaround and high accuracy are required. It can produce text that contains special Greek or mathematical symbols. Written in FORTRAN and MACRO, the program TXT operates on a PDP-11 minicomputer under the RSX-11M multitask multiuser monitor. Peripheral hardware includes videoterminals, electrostatic printers, and magnetic disks. Either data- or word-processing tasks may be performed at the terminals. The repertoire of operations has been restricted so as to minimize user training and memory burden. Spectarial staff may be readily trained to make corrections from annotated copy. Some examples of camera-ready copy are provided.« less

Scientists feature their work in Arctic-focused short videos by FrontierScientists

NASA Astrophysics Data System (ADS)

Nielsen, L.; O'Connell, E.

2013-12-01

Whether they're guiding an unmanned aerial vehicle into a volcanic plume to sample aerosols, or documenting core drilling at a frozen lake in Siberia formed 3.6 million years ago by a massive meteorite impact, Arctic scientists are using video to enhance and expand their science and science outreach. FrontierScientists (FS), a forum for showcasing scientific work, produces and promotes radically different video blogs featuring Arctic scientists. Three- to seven- minute multimedia vlogs help deconstruct researcher's efforts and disseminate stories, communicating scientific discoveries to our increasingly connected world. The videos cover a wide range of current field work being performed in the Arctic. All videos are freely available to view or download from the FrontierScientists.com website, accessible via any internet browser or via the FrontierScientists app. FS' filming process fosters a close collaboration between the scientist and the media maker. Film creation helps scientists reach out to the public, communicate the relevance of their scientific findings, and craft a discussion. Videos keep audience tuned in; combining field footage, pictures, audio, and graphics with a verbal explanation helps illustrate ideas, allowing one video to reach people with different learning strategies. The scientists' stories are highlighted through social media platforms online. Vlogs grant scientists a voice, letting them illustrate their own work while ensuring accuracy. Each scientific topic on FS has its own project page where easy-to-navigate videos are featured prominently. Video sets focus on different aspects of a researcher's work or follow one of their projects into the field. We help the scientist slip the answers to their five most-asked questions into the casual script in layman's terms in order to free the viewers' minds to focus on new concepts. Videos are accompanied by written blogs intended to systematically demystify related facts so the scientists can focus on presenting what they're passionate about, not get bogged down by basic groundwork. Vlogs and short video bios showcase the enthusiasm and personality of the scientists, an important ingredient in crafting compelling videos. Featured scientists become better communicators, and learn to bring their research to life. When viewers see that genuine wonder, they can be motivated to ask questions and pursue more information about the topic, broadening community participation. The website interface opens the door to audience discussion. Digital media is a community builder, an inclusive tool that lets people continents-apart engage with compelling stories and then interact. Internet videos have become a means of supplementing face-to-face education; video reaches people, it's informal self-education from the comfort of one's own computer screen. FS uses videos and social media as part of an education outreach effort directed at lifelong learners. We feature not only scientists, but also teachers who've gone into the field to add to their own science knowledge, and to bring back new lessons for their students. Students who are exposed to FS videos see science in action in the professional world, which might inspire them in a STEM academic and career path, encouraging the next generation of researchers, as well as scientific and environmental literacy.

Scientific Computing

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

Fermilab

2017-09-01

Scientists, engineers and programmers at Fermilab are tackling today’s most challenging computational problems. Their solutions, motivated by the needs of worldwide research in particle physics and accelerators, help America stay at the forefront of innovation.

An Analysis of Cloud Computing with Amazon Web Services for the Atmospheric Science Data Center

NASA Astrophysics Data System (ADS)

Gleason, J. L.; Little, M. M.

2013-12-01

NASA science and engineering efforts rely heavily on compute and data handling systems. The nature of NASA science data is such that it is not restricted to NASA users, instead it is widely shared across a globally distributed user community including scientists, educators, policy decision makers, and the public. Therefore NASA science computing is a candidate use case for cloud computing where compute resources are outsourced to an external vendor. Amazon Web Services (AWS) is a commercial cloud computing service developed to use excess computing capacity at Amazon, and potentially provides an alternative to costly and potentially underutilized dedicated acquisitions whenever NASA scientists or engineers require additional data processing. AWS desires to provide a simplified avenue for NASA scientists and researchers to share large, complex data sets with external partners and the public. AWS has been extensively used by JPL for a wide range of computing needs and was previously tested on a NASA Agency basis during the Nebula testing program. Its ability to support the Langley Science Directorate needs to be evaluated by integrating it with real world operational needs across NASA and the associated maturity that would come with that. The strengths and weaknesses of this architecture and its ability to support general science and engineering applications has been demonstrated during the previous testing. The Langley Office of the Chief Information Officer in partnership with the Atmospheric Sciences Data Center (ASDC) has established a pilot business interface to utilize AWS cloud computing resources on a organization and project level pay per use model. This poster discusses an effort to evaluate the feasibility of the pilot business interface from a project level perspective by specifically using a processing scenario involving the Clouds and Earth's Radiant Energy System (CERES) project.

OptFuels: Fuel treatment optimization

Treesearch

Greg Jones

2011-01-01

Scientists at the USDA Forest Service, Rocky Mountain Research Station, in Missoula, MT, in collaboration with scientists at the University of Montana, are developing a tool to help forest managers prioritize forest fuel reduction treatments. Although several computer models analyze fuels and fire behavior, stand-level effects of fuel treatments, and priority planning...

Four Argonne National Laboratory scientists receive Early Career Research

Science.gov Websites

Media Contacts Social Media Photos Videos Fact Sheets, Brochures and Reports Summer Science Writing Writing Internship Four Argonne National Laboratory scientists receive Early Career Research Program economic impact of cascading shortages. He will also seek to enable scaling on high-performance computing

Air Force Laboratory’s 2005 Technology Milestones

DTIC Science & Technology

2006-01-01

Computational materials science methods can benefit the design and property prediction of complex real-world materials. With these models , scientists and...Warfighter Page Air High - Frequency Acoustic System...800) 203-6451 High - Frequency Acoustic System Payoff Scientists created the High - Frequency Acoustic Suppression Technology (HiFAST) airflow control

A toolbox and a record for scientific model development

NASA Technical Reports Server (NTRS)

Ellman, Thomas

1994-01-01

Scientific computation can benefit from software tools that facilitate construction of computational models, control the application of models, and aid in revising models to handle new situations. Existing environments for scientific programming provide only limited means of handling these tasks. This paper describes a two pronged approach for handling these tasks: (1) designing a 'Model Development Toolbox' that includes a basic set of model constructing operations; and (2) designing a 'Model Development Record' that is automatically generated during model construction. The record is subsequently exploited by tools that control the application of scientific models and revise models to handle new situations. Our two pronged approach is motivated by our belief that the model development toolbox and record should be highly interdependent. In particular, a suitable model development record can be constructed only when models are developed using a well defined set of operations. We expect this research to facilitate rapid development of new scientific computational models, to help ensure appropriate use of such models and to facilitate sharing of such models among working computational scientists. We are testing this approach by extending SIGMA, and existing knowledge-based scientific software design tool.

High-throughput landslide modelling using computational grids

NASA Astrophysics Data System (ADS)

Wallace, M.; Metson, S.; Holcombe, L.; Anderson, M.; Newbold, D.; Brook, N.

2012-04-01

Landslides are an increasing problem in developing countries. Multiple landslides can be triggered by heavy rainfall resulting in loss of life, homes and critical infrastructure. Through computer simulation of individual slopes it is possible to predict the causes, timing and magnitude of landslides and estimate the potential physical impact. Geographical scientists at the University of Bristol have developed software that integrates a physically-based slope hydrology and stability model (CHASM) with an econometric model (QUESTA) in order to predict landslide risk over time. These models allow multiple scenarios to be evaluated for each slope, accounting for data uncertainties, different engineering interventions, risk management approaches and rainfall patterns. Individual scenarios can be computationally intensive, however each scenario is independent and so multiple scenarios can be executed in parallel. As more simulations are carried out the overhead involved in managing input and output data becomes significant. This is a greater problem if multiple slopes are considered concurrently, as is required both for landslide research and for effective disaster planning at national levels. There are two critical factors in this context: generated data volumes can be in the order of tens of terabytes, and greater numbers of simulations result in long total runtimes. Users of such models, in both the research community and in developing countries, need to develop a means for handling the generation and submission of landside modelling experiments, and the storage and analysis of the resulting datasets. Additionally, governments in developing countries typically lack the necessary computing resources and infrastructure. Consequently, knowledge that could be gained by aggregating simulation results from many different scenarios across many different slopes remains hidden within the data. To address these data and workload management issues, University of Bristol particle physicists and geographical scientists are collaborating to develop methods for providing simple and effective access to landslide models and associated simulation data. Particle physicists have valuable experience in dealing with data complexity and management due to the scale of data generated by particle accelerators such as the Large Hadron Collider (LHC). The LHC generates tens of petabytes of data every year which is stored and analysed using the Worldwide LHC Computing Grid (WLCG). Tools and concepts from the WLCG are being used to drive the development of a Software-as-a-Service (SaaS) platform to provide access to hosted landslide simulation software and data. It contains advanced data management features and allows landslide simulations to be run on the WLCG, dramatically reducing simulation runtimes by parallel execution. The simulations are accessed using a web page through which users can enter and browse input data, submit jobs and visualise results. Replication of the data ensures a local copy can be accessed should a connection to the platform be unavailable. The platform does not know the details of the simulation software it runs, so it is therefore possible to use it to run alternative models at similar scales. This creates the opportunity for activities such as model sensitivity analysis and performance comparison at scales that are impractical using standalone software.

Pathway Design, Engineering, and Optimization.

PubMed

Garcia-Ruiz, Eva; HamediRad, Mohammad; Zhao, Huimin

The microbial metabolic versatility found in nature has inspired scientists to create microorganisms capable of producing value-added compounds. Many endeavors have been made to transfer and/or combine pathways, existing or even engineered enzymes with new function to tractable microorganisms to generate new metabolic routes for drug, biofuel, and specialty chemical production. However, the success of these pathways can be impeded by different complications from an inherent failure of the pathway to cell perturbations. Pursuing ways to overcome these shortcomings, a wide variety of strategies have been developed. This chapter will review the computational algorithms and experimental tools used to design efficient metabolic routes, and construct and optimize biochemical pathways to produce chemicals of high interest.

Energy Systems Integration Facility (ESIF): Golden, CO - Energy Integration

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

Sheppy, Michael; VanGeet, Otto; Pless, Shanti

2015-03-01

At NREL's Energy Systems Integration Facility (ESIF) in Golden, Colo., scientists and engineers work to overcome challenges related to how the nation generates, delivers and uses energy by modernizing the interplay between energy sources, infrastructure, and data. Test facilities include a megawatt-scale ac electric grid, photovoltaic simulators and a load bank. Additionally, a high performance computing data center (HPCDC) is dedicated to advancing renewable energy and energy efficient technologies. A key design strategy is to use waste heat from the HPCDC to heat parts of the building. The ESIF boasts an annual EUI of 168.3 kBtu/ft2. This article describes themore » building's procurement, design and first year of performance.« less

BIG DATA AND STATISTICS

PubMed Central

Rossell, David

2016-01-01

Big Data brings unprecedented power to address scientific, economic and societal issues, but also amplifies the possibility of certain pitfalls. These include using purely data-driven approaches that disregard understanding the phenomenon under study, aiming at a dynamically moving target, ignoring critical data collection issues, summarizing or preprocessing the data inadequately and mistaking noise for signal. We review some success stories and illustrate how statistical principles can help obtain more reliable information from data. We also touch upon current challenges that require active methodological research, such as strategies for efficient computation, integration of heterogeneous data, extending the underlying theory to increasingly complex questions and, perhaps most importantly, training a new generation of scientists to develop and deploy these strategies. PMID:27722040

A toolbox and record for scientific models

NASA Technical Reports Server (NTRS)

Ellman, Thomas

1994-01-01

Computational science presents a host of challenges for the field of knowledge-based software design. Scientific computation models are difficult to construct. Models constructed by one scientist are easily misapplied by other scientists to problems for which they are not well-suited. Finally, models constructed by one scientist are difficult for others to modify or extend to handle new types of problems. Construction of scientific models actually involves much more than the mechanics of building a single computational model. In the course of developing a model, a scientist will often test a candidate model against experimental data or against a priori expectations. Test results often lead to revisions of the model and a consequent need for additional testing. During a single model development session, a scientist typically examines a whole series of alternative models, each using different simplifying assumptions or modeling techniques. A useful scientific software design tool must support these aspects of the model development process as well. In particular, it should propose and carry out tests of candidate models. It should analyze test results and identify models and parts of models that must be changed. It should determine what types of changes can potentially cure a given negative test result. It should organize candidate models, test data, and test results into a coherent record of the development process. Finally, it should exploit the development record for two purposes: (1) automatically determining the applicability of a scientific model to a given problem; (2) supporting revision of a scientific model to handle a new type of problem. Existing knowledge-based software design tools must be extended in order to provide these facilities.

PseKNC: a flexible web server for generating pseudo K-tuple nucleotide composition.

PubMed

Chen, Wei; Lei, Tian-Yu; Jin, Dian-Chuan; Lin, Hao; Chou, Kuo-Chen

2014-07-01

The pseudo oligonucleotide composition, or pseudo K-tuple nucleotide composition (PseKNC), can be used to represent a DNA or RNA sequence with a discrete model or vector yet still keep considerable sequence order information, particularly the global or long-range sequence order information, via the physicochemical properties of its constituent oligonucleotides. Therefore, the PseKNC approach may hold very high potential for enhancing the power in dealing with many problems in computational genomics and genome sequence analysis. However, dealing with different DNA or RNA problems may need different kinds of PseKNC. Here, we present a flexible and user-friendly web server for PseKNC (at http://lin.uestc.edu.cn/pseknc/default.aspx) by which users can easily generate many different modes of PseKNC according to their need by selecting various parameters and physicochemical properties. Furthermore, for the convenience of the vast majority of experimental scientists, a step-by-step guide is provided on how to use the current web server to generate their desired PseKNC without the need to follow the complicated mathematical equations, which are presented in this article just for the integrity of PseKNC formulation and its development. It is anticipated that the PseKNC web server will become a very useful tool in computational genomics and genome sequence analysis. Copyright © 2014 Elsevier Inc. All rights reserved.

Computer Series, 98. Electronics for Scientists: A Computer-Intensive Approach.

ERIC Educational Resources Information Center

Scheeline, Alexander; Mork, Brian J.

1988-01-01

Reports the design for a principles-before-details presentation of electronics for an instrumental analysis class. Uses computers for data collection and simulations. Requires one semester with two 2.5-hour periods and two lectures per week. Includes lab and lecture syllabi. (MVL)

Big data computing: Building a vision for ARS information management

USDA-ARS?s Scientific Manuscript database

Improvements are needed within the ARS to increase scientific capacity and keep pace with new developments in computer technologies that support data acquisition and analysis. Enhancements in computing power and IT infrastructure are needed to provide scientists better access to high performance com...

Science-Driven Computing: NERSC's Plan for 2006-2010

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

Simon, Horst D.; Kramer, William T.C.; Bailey, David H.

NERSC has developed a five-year strategic plan focusing on three components: Science-Driven Systems, Science-Driven Services, and Science-Driven Analytics. (1) Science-Driven Systems: Balanced introduction of the best new technologies for complete computational systems--computing, storage, networking, visualization and analysis--coupled with the activities necessary to engage vendors in addressing the DOE computational science requirements in their future roadmaps. (2) Science-Driven Services: The entire range of support activities, from high-quality operations and user services to direct scientific support, that enable a broad range of scientists to effectively use NERSC systems in their research. NERSC will concentrate on resources needed to realize the promise ofmore » the new highly scalable architectures for scientific discovery in multidisciplinary computational science projects. (3) Science-Driven Analytics: The architectural and systems enhancements and services required to integrate NERSC's powerful computational and storage resources to provide scientists with new tools to effectively manipulate, visualize, and analyze the huge data sets derived from simulations and experiments.« less

Optimizing high performance computing workflow for protein functional annotation.

PubMed

Stanberry, Larissa; Rekepalli, Bhanu; Liu, Yuan; Giblock, Paul; Higdon, Roger; Montague, Elizabeth; Broomall, William; Kolker, Natali; Kolker, Eugene

2014-09-10

Functional annotation of newly sequenced genomes is one of the major challenges in modern biology. With modern sequencing technologies, the protein sequence universe is rapidly expanding. Newly sequenced bacterial genomes alone contain over 7.5 million proteins. The rate of data generation has far surpassed that of protein annotation. The volume of protein data makes manual curation infeasible, whereas a high compute cost limits the utility of existing automated approaches. In this work, we present an improved and optmized automated workflow to enable large-scale protein annotation. The workflow uses high performance computing architectures and a low complexity classification algorithm to assign proteins into existing clusters of orthologous groups of proteins. On the basis of the Position-Specific Iterative Basic Local Alignment Search Tool the algorithm ensures at least 80% specificity and sensitivity of the resulting classifications. The workflow utilizes highly scalable parallel applications for classification and sequence alignment. Using Extreme Science and Engineering Discovery Environment supercomputers, the workflow processed 1,200,000 newly sequenced bacterial proteins. With the rapid expansion of the protein sequence universe, the proposed workflow will enable scientists to annotate big genome data.

Fragment-Based Docking: Development of the CHARMMing Web User Interface as a Platform for Computer-Aided Drug Design

PubMed Central

2015-01-01

Web-based user interfaces to scientific applications are important tools that allow researchers to utilize a broad range of software packages with just an Internet connection and a browser.1 One such interface, CHARMMing (CHARMM interface and graphics), facilitates access to the powerful and widely used molecular software package CHARMM. CHARMMing incorporates tasks such as molecular structure analysis, dynamics, multiscale modeling, and other techniques commonly used by computational life scientists. We have extended CHARMMing’s capabilities to include a fragment-based docking protocol that allows users to perform molecular docking and virtual screening calculations either directly via the CHARMMing Web server or on computing resources using the self-contained job scripts generated via the Web interface. The docking protocol was evaluated by performing a series of “re-dockings” with direct comparison to top commercial docking software. Results of this evaluation showed that CHARMMing’s docking implementation is comparable to many widely used software packages and validates the use of the new CHARMM generalized force field for docking and virtual screening. PMID:25151852

Optimizing high performance computing workflow for protein functional annotation

PubMed Central

Stanberry, Larissa; Rekepalli, Bhanu; Liu, Yuan; Giblock, Paul; Higdon, Roger; Montague, Elizabeth; Broomall, William; Kolker, Natali; Kolker, Eugene

2014-01-01

Functional annotation of newly sequenced genomes is one of the major challenges in modern biology. With modern sequencing technologies, the protein sequence universe is rapidly expanding. Newly sequenced bacterial genomes alone contain over 7.5 million proteins. The rate of data generation has far surpassed that of protein annotation. The volume of protein data makes manual curation infeasible, whereas a high compute cost limits the utility of existing automated approaches. In this work, we present an improved and optmized automated workflow to enable large-scale protein annotation. The workflow uses high performance computing architectures and a low complexity classification algorithm to assign proteins into existing clusters of orthologous groups of proteins. On the basis of the Position-Specific Iterative Basic Local Alignment Search Tool the algorithm ensures at least 80% specificity and sensitivity of the resulting classifications. The workflow utilizes highly scalable parallel applications for classification and sequence alignment. Using Extreme Science and Engineering Discovery Environment supercomputers, the workflow processed 1,200,000 newly sequenced bacterial proteins. With the rapid expansion of the protein sequence universe, the proposed workflow will enable scientists to annotate big genome data. PMID:25313296

Fragment-based docking: development of the CHARMMing Web user interface as a platform for computer-aided drug design.

PubMed

Pevzner, Yuri; Frugier, Emilie; Schalk, Vinushka; Caflisch, Amedeo; Woodcock, H Lee

2014-09-22

Web-based user interfaces to scientific applications are important tools that allow researchers to utilize a broad range of software packages with just an Internet connection and a browser. One such interface, CHARMMing (CHARMM interface and graphics), facilitates access to the powerful and widely used molecular software package CHARMM. CHARMMing incorporates tasks such as molecular structure analysis, dynamics, multiscale modeling, and other techniques commonly used by computational life scientists. We have extended CHARMMing's capabilities to include a fragment-based docking protocol that allows users to perform molecular docking and virtual screening calculations either directly via the CHARMMing Web server or on computing resources using the self-contained job scripts generated via the Web interface. The docking protocol was evaluated by performing a series of "re-dockings" with direct comparison to top commercial docking software. Results of this evaluation showed that CHARMMing's docking implementation is comparable to many widely used software packages and validates the use of the new CHARMM generalized force field for docking and virtual screening.

Students as Citizen Scientists - Earth Conservation Corps

EPA Pesticide Factsheets

This document has an overview of the student workshops on water quality monitoring used to generate citizen scientists. It also includes the main components of the curriculum and contact information for the Earth Conservation Corps to interested parties.

What can scientific practice look like in a classroom? Insights from scientists' critique of high school students' climate change argumentation practice

NASA Astrophysics Data System (ADS)

Walsh, E.; McGowan, V. C.

2015-12-01

The Next Generation Science Standards promote a vision in which learners engage in authentic knowledge in practice to tackle personally consequential science problems in the classroom. However, there is not yet a clear understanding amongst researchers and educators of what authentic practice looks like in a classroom and how this can be accomplished. This study explores these questions by examining interactions between scientists and students on a social media platform during two pilot enactments of a project-based curriculum focusing on the ecological impacts of climate change. During this unit, scientists provided feedback to students on infographics, visual representations of scientific information meant to communicate to an audience about climate change. We conceptualize the feedback and student work as boundary objects co-created by students and scientists moving between the school and scientific contexts, and analyze the structure and content of the scientists' feedback. We find that when giving feedback on a particular practice (e.g. argumentation), scientists would provide avenues, critiques and questions that incorporated many other practices (e.g. data analysis, visual communication); thus, scientists encouraged students to participate systemically in practices instead of isolating one particular practice. In addition, scientists drew attention to particular habits of mind that are valued in the scientific community and noted when students' work aligned with scientific values. In this way, scientists positioned students as capable of participating "scientifically." While traditionally, incorporating scientific inquiry in a classroom has emphasized student experimentation and data generation, in this work, we found that engaging with scientists around established scientific texts and data sets provided students with a platform for developing expertise in other important scientific practices during argment construction.

The Handicap Principle for Trust in Computer Security, the Semantic Web and Social Networking

NASA Astrophysics Data System (ADS)

Ma, Zhanshan (Sam); Krings, Axel W.; Hung, Chih-Cheng

Communication is a fundamental function of life, and it exists in almost all living things: from single-cell bacteria to human beings. Communication, together with competition and cooperation,arethree fundamental processes in nature. Computer scientists are familiar with the study of competition or 'struggle for life' through Darwin's evolutionary theory, or even evolutionary computing. They may be equally familiar with the study of cooperation or altruism through the Prisoner's Dilemma (PD) game. However, they are likely to be less familiar with the theory of animal communication. The objective of this article is three-fold: (i) To suggest that the study of animal communication, especially the honesty (reliability) of animal communication, in which some significant advances in behavioral biology have been achieved in the last three decades, should be on the verge to spawn important cross-disciplinary research similar to that generated by the study of cooperation with the PD game. One of the far-reaching advances in the field is marked by the publication of "The Handicap Principle: a Missing Piece of Darwin's Puzzle" by Zahavi (1997). The 'Handicap' principle [34][35], which states that communication signals must be costly in some proper way to be reliable (honest), is best elucidated with evolutionary games, e.g., Sir Philip Sidney (SPS) game [23]. Accordingly, we suggest that the Handicap principle may serve as a fundamental paradigm for trust research in computer science. (ii) To suggest to computer scientists that their expertise in modeling computer networks may help behavioral biologists in their study of the reliability of animal communication networks. This is largely due to the historical reason that, until the last decade, animal communication was studied with the dyadic paradigm (sender-receiver) rather than with the network paradigm. (iii) To pose several open questions, the answers to which may bear some refreshing insights to trust research in computer science, especially secure and resilient computing, the semantic web, and social networking. One important thread unifying the three aspects is the evolutionary game theory modeling or its extensions with survival analysis and agreement algorithms [19][20], which offer powerful game models for describing time-, space-, and covariate-dependent frailty (uncertainty and vulnerability) and deception (honesty).

High-Performance Computing Unlocks Innovation at NREL

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

None

Need to fly around a wind farm? Or step inside a molecule? NREL scientists use a super powerful (and highly energy-efficient) computer to visualize and solve big problems in renewable energy research.

Mathematical computer programs: A compilation

NASA Technical Reports Server (NTRS)

1972-01-01

Computer programs, routines, and subroutines for aiding engineers, scientists, and mathematicians in direct problem solving are presented. Also included is a group of items that affords the same users greater flexibility in the use of software.

A Modular Environment for Geophysical Inversion and Run-time Autotuning using Heterogeneous Computing Systems

NASA Astrophysics Data System (ADS)

Myre, Joseph M.

Heterogeneous computing systems have recently come to the forefront of the High-Performance Computing (HPC) community's interest. HPC computer systems that incorporate special purpose accelerators, such as Graphics Processing Units (GPUs), are said to be heterogeneous. Large scale heterogeneous computing systems have consistently ranked highly on the Top500 list since the beginning of the heterogeneous computing trend. By using heterogeneous computing systems that consist of both general purpose processors and special- purpose accelerators, the speed and problem size of many simulations could be dramatically increased. Ultimately this results in enhanced simulation capabilities that allows, in some cases for the first time, the execution of parameter space and uncertainty analyses, model optimizations, and other inverse modeling techniques that are critical for scientific discovery and engineering analysis. However, simplifying the usage and optimization of codes for heterogeneous computing systems remains a challenge. This is particularly true for scientists and engineers for whom understanding HPC architectures and undertaking performance analysis may not be primary research objectives. To enable scientists and engineers to remain focused on their primary research objectives, a modular environment for geophysical inversion and run-time autotuning on heterogeneous computing systems is presented. This environment is composed of three major components: 1) CUSH---a framework for reducing the complexity of programming heterogeneous computer systems, 2) geophysical inversion routines which can be used to characterize physical systems, and 3) run-time autotuning routines designed to determine configurations of heterogeneous computing systems in an attempt to maximize the performance of scientific and engineering codes. Using three case studies, a lattice-Boltzmann method, a non-negative least squares inversion, and a finite-difference fluid flow method, it is shown that this environment provides scientists and engineers with means to reduce the programmatic complexity of their applications, to perform geophysical inversions for characterizing physical systems, and to determine high-performing run-time configurations of heterogeneous computing systems using a run-time autotuner.

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

Nikolic, R J

This month's issue has the following articles: (1) Dawn of a New Era of Scientific Discovery - Commentary by Edward I. Moses; (2) At the Frontiers of Fundamental Science Research - Collaborators from national laboratories, universities, and international organizations are using the National Ignition Facility to probe key fundamental science questions; (3) Livermore Responds to Crisis in Post-Earthquake Japan - More than 70 Laboratory scientists provided round-the-clock expertise in radionuclide analysis and atmospheric dispersion modeling as part of the nation's support to Japan following the March 2011 earthquake and nuclear accident; (4) A Comprehensive Resource for Modeling, Simulation, and Experimentsmore » - A new Web-based resource called MIDAS is a central repository for material properties, experimental data, and computer models; and (5) Finding Data Needles in Gigabit Haystacks - Livermore computer scientists have developed a novel computer architecture based on 'persistent' memory to ease data-intensive computations.« less

Information Power Grid: Distributed High-Performance Computing and Large-Scale Data Management for Science and Engineering

NASA Technical Reports Server (NTRS)

Johnston, William E.; Gannon, Dennis; Nitzberg, Bill; Feiereisen, William (Technical Monitor)

2000-01-01

The term "Grid" refers to distributed, high performance computing and data handling infrastructure that incorporates geographically and organizationally dispersed, heterogeneous resources that are persistent and supported. The vision for NASN's Information Power Grid - a computing and data Grid - is that it will provide significant new capabilities to scientists and engineers by facilitating routine construction of information based problem solving environments / frameworks that will knit together widely distributed computing, data, instrument, and human resources into just-in-time systems that can address complex and large-scale computing and data analysis problems. IPG development and deployment is addressing requirements obtained by analyzing a number of different application areas, in particular from the NASA Aero-Space Technology Enterprise. This analysis has focussed primarily on two types of users: The scientist / design engineer whose primary interest is problem solving (e.g., determining wing aerodynamic characteristics in many different operating environments), and whose primary interface to IPG will be through various sorts of problem solving frameworks. The second type of user if the tool designer: The computational scientists who convert physics and mathematics into code that can simulate the physical world. These are the two primary users of IPG, and they have rather different requirements. This paper describes the current state of IPG (the operational testbed), the set of capabilities being put into place for the operational prototype IPG, as well as some of the longer term R&D tasks.

The Effects of a Robot Game Environment on Computer Programming Education for Elementary School Students

ERIC Educational Resources Information Center

Shim, Jaekwoun; Kwon, Daiyoung; Lee, Wongyu

2017-01-01

In the past, computer programming was perceived as a task only carried out by computer scientists; in the 21st century, however, computer programming is viewed as a critical and necessary skill that everyone should learn. In order to improve teaching of problem-solving abilities in a computing environment, extensive research is being done on…

Trace: a high-throughput tomographic reconstruction engine for large-scale datasets

DOE PAGES

Bicer, Tekin; Gursoy, Doga; Andrade, Vincent De; ...

2017-01-28

Here, synchrotron light source and detector technologies enable scientists to perform advanced experiments. These scientific instruments and experiments produce data at such scale and complexity that large-scale computation is required to unleash their full power. One of the widely used data acquisition technique at light sources is Computed Tomography, which can generate tens of GB/s depending on x-ray range. A large-scale tomographic dataset, such as mouse brain, may require hours of computation time with a medium size workstation. In this paper, we present Trace, a data-intensive computing middleware we developed for implementation and parallelization of iterative tomographic reconstruction algorithms. Tracemore » provides fine-grained reconstruction of tomography datasets using both (thread level) shared memory and (process level) distributed memory parallelization. Trace utilizes a special data structure called replicated reconstruction object to maximize application performance. We also present the optimizations we have done on the replicated reconstruction objects and evaluate them using a shale and a mouse brain sinogram. Our experimental evaluations show that the applied optimizations and parallelization techniques can provide 158x speedup (using 32 compute nodes) over single core configuration, which decreases the reconstruction time of a sinogram (with 4501 projections and 22400 detector resolution) from 12.5 hours to less than 5 minutes per iteration.« less

Trace: a high-throughput tomographic reconstruction engine for large-scale datasets

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

Bicer, Tekin; Gursoy, Doga; Andrade, Vincent De

Here, synchrotron light source and detector technologies enable scientists to perform advanced experiments. These scientific instruments and experiments produce data at such scale and complexity that large-scale computation is required to unleash their full power. One of the widely used data acquisition technique at light sources is Computed Tomography, which can generate tens of GB/s depending on x-ray range. A large-scale tomographic dataset, such as mouse brain, may require hours of computation time with a medium size workstation. In this paper, we present Trace, a data-intensive computing middleware we developed for implementation and parallelization of iterative tomographic reconstruction algorithms. Tracemore » provides fine-grained reconstruction of tomography datasets using both (thread level) shared memory and (process level) distributed memory parallelization. Trace utilizes a special data structure called replicated reconstruction object to maximize application performance. We also present the optimizations we have done on the replicated reconstruction objects and evaluate them using a shale and a mouse brain sinogram. Our experimental evaluations show that the applied optimizations and parallelization techniques can provide 158x speedup (using 32 compute nodes) over single core configuration, which decreases the reconstruction time of a sinogram (with 4501 projections and 22400 detector resolution) from 12.5 hours to less than 5 minutes per iteration.« less

Alliance for NanoHealth (ANH) Training Program for the development of future generations of interdisciplinary scientists and collaborative research focused upon the advancement of nanomedicine

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

Gorenstein, David

The objectives of this program are to promote the mission of the Department of Energy (DOE) Science, Technology, Engineering, Math (STEM) Program by recruiting students to science and engineering disciplines with the intent of mentoring and supporting the next generation of scientists; to foster interdisciplinary and collaborative research under the sponsorship of ANH for the discovery and design of nano-based materials and devices with novel structures, functions, and properties; and to prepare a diverse work force of scientists, engineers, and clinicians by utilizing the unique intellectual and physical resources to develop novel nanotechnology paradigms for clinical application.

RIACS

NASA Technical Reports Server (NTRS)

Moore, Robert C.

1998-01-01

The Research Institute for Advanced Computer Science (RIACS) was established by the Universities Space Research Association (USRA) at the NASA Ames Research Center (ARC) on June 6, 1983. RIACS is privately operated by USRA, a consortium of universities that serves as a bridge between NASA and the academic community. Under a five-year co-operative agreement with NASA, research at RIACS is focused on areas that are strategically enabling to the Ames Research Center's role as NASA's Center of Excellence for Information Technology. Research is carried out by a staff of full-time scientist,augmented by visitors, students, post doctoral candidates and visiting university faculty. The primary mission of RIACS is charted to carry out research and development in computer science. This work is devoted in the main to tasks that are strategically enabling with respect to NASA's bold mission in space exploration and aeronautics. There are three foci for this work: Automated Reasoning. Human-Centered Computing. and High Performance Computing and Networking. RIACS has the additional goal of broadening the base of researcher in these areas of importance to the nation's space and aeronautics enterprises. Through its visiting scientist program, RIACS facilitates the participation of university-based researchers, including both faculty and students, in the research activities of NASA and RIACS. RIACS researchers work in close collaboration with NASA computer scientists on projects such as the Remote Agent Experiment on Deep Space One mission, and Super-Resolution Surface Modeling.

Computational chemistry at Janssen

NASA Astrophysics Data System (ADS)

van Vlijmen, Herman; Desjarlais, Renee L.; Mirzadegan, Tara

2017-03-01

Computer-aided drug discovery activities at Janssen are carried out by scientists in the Computational Chemistry group of the Discovery Sciences organization. This perspective gives an overview of the organizational and operational structure, the science, internal and external collaborations, and the impact of the group on Drug Discovery at Janssen.

Computing Life

ERIC Educational Resources Information Center

National Institute of General Medical Sciences (NIGMS), 2009

2009-01-01

Computer advances now let researchers quickly search through DNA sequences to find gene variations that could lead to disease, simulate how flu might spread through one's school, and design three-dimensional animations of molecules that rival any video game. By teaming computers and biology, scientists can answer new and old questions that could…

Cloudgene: A graphical execution platform for MapReduce programs on private and public clouds

PubMed Central

2012-01-01

Background The MapReduce framework enables a scalable processing and analyzing of large datasets by distributing the computational load on connected computer nodes, referred to as a cluster. In Bioinformatics, MapReduce has already been adopted to various case scenarios such as mapping next generation sequencing data to a reference genome, finding SNPs from short read data or matching strings in genotype files. Nevertheless, tasks like installing and maintaining MapReduce on a cluster system, importing data into its distributed file system or executing MapReduce programs require advanced knowledge in computer science and could thus prevent scientists from usage of currently available and useful software solutions. Results Here we present Cloudgene, a freely available platform to improve the usability of MapReduce programs in Bioinformatics by providing a graphical user interface for the execution, the import and export of data and the reproducibility of workflows on in-house (private clouds) and rented clusters (public clouds). The aim of Cloudgene is to build a standardized graphical execution environment for currently available and future MapReduce programs, which can all be integrated by using its plug-in interface. Since Cloudgene can be executed on private clusters, sensitive datasets can be kept in house at all time and data transfer times are therefore minimized. Conclusions Our results show that MapReduce programs can be integrated into Cloudgene with little effort and without adding any computational overhead to existing programs. This platform gives developers the opportunity to focus on the actual implementation task and provides scientists a platform with the aim to hide the complexity of MapReduce. In addition to MapReduce programs, Cloudgene can also be used to launch predefined systems (e.g. Cloud BioLinux, RStudio) in public clouds. Currently, five different bioinformatic programs using MapReduce and two systems are integrated and have been successfully deployed. Cloudgene is freely available at http://cloudgene.uibk.ac.at. PMID:22888776

Visual Analytics for Heterogeneous Geoscience Data

NASA Astrophysics Data System (ADS)

Pan, Y.; Yu, L.; Zhu, F.; Rilee, M. L.; Kuo, K. S.; Jiang, H.; Yu, H.

2017-12-01

Geoscience data obtained from diverse sources have been routinely leveraged by scientists to study various phenomena. The principal data sources include observations and model simulation outputs. These data are characterized by spatiotemporal heterogeneity originated from different instrument design specifications and/or computational model requirements used in data generation processes. Such inherent heterogeneity poses several challenges in exploring and analyzing geoscience data. First, scientists often wish to identify features or patterns co-located among multiple data sources to derive and validate certain hypotheses. Heterogeneous data make it a tedious task to search such features in dissimilar datasets. Second, features of geoscience data are typically multivariate. It is challenging to tackle the high dimensionality of geoscience data and explore the relations among multiple variables in a scalable fashion. Third, there is a lack of transparency in traditional automated approaches, such as feature detection or clustering, in that scientists cannot intuitively interact with their analysis processes and interpret results. To address these issues, we present a new scalable approach that can assist scientists in analyzing voluminous and diverse geoscience data. We expose a high-level query interface that allows users to easily express their customized queries to search features of interest across multiple heterogeneous datasets. For identified features, we develop a visualization interface that enables interactive exploration and analytics in a linked-view manner. Specific visualization techniques such as scatter plots to parallel coordinates are employed in each view to allow users to explore various aspects of features. Different views are linked and refreshed according to user interactions in any individual view. In such a manner, a user can interactively and iteratively gain understanding into the data through a variety of visual analytics operations. We demonstrate with use cases how scientists can combine the query and visualization interfaces to enable a customized workflow facilitating studies using heterogeneous geoscience datasets.

Integration and Exposure of Large Scale Computational Resources Across the Earth System Grid Federation (ESGF)

NASA Astrophysics Data System (ADS)

Duffy, D.; Maxwell, T. P.; Doutriaux, C.; Williams, D. N.; Chaudhary, A.; Ames, S.

2015-12-01

As the size of remote sensing observations and model output data grows, the volume of the data has become overwhelming, even to many scientific experts. As societies are forced to better understand, mitigate, and adapt to climate changes, the combination of Earth observation data and global climate model projects is crucial to not only scientists but to policy makers, downstream applications, and even the public. Scientific progress on understanding climate is critically dependent on the availability of a reliable infrastructure that promotes data access, management, and provenance. The Earth System Grid Federation (ESGF) has created such an environment for the Intergovernmental Panel on Climate Change (IPCC). ESGF provides a federated global cyber infrastructure for data access and management of model outputs generated for the IPCC Assessment Reports (AR). The current generation of the ESGF federated grid allows consumers of the data to find and download data with limited capabilities for server-side processing. Since the amount of data for future AR is expected to grow dramatically, ESGF is working on integrating server-side analytics throughout the federation. The ESGF Compute Working Team (CWT) has created a Web Processing Service (WPS) Application Programming Interface (API) to enable access scalable computational resources. The API is the exposure point to high performance computing resources across the federation. Specifically, the API allows users to execute simple operations, such as maximum, minimum, average, and anomalies, on ESGF data without having to download the data. These operations are executed at the ESGF data node site with access to large amounts of parallel computing capabilities. This presentation will highlight the WPS API, its capabilities, provide implementation details, and discuss future developments.

The Study Team for Early Life Asthma Research (STELAR) consortium ‘Asthma e-lab’: team science bringing data, methods and investigators together

PubMed Central

Custovic, Adnan; Ainsworth, John; Arshad, Hasan; Bishop, Christopher; Buchan, Iain; Cullinan, Paul; Devereux, Graham; Henderson, John; Holloway, John; Roberts, Graham; Turner, Steve; Woodcock, Ashley; Simpson, Angela

2015-01-01

We created Asthma e-Lab, a secure web-based research environment to support consistent recording, description and sharing of data, computational/statistical methods and emerging findings across the five UK birth cohorts. The e-Lab serves as a data repository for our unified dataset and provides the computational resources and a scientific social network to support collaborative research. All activities are transparent, and emerging findings are shared via the e-Lab, linked to explanations of analytical methods, thus enabling knowledge transfer. eLab facilitates the iterative interdisciplinary dialogue between clinicians, statisticians, computer scientists, mathematicians, geneticists and basic scientists, capturing collective thought behind the interpretations of findings. PMID:25805205

Identifying the Factors Leading to Success: How an Innovative Science Curriculum Cultivates Student Motivation

ERIC Educational Resources Information Center

Scogin, Stephen C.

2016-01-01

"PlantingScience" is an award-winning program recognized for its innovation and use of computer-supported scientist mentoring. Science learners work on inquiry-based experiments in their classrooms and communicate asynchronously with practicing plant scientist-mentors about the projects. The purpose of this study was to identify specific…

Tessera: Open source software for accelerated data science

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

Sego, Landon H.; Hafen, Ryan P.; Director, Hannah M.

2014-06-30

Extracting useful, actionable information from data can be a formidable challenge for the safeguards, nonproliferation, and arms control verification communities. Data scientists are often on the “front-lines” of making sense of complex and large datasets. They require flexible tools that make it easy to rapidly reformat large datasets, interactively explore and visualize data, develop statistical algorithms, and validate their approaches—and they need to perform these activities with minimal lines of code. Existing commercial software solutions often lack extensibility and the flexibility required to address the nuances of the demanding and dynamic environments where data scientists work. To address this need,more » Pacific Northwest National Laboratory developed Tessera, an open source software suite designed to enable data scientists to interactively perform their craft at the terabyte scale. Tessera automatically manages the complicated tasks of distributed storage and computation, empowering data scientists to do what they do best: tackling critical research and mission objectives by deriving insight from data. We illustrate the use of Tessera with an example analysis of computer network data.« less

Preface: SciDAC 2006

NASA Astrophysics Data System (ADS)

Tang, William M., Dr.

2006-01-01

The second annual Scientific Discovery through Advanced Computing (SciDAC) Conference was held from June 25-29, 2006 at the new Hyatt Regency Hotel in Denver, Colorado. This conference showcased outstanding SciDAC-sponsored computational science results achieved during the past year across many scientific domains, with an emphasis on science at scale. Exciting computational science that has been accomplished outside of the SciDAC program both nationally and internationally was also featured to help foster communication between SciDAC computational scientists and those funded by other agencies. This was illustrated by many compelling examples of how domain scientists collaborated productively with applied mathematicians and computer scientists to effectively take advantage of terascale computers (capable of performing trillions of calculations per second) not only to accelerate progress in scientific discovery in a variety of fields but also to show great promise for being able to utilize the exciting petascale capabilities in the near future. The SciDAC program was originally conceived as an interdisciplinary computational science program based on the guiding principle that strong collaborative alliances between domain scientists, applied mathematicians, and computer scientists are vital to accelerated progress and associated discovery on the world's most challenging scientific problems. Associated verification and validation are essential in this successful program, which was funded by the US Department of Energy Office of Science (DOE OS) five years ago. As is made clear in many of the papers in these proceedings, SciDAC has fundamentally changed the way that computational science is now carried out in response to the exciting challenge of making the best use of the rapid progress in the emergence of more and more powerful computational platforms. In this regard, Dr. Raymond Orbach, Energy Undersecretary for Science at the DOE and Director of the OS has stated: `SciDAC has strengthened the role of high-end computing in furthering science. It is defining whole new fields for discovery.' (SciDAC Review, Spring 2006, p8). Application domains within the SciDAC 2006 conference agenda encompassed a broad range of science including: (i) the DOE core mission of energy research involving combustion studies relevant to fuel efficiency and pollution issues faced today and magnetic fusion investigations impacting prospects for future energy sources; (ii) fundamental explorations into the building blocks of matter, ranging from quantum chromodynamics - the basic theory that describes how quarks make up the protons and neutrons of all matter - to the design of modern high-energy accelerators; (iii) the formidable challenges of predicting and controlling the behavior of molecules in quantum chemistry and the complex biomolecules determining the evolution of biological systems; (iv) studies of exploding stars for insights into the nature of the universe; and (v) integrated climate modeling to enable realistic analysis of earth's changing climate. Associated research has made it quite clear that advanced computation is often the only means by which timely progress is feasible when dealing with these complex, multi-component physical, chemical, and biological systems operating over huge ranges of temporal and spatial scales. Working with the domain scientists, applied mathematicians and computer scientists have continued to develop the discretizations of the underlying equations and the complementary algorithms to enable improvements in solutions on modern parallel computing platforms as they evolve from the terascale toward the petascale regime. Moreover, the associated tremendous growth of data generated from the terabyte to the petabyte range demands not only the advanced data analysis and visualization methods to harvest the scientific information but also the development of efficient workflow strategies which can deal with the data input/output, management, movement, and storage challenges. If scientific discovery is expected to keep apace with the continuing progression from tera- to petascale platforms, the vital alliance between domain scientists, applied mathematicians, and computer scientists will be even more crucial. During the SciDAC 2006 Conference, some of the future challenges and opportunities in interdisciplinary computational science were emphasized in the Advanced Architectures Panel and by Dr. Victor Reis, Senior Advisor to the Secretary of Energy, who gave a featured presentation on `Simulation, Computation, and the Global Nuclear Energy Partnership.' Overall, the conference provided an excellent opportunity to highlight the rising importance of computational science in the scientific enterprise and to motivate future investment in this area. As Michael Strayer, SciDAC Program Director, has noted: `While SciDAC may have started out as a specific program, Scientific Discovery through Advanced Computing has become a powerful concept for addressing some of the biggest challenges facing our nation and our world.' Looking forward to next year, the SciDAC 2007 Conference will be held from June 24-28 at the Westin Copley Plaza in Boston, Massachusetts. Chairman: David Keyes, Columbia University. The Organizing Committee for the SciDAC 2006 Conference would like to acknowledge the individuals whose talents and efforts were essential to the success of the meeting. Special thanks go to Betsy Riley for her leadership in building the infrastructure support for the conference, for identifying and then obtaining contributions from our corporate sponsors, for coordinating all media communications, and for her efforts in organizing and preparing the conference proceedings for publication; to Tim Jones for handling the hotel scouting, subcontracts, and exhibits and stage production; to Angela Harris for handling supplies, shipping, and tracking, poster sessions set-up, and for her efforts in coordinating and scheduling the promotional activities that took place during the conference; to John Bui and John Smith for their superb wireless networking and A/V set-up and support; to Cindy Latham for Web site design, graphic design, and quality control of proceedings submissions; and to Pamelia Nixon-Hartje of Ambassador for budget and quality control of catering. We are grateful for the highly professional dedicated efforts of all of these individuals, who were the cornerstones of the SciDAC 2006 Conference. Thanks also go to Angela Beach of the ORNL Conference Center for her efforts in executing the contracts with the hotel, Carolyn James of Colorado State for on-site registration supervision, Lora Wolfe and Brittany Hagen for administrative support at ORNL, and Dami Rich and Andrew Sproles for graphic design and production. We are also most grateful to the Oak Ridge National Laboratory, especially Jeff Nichols, and to our corporate sponsors, Data Direct Networks, Cray, IBM, SGI, and Institute of Physics Publishing for their support. We especially express our gratitude to the featured speakers, invited oral speakers, invited poster presenters, session chairs, and advanced architecture panelists and chair for their excellent contributions on behalf of SciDAC 2006. We would like to express our deep appreciation to Lali Chatterjee, Graham Douglas, Margaret Smith, and the production team of Institute of Physics Publishing, who worked tirelessly to publish the final conference proceedings in a timely manner. Finally, heartfelt thanks are extended to Michael Strayer, Associate Director for OASCR and SciDAC Director, and to the DOE program managers associated with SciDAC for their continuing enthusiasm and strong support for the annual SciDAC Conferences as a special venue to showcase the exciting scientific discovery achievements enabled by the interdisciplinary collaborations championed by the SciDAC program.

Cross Domain Deterrence: Livermore Technical Report, 2014-2016

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

Barnes, Peter D.; Bahney, Ben; Matarazzo, Celeste

2016-08-03

Lawrence Livermore National Laboratory (LLNL) is an original collaborator on the project titled “Deterring Complex Threats: The Effects of Asymmetry, Interdependence, and Multi-polarity on International Strategy,” (CDD Project) led by the UC Institute on Global Conflict and Cooperation at UCSD under PIs Jon Lindsay and Erik Gartzke , and funded through the DoD Minerva Research Initiative. In addition to participating in workshops and facilitating interaction among UC social scientists, LLNL is leading the computational modeling effort and assisting with empirical case studies to probe the viability of analytic, modeling and data analysis concepts. This report summarizes LLNL work on themore » CDD Project to date, primarily in Project Years 1-2, corresponding to Federal fiscal year 2015. LLNL brings two unique domains of expertise to bear on this Project: (1) access to scientific expertise on the technical dimensions of emerging threat technology, and (2) high performance computing (HPC) expertise, required for analyzing the complexity of bargaining interactions in the envisioned threat models. In addition, we have a small group of researchers trained as social scientists who are intimately familiar with the International Relations research. We find that pairing simulation scientists, who are typically trained in computer science, with domain experts, social scientists in this case, is the most effective route to developing powerful new simulation tools capable of representing domain concepts accurately and answering challenging questions in the field.« less

Implementations of the CC'01 Human-Computer Interaction Guidelines Using Bloom's Taxonomy

ERIC Educational Resources Information Center

Manaris, Bill; Wainer, Michael; Kirkpatrick, Arthur E.; Stalvey, RoxAnn H.; Shannon, Christine; Leventhal, Laura; Barnes, Julie; Wright, John; Schafer, J. Ben; Sanders, Dean

2007-01-01

In today's technology-laden society human-computer interaction (HCI) is an important knowledge area for computer scientists and software engineers. This paper surveys existing approaches to incorporate HCI into computer science (CS) and such related issues as the perceived gap between the interests of the HCI community and the needs of CS…

Eckert, Wallace John (1902-71)

NASA Astrophysics Data System (ADS)

Murdin, P.

2000-11-01

Computer scientist and astronomer. Born in Pittsburgh, PA, Eckert was a pioneer of the use of IBM punched card equipment for astronomical calculations. As director of the US Nautical Almanac Office he introduced computer methods to calculate and print tables instead of relying on human `computers'. When, later, he became director of the Watson Scientific Computing Laboratory at Columbia Universit...

"I'm Good, but Not That Good": Digitally-Skilled Young People's Identity in Computing

ERIC Educational Resources Information Center

Wong, Billy

2017-01-01

Computers and information technology are fast becoming a part of young people's everyday life. However, there remains a difference between the majority who can use computers and the minority who are computer scientists or professionals. Drawing on 32 semi-structured interviews with digitally skilled young people (aged 13-19), we explore their…

Computers in Education: Realizing the Potential. Chairmen's Report of a Research Conference, Pittsburgh, Pennsylvania, November 20-24, 1982.

ERIC Educational Resources Information Center

Lesgold, Alan; Reif, Frederick

The future of computers in education and the research needed to realize the computer's potential are discussed in this report, which presents a summary and the conclusions from an invitational conference involving 40 computer scientists, psychologists, educational researchers, teachers, school administrators, and parents. The summary stresses the…

2005 White Paper on Institutional Capability Computing Requirements

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

Carnes, B; McCoy, M; Seager, M

This paper documents the need for a significant increase in the computing infrastructure provided to scientists working in the unclassified domains at Lawrence Livermore National Laboratory (LLNL). This need could be viewed as the next step in a broad strategy outlined in the January 2002 White Paper (UCRL-ID-147449) that bears essentially the same name as this document. Therein we wrote: 'This proposed increase could be viewed as a step in a broader strategy linking hardware evolution to applications development that would take LLNL unclassified computational science to a position of distinction if not preeminence by 2006.' This position of distinctionmore » has certainly been achieved. This paper provides a strategy for sustaining this success but will diverge from its 2002 predecessor in that it will: (1) Amplify the scientific and external success LLNL has enjoyed because of the investments made in 2002 (MCR, 11 TF) and 2004 (Thunder, 23 TF). (2) Describe in detail the nature of additional investments that are important to meet both the institutional objectives of advanced capability for breakthrough science and the scientists clearly stated request for adequate capacity and more rapid access to moderate-sized resources. (3) Put these requirements in the context of an overall strategy for simulation science and external collaboration. While our strategy for Multiprogrammatic and Institutional Computing (M&IC) has worked well, three challenges must be addressed to assure and enhance our position. The first is that while we now have over 50 important classified and unclassified simulation codes available for use by our computational scientists, we find ourselves coping with high demand for access and long queue wait times. This point was driven home in the 2005 Institutional Computing Executive Group (ICEG) 'Report Card' to the Deputy Director for Science and Technology (DDST) Office and Computation Directorate management. The second challenge is related to the balance that should be maintained in the simulation environment. With the advent of Thunder, the institution directed a change in course from past practice. Instead of making Thunder available to the large body of scientists, as was MCR, and effectively using it as a capacity system, the intent was to make it available to perhaps ten projects so that these teams could run very aggressive problems for breakthrough science. This usage model established Thunder as a capability system. The challenge this strategy raises is that the majority of scientists have not seen an improvement in capacity computing resources since MCR, thus creating significant tension in the system. The question then is: 'How do we address the institution's desire to maintain the potential for breakthrough science and also meet the legitimate requests from the ICEG to achieve balance?' Both the capability and the capacity environments must be addressed through this one procurement. The third challenge is to reach out more aggressively to the national science community to encourage access to LLNL resources as part of a strategy for sharpening our science through collaboration. Related to this, LLNL has been unable in the past to provide access for sensitive foreign nationals (SFNs) to the Livermore Computing (LC) unclassified 'yellow' network. Identifying some mechanism for data sharing between LLNL computational scientists and SFNs would be a first practical step in fostering cooperative, collaborative relationships with an important and growing sector of the American science community.« less

75 FR 60820 - United States v. Adobe Systems, Inc., et al.; Proposed Final Judgment and Competitive Impact...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-01

... compete for high tech employees, and in particular specialized computer science and engineering talent on the basis of salaries, benefits, and career opportunities. In recent years, talented computer... Venue 4. Each Defendant hires specialized computer engineers and scientists throughout the United States...

Advanced Biomedical Computing Center (ABCC) | DSITP

Cancer.gov

The Advanced Biomedical Computing Center (ABCC), located in Frederick Maryland (MD), provides HPC resources for both NIH/NCI intramural scientists and the extramural biomedical research community. Its mission is to provide HPC support, to provide collaborative research, and to conduct in-house research in various areas of computational biology and biomedical research.

Computer Art--A New Tool in Advertising Graphics.

ERIC Educational Resources Information Center

Wassmuth, Birgit L.

Using computers to produce art began with scientists, mathematicians, and individuals with strong technical backgrounds who used the graphic material as visualizations of data in technical fields. People are using computer art in advertising, as well as in painting; sculpture; music; textile, product, industrial, and interior design; architecture;…

Integrating Computational Science Tools into a Thermodynamics Course

ERIC Educational Resources Information Center

Vieira, Camilo; Magana, Alejandra J.; García, R. Edwin; Jana, Aniruddha; Krafcik, Matthew

2018-01-01

Computational tools and methods have permeated multiple science and engineering disciplines, because they enable scientists and engineers to process large amounts of data, represent abstract phenomena, and to model and simulate complex concepts. In order to prepare future engineers with the ability to use computational tools in the context of…

1001 Ways to run AutoDock Vina for virtual screening

NASA Astrophysics Data System (ADS)

Jaghoori, Mohammad Mahdi; Bleijlevens, Boris; Olabarriaga, Silvia D.

2016-03-01

Large-scale computing technologies have enabled high-throughput virtual screening involving thousands to millions of drug candidates. It is not trivial, however, for biochemical scientists to evaluate the technical alternatives and their implications for running such large experiments. Besides experience with the molecular docking tool itself, the scientist needs to learn how to run it on high-performance computing (HPC) infrastructures, and understand the impact of the choices made. Here, we review such considerations for a specific tool, AutoDock Vina, and use experimental data to illustrate the following points: (1) an additional level of parallelization increases virtual screening throughput on a multi-core machine; (2) capturing of the random seed is not enough (though necessary) for reproducibility on heterogeneous distributed computing systems; (3) the overall time spent on the screening of a ligand library can be improved by analysis of factors affecting execution time per ligand, including number of active torsions, heavy atoms and exhaustiveness. We also illustrate differences among four common HPC infrastructures: grid, Hadoop, small cluster and multi-core (virtual machine on the cloud). Our analysis shows that these platforms are suitable for screening experiments of different sizes. These considerations can guide scientists when choosing the best computing platform and set-up for their future large virtual screening experiments.

1001 Ways to run AutoDock Vina for virtual screening.

PubMed

Jaghoori, Mohammad Mahdi; Bleijlevens, Boris; Olabarriaga, Silvia D

2016-03-01

Large-scale computing technologies have enabled high-throughput virtual screening involving thousands to millions of drug candidates. It is not trivial, however, for biochemical scientists to evaluate the technical alternatives and their implications for running such large experiments. Besides experience with the molecular docking tool itself, the scientist needs to learn how to run it on high-performance computing (HPC) infrastructures, and understand the impact of the choices made. Here, we review such considerations for a specific tool, AutoDock Vina, and use experimental data to illustrate the following points: (1) an additional level of parallelization increases virtual screening throughput on a multi-core machine; (2) capturing of the random seed is not enough (though necessary) for reproducibility on heterogeneous distributed computing systems; (3) the overall time spent on the screening of a ligand library can be improved by analysis of factors affecting execution time per ligand, including number of active torsions, heavy atoms and exhaustiveness. We also illustrate differences among four common HPC infrastructures: grid, Hadoop, small cluster and multi-core (virtual machine on the cloud). Our analysis shows that these platforms are suitable for screening experiments of different sizes. These considerations can guide scientists when choosing the best computing platform and set-up for their future large virtual screening experiments.

hackseq: Catalyzing collaboration between biological and computational scientists via hackathon.

PubMed

2017-01-01

hackseq ( http://www.hackseq.com) was a genomics hackathon with the aim of bringing together a diverse set of biological and computational scientists to work on collaborative bioinformatics projects. In October 2016, 66 participants from nine nations came together for three days for hackseq and collaborated on nine projects ranging from data visualization to algorithm development. The response from participants was overwhelmingly positive with 100% (n = 54) of survey respondents saying they would like to participate in future hackathons. We detail key steps for others interested in organizing a successful hackathon and report excerpts from each project.

hackseq: Catalyzing collaboration between biological and computational scientists via hackathon

PubMed Central

2017-01-01

hackseq ( http://www.hackseq.com) was a genomics hackathon with the aim of bringing together a diverse set of biological and computational scientists to work on collaborative bioinformatics projects. In October 2016, 66 participants from nine nations came together for three days for hackseq and collaborated on nine projects ranging from data visualization to algorithm development. The response from participants was overwhelmingly positive with 100% (n = 54) of survey respondents saying they would like to participate in future hackathons. We detail key steps for others interested in organizing a successful hackathon and report excerpts from each project. PMID:28417000

PVT: An Efficient Computational Procedure to Speed up Next-generation Sequence Analysis

PubMed Central

2014-01-01

Background High-throughput Next-Generation Sequencing (NGS) techniques are advancing genomics and molecular biology research. This technology generates substantially large data which puts up a major challenge to the scientists for an efficient, cost and time effective solution to analyse such data. Further, for the different types of NGS data, there are certain common challenging steps involved in analysing those data. Spliced alignment is one such fundamental step in NGS data analysis which is extremely computational intensive as well as time consuming. There exists serious problem even with the most widely used spliced alignment tools. TopHat is one such widely used spliced alignment tools which although supports multithreading, does not efficiently utilize computational resources in terms of CPU utilization and memory. Here we have introduced PVT (Pipelined Version of TopHat) where we take up a modular approach by breaking TopHat’s serial execution into a pipeline of multiple stages, thereby increasing the degree of parallelization and computational resource utilization. Thus we address the discrepancies in TopHat so as to analyze large NGS data efficiently. Results We analysed the SRA dataset (SRX026839 and SRX026838) consisting of single end reads and SRA data SRR1027730 consisting of paired-end reads. We used TopHat v2.0.8 to analyse these datasets and noted the CPU usage, memory footprint and execution time during spliced alignment. With this basic information, we designed PVT, a pipelined version of TopHat that removes the redundant computational steps during ‘spliced alignment’ and breaks the job into a pipeline of multiple stages (each comprising of different step(s)) to improve its resource utilization, thus reducing the execution time. Conclusions PVT provides an improvement over TopHat for spliced alignment of NGS data analysis. PVT thus resulted in the reduction of the execution time to ~23% for the single end read dataset. Further, PVT designed for paired end reads showed an improved performance of ~41% over TopHat (for the chosen data) with respect to execution time. Moreover we propose PVT-Cloud which implements PVT pipeline in cloud computing system. PMID:24894600

PVT: an efficient computational procedure to speed up next-generation sequence analysis.

PubMed

Maji, Ranjan Kumar; Sarkar, Arijita; Khatua, Sunirmal; Dasgupta, Subhasis; Ghosh, Zhumur

2014-06-04

High-throughput Next-Generation Sequencing (NGS) techniques are advancing genomics and molecular biology research. This technology generates substantially large data which puts up a major challenge to the scientists for an efficient, cost and time effective solution to analyse such data. Further, for the different types of NGS data, there are certain common challenging steps involved in analysing those data. Spliced alignment is one such fundamental step in NGS data analysis which is extremely computational intensive as well as time consuming. There exists serious problem even with the most widely used spliced alignment tools. TopHat is one such widely used spliced alignment tools which although supports multithreading, does not efficiently utilize computational resources in terms of CPU utilization and memory. Here we have introduced PVT (Pipelined Version of TopHat) where we take up a modular approach by breaking TopHat's serial execution into a pipeline of multiple stages, thereby increasing the degree of parallelization and computational resource utilization. Thus we address the discrepancies in TopHat so as to analyze large NGS data efficiently. We analysed the SRA dataset (SRX026839 and SRX026838) consisting of single end reads and SRA data SRR1027730 consisting of paired-end reads. We used TopHat v2.0.8 to analyse these datasets and noted the CPU usage, memory footprint and execution time during spliced alignment. With this basic information, we designed PVT, a pipelined version of TopHat that removes the redundant computational steps during 'spliced alignment' and breaks the job into a pipeline of multiple stages (each comprising of different step(s)) to improve its resource utilization, thus reducing the execution time. PVT provides an improvement over TopHat for spliced alignment of NGS data analysis. PVT thus resulted in the reduction of the execution time to ~23% for the single end read dataset. Further, PVT designed for paired end reads showed an improved performance of ~41% over TopHat (for the chosen data) with respect to execution time. Moreover we propose PVT-Cloud which implements PVT pipeline in cloud computing system.

49 CFR 40.129 - What are the MRO's functions in reviewing laboratory confirmed non-negative drug test results?

Code of Federal Regulations, 2010 CFR

2010-10-01

... scientist signed the form. You are not required to review any other documentation generated by the... of the CCF, containing the certifying scientist's signature. (c) With respect to verified positive...

49 CFR 40.129 - What are the MRO's functions in reviewing laboratory confirmed non-negative drug test results?

Code of Federal Regulations, 2011 CFR

2011-10-01

... scientist signed the form. You are not required to review any other documentation generated by the... of the CCF, containing the certifying scientist's signature. (c) With respect to verified positive...

Comte, Mach, Planck, and Eddington: a study of influence across generations

NASA Astrophysics Data System (ADS)

Batten, Alan H.

2016-04-01

Auguste Comte is frequently ridiculed by astronomers for saying that human beings would never be able to know the physical nature and constitution of the stars. His philosophy, however, influenced scientists throughout his lifetime and for over a century after his death. That influence is traced here in the work of three outstanding scientists who spanned, roughly speaking, three successive generations after his own, namely, Ernst Mach, Max Planck and Arthur Stanley Eddington.

What Physicists Should Know About High Performance Computing - Circa 2002

NASA Astrophysics Data System (ADS)

Frederick, Donald

2002-08-01

High Performance Computing (HPC) is a dynamic, cross-disciplinary field that traditionally has involved applied mathematicians, computer scientists, and others primarily from the various disciplines that have been major users of HPC resources - physics, chemistry, engineering, with increasing use by those in the life sciences. There is a technological dynamic that is powered by economic as well as by technical innovations and developments. This talk will discuss practical ideas to be considered when developing numerical applications for research purposes. Even with the rapid pace of development in the field, the author believes that these concepts will not become obsolete for a while, and will be of use to scientists who either are considering, or who have already started down the HPC path. These principles will be applied in particular to current parallel HPC systems, but there will also be references of value to desktop users. The talk will cover such topics as: computing hardware basics, single-cpu optimization, compilers, timing, numerical libraries, debugging and profiling tools and the emergence of Computational Grids.

Canopy in the Clouds: Integrating Science and Media to Inspire a New Generation of Scientists

NASA Astrophysics Data System (ADS)

Goldsmith, G. R.; Fulton, A. D.; Witherill, C. D.

2008-12-01

Innovative approaches to science education are critical for inspiring a new generation of scientists. In a world where students are inundated with digital media inviting them to explore exciting, emerging disciplines, science often lags behind in using progressive media techniques. Additionally, science education media often neglects to include the scientists conducting research, thereby disconnecting students from the excitement, adventure, and beauty of conducting research in the field. Here we present initial work from a science education media project entitled Canopy in the Clouds. In particular, we address the goals and approach of the project, the logistics associated with generating educational material at a foreign field site, and the challenges associated with effectively integrating science and media. Canopy in the Clouds is designed to engage students in research, motivate a new generation of young scientists, and promote conservation from the perspective of a current research project being conducted in the canopy of a tropical montane cloud forest located in Monteverde, Costa Rica. The project seeks to generate curriculum based on multiple, immersive forms of novel digital media that attract and maintain student attention. By doing so from the perspective of an adventurous research project in a beautiful and highly biodiverse region, we hope to engage students in science and enhance bioliteracy. However, there are considerable logistic considerations associated with such an approach, including safety, travel, permitting, and equipment maintenance. Additionally, the goals of both the scientific research and the educational media project must be balanced in order to meet objectives in a timely fashion. Finally, materials generated in the field must be translated to viable final products and distributed. Work associated with Canopy in the Clouds will thus provide insight into this process and can serve to inform future science education and outreach efforts.

Using pilot data to size a two-arm randomized trial to find a nearly optimal personalized treatment strategy.

PubMed

Laber, Eric B; Zhao, Ying-Qi; Regh, Todd; Davidian, Marie; Tsiatis, Anastasios; Stanford, Joseph B; Zeng, Donglin; Song, Rui; Kosorok, Michael R

2016-04-15

A personalized treatment strategy formalizes evidence-based treatment selection by mapping patient information to a recommended treatment. Personalized treatment strategies can produce better patient outcomes while reducing cost and treatment burden. Thus, among clinical and intervention scientists, there is a growing interest in conducting randomized clinical trials when one of the primary aims is estimation of a personalized treatment strategy. However, at present, there are no appropriate sample size formulae to assist in the design of such a trial. Furthermore, because the sampling distribution of the estimated outcome under an estimated optimal treatment strategy can be highly sensitive to small perturbations in the underlying generative model, sample size calculations based on standard (uncorrected) asymptotic approximations or computer simulations may not be reliable. We offer a simple and robust method for powering a single stage, two-armed randomized clinical trial when the primary aim is estimating the optimal single stage personalized treatment strategy. The proposed method is based on inverting a plugin projection confidence interval and is thereby regular and robust to small perturbations of the underlying generative model. The proposed method requires elicitation of two clinically meaningful parameters from clinical scientists and uses data from a small pilot study to estimate nuisance parameters, which are not easily elicited. The method performs well in simulated experiments and is illustrated using data from a pilot study of time to conception and fertility awareness. Copyright © 2015 John Wiley & Sons, Ltd.

Culture and Workplace Communications: A Comparison of the Technical Communications Practices of Japanese and U.S. Aerospace Engineers and Scientists.

ERIC Educational Resources Information Center

Pinelli, Thomas E.; Sato, Yuko; Barclay, Rebecca O.; Kennedy, John M.

1997-01-01

Japanese (n=94) and U.S. (n=340) aerospace scientists/engineers described time spent communicating information, collaborative writing, importance of technical communication courses, and the use of libraries, computer networks, and technical reports. Japanese respondents had greater language fluency; U.S. respondents spent more time with…

MeDICi Software Superglue for Data Analysis Pipelines

ScienceCinema

Ian Gorton

2017-12-09

The Middleware for Data-Intensive Computing (MeDICi) Integration Framework is an integrated middleware platform developed to solve data analysis and processing needs of scientists across many domains. MeDICi is scalable, easily modified, and robust to multiple languages, protocols, and hardware platforms, and in use today by PNNL scientists for bioinformatics, power grid failure analysis, and text analysis.

Multiscale computing.

PubMed

Kobayashi, M; Irino, T; Sweldens, W

2001-10-23

Multiscale computing (MSC) involves the computation, manipulation, and analysis of information at different resolution levels. Widespread use of MSC algorithms and the discovery of important relationships between different approaches to implementation were catalyzed, in part, by the recent interest in wavelets. We present two examples that demonstrate how MSC can help scientists understand complex data. The first is from acoustical signal processing and the second is from computer graphics.

Information processing, computation, and cognition

PubMed Central

Scarantino, Andrea

2010-01-01

Computation and information processing are among the most fundamental notions in cognitive science. They are also among the most imprecisely discussed. Many cognitive scientists take it for granted that cognition involves computation, information processing, or both – although others disagree vehemently. Yet different cognitive scientists use ‘computation’ and ‘information processing’ to mean different things, sometimes without realizing that they do. In addition, computation and information processing are surrounded by several myths; first and foremost, that they are the same thing. In this paper, we address this unsatisfactory state of affairs by presenting a general and theory-neutral account of computation and information processing. We also apply our framework by analyzing the relations between computation and information processing on one hand and classicism, connectionism, and computational neuroscience on the other. We defend the relevance to cognitive science of both computation, at least in a generic sense, and information processing, in three important senses of the term. Our account advances several foundational debates in cognitive science by untangling some of their conceptual knots in a theory-neutral way. By leveling the playing field, we pave the way for the future resolution of the debates’ empirical aspects. PMID:22210958

PREPARING FOR EXASCALE: ORNL Leadership Computing Application Requirements and Strategy

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

Joubert, Wayne; Kothe, Douglas B; Nam, Hai Ah

2009-12-01

In 2009 the Oak Ridge Leadership Computing Facility (OLCF), a U.S. Department of Energy (DOE) facility at the Oak Ridge National Laboratory (ORNL) National Center for Computational Sciences (NCCS), elicited petascale computational science requirements from leading computational scientists in the international science community. This effort targeted science teams whose projects received large computer allocation awards on OLCF systems. A clear finding of this process was that in order to reach their science goals over the next several years, multiple projects will require computational resources in excess of an order of magnitude more powerful than those currently available. Additionally, for themore » longer term, next-generation science will require computing platforms of exascale capability in order to reach DOE science objectives over the next decade. It is generally recognized that achieving exascale in the proposed time frame will require disruptive changes in computer hardware and software. Processor hardware will become necessarily heterogeneous and will include accelerator technologies. Software must undergo the concomitant changes needed to extract the available performance from this heterogeneous hardware. This disruption portends to be substantial, not unlike the change to the message passing paradigm in the computational science community over 20 years ago. Since technological disruptions take time to assimilate, we must aggressively embark on this course of change now, to insure that science applications and their underlying programming models are mature and ready when exascale computing arrives. This includes initiation of application readiness efforts to adapt existing codes to heterogeneous architectures, support of relevant software tools, and procurement of next-generation hardware testbeds for porting and testing codes. The 2009 OLCF requirements process identified numerous actions necessary to meet this challenge: (1) Hardware capabilities must be advanced on multiple fronts, including peak flops, node memory capacity, interconnect latency, interconnect bandwidth, and memory bandwidth. (2) Effective parallel programming interfaces must be developed to exploit the power of emerging hardware. (3) Science application teams must now begin to adapt and reformulate application codes to the new hardware and software, typified by hierarchical and disparate layers of compute, memory and concurrency. (4) Algorithm research must be realigned to exploit this hierarchy. (5) When possible, mathematical libraries must be used to encapsulate the required operations in an efficient and useful way. (6) Software tools must be developed to make the new hardware more usable. (7) Science application software must be improved to cope with the increasing complexity of computing systems. (8) Data management efforts must be readied for the larger quantities of data generated by larger, more accurate science models. Requirements elicitation, analysis, validation, and management comprise a difficult and inexact process, particularly in periods of technological change. Nonetheless, the OLCF requirements modeling process is becoming increasingly quantitative and actionable, as the process becomes more developed and mature, and the process this year has identified clear and concrete steps to be taken. This report discloses (1) the fundamental science case driving the need for the next generation of computer hardware, (2) application usage trends that illustrate the science need, (3) application performance characteristics that drive the need for increased hardware capabilities, (4) resource and process requirements that make the development and deployment of science applications on next-generation hardware successful, and (5) summary recommendations for the required next steps within the computer and computational science communities.« less

The experiences of female high school students and interest in STEM: Factors leading to the selection of an engineering or computer science major

NASA Astrophysics Data System (ADS)

Genoways, Sharon K.

STEM (Science, Technology, Engineering and Math) education creates critical thinkers, increases science literacy, and enables the next generation of innovators, which leads to new products and processes that sustain our economy (Hossain & Robinson, 2012). We have been hearing the warnings for several years, that there simply are not enough young scientists entering into the STEM professional pathways to replace all of the retiring professionals (Brown, Brown, Reardon, & Merrill, 2011; Harsh, Maltese, & Tai, 2012; Heilbronner, 2011; Scott, 2012). The problem is not necessarily due to a lack of STEM skills and concept proficiency. There also appears to be a lack of interest in these fields. Recent evidence suggests that many of the most proficient students, especially minority students and women, have been gravitating away from science and engineering toward other professions. (President's Council of Advisors on Science and Technology, 2010). The purpose of this qualitative research study was an attempt to determine how high schools can best prepare and encourage young women for a career in engineering or computer science. This was accomplished by interviewing a pool of 21 women, 5 recent high school graduates planning to major in STEM, 5 college students who had completed at least one full year of coursework in an engineering or computer science major and 11 professional women who had been employed as an engineer or computer scientist for at least one full year. These women were asked to share the high school courses, activities, and experiences that best prepared them to pursue an engineering or computer science major. Five central themes emerged from this study; coursework in physics and calculus, promotion of STEM camps and clubs, teacher encouragement of STEM capabilities and careers, problem solving, critical thinking and confidence building activities in the classroom, and allowing students the opportunity to fail and ask questions in a safe environment. These themes may be implemented by any instructor, in any course, who wishes to provide students with the means to success in their quest for a STEM career.

Mobile Devices and GPU Parallelism in Ionospheric Data Processing

NASA Astrophysics Data System (ADS)

Mascharka, D.; Pankratius, V.

2015-12-01

Scientific data acquisition in the field is often constrained by data transfer backchannels to analysis environments. Geoscientists are therefore facing practical bottlenecks with increasing sensor density and variety. Mobile devices, such as smartphones and tablets, offer promising solutions to key problems in scientific data acquisition, pre-processing, and validation by providing advanced capabilities in the field. This is due to affordable network connectivity options and the increasing mobile computational power. This contribution exemplifies a scenario faced by scientists in the field and presents the "Mahali TEC Processing App" developed in the context of the NSF-funded Mahali project. Aimed at atmospheric science and the study of ionospheric Total Electron Content (TEC), this app is able to gather data from various dual-frequency GPS receivers. It demonstrates parsing of full-day RINEX files on mobile devices and on-the-fly computation of vertical TEC values based on satellite ephemeris models that are obtained from NASA. Our experiments show how parallel computing on the mobile device GPU enables fast processing and visualization of up to 2 million datapoints in real-time using OpenGL. GPS receiver bias is estimated through minimum TEC approximations that can be interactively adjusted by scientists in the graphical user interface. Scientists can also perform approximate computations for "quickviews" to reduce CPU processing time and memory consumption. In the final stage of our mobile processing pipeline, scientists can upload data to the cloud for further processing. Acknowledgements: The Mahali project (http://mahali.mit.edu) is funded by the NSF INSPIRE grant no. AGS-1343967 (PI: V. Pankratius). We would like to acknowledge our collaborators at Boston College, Virginia Tech, Johns Hopkins University, Colorado State University, as well as the support of UNAVCO for loans of dual-frequency GPS receivers for use in this project, and Intel for loans of smartphones.

Space Station Simulation Computer System (SCS) study for NASA/MSFC. Volume 2: Baseline architecture report

NASA Technical Reports Server (NTRS)

1990-01-01

NASA's Space Station Freedom Program (SSFP) planning efforts have identified a need for a payload training simulator system to serve as both a training facility and as a demonstrator to validate operational concepts. The envisioned MSFC Payload Training Complex (PTC) required to meet this need will train the Space Station payload scientists, station scientists, and ground controllers to operate the wide variety of experiments that will be onboard the Space Station Freedom. The Simulation Computer System (SCS) is the computer hardware, software, and workstations that will support the Payload Training Complex at MSFC. The purpose of this SCS Study is to investigate issues related to the SCS, alternative requirements, simulator approaches, and state-of-the-art technologies to develop candidate concepts and designs.

Space Station Simulation Computer System (SCS) study for NASA/MSFC. Phased development plan

NASA Technical Reports Server (NTRS)

1990-01-01

NASA's Space Station Freedom Program (SSFP) planning efforts have identified a need for a payload training simulator system to serve as both a training facility and as a demonstrator to validate operational concepts. The envisioned MSFC Payload Training Complex (PTC) required to meet this need will train the Space Station payload scientists, station scientists and ground controllers to operate the wide variety of experiments that will be onboard the Space Station Freedom. The Simulation Computer System (SCS) is made up of computer hardware, software, and workstations that will support the Payload Training Complex at MSFC. The purpose of this SCS Study is to investigate issues related to the SCS, alternative requirements, simulator approaches, and state-of-the-art technologies to develop candidate concepts and designs.

BioImg.org: A Catalog of Virtual Machine Images for the Life Sciences

PubMed Central

Dahlö, Martin; Haziza, Frédéric; Kallio, Aleksi; Korpelainen, Eija; Bongcam-Rudloff, Erik; Spjuth, Ola

2015-01-01

Virtualization is becoming increasingly important in bioscience, enabling assembly and provisioning of complete computer setups, including operating system, data, software, and services packaged as virtual machine images (VMIs). We present an open catalog of VMIs for the life sciences, where scientists can share information about images and optionally upload them to a server equipped with a large file system and fast Internet connection. Other scientists can then search for and download images that can be run on the local computer or in a cloud computing environment, providing easy access to bioinformatics environments. We also describe applications where VMIs aid life science research, including distributing tools and data, supporting reproducible analysis, and facilitating education. BioImg.org is freely available at: https://bioimg.org. PMID:26401099

Space Station Simulation Computer System (SCS) study for NASA/MSFC. Volume 1: Baseline architecture report

NASA Technical Reports Server (NTRS)

1990-01-01

NASA's Space Station Freedom Program (SSFP) planning efforts have identified a need for a payload training simulator system to serve as both a training facility and as a demonstrator to validate operational concepts. The envisioned MSFC Payload Training Complex (PTC) required to meet this need will train the Space Station payload scientists, station scientists, and ground controllers to operate the wide variety of experiments that will be onboard the Space Station Freedom. The Simulation Computer System (SCS) is made up of the computer hardware, software, and workstations that will support the Payload Training Complex at MSFC. The purpose of this SCS Study is to investigate issues related to the SCS, alternative requirements, simulator approaches, and state-of-the-art technologies to develop candidate concepts and designs.

BioImg.org: A Catalog of Virtual Machine Images for the Life Sciences.

PubMed

Dahlö, Martin; Haziza, Frédéric; Kallio, Aleksi; Korpelainen, Eija; Bongcam-Rudloff, Erik; Spjuth, Ola

2015-01-01

Virtualization is becoming increasingly important in bioscience, enabling assembly and provisioning of complete computer setups, including operating system, data, software, and services packaged as virtual machine images (VMIs). We present an open catalog of VMIs for the life sciences, where scientists can share information about images and optionally upload them to a server equipped with a large file system and fast Internet connection. Other scientists can then search for and download images that can be run on the local computer or in a cloud computing environment, providing easy access to bioinformatics environments. We also describe applications where VMIs aid life science research, including distributing tools and data, supporting reproducible analysis, and facilitating education. BioImg.org is freely available at: https://bioimg.org.

Space Station Simulation Computer System (SCS) study for NASA/MSFC. Operations concept report

NASA Technical Reports Server (NTRS)

1990-01-01

NASA's Space Station Freedom Program (SSFP) planning efforts have identified a need for a payload training simulator system to serve as both a training facility and as a demonstrator to validate operational concepts. The envisioned MSFC Payload Training Complex (PTC) required to meet this need will train the Space Station payload scientists, station scientists, and ground controllers to operate the wide variety of experiments that will be onboard the Space Station Freedom. The Simulation Computer System (SCS) is made up of computer hardware, software, and workstations that will support the Payload Training Complex at MSFC. The purpose of this SCS Study is to investigate issues related to the SCS, alternative requirements, simulator approaches, and state-of-the-art technologies to develop candidate concepts and designs.

Ground Support Software for Spaceborne Instrumentation

NASA Technical Reports Server (NTRS)

Anicich, Vincent; Thorpe, rob; Fletcher, Greg; Waite, Hunter; Xu, Hykua; Walter, Erin; Frick, Kristie; Farris, Greg; Gell, Dave; Furman, Jufy;

Preparing for in situ processing on upcoming leading-edge supercomputers

DOE PAGES

Kress, James; Churchill, Randy Michael; Klasky, Scott; ...

2016-10-01

High performance computing applications are producing increasingly large amounts of data and placing enormous stress on current capabilities for traditional post-hoc visualization techniques. Because of the growing compute and I/O imbalance, data reductions, including in situ visualization, are required. These reduced data are used for analysis and visualization in a variety of different ways. Many of he visualization and analysis requirements are known a priori, but when they are not, scientists are dependent on the reduced data to accurately represent the simulation in post hoc analysis. The contributions of this paper is a description of the directions we are pursuingmore » to assist a large scale fusion simulation code succeed on the next generation of supercomputers. Finally, these directions include the role of in situ processing for performing data reductions, as well as the tradeoffs between data size and data integrity within the context of complex operations in a typical scientific workflow.« less

An interactive environment for agile analysis and visualization of ChIP-sequencing data.

PubMed

Lerdrup, Mads; Johansen, Jens Vilstrup; Agrawal-Singh, Shuchi; Hansen, Klaus

2016-04-01

To empower experimentalists with a means for fast and comprehensive chromatin immunoprecipitation sequencing (ChIP-seq) data analyses, we introduce an integrated computational environment, EaSeq. The software combines the exploratory power of genome browsers with an extensive set of interactive and user-friendly tools for genome-wide abstraction and visualization. It enables experimentalists to easily extract information and generate hypotheses from their own data and public genome-wide datasets. For demonstration purposes, we performed meta-analyses of public Polycomb ChIP-seq data and established a new screening approach to analyze more than 900 datasets from mouse embryonic stem cells for factors potentially associated with Polycomb recruitment. EaSeq, which is freely available and works on a standard personal computer, can substantially increase the throughput of many analysis workflows, facilitate transparency and reproducibility by automatically documenting and organizing analyses, and enable a broader group of scientists to gain insights from ChIP-seq data.

Alliance for Computational Science Collaboration HBCU Partnership at Fisk University. Final Report 2001

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

Collins, W. E.

2004-08-16

Computational Science plays a big role in research and development in mathematics, science, engineering and biomedical disciplines. The Alliance for Computational Science Collaboration (ACSC) has the goal of training African-American and other minority scientists in the computational science field for eventual employment with the Department of Energy (DOE). The involvements of Historically Black Colleges and Universities (HBCU) in the Alliance provide avenues for producing future DOE African-American scientists. Fisk University has been participating in this program through grants from the DOE. The DOE grant supported computational science activities at Fisk University. The research areas included energy related projects, distributed computing,more » visualization of scientific systems and biomedical computing. Students' involvement in computational science research included undergraduate summer research at Oak Ridge National Lab, on-campus research involving the participation of undergraduates, participation of undergraduate and faculty members in workshops, and mentoring of students. These activities enhanced research and education in computational science, thereby adding to Fisk University's spectrum of research and educational capabilities. Among the successes of the computational science activities are the acceptance of three undergraduate students to graduate schools with full scholarships beginning fall 2002 (one for master degree program and two for Doctoral degree program).« less

Staff | Computational Science | NREL

Science.gov Websites

develops and leads laboratory-wide efforts in high-performance computing and energy-efficient data centers Professional IV-High Perf Computing Jim.Albin@nrel.gov 303-275-4069 Ananthan, Shreyas Senior Scientist - High -Performance Algorithms and Modeling Shreyas.Ananthan@nrel.gov 303-275-4807 Bendl, Kurt IT Professional IV-High

Parallel computer vision

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

Uhr, L.

1987-01-01

This book is written by research scientists involved in the development of massively parallel, but hierarchically structured, algorithms, architectures, and programs for image processing, pattern recognition, and computer vision. The book gives an integrated picture of the programs and algorithms that are being developed, and also of the multi-computer hardware architectures for which these systems are designed.

How to Teach Residue Number System to Computer Scientists and Engineers

ERIC Educational Resources Information Center

Navi, K.; Molahosseini, A. S.; Esmaeildoust, M.

2011-01-01

The residue number system (RNS) has been an important research field in computer arithmetic for many decades, mainly because of its carry-free nature, which can provide high-performance computing architectures with superior delay specifications. Recently, research on RNS has found new directions that have resulted in the introduction of efficient…

A Research and Development Strategy for High Performance Computing.

ERIC Educational Resources Information Center

Office of Science and Technology Policy, Washington, DC.

This report is the result of a systematic review of the status and directions of high performance computing and its relationship to federal research and development. Conducted by the Federal Coordinating Council for Science, Engineering, and Technology (FCCSET), the review involved a series of workshops attended by numerous computer scientists and…

Relevancy in Problem Solving: A Computational Framework

ERIC Educational Resources Information Center

Kwisthout, Johan

2012-01-01

When computer scientists discuss the computational complexity of, for example, finding the shortest path from building A to building B in some town or city, their starting point typically is a formal description of the problem at hand, e.g., a graph with weights on every edge where buildings correspond to vertices, routes between buildings to…

Cultivating Critique: A (Humanoid) Response to the Online Teaching of Critical Thinking

ERIC Educational Resources Information Center

Waggoner, Matt

2013-01-01

The Turing era, defined by British mathematician and computer science pioneer Alan Turing's question about whether or not computers can think, is not over. Philosophers and scientists will continue to haggle over whether thought necessitates intentionality, and whether computation can rise to that level. Meanwhile, another frontier is emerging in…

Knowledge Discovery from Climate Data using Graph-Based Methods

NASA Astrophysics Data System (ADS)

Steinhaeuser, K.

2012-04-01

Climate and Earth sciences have recently experienced a rapid transformation from a historically data-poor to a data-rich environment, thus bringing them into the realm of the Fourth Paradigm of scientific discovery - a term coined by the late Jim Gray (Hey et al. 2009), the other three being theory, experimentation and computer simulation. In particular, climate-related observations from remote sensors on satellites and weather radars, in situ sensors and sensor networks, as well as outputs of climate or Earth system models from large-scale simulations, provide terabytes of spatio-temporal data. These massive and information-rich datasets offer a significant opportunity for advancing climate science and our understanding of the global climate system, yet current analysis techniques are not able to fully realize their potential benefits. We describe a class of computational approaches, specifically from the data mining and machine learning domains, which may be novel to the climate science domain and can assist in the analysis process. Computer scientists have developed spatial and spatio-temporal analysis techniques for a number of years now, and many of them may be applicable and/or adaptable to problems in climate science. We describe a large-scale, NSF-funded project aimed at addressing climate science question using computational analysis methods; team members include computer scientists, statisticians, and climate scientists from various backgrounds. One of the major thrusts is in the development of graph-based methods, and several illustrative examples of recent work in this area will be presented.

Gordian Knots of Prevision: The lessons of history

NASA Astrophysics Data System (ADS)

Fleming, J. R.

2017-12-01

Atmospheric researchers have long attempted to untie the Gordian Knot of meteorology—that intractable and intertwined tangle of observational imprecision, theoretical uncertainties, and non-linear influences—that, if unraveled, would provide perfect prevision of the weather for ten days, of seasonal conditions for the year, and of climatic conditions for a decade, a century, a millennium, or longer. This presentation, based on Inventing Atmospheric Science (M.I.T. Press, 2016), examines the work of four interconnected generations of scientists (Vilhelm Bjerknes, C.-G. Rossby, Harry Wexler, Ed Lorenz) and the influence of four transformative technologies (radio, nuclear, computation, aerospace) from the dawn of applied fluid dynamics to the emergence of the interdisciplinary atmospheric sciences and the new Gordian Knot of chaos.

SOURCE EXPLORER: Towards Web Browser Based Tools for Astronomical Source Visualization and Analysis

NASA Astrophysics Data System (ADS)

Young, M. D.; Hayashi, S.; Gopu, A.

2014-05-01

As a new generation of large format, high-resolution imagers come online (ODI, DECAM, LSST, etc.) we are faced with the daunting prospect of astronomical images containing upwards of hundreds of thousands of identifiable sources. Visualizing and interacting with such large datasets using traditional astronomical tools appears to be unfeasible, and a new approach is required. We present here a method for the display and analysis of arbitrarily large source datasets using dynamically scaling levels of detail, enabling scientists to rapidly move from large-scale spatial overviews down to the level of individual sources and everything in-between. Based on the recognized standards of HTML5+JavaScript, we enable observers and archival users to interact with their images and sources from any modern computer without having to install specialized software. We demonstrate the ability to produce large-scale source lists from the images themselves, as well as overlaying data from publicly available source ( 2MASS, GALEX, SDSS, etc.) or user provided source lists. A high-availability cluster of computational nodes allows us to produce these source maps on demand and customized based on user input. User-generated source lists and maps are persistent across sessions and are available for further plotting, analysis, refinement, and culling.

NAS technical summaries: Numerical aerodynamic simulation program, March 1991 - February 1992

NASA Technical Reports Server (NTRS)

1992-01-01

NASA created the Numerical Aerodynamic Simulation (NAS) Program in 1987 to focus resources on solving critical problems in aeroscience and related disciplines by utilizing the power of the most advanced supercomputers available. The NAS Program provides scientists with the necessary computing power to solve today's most demanding computational fluid dynamics problems and serves as a pathfinder in integrating leading-edge supercomputing technologies, thus benefiting other supercomputer centers in Government and industry. This report contains selected scientific results from the 1991-92 NAS Operational Year, March 4, 1991 to March 3, 1992, which is the fifth year of operation. During this year, the scientific community was given access to a Cray-2 and a Cray Y-MP. The Cray-2, the first generation supercomputer, has four processors, 256 megawords of central memory, and a total sustained speed of 250 million floating point operations per second. The Cray Y-MP, the second generation supercomputer, has eight processors and a total sustained speed of one billion floating point operations per second. Additional memory was installed this year, doubling capacity from 128 to 256 megawords of solid-state storage-device memory. Because of its higher performance, the Cray Y-MP delivered approximately 77 percent of the total number of supercomputer hours used during this year.

Architecture for the Next Generation System Management Tools

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

Gallard, Jerome; Lebre, I Adrien; Morin, Christine

2011-01-01

To get more results or greater accuracy, computational scientists execute their applications on distributed computing platforms such as Clusters, Grids and Clouds. These platforms are different in terms of hardware and software resources as well as locality: some span across multiple sites and multiple administrative domains whereas others are limited to a single site/domain. As a consequence, in order to scale their applica- tions up the scientists have to manage technical details for each target platform. From our point of view, this complexity should be hidden from the scientists who, in most cases, would prefer to focus on their researchmore » rather than spending time dealing with platform configuration concerns. In this article, we advocate for a system management framework that aims to automatically setup the whole run-time environment according to the applications needs. The main difference with regards to usual approaches is that they generally only focus on the software layer whereas we address both the hardware and the software expecta- tions through a unique system. For each application, scientists describe their requirements through the definition of a Virtual Platform (VP) and a Virtual System Environment (VSE). Relying on the VP/VSE definitions, the framework is in charge of: (i) the configuration of the physical infrastructure to satisfy the VP requirements, (ii) the setup of the VP, and (iii) the customization of the execution environment (VSE) upon the former VP. We propose a new formalism that the system can rely upon to successfully perform each of these three steps without burdening the user with the specifics of the configuration for the physical resources, and system management tools. This formalism leverages Goldberg s theory for recursive virtual machines by introducing new concepts based on system virtualization (identity, partitioning, aggregation) and emulation (simple, abstraction). This enables the definition of complex VP/VSE configurations without making assumptions about the hardware and the software re- sources. For each requirement, the system executes the corresponding operation with the appropriate management tool. As a proof of concept, we implemented a first prototype that currently interacts with several system management tools (e.g., OSCAR, the Grid 5000 toolkit, and XtreemOS) and that can be easily extended to integrate new resource brokers or cloud systems such as Nimbus, OpenNebula or Eucalyptus for instance.« less

Protecting genomic data analytics in the cloud: state of the art and opportunities.

PubMed

Tang, Haixu; Jiang, Xiaoqian; Wang, Xiaofeng; Wang, Shuang; Sofia, Heidi; Fox, Dov; Lauter, Kristin; Malin, Bradley; Telenti, Amalio; Xiong, Li; Ohno-Machado, Lucila

2016-10-13

The outsourcing of genomic data into public cloud computing settings raises concerns over privacy and security. Significant advancements in secure computation methods have emerged over the past several years, but such techniques need to be rigorously evaluated for their ability to support the analysis of human genomic data in an efficient and cost-effective manner. With respect to public cloud environments, there are concerns about the inadvertent exposure of human genomic data to unauthorized users. In analyses involving multiple institutions, there is additional concern about data being used beyond agreed research scope and being prcoessed in untrused computational environments, which may not satisfy institutional policies. To systematically investigate these issues, the NIH-funded National Center for Biomedical Computing iDASH (integrating Data for Analysis, 'anonymization' and SHaring) hosted the second Critical Assessment of Data Privacy and Protection competition to assess the capacity of cryptographic technologies for protecting computation over human genomes in the cloud and promoting cross-institutional collaboration. Data scientists were challenged to design and engineer practical algorithms for secure outsourcing of genome computation tasks in working software, whereby analyses are performed only on encrypted data. They were also challenged to develop approaches to enable secure collaboration on data from genomic studies generated by multiple organizations (e.g., medical centers) to jointly compute aggregate statistics without sharing individual-level records. The results of the competition indicated that secure computation techniques can enable comparative analysis of human genomes, but greater efficiency (in terms of compute time and memory utilization) are needed before they are sufficiently practical for real world environments.

Perceptions of the Nature and 'Goodness' of Argument among College Students, Science Teachers, and Scientists

NASA Astrophysics Data System (ADS)

Abi-El-Mona, Issam; Abd-El-Khalick, Fouad

2011-03-01

This study aimed to elucidate college freshmen science students, secondary science teachers, and scientists' perceptions of 'scientific' argument; to compare participants' perceptions with Stephen Toulmin's analytical framework of argument; and to characterize the criteria that participants deployed when assessing the 'quality' or 'goodness' of arguments. Thirty students, teachers, and scientists-with 10 members in each group-participated in two semi-structured individual interviews. During the first interview, participants generated an argument in response to a socioscientific issue. In the second interview, each participant 'evaluated' three arguments generated by a member from each participant group without being privy to the arguer's group membership. Interview transcripts were qualitatively analyzed. The findings point to both similarities and differences between participants' conceptions of argument and those based on Toulmin's analytical framework. Participants used an array of common and idiosyncratic criteria to judge the quality or goodness of argument. Finally, contrary to expectations, participants independently agreed that the 'best' arguments were those generated by participant science teachers.

The making of the Women in Biology forum (WiB) at Bioclues.

PubMed

Singhania, Reeta Rani; Madduru, Dhatri; Pappu, Pranathi; Panchangam, Sameera; Suravajhala, Renuka; Chandrasekharan, Mohanalatha

2014-01-01

The Women in Biology forum (WiB) of Bioclues (India) began in 2009 to promote and support women pursuing careers in bioinformatics and computational biology. WiB was formed in order to help women scientists deprived of basic research, boost the prominence of women scientists particularly from developing countries, and bridge the gender gap to innovation. WiB has also served as a platform to highlight the work of established female scientists in these fields. Several award-winning women researchers have shared their experiences and provided valuable suggestions to WiB. Headed by Mohanalatha Chandrasekharan and supported by Dr. Reeta Rani Singhania and Renuka Suravajhala, WiB has seen major progress in the last couple of years particularly in the two avenues Mentoring and Research, off the four avenues in Bioclues: Mentoring, Outreach, Research and Entrepreneurship (MORE). In line with the Bioclues vision for bioinformatics in India, the WiB Journal Club (JoC) recognizes women scientists working on functional genomics and bioinformatics, and provides scientific mentorship and support for project design and hypothesis formulation. As a part of Bioclues, WiB members practice the group's open-desk policy and its belief that all members are free to express their own thoughts and opinions. The WiB forum appreciates suggestions and welcomes scientists from around the world to be a part of their mission to encourage women to pursue computational biology and bioinformatics.

eButterfly: Leveraging Massive Online Citizen Science for Butterfly Conservation

PubMed Central

Prudic, Kathleen L.; McFarland, Kent P.; Oliver, Jeffrey C.; Hutchinson, Rebecca A.; Long, Elizabeth C.; Kerr, Jeremy T.; Larrivée, Maxim

2017-01-01

Data collection, storage, analysis, visualization, and dissemination are changing rapidly due to advances in new technologies driven by computer science and universal access to the internet. These technologies and web connections place human observers front and center in citizen science-driven research and are critical in generating new discoveries and innovation in such fields as astronomy, biodiversity, and meteorology. Research projects utilizing a citizen science approach address scientific problems at regional, continental, and even global scales otherwise impossible for a single lab or even a small collection of academic researchers. Here we describe eButterfly an integrative checklist-based butterfly monitoring and database web-platform that leverages the skills and knowledge of recreational butterfly enthusiasts to create a globally accessible unified database of butterfly observations across North America. Citizen scientists, conservationists, policy makers, and scientists are using eButterfly data to better understand the biological patterns of butterfly species diversity and how environmental conditions shape these patterns in space and time. eButterfly in collaboration with thousands of butterfly enthusiasts has created a near real-time butterfly data resource producing tens of thousands of observations per year open to all to share and explore. PMID:28524117

Cheaper faster drug development validated by the repositioning of drugs against neglected tropical diseases.

PubMed

Williams, Kevin; Bilsland, Elizabeth; Sparkes, Andrew; Aubrey, Wayne; Young, Michael; Soldatova, Larisa N; De Grave, Kurt; Ramon, Jan; de Clare, Michaela; Sirawaraporn, Worachart; Oliver, Stephen G; King, Ross D

2015-03-06

There is an urgent need to make drug discovery cheaper and faster. This will enable the development of treatments for diseases currently neglected for economic reasons, such as tropical and orphan diseases, and generally increase the supply of new drugs. Here, we report the Robot Scientist 'Eve' designed to make drug discovery more economical. A Robot Scientist is a laboratory automation system that uses artificial intelligence (AI) techniques to discover scientific knowledge through cycles of experimentation. Eve integrates and automates library-screening, hit-confirmation, and lead generation through cycles of quantitative structure activity relationship learning and testing. Using econometric modelling we demonstrate that the use of AI to select compounds economically outperforms standard drug screening. For further efficiency Eve uses a standardized form of assay to compute Boolean functions of compound properties. These assays can be quickly and cheaply engineered using synthetic biology, enabling more targets to be assayed for a given budget. Eve has repositioned several drugs against specific targets in parasites that cause tropical diseases. One validated discovery is that the anti-cancer compound TNP-470 is a potent inhibitor of dihydrofolate reductase from the malaria-causing parasite Plasmodium vivax.

eButterfly: Leveraging Massive Online Citizen Science for Butterfly Consevation.

PubMed

Prudic, Kathleen L; McFarland, Kent P; Oliver, Jeffrey C; Hutchinson, Rebecca A; Long, Elizabeth C; Kerr, Jeremy T; Larrivée, Maxim

2017-05-18

Data collection, storage, analysis, visualization, and dissemination are changing rapidly due to advances in new technologies driven by computer science and universal access to the internet. These technologies and web connections place human observers front and center in citizen science-driven research and are critical in generating new discoveries and innovation in such fields as astronomy, biodiversity, and meteorology. Research projects utilizing a citizen science approach address scientific problems at regional, continental, and even global scales otherwise impossible for a single lab or even a small collection of academic researchers. Here we describe eButterfly an integrative checklist-based butterfly monitoring and database web-platform that leverages the skills and knowledge of recreational butterfly enthusiasts to create a globally accessible unified database of butterfly observations across North America. Citizen scientists, conservationists, policy makers, and scientists are using eButterfly data to better understand the biological patterns of butterfly species diversity and how environmental conditions shape these patterns in space and time. eButterfly in collaboration with thousands of butterfly enthusiasts has created a near real-time butterfly data resource producing tens of thousands of observations per year open to all to share and explore.

Cheaper faster drug development validated by the repositioning of drugs against neglected tropical diseases

PubMed Central

Williams, Kevin; Bilsland, Elizabeth; Sparkes, Andrew; Aubrey, Wayne; Young, Michael; Soldatova, Larisa N.; De Grave, Kurt; Ramon, Jan; de Clare, Michaela; Sirawaraporn, Worachart; Oliver, Stephen G.; King, Ross D.

2015-01-01

There is an urgent need to make drug discovery cheaper and faster. This will enable the development of treatments for diseases currently neglected for economic reasons, such as tropical and orphan diseases, and generally increase the supply of new drugs. Here, we report the Robot Scientist ‘Eve’ designed to make drug discovery more economical. A Robot Scientist is a laboratory automation system that uses artificial intelligence (AI) techniques to discover scientific knowledge through cycles of experimentation. Eve integrates and automates library-screening, hit-confirmation, and lead generation through cycles of quantitative structure activity relationship learning and testing. Using econometric modelling we demonstrate that the use of AI to select compounds economically outperforms standard drug screening. For further efficiency Eve uses a standardized form of assay to compute Boolean functions of compound properties. These assays can be quickly and cheaply engineered using synthetic biology, enabling more targets to be assayed for a given budget. Eve has repositioned several drugs against specific targets in parasites that cause tropical diseases. One validated discovery is that the anti-cancer compound TNP-470 is a potent inhibitor of dihydrofolate reductase from the malaria-causing parasite Plasmodium vivax. PMID:25652463

Synergies and Distinctions between Computational Disciplines in Biomedical Research: Perspective from the Clinical and Translational Science Award Programs

PubMed Central

Bernstam, Elmer V.; Hersh, William R.; Johnson, Stephen B.; Chute, Christopher G.; Nguyen, Hien; Sim, Ida; Nahm, Meredith; Weiner, Mark; Miller, Perry; DiLaura, Robert P.; Overcash, Marc; Lehmann, Harold P.; Eichmann, David; Athey, Brian D.; Scheuermann, Richard H.; Anderson, Nick; Starren, Justin B.; Harris, Paul A.; Smith, Jack W.; Barbour, Ed; Silverstein, Jonathan C.; Krusch, David A.; Nagarajan, Rakesh; Becich, Michael J.

2010-01-01

Clinical and translational research increasingly requires computation. Projects may involve multiple computationally-oriented groups including information technology (IT) professionals, computer scientists and biomedical informaticians. However, many biomedical researchers are not aware of the distinctions among these complementary groups, leading to confusion, delays and sub-optimal results. Although written from the perspective of clinical and translational science award (CTSA) programs within academic medical centers, the paper addresses issues that extend beyond clinical and translational research. The authors describe the complementary but distinct roles of operational IT, research IT, computer science and biomedical informatics using a clinical data warehouse as a running example. In general, IT professionals focus on technology. The authors distinguish between two types of IT groups within academic medical centers: central or administrative IT (supporting the administrative computing needs of large organizations) and research IT (supporting the computing needs of researchers). Computer scientists focus on general issues of computation such as designing faster computers or more efficient algorithms, rather than specific applications. In contrast, informaticians are concerned with data, information and knowledge. Biomedical informaticians draw on a variety of tools, including but not limited to computers, to solve information problems in health care and biomedicine. The paper concludes with recommendations regarding administrative structures that can help to maximize the benefit of computation to biomedical research within academic health centers. PMID:19550198

Research Projects, Technical Reports and Publications

NASA Technical Reports Server (NTRS)

Oliger, Joseph

1996-01-01

The Research Institute for Advanced Computer Science (RIACS) was established by the Universities Space Research Association (USRA) at the NASA Ames Research Center (ARC) on June 6, 1983. RIACS is privately operated by USRA, a consortium of universities with research programs in the aerospace sciences, under contract with NASA. The primary mission of RIACS is to provide research and expertise in computer science and scientific computing to support the scientific missions of NASA ARC. The research carried out at RIACS must change its emphasis from year to year in response to NASA ARC's changing needs and technological opportunities. A flexible scientific staff is provided through a university faculty visitor program, a post doctoral program, and a student visitor program. Not only does this provide appropriate expertise but it also introduces scientists outside of NASA to NASA problems. A small group of core RIACS staff provides continuity and interacts with an ARC technical monitor and scientific advisory group to determine the RIACS mission. RIACS activities are reviewed and monitored by a USRA advisory council and ARC technical monitor. Research at RIACS is currently being done in the following areas: Advanced Methods for Scientific Computing High Performance Networks During this report pefiod Professor Antony Jameson of Princeton University, Professor Wei-Pai Tang of the University of Waterloo, Professor Marsha Berger of New York University, Professor Tony Chan of UCLA, Associate Professor David Zingg of University of Toronto, Canada and Assistant Professor Andrew Sohn of New Jersey Institute of Technology have been visiting RIACS. January 1, 1996 through September 30, 1996 RIACS had three staff scientists, four visiting scientists, one post-doctoral scientist, three consultants, two research associates and one research assistant. RIACS held a joint workshop with Code 1 29-30 July 1996. The workshop was held to discuss needs and opportunities in basic research in computer science in and for NASA applications. There were 14 talks given by NASA, industry and university scientists and three open discussion sessions. There were approximately fifty participants. A proceedings is being prepared. It is planned to have similar workshops on an annual basis. RIACS technical reports are usually preprints of manuscripts that have been submitted to research 'ournals or conference proceedings. A list of these reports for the period January i 1, 1996 through September 30, 1996 is in the Reports and Abstracts section of this report.

Determination of Perceptions of the Teacher Candidates Studying in the Computer and Instructional Technology Department towards Human-Computer Interaction and Related Basic Concepts

ERIC Educational Resources Information Center

Kiyici, Mubin

2011-01-01

HCI is a field which has an increasing popularity by virtue of the spread of the computers and internet and gradually contributes to the production of the user-friendlier software and hardware with the contribution of the scientists from different disciplines. Teacher candidates studying at the computer and instructional technologies department…

Students as Virtual Scientists: An Exploration of Students' and Teachers' Perceived Realness of a Remote Electron Microscopy Investigation

ERIC Educational Resources Information Center

Childers, Gina; Jones, M. Gail

2015-01-01

Remote access technologies enable students to investigate science by utilizing scientific tools and communicating in real-time with scientists and researchers with only a computer and an Internet connection. Very little is known about student perceptions of how real remote investigations are and how immersed the students are in the experience.…

Resident research associateships, postdoctoral research awards 1989: opportunities for research at the U.S. Geological Survey, U.S. Department of the Interior

USGS Publications Warehouse

,; ,

1989-01-01

The scientists of the U.S. Geological Survey are engaged in a wide range of geologic, geophysical, geochemical, hydrologic, and cartographic programs, including the application of computer science to them. These programs offer exciting possibilities for scientific achievement and professional growth to young scientists through participation as Research Associates.

Biography Today: Profiles of People of Interest to Young Readers. Scientists & Inventors Series, Volume 5.

ERIC Educational Resources Information Center

Abbey, Cherie D., Ed.

This book, a special volume focusing on computer-related scientists and inventors, provides 12 biographical profiles of interest to readers ages 9 and above. The Biography Today series was created to appeal to young readers in a format they can enjoy reading and readily understand. Each entry provides at least one picture of the individual…

A survey of big data research

PubMed Central

Fang, Hua; Zhang, Zhaoyang; Wang, Chanpaul Jin; Daneshmand, Mahmoud; Wang, Chonggang; Wang, Honggang

2015-01-01

Big data create values for business and research, but pose significant challenges in terms of networking, storage, management, analytics and ethics. Multidisciplinary collaborations from engineers, computer scientists, statisticians and social scientists are needed to tackle, discover and understand big data. This survey presents an overview of big data initiatives, technologies and research in industries and academia, and discusses challenges and potential solutions. PMID:26504265

Integrating citizen-science data with movement models to estimate the size of a migratory golden eagle population

Treesearch

Andrew J. Dennhardt; Adam E. Duerr; David Brandes; Todd E. Katzner

2015-01-01

Estimating population size is fundamental to conservation and management. Population size is typically estimated using survey data, computer models, or both. Some of the most extensive and often least expensive survey data are those collected by citizen-scientists. A challenge to citizen-scientists is that the vagility of many organisms can complicate data collection....

Grid Computing Environment using a Beowulf Cluster

NASA Astrophysics Data System (ADS)

Alanis, Fransisco; Mahmood, Akhtar

2003-10-01

Custom-made Beowulf clusters using PCs are currently replacing expensive supercomputers to carry out complex scientific computations. At the University of Texas - Pan American, we built a 8 Gflops Beowulf Cluster for doing HEP research using RedHat Linux 7.3 and the LAM-MPI middleware. We will describe how we built and configured our Cluster, which we have named the Sphinx Beowulf Cluster. We will describe the results of our cluster benchmark studies and the run-time plots of several parallel application codes that were compiled in C on the cluster using the LAM-XMPI graphics user environment. We will demonstrate a "simple" prototype grid environment, where we will submit and run parallel jobs remotely across multiple cluster nodes over the internet from the presentation room at Texas Tech. University. The Sphinx Beowulf Cluster will be used for monte-carlo grid test-bed studies for the LHC-ATLAS high energy physics experiment. Grid is a new IT concept for the next generation of the "Super Internet" for high-performance computing. The Grid will allow scientist worldwide to view and analyze huge amounts of data flowing from the large-scale experiments in High Energy Physics. The Grid is expected to bring together geographically and organizationally dispersed computational resources, such as CPUs, storage systems, communication systems, and data sources.

Four stages of a scientific discipline; four types of scientist.

PubMed

Shneider, Alexander M

2009-05-01

In this article I propose the classification of the evolutionary stages that a scientific discipline evolves through and the type of scientists that are the most productive at each stage. I believe that each scientific discipline evolves sequentially through four stages. Scientists at stage one introduce new objects and phenomena as subject matter for a new scientific discipline. To do this they have to introduce a new language adequately describing the subject matter. At stage two, scientists develop a toolbox of methods and techniques for the new discipline. Owing to this advancement in methodology, the spectrum of objects and phenomena that fall into the realm of the new science are further understood at this stage. Most of the specific knowledge is generated at the third stage, at which the highest number of original research publications is generated. The majority of third-stage investigation is based on the initial application of new research methods to objects and/or phenomena. The purpose of the fourth stage is to maintain and pass on scientific knowledge generated during the first three stages. Groundbreaking new discoveries are not made at this stage. However, new ways to present scientific information are generated, and crucial revisions are often made of the role of the discipline within the constantly evolving scientific environment. The very nature of each stage determines the optimal psychological type and modus operandi of the scientist operating within it. Thus, it is not only the talent and devotion of scientists that determines whether they are capable of contributing substantially but, rather, whether they have the 'right type' of talent for the chosen scientific discipline at that time. Understanding the four different evolutionary stages of a scientific discipline might be instrumental for many scientists in optimizing their career path, in addition to being useful in assembling scientific teams, precluding conflicts and maximizing productivity. The proposed model of scientific evolution might also be instrumental for society in organizing and managing the scientific process. No public policy aimed at stimulating the scientific process can be equally beneficial for all four stages. Attempts to apply the same criteria to scientists working on scientific disciplines at different stages of their scientific evolution would be stimulating for one and detrimental for another. In addition, researchers operating at a certain stage of scientific evolution might not possess the mindset adequate to evaluate and stimulate a discipline that is at a different evolutionary stage. This could be the reason for suboptimal implementation of otherwise well-conceived scientific policies.

A Collection of Articles Reprinted from Science & Technology Review on University Relations Program

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

Radousky, H; Rennie, G; Henke, A

2006-08-23

This month's issue has the following articles: (1) The Power of Partnership--Livermore researchers forge strategic collaborations with colleagues from other University of California campuses to further science and better protect the nation; (2) Collaborative Research Prepares Our Next-Generation Scientists and Engineers--Commentary by Laura R. Gilliom; (3) Next-Generation Scientists and Engineers Tap Lab's Resources--University of California Ph.D. candidates work with Livermore scientists and engineers to conduct fundamental research as part of their theses; (4) The Best and the Brightest Come to Livermore--The Lawrence Fellowship Program attracts the most sought-after postdoctoral researchers to the Laboratory; and (5) Faculty on Sabbatical Find amore » Good Home at Livermore--Faculty members from around the world come to the Laboratory as sabbatical scholars.« less

Welcome to the NASA High Performance Computing and Communications Computational Aerosciences (CAS) Workshop 2000

NASA Technical Reports Server (NTRS)

Schulbach, Catherine H. (Editor)

2000-01-01

The purpose of the CAS workshop is to bring together NASA's scientists and engineers and their counterparts in industry, other government agencies, and academia working in the Computational Aerosciences and related fields. This workshop is part of the technology transfer plan of the NASA High Performance Computing and Communications (HPCC) Program. Specific objectives of the CAS workshop are to: (1) communicate the goals and objectives of HPCC and CAS, (2) promote and disseminate CAS technology within the appropriate technical communities, including NASA, industry, academia, and other government labs, (3) help promote synergy among CAS and other HPCC scientists, and (4) permit feedback from peer researchers on issues facing High Performance Computing in general and the CAS project in particular. This year we had a number of exciting presentations in the traditional aeronautics, aerospace sciences, and high-end computing areas and in the less familiar (to many of us affiliated with CAS) earth science, space science, and revolutionary computing areas. Presentations of more than 40 high quality papers were organized into ten sessions and presented over the three-day workshop. The proceedings are organized here for easy access: by author, title and topic.

Scalable data management, analysis and visualization (SDAV) Institute. Final Scientific/Technical Report

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

Geveci, Berk

The purpose of the SDAV institute is to provide tools and expertise in scientific data management, analysis, and visualization to DOE’s application scientists. Our goal is to actively work with application teams to assist them in achieving breakthrough science, and to provide technical solutions in the data management, analysis, and visualization regimes that are broadly used by the computational science community. Over the last 5 years members of our institute worked directly with application scientists and DOE leadership-class facilities to assist them by applying the best tools and technologies at our disposal. We also enhanced our tools based on inputmore » from scientists on their needs. Many of the applications we have been working with are based on connections with scientists established in previous years. However, we contacted additional scientists though our outreach activities, as well as engaging application teams running on leading DOE computing systems. Our approach is to employ an evolutionary development and deployment process: first considering the application of existing tools, followed by the customization necessary for each particular application, and then the deployment in real frameworks and infrastructures. The institute is organized into three areas, each with area leaders, who keep track of progress, engagement of application scientists, and results. The areas are: (1) Data Management, (2) Data Analysis, and (3) Visualization. Kitware has been involved in the Visualization area. This report covers Kitware’s contributions over the last 5 years (February 2012 – February 2017). For details on the work performed by the SDAV institute as a whole, please see the SDAV final report.« less

Moon Search Algorithms for NASA's Dawn Mission to Asteroid Vesta

NASA Technical Reports Server (NTRS)

Memarsadeghi, Nargess; Mcfadden, Lucy A.; Skillman, David R.; McLean, Brian; Mutchler, Max; Carsenty, Uri; Palmer, Eric E.

2012-01-01

A moon or natural satellite is a celestial body that orbits a planetary body such as a planet, dwarf planet, or an asteroid. Scientists seek understanding the origin and evolution of our solar system by studying moons of these bodies. Additionally, searches for satellites of planetary bodies can be important to protect the safety of a spacecraft as it approaches or orbits a planetary body. If a satellite of a celestial body is found, the mass of that body can also be calculated once its orbit is determined. Ensuring the Dawn spacecraft's safety on its mission to the asteroid Vesta primarily motivated the work of Dawn's Satellite Working Group (SWG) in summer of 2011. Dawn mission scientists and engineers utilized various computational tools and techniques for Vesta's satellite search. The objectives of this paper are to 1) introduce the natural satellite search problem, 2) present the computational challenges, approaches, and tools used when addressing this problem, and 3) describe applications of various image processing and computational algorithms for performing satellite searches to the electronic imaging and computer science community. Furthermore, we hope that this communication would enable Dawn mission scientists to improve their satellite search algorithms and tools and be better prepared for performing the same investigation in 2015, when the spacecraft is scheduled to approach and orbit the dwarf planet Ceres.

A short course on measure and probability theories

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

Pebay, Philippe Pierre

2004-02-01

This brief Introduction to Measure Theory, and its applications to Probabilities, corresponds to the lecture notes of a seminar series given at Sandia National Laboratories in Livermore, during the spring of 2003. The goal of these seminars was to provide a minimal background to Computational Combustion scientists interested in using more advanced stochastic concepts and methods, e.g., in the context of uncertainty quantification. Indeed, most mechanical engineering curricula do not provide students with formal training in the field of probability, and even in less in measure theory. However, stochastic methods have been used more and more extensively in the pastmore » decade, and have provided more successful computational tools. Scientists at the Combustion Research Facility of Sandia National Laboratories have been using computational stochastic methods for years. Addressing more and more complex applications, and facing difficult problems that arose in applications showed the need for a better understanding of theoretical foundations. This is why the seminar series was launched, and these notes summarize most of the concepts which have been discussed. The goal of the seminars was to bring a group of mechanical engineers and computational combustion scientists to a full understanding of N. WIENER'S polynomial chaos theory. Therefore, these lectures notes are built along those lines, and are not intended to be exhaustive. In particular, the author welcomes any comments or criticisms.« less

RDNAnalyzer: A tool for DNA secondary structure prediction and sequence analysis

PubMed Central

Afzal, Muhammad; Shahid, Ahmad Ali; Shehzadi, Abida; Nadeem, Shahid; Husnain, Tayyab

2012-01-01

RDNAnalyzer is an innovative computer based tool designed for DNA secondary structure prediction and sequence analysis. It can randomly generate the DNA sequence or user can upload the sequences of their own interest in RAW format. It uses and extends the Nussinov dynamic programming algorithm and has various application for the sequence analysis. It predicts the DNA secondary structure and base pairings. It also provides the tools for routinely performed sequence analysis by the biological scientists such as DNA replication, reverse compliment generation, transcription, translation, sequence specific information as total number of nucleotide bases, ATGC base contents along with their respective percentages and sequence cleaner. RDNAnalyzer is a unique tool developed in Microsoft Visual Studio 2008 using Microsoft Visual C# and Windows Presentation Foundation and provides user friendly environment for sequence analysis. It is freely available. Availability http://www.cemb.edu.pk/sw.html Abbreviations RDNAnalyzer - Random DNA Analyser, GUI - Graphical user interface, XAML - Extensible Application Markup Language. PMID:23055611

Compressing climate model simulations: reducing storage burden while preserving information

NASA Astrophysics Data System (ADS)

Hammerling, Dorit; Baker, Allison; Xu, Haiying; Clyne, John; Li, Samuel

2017-04-01

Climate models, which are run at high spatial and temporal resolutions, generate massive quantities of data. As our computing capabilities continue to increase, storing all of the generated data is becoming a bottleneck, which negatively affects scientific progress. It is thus important to develop methods for representing the full datasets by smaller compressed versions, which still preserve all the critical information and, as an added benefit, allow for faster read and write operations during analysis work. Traditional lossy compression algorithms, as for example used for image files, are not necessarily ideally suited for climate data. While visual appearance is relevant, climate data has additional critical features such as the preservation of extreme values and spatial and temporal gradients. Developing alternative metrics to quantify information loss in a manner that is meaningful to climate scientists is an ongoing process still in its early stages. We will provide an overview of current efforts to develop such metrics to assess existing algorithms and to guide the development of tailored compression algorithms to address this pressing challenge.

Archiving Software Systems: Approaches to Preserve Computational Capabilities

NASA Astrophysics Data System (ADS)

King, T. A.

2014-12-01

A great deal of effort is made to preserve scientific data. Not only because data is knowledge, but it is often costly to acquire and is sometimes collected under unique circumstances. Another part of the science enterprise is the development of software to process and analyze the data. Developed software is also a large investment and worthy of preservation. However, the long term preservation of software presents some challenges. Software often requires a specific technology stack to operate. This can include software, operating systems and hardware dependencies. One past approach to preserve computational capabilities is to maintain ancient hardware long past its typical viability. On an archive horizon of 100 years, this is not feasible. Another approach to preserve computational capabilities is to archive source code. While this can preserve details of the implementation and algorithms, it may not be possible to reproduce the technology stack needed to compile and run the resulting applications. This future forward dilemma has a solution. Technology used to create clouds and process big data can also be used to archive and preserve computational capabilities. We explore how basic hardware, virtual machines, containers and appropriate metadata can be used to preserve computational capabilities and to archive functional software systems. In conjunction with data archives, this provides scientist with both the data and capability to reproduce the processing and analysis used to generate past scientific results.

Experiences with Efficient Methodologies for Teaching Computer Programming to Geoscientists

ERIC Educational Resources Information Center

Jacobs, Christian T.; Gorman, Gerard J.; Rees, Huw E.; Craig, Lorraine E.

2016-01-01

Computer programming was once thought of as a skill required only by professional software developers. But today, given the ubiquitous nature of computation and data science it is quickly becoming necessary for all scientists and engineers to have at least a basic knowledge of how to program. Teaching how to program, particularly to those students…

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…

ICASE

NASA Technical Reports Server (NTRS)

1994-01-01

This report summarizes research conducted at the Institute for Computer Applications in Science and Engineering in the areas of (1) applied and numerical mathematics, including numerical analysis and algorithm development; (2) theoretical and computational research in fluid mechanics in selected areas of interest, including acoustics and combustion; (3) experimental research in transition and turbulence and aerodynamics involving Langley facilities and scientists; and (4) computer science.

Is there a glass ceiling for highly cited scientists at the top of research universities?

PubMed

Ioannidis, John P A

2010-12-01

University leaders aim to protect, shape, and promote the missions of their institutions. I evaluated whether top highly cited scientists are likely to occupy these positions. Of the current leaders of 96 U.S. high research activity universities, only 6 presidents or chancellors were found among the 4009 U.S. scientists listed in the ISIHighlyCited.com database. Of the current leaders of 77 UK universities, only 2 vice-chancellors were found among the 483 UK scientists listed in the same database. In a sample of 100 top-cited clinical medicine scientists and 100 top-cited biology and biochemistry scientists, only 1 and 1, respectively, had served at any time as president of a university. Among the leaders of 25 U.S. universities with the highest citation volumes, only 12 had doctoral degrees in life, natural, physical or computer sciences, and 5 of these 12 had a Hirsch citation index m < 1.0. The participation of highly cited scientists in the top leadership of universities is limited. This could have consequences for the research and overall mission of universities.

New computer system simplifies programming of mathematical equations

NASA Technical Reports Server (NTRS)

Reinfelds, J.; Seitz, R. N.; Wood, L. H.

1966-01-01

Automatic Mathematical Translator /AMSTRAN/ permits scientists or engineers to enter mathematical equations in their natural mathematical format and to obtain an immediate graphical display of the solution. This automatic-programming, on-line, multiterminal computer system allows experienced programmers to solve nonroutine problems.

NASA/DOD Aerospace Knowledge Diffusion Research Project. Paper 14: An analysis of the technical communications practices reported by Israeli and US aerospace engineers and scientists

NASA Technical Reports Server (NTRS)

Barclay, Rebecca O.; Pinelli, Thomas E.; Elazar, David; Kennedy, John M.

1991-01-01

As part of Phase 4 of the NASA/DoD Aerospace Knowledge Diffusion Research Project, two pilot studies were conducted that investigated the technical communications practices of Israeli and U.S. aerospace engineers and scientists. Both studies had the same five objectives: first, to solicit the opinions of aerospace engineers and scientists regarding the importance of technical communications to their profession; second, to determine the use and production of technical communications by aerospace engineers and scientists; third, to seek their view about the appropriate content of an undergraduate course in technical communications; fourth, to determine aerospace engineers' and scientists' use of libraries, technical information centers, and on-line databases; and fifth, to determine the use and importance of computer and information technology to them. A self-administered questionnaire was mailed to randomly selected U.S. aerospace engineers and scientists who are working in cryogenics, adaptive walls, and magnetic suspension. A slightly modified version was sent to Israeli aerospace engineers and scientists working at Israel Aircraft Industries, LTD. Responses of the Israeli and U.S. aerospace engineers and scientists to selected questions are presented in this paper.

The Next Frontier in Communication and the ECLIPPSE Study: Bridging the Linguistic Divide in Secure Messaging.

PubMed

Schillinger, Dean; McNamara, Danielle; Crossley, Scott; Lyles, Courtney; Moffet, Howard H; Sarkar, Urmimala; Duran, Nicholas; Allen, Jill; Liu, Jennifer; Oryn, Danielle; Ratanawongsa, Neda; Karter, Andrew J

2017-01-01

Health systems are heavily promoting patient portals. However, limited health literacy (HL) can restrict online communication via secure messaging (SM) because patients' literacy skills must be sufficient to convey and comprehend content while clinicians must encourage and elicit communication from patients and match patients' literacy level. This paper describes the Employing Computational Linguistics to Improve Patient-Provider Secure Email (ECLIPPSE) study, an interdisciplinary effort bringing together scientists in communication, computational linguistics, and health services to employ computational linguistic methods to (1) create a novel Linguistic Complexity Profile (LCP) to characterize communications of patients and clinicians and demonstrate its validity and (2) examine whether providers accommodate communication needs of patients with limited HL by tailoring their SM responses. We will study >5 million SMs generated by >150,000 ethnically diverse type 2 diabetes patients and >9000 clinicians from two settings: an integrated delivery system and a public (safety net) system. Finally, we will then create an LCP-based automated aid that delivers real-time feedback to clinicians to reduce the linguistic complexity of their SMs. This research will support health systems' journeys to become health literate healthcare organizations and reduce HL-related disparities in diabetes care.

Science& Technology Review June 2003

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

McMahon, D

This month's issue has the following articles: (1) Livermore's Three-Pronged Strategy for High-Performance Computing, Commentary by Dona Crawford; (2) Riding the Waves of Supercomputing Technology--Livermore's Computation Directorate is exploiting multiple technologies to ensure high-performance, cost-effective computing; (3) Chromosome 19 and Lawrence Livermore Form a Long-Lasting Bond--Lawrence Livermore biomedical scientists have played an important role in the Human Genome Project through their long-term research on chromosome 19; (4) A New Way to Measure the Mass of Stars--For the first time, scientists have determined the mass of a star in isolation from other celestial bodies; and (5) Flexibly Fueled Storage Tank Bringsmore » Hydrogen-Powered Cars Closer to Reality--Livermore's cryogenic hydrogen fuel storage tank for passenger cars of the future can accommodate three forms of hydrogen fuel separately or in combination.« less

Community Petascale Project for Accelerator Science and Simulation: Advancing Computational Science for Future Accelerators and Accelerator Technologies

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

Spentzouris, P.; /Fermilab; Cary, J.

The design and performance optimization of particle accelerators are essential for the success of the DOE scientific program in the next decade. Particle accelerators are very complex systems whose accurate description involves a large number of degrees of freedom and requires the inclusion of many physics processes. Building on the success of the SciDAC-1 Accelerator Science and Technology project, the SciDAC-2 Community Petascale Project for Accelerator Science and Simulation (ComPASS) is developing a comprehensive set of interoperable components for beam dynamics, electromagnetics, electron cooling, and laser/plasma acceleration modelling. ComPASS is providing accelerator scientists the tools required to enable the necessarymore » accelerator simulation paradigm shift from high-fidelity single physics process modeling (covered under SciDAC1) to high-fidelity multiphysics modeling. Our computational frameworks have been used to model the behavior of a large number of accelerators and accelerator R&D experiments, assisting both their design and performance optimization. As parallel computational applications, the ComPASS codes have been shown to make effective use of thousands of processors. ComPASS is in the first year of executing its plan to develop the next-generation HPC accelerator modeling tools. ComPASS aims to develop an integrated simulation environment that will utilize existing and new accelerator physics modules with petascale capabilities, by employing modern computing and solver technologies. The ComPASS vision is to deliver to accelerator scientists a virtual accelerator and virtual prototyping modeling environment, with the necessary multiphysics, multiscale capabilities. The plan for this development includes delivering accelerator modeling applications appropriate for each stage of the ComPASS software evolution. Such applications are already being used to address challenging problems in accelerator design and optimization. The ComPASS organization for software development and applications accounts for the natural domain areas (beam dynamics, electromagnetics, and advanced acceleration), and all areas depend on the enabling technologies activities, such as solvers and component technology, to deliver the desired performance and integrated simulation environment. The ComPASS applications focus on computationally challenging problems important for design or performance optimization to all major HEP, NP, and BES accelerator facilities. With the cost and complexity of particle accelerators rising, the use of computation to optimize their designs and find improved operating regimes becomes essential, potentially leading to significant cost savings with modest investment.« less

Community Coordinated Modeling Center: A Powerful Resource in Space Science and Space Weather Education

NASA Astrophysics Data System (ADS)

Chulaki, A.; Kuznetsova, M. M.; Rastaetter, L.; MacNeice, P. J.; Shim, J. S.; Pulkkinen, A. A.; Taktakishvili, A.; Mays, M. L.; Mendoza, A. M. M.; Zheng, Y.; Mullinix, R.; Collado-Vega, Y. M.; Maddox, M. M.; Pembroke, A. D.; Wiegand, C.

2015-12-01

Community Coordinated Modeling Center (CCMC) is a NASA affiliated interagency partnership with the primary goal of aiding the transition of modern space science models into space weather forecasting while supporting space science research. Additionally, over the past ten years it has established itself as a global space science education resource supporting undergraduate and graduate education and research, and spreading space weather awareness worldwide. A unique combination of assets, capabilities and close ties to the scientific and educational communities enable this small group to serve as a hub for raising generations of young space scientists and engineers. CCMC resources are publicly available online, providing unprecedented global access to the largest collection of modern space science models (developed by the international research community). CCMC has revolutionized the way simulations are utilized in classrooms settings, student projects, and scientific labs and serves hundreds of educators, students and researchers every year. Another major CCMC asset is an expert space weather prototyping team primarily serving NASA's interplanetary space weather needs. Capitalizing on its unrivaled capabilities and experiences, the team provides in-depth space weather training to students and professionals worldwide, and offers an amazing opportunity for undergraduates to engage in real-time space weather monitoring, analysis, forecasting and research. In-house development of state-of-the-art space weather tools and applications provides exciting opportunities to students majoring in computer science and computer engineering fields to intern with the software engineers at the CCMC while also learning about the space weather from the NASA scientists.

Google Earth Engine: a new cloud-computing platform for global-scale earth observation data and analysis

NASA Astrophysics Data System (ADS)

Moore, R. T.; Hansen, M. C.

2011-12-01

Google Earth Engine is a new technology platform that enables monitoring and measurement of changes in the earth's environment, at planetary scale, on a large catalog of earth observation data. The platform offers intrinsically-parallel computational access to thousands of computers in Google's data centers. Initial efforts have focused primarily on global forest monitoring and measurement, in support of REDD+ activities in the developing world. The intent is to put this platform into the hands of scientists and developing world nations, in order to advance the broader operational deployment of existing scientific methods, and strengthen the ability for public institutions and civil society to better understand, manage and report on the state of their natural resources. Earth Engine currently hosts online nearly the complete historical Landsat archive of L5 and L7 data collected over more than twenty-five years. Newly-collected Landsat imagery is downloaded from USGS EROS Center into Earth Engine on a daily basis. Earth Engine also includes a set of historical and current MODIS data products. The platform supports generation, on-demand, of spatial and temporal mosaics, "best-pixel" composites (for example to remove clouds and gaps in satellite imagery), as well as a variety of spectral indices. Supervised learning methods are available over the Landsat data catalog. The platform also includes a new application programming framework, or "API", that allows scientists access to these computational and data resources, to scale their current algorithms or develop new ones. Under the covers of the Google Earth Engine API is an intrinsically-parallel image-processing system. Several forest monitoring applications powered by this API are currently in development and expected to be operational in 2011. Combining science with massive data and technology resources in a cloud-computing framework can offer advantages of computational speed, ease-of-use and collaboration, as well as transparency in data and methods. Methods developed for global processing of MODIS data to map land cover are being adopted for use with Landsat data. Specifically, the MODIS Vegetation Continuous Field product methodology has been applied for mapping forest extent and change at national scales using Landsat time-series data sets. Scaling this method to continental and global scales is enabled by Google Earth Engine computing capabilities. By combining the supervised learning VCF approach with the Landsat archive and cloud computing, unprecedented monitoring of land cover dynamics is enabled.

Reducing the Analytical Bottleneck for Domain Scientists: Lessons from a Climate Data Visualization Case Study

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

Dasgupta, Aritra; Poco, Jorge; Bertini, Enrico

2016-01-01

The gap between large-scale data production rate and the rate of generation of data-driven scientific insights has led to an analytical bottleneck in scientific domains like climate, biology, etc. This is primarily due to the lack of innovative analytical tools that can help scientists efficiently analyze and explore alternative hypotheses about the data, and communicate their findings effectively to a broad audience. In this paper, by reflecting on a set of successful collaborative research efforts between with a group of climate scientists and visualization researchers, we introspect how interactive visualization can help reduce the analytical bottleneck for domain scientists.

Triangle Computer Science Distinguished Lecture Series

DTIC Science & Technology

2018-01-30

scientific inquiry - the cell, the brain, the market - as well as in the models developed by scientists over the centuries for studying them. Human...the great objects of scientific inquiry - the cell, the brain, the market - as well as in the models developed by scientists over the centuries for...in principle , secure system operation can be achieved. Massive-Scale Streaming Analytics David Bader, Georgia Institute of Technology (telecast from

The Computer Simulation of Liquids by Molecular Dynamics.

ERIC Educational Resources Information Center

Smith, W.

1987-01-01

Proposes a mathematical computer model for the behavior of liquids using the classical dynamic principles of Sir Isaac Newton and the molecular dynamics method invented by other scientists. Concludes that other applications will be successful using supercomputers to go beyond simple Newtonian physics. (CW)

Interfacing the Experimenter to the Computer: Languages for Psychologists

ERIC Educational Resources Information Center

Wood, Ronald W.; And Others

1975-01-01

An examination and comparison of the computer languages which behavioral scientists are most likely to use: SCAT, INTERACT, SKED, OS/8 Fortran IV, RT11/Fortran, RSX-11M, Data General's Real-Time; Disk Operating System and its Fortran, and interpretative Languages. (EH)

Bioseguridad in Mexico: Pursuing Security between Local and Global Biologies.

PubMed

Wanderer, Emily Mannix

2017-09-01

In the aftermath of the 2009 outbreak of H1N1 influenza, scientists in Mexico sought to develop bioseguridad, that is, to protect biological life in Mexico by safely conducting research on infectious disease. Drawing on ethnographic research in laboratories and with scientists in Mexico, I look at how scientists make claims about local differences in regulations, infrastructure, bodies, and culture. The scientists working with infectious microbes sought to establish how different microbial ecologies, human immune systems, and political and regulatory systems made the risks of research different in Mexico from other countries. In developing bioseguridad, the idea of globalized biology that animates many public health projects was undermined as scientists attended to the elements of place that affected human health and safety. Scientists argued for the importance of local biologies, generating tension with global public health projects and regulations premised on the universality of biology. © 2016 by the American Anthropological Association.

Educational NASA Computational and Scientific Studies (enCOMPASS)

NASA Technical Reports Server (NTRS)

Memarsadeghi, Nargess

2013-01-01

Educational NASA Computational and Scientific Studies (enCOMPASS) is an educational project of NASA Goddard Space Flight Center aimed at bridging the gap between computational objectives and needs of NASA's scientific research, missions, and projects, and academia's latest advances in applied mathematics and computer science. enCOMPASS achieves this goal via bidirectional collaboration and communication between NASA and academia. Using developed NASA Computational Case Studies in university computer science/engineering and applied mathematics classes is a way of addressing NASA's goals of contributing to the Science, Technology, Education, and Math (STEM) National Objective. The enCOMPASS Web site at http://encompass.gsfc.nasa.gov provides additional information. There are currently nine enCOMPASS case studies developed in areas of earth sciences, planetary sciences, and astrophysics. Some of these case studies have been published in AIP and IEEE's Computing in Science and Engineering magazines. A few university professors have used enCOMPASS case studies in their computational classes and contributed their findings to NASA scientists. In these case studies, after introducing the science area, the specific problem, and related NASA missions, students are first asked to solve a known problem using NASA data and past approaches used and often published in a scientific/research paper. Then, after learning about the NASA application and related computational tools and approaches for solving the proposed problem, students are given a harder problem as a challenge for them to research and develop solutions for. This project provides a model for NASA scientists and engineers on one side, and university students, faculty, and researchers in computer science and applied mathematics on the other side, to learn from each other's areas of work, computational needs and solutions, and the latest advances in research and development. This innovation takes NASA science and engineering applications to computer science and applied mathematics university classes, and makes NASA objectives part of the university curricula. There is great potential for growth and return on investment of this program to the point where every major university in the U.S. would use at least one of these case studies in one of their computational courses, and where every NASA scientist and engineer facing a computational challenge (without having resources or expertise to solve it) would use enCOMPASS to formulate the problem as a case study, provide it to a university, and get back their solutions and ideas.

An automated framework for hypotheses generation using literature.

PubMed

Abedi, Vida; Zand, Ramin; Yeasin, Mohammed; Faisal, Fazle Elahi

2012-08-29

In bio-medicine, exploratory studies and hypothesis generation often begin with researching existing literature to identify a set of factors and their association with diseases, phenotypes, or biological processes. Many scientists are overwhelmed by the sheer volume of literature on a disease when they plan to generate a new hypothesis or study a biological phenomenon. The situation is even worse for junior investigators who often find it difficult to formulate new hypotheses or, more importantly, corroborate if their hypothesis is consistent with existing literature. It is a daunting task to be abreast with so much being published and also remember all combinations of direct and indirect associations. Fortunately there is a growing trend of using literature mining and knowledge discovery tools in biomedical research. However, there is still a large gap between the huge amount of effort and resources invested in disease research and the little effort in harvesting the published knowledge. The proposed hypothesis generation framework (HGF) finds "crisp semantic associations" among entities of interest - that is a step towards bridging such gaps. The proposed HGF shares similar end goals like the SWAN but are more holistic in nature and was designed and implemented using scalable and efficient computational models of disease-disease interaction. The integration of mapping ontologies with latent semantic analysis is critical in capturing domain specific direct and indirect "crisp" associations, and making assertions about entities (such as disease X is associated with a set of factors Z). Pilot studies were performed using two diseases. A comparative analysis of the computed "associations" and "assertions" with curated expert knowledge was performed to validate the results. It was observed that the HGF is able to capture "crisp" direct and indirect associations, and provide knowledge discovery on demand. The proposed framework is fast, efficient, and robust in generating new hypotheses to identify factors associated with a disease. A full integrated Web service application is being developed for wide dissemination of the HGF. A large-scale study by the domain experts and associated researchers is underway to validate the associations and assertions computed by the HGF.

A History of the Liberal Arts Computer Science Consortium and Its Model Curricula

ERIC Educational Resources Information Center

Bruce, Kim B.; Cupper, Robert D.; Scot Drysdale, Robert L.

2010-01-01

With the support of a grant from the Sloan Foundation, nine computer scientists from liberal arts colleges came together in October, 1984 to form the Liberal Arts Computer Science Consortium (LACS) and to create a model curriculum appropriate for liberal arts colleges. Over the years the membership has grown and changed, but the focus has remained…

Computers in Education: Realizing the Potential. Report of a Research Conference, Pittsburgh, Pennsylvania, November 20-24, 1982.

ERIC Educational Resources Information Center

Lesgold, Alan M., Ed.; Reif, Frederick, Ed.

The full proceedings are provided here of a conference of 40 teachers, educational researchers, and scientists from both the public and private sectors that centered on the future of computers in education and the research required to realize the computer's educational potential. A summary of the research issues considered and suggested means for…

Simulation Modeling of Lakes in Undergraduate and Graduate Classrooms Increases Comprehension of Climate Change Concepts and Experience with Computational Tools

ERIC Educational Resources Information Center

Carey, Cayelan C.; Gougis, Rebekka Darner

2017-01-01

Ecosystem modeling is a critically important tool for environmental scientists, yet is rarely taught in undergraduate and graduate classrooms. To address this gap, we developed a teaching module that exposes students to a suite of modeling skills and tools (including computer programming, numerical simulation modeling, and distributed computing)…

Sustaining and Extending the Open Science Grid: Science Innovation on a PetaScale Nationwide Facility (DE-FC02-06ER41436) SciDAC-2 Closeout Report

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

Livny, Miron; Shank, James; Ernst, Michael

Under this SciDAC-2 grant the project’s goal w a s t o stimulate new discoveries by providing scientists with effective and dependable access to an unprecedented national distributed computational facility: the Open Science Grid (OSG). We proposed to achieve this through the work of the Open Science Grid Consortium: a unique hands-on multi-disciplinary collaboration of scientists, software developers and providers of computing resources. Together the stakeholders in this consortium sustain and use a shared distributed computing environment that transforms simulation and experimental science in the US. The OSG consortium is an open collaboration that actively engages new research communities. Wemore » operate an open facility that brings together a broad spectrum of compute, storage, and networking resources and interfaces to other cyberinfrastructures, including the US XSEDE (previously TeraGrid), the European Grids for ESciencE (EGEE), as well as campus and regional grids. We leverage middleware provided by computer science groups, facility IT support organizations, and computing programs of application communities for the benefit of consortium members and the US national CI.« less

The Man computer Interactive Data Access System: 25 Years of Interactive Processing.

NASA Astrophysics Data System (ADS)

Lazzara, Matthew A.; Benson, John M.; Fox, Robert J.; Laitsch, Denise J.; Rueden, Joseph P.; Santek, David A.; Wade, Delores M.; Whittaker, Thomas M.; Young, J. T.

1999-02-01

On 12 October 1998, it was the 25th anniversary of the Man computer Interactive Data Access System (McIDAS). On that date in 1973, McIDAS was first used operationally by scientists as a tool for data analysis. Over the last 25 years, McIDAS has undergone numerous architectural changes in an effort to keep pace with changing technology. In its early years, significant technological breakthroughs were required to achieve the functionality needed by atmospheric scientists. Today McIDAS is challenged by new Internet-based approaches to data access and data display. The history and impact of McIDAS, along with some of the lessons learned, are presented here

Applications of genetic programming in cancer research.

PubMed

Worzel, William P; Yu, Jianjun; Almal, Arpit A; Chinnaiyan, Arul M

2009-02-01

The theory of Darwinian evolution is the fundamental keystones of modern biology. Late in the last century, computer scientists began adapting its principles, in particular natural selection, to complex computational challenges, leading to the emergence of evolutionary algorithms. The conceptual model of selective pressure and recombination in evolutionary algorithms allow scientists to efficiently search high dimensional space for solutions to complex problems. In the last decade, genetic programming has been developed and extensively applied for analysis of molecular data to classify cancer subtypes and characterize the mechanisms of cancer pathogenesis and development. This article reviews current successes using genetic programming and discusses its potential impact in cancer research and treatment in the near future.

Bridge over troubled waters: A Synthesis Session to connect ...

EPA Pesticide Factsheets

Lack of access to relevant scientific data has limited decision makers from incorporating scientific information into their management and policy schemes. Yet, there is increasing interest among decision makers and scientists to integrate coastal and marine science into the policy and management process. Strategies designed to build communication between decision makers and scientists can be an effective means to disseminate and/or generate policy relevant scientific information. Here researchers develop, test, and present a workshop model designed to bridge the gap between coastal and marine decision makers and scientists. Researchers identify successful components of such a workshop as well as areas for improvement and recommendations to design and conduct similar workshops in the future. This novel workshop format can be used in other fora to effectively connect decision makers and scientists, and to initiate an iterative process to generate and transfer policy relevant scientific information into evidence-based decisions, an important element in protecting coastal and marine resources. In this paper we develop and present a model for increasing collaboration between scientists and decision makers to promote evidence based decisions. Successes and areas for improvement in the tested model are discussed. This novel workshop model is intended to build and sustain connections, with the ultimate goal of creating better policy and management practices. In a recent

Enabling Wide-Scale Computer Science Education through Improved Automated Assessment Tools

NASA Astrophysics Data System (ADS)

Boe, Bryce A.

There is a proliferating demand for newly trained computer scientists as the number of computer science related jobs continues to increase. University programs will only be able to train enough new computer scientists to meet this demand when two things happen: when there are more primary and secondary school students interested in computer science, and when university departments have the resources to handle the resulting increase in enrollment. To meet these goals, significant effort is being made to both incorporate computational thinking into existing primary school education, and to support larger university computer science class sizes. We contribute to this effort through the creation and use of improved automated assessment tools. To enable wide-scale computer science education we do two things. First, we create a framework called Hairball to support the static analysis of Scratch programs targeted for fourth, fifth, and sixth grade students. Scratch is a popular building-block language utilized to pique interest in and teach the basics of computer science. We observe that Hairball allows for rapid curriculum alterations and thus contributes to wide-scale deployment of computer science curriculum. Second, we create a real-time feedback and assessment system utilized in university computer science classes to provide better feedback to students while reducing assessment time. Insights from our analysis of student submission data show that modifications to the system configuration support the way students learn and progress through course material, making it possible for instructors to tailor assignments to optimize learning in growing computer science classes.

The Gendering of Albert Einstein and Marie Curie in Children's Biographies: Some Tensions

ERIC Educational Resources Information Center

Wilson, Rachel E.; Jarrard, Amber R.; Tippins, Deborah J.

2009-01-01

Few twentieth century scientists have generated as much interest as Albert Einstein and Marie Currie. Their lives are centrally depicted in numerous children's biographies of famous scientists. Yet their stories reflect interesting paradoxes and tacit sets of unexplored sociocultural assumptions about gender in science education and the larger…

ESIP’s new ICUC smartphone app - linking citizen scientists to their own places of wonder

EPA Science Inventory

The Gulf of Maine Council’s EcoSystem Indicator Partnership (ESIP) was formed in 2006 to look at changes in the health of the Gulf of Maine ecosystem through the use of environmental indicators. ESIP has always recognized the value of datasets generated by citizen scientist...

Investigation into Omani Secondary School Students' Perceptions of Scientists and Their Work

ERIC Educational Resources Information Center

Ambusaidi, Abdullah; Al-Muqeemi, Fatma; Al-Salmi, Maya

2015-01-01

The purpose of this study was to investigate Omani 12th grade students' perceptions about scientists and their work and accordingly propose some recommendations in order to encourage new generations to choose science and engineering-oriented specialisations in higher education. A 37-item questionnaire was designed to determine these perceptions…

Methods for Creating and Animating a Computer Model Depicting the Structure and Function of the Sarcoplasmic Reticulum Calcium ATPase Enzyme.

ERIC Educational Resources Information Center

Chen, Alice Y.; McKee, Nancy

1999-01-01

Describes the developmental process used to visualize the calcium ATPase enzyme of the sarcoplasmic reticulum which involves evaluating scientific information, consulting scientists, model making, storyboarding, and creating and editing in a computer medium. (Author/CCM)

Inquiring Minds

Science.gov Websites

-performance Computing Grid Computing Networking Mass Storage Plan for the Future State of the Laboratory to help decipher the language of high-energy physics. Virtual Ask-a-Scientist Read transcripts from past online chat sessions. last modified 1/04/2005 email Fermilab Fermi National Accelerator Laboratory

Computing Logarithms by Hand

ERIC Educational Resources Information Center

Reed, Cameron

2016-01-01

How can old-fashioned tables of logarithms be computed without technology? Today, of course, no practicing mathematician, scientist, or engineer would actually use logarithms to carry out a calculation, let alone worry about deriving them from scratch. But high school students may be curious about the process. This article develops a…

Broken Robustness Analysis: How to make proper climate change conclusions in contradictory multimodal measurement contexts.

NASA Astrophysics Data System (ADS)

Keyser, V.

2015-12-01

Philosophers of science discuss how multiple modes of measurement can generate evidence for the existence and character of a phenomenon (Horwich 1982; Hacking 1983; Franklin and Howson 1984; Collins 1985; Sober 1989; Trout 1993; Culp 1995; Keeley 2002; Staley 2004; Weber 2005; Keyser 2012). But how can this work systematically in climate change measurement? Additionally, what conclusions can scientists and policy-makers draw when different modes of measurement fail to be robust by producing contradictory results? First, I present a new technical account of robust measurement (RAMP) that focuses on the physical independence of measurement processes. I detail how physically independent measurement processes "check each other's results." (This account is in contrast to philosophical accounts of robustness analysis that focus on independent model assumptions or independent measurement products or results.) Second, I present a puzzle about contradictory and divergent climate change measures, which has consistently re-emerged in climate measurement. This discussion will focus on land, drilling, troposphere, and computer simulation measures. Third, to systematically solve this climate measurement puzzle, I use RAMP in the context of drought measurement in order to generate a classification of measurement processes. Here, I discuss how multimodal precipitation measures—e.g., measures of precipitation deficit like the Standard Precipitation Index vs. air humidity measures like the Standardized Relative Humidity Index--can help with the classification scheme of climate change measurement processes. Finally, I discuss how this classification of measures can help scientists and policy-makers draw effective conclusions in contradictory multimodal climate change measurement contexts.

Dante's Volcano

NASA Technical Reports Server (NTRS)

1994-01-01

This video contains two segments: one a 0:01:50 spot and the other a 0:08:21 feature. Dante 2, an eight-legged walking machine, is shown during field trials as it explores the inner depths of an active volcano at Mount Spurr, Alaska. A NASA sponsored team at Carnegie Mellon University built Dante to withstand earth's harshest conditions, to deliver a science payload to the interior of a volcano, and to report on its journey to the floor of a volcano. Remotely controlled from 80-miles away, the robot explored the inner depths of the volcano and information from onboard video cameras and sensors was relayed via satellite to scientists in Anchorage. There, using a computer generated image, controllers tracked the robot's movement. Ultimately the robot team hopes to apply the technology to future planetary missions.

How to See a Recently Discovered Supernova

ScienceCinema

Nugent, Peter

2017-12-12

Berkeley Lab scientist Peter Nugent discusses a recently discovered supernova that is closer to Earth — approximately 21 million light-years away — than any other of its kind in a generation. Astronomers believe they caught the supernova within hours of its explosion, a rare feat made possible with a specialized survey telescope and state-of-the-art computational tools. The finding of such a supernova so early and so close has energized the astronomical community as they are scrambling to observe it with as many telescopes as possible, including the Hubble Space Telescope. More info on how to see it: http://newscenter.lbl.gov/feature-stories/2011/08/31/glimpse-cosmic-explosion/ News release: http://newscenter.lbl.gov/feature-stories/2011/08/25/supernova/

How to See a Recently Discovered Supernova

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

Nugent, Peter

2011-08-31

Berkeley Lab scientist Peter Nugent discusses a recently discovered supernova that is closer to Earth — approximately 21 million light-years away — than any other of its kind in a generation. Astronomers believe they caught the supernova within hours of its explosion, a rare feat made possible with a specialized survey telescope and state-of-the-art computational tools. The finding of such a supernova so early and so close has energized the astronomical community as they are scrambling to observe it with as many telescopes as possible, including the Hubble Space Telescope. More info on how to see it: http://newscenter.lbl.gov/feature-stories/2011/08/31/glimpse-cosmic-explosion/ News release:more » http://newscenter.lbl.gov/feature-stories/2011/08/25/supernova/« less

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

None, None

The Second SIAM Conference on Computational Science and Engineering was held in San Diego from February 10-12, 2003. Total conference attendance was 553. This is a 23% increase in attendance over the first conference. The focus of this conference was to draw attention to the tremendous range of major computational efforts on large problems in science and engineering, to promote the interdisciplinary culture required to meet these large-scale challenges, and to encourage the training of the next generation of computational scientists. Computational Science & Engineering (CS&E) is now widely accepted, along with theory and experiment, as a crucial third modemore » of scientific investigation and engineering design. Aerospace, automotive, biological, chemical, semiconductor, and other industrial sectors now rely on simulation for technical decision support. For federal agencies also, CS&E has become an essential support for decisions on resources, transportation, and defense. CS&E is, by nature, interdisciplinary. It grows out of physical applications and it depends on computer architecture, but at its heart are powerful numerical algorithms and sophisticated computer science techniques. From an applied mathematics perspective, much of CS&E has involved analysis, but the future surely includes optimization and design, especially in the presence of uncertainty. Another mathematical frontier is the assimilation of very large data sets through such techniques as adaptive multi-resolution, automated feature search, and low-dimensional parameterization. The themes of the 2003 conference included, but were not limited to: Advanced Discretization Methods; Computational Biology and Bioinformatics; Computational Chemistry and Chemical Engineering; Computational Earth and Atmospheric Sciences; Computational Electromagnetics; Computational Fluid Dynamics; Computational Medicine and Bioengineering; Computational Physics and Astrophysics; Computational Solid Mechanics and Materials; CS&E Education; Meshing and Adaptivity; Multiscale and Multiphysics Problems; Numerical Algorithms for CS&E; Discrete and Combinatorial Algorithms for CS&E; Inverse Problems; Optimal Design, Optimal Control, and Inverse Problems; Parallel and Distributed Computing; Problem-Solving Environments; Software and Wddleware Systems; Uncertainty Estimation and Sensitivity Analysis; and Visualization and Computer Graphics.« less

Low-cost Citizen Science Balloon Platform for Measuring Air Pollutants to Improve Satellite Retrieval Algorithms

NASA Astrophysics Data System (ADS)

Potosnak, M. J.; Beck-Winchatz, B.; Ritter, P.

2016-12-01

High-altitude balloons (HABs) are an engaging platform for citizen science and formal and informal STEM education. However, the logistics of launching, chasing and recovering a payload on a 1200 g or 1500 g balloon can be daunting for many novice school groups and citizen scientists, and the cost can be prohibitive. In addition, there are many interesting scientific applications that do not require reaching the stratosphere, including measuring atmospheric pollutants in the planetary boundary layer. With a large number of citizen scientist flights, these data can be used to constrain satellite retrieval algorithms. In this poster presentation, we discuss a novel approach based on small (30 g) balloons that are cheap and easy to handle, and low-cost tracking devices (SPOT trackers for hikers) that do not require a radio license. Our scientific goal is to measure air quality in the lower troposphere. For example, particulate matter (PM) is an air pollutant that varies on small spatial scales and has sources in rural areas like biomass burning and farming practices such as tilling. Our HAB platform test flight incorporates an optical PM sensor, an integrated single board computer that records the PM sensor signal in addition to flight parameters (pressure, location and altitude), and a low-cost tracking system. Our goal is for the entire platform to cost less than $500. While the datasets generated by these flights are typically small, integrating a network of flight data from citizen scientists into a form usable for comparison to satellite data will require big data techniques.

Computer measurement of particle sizes in electron microscope images

NASA Technical Reports Server (NTRS)

Hall, E. L.; Thompson, W. B.; Varsi, G.; Gauldin, R.

1976-01-01

Computer image processing techniques have been applied to particle counting and sizing in electron microscope images. Distributions of particle sizes were computed for several images and compared to manually computed distributions. The results of these experiments indicate that automatic particle counting within a reasonable error and computer processing time is feasible. The significance of the results is that the tedious task of manually counting a large number of particles can be eliminated while still providing the scientist with accurate results.

Nature apps: Waiting for the revolution.

PubMed

Jepson, Paul; Ladle, Richard J

2015-12-01

Apps are small task-orientated programs with the potential to integrate the computational and sensing capacities of smartphones with the power of cloud computing, social networking, and crowdsourcing. They have the potential to transform how humans interact with nature, cause a step change in the quantity and resolution of biodiversity data, democratize access to environmental knowledge, and reinvigorate ways of enjoying nature. To assess the extent to which this potential is being exploited in relation to nature, we conducted an automated search of the Google Play Store using 96 nature-related terms. This returned data on ~36 304 apps, of which ~6301 were nature-themed. We found that few of these fully exploit the full range of capabilities inherent in the technology and/or have successfully captured the public imagination. Such breakthroughs will only be achieved by increasing the frequency and quality of collaboration between environmental scientists, information engineers, computer scientists, and interested publics.

TravelingGeologist: an online platform for dissemination of earth science to the masses

NASA Astrophysics Data System (ADS)

Spencer, C. J.; Hoiland, C. W.; Gunderson, K. L.

2016-12-01

To more effectively inspire the next generation of scientists, the earth science community's public outreach efforts must adapt to the changing technological and informational ecosystems in which young people interact online (e.g. blogs, social media, viral marketing, web-based education, etc.). Although there are currently a number of successful individual and institutional efforts to reach potential students through web-based outlets, many of these efforts fail to connect primary researchers directly to a lay audience, relying instead on intermediaries that tend to dilute the recruiting impact of "producer-to-consumer" interactions. Few, if any of these efforts appear to have reached a critical mass of contributing authors and subscribed followers; and there are few available detailed metrics on growth trajectories, impact, or lay reach. We offer data from the TravelingGeologist as a case study in successful direct-to-consumer science outreach and recruitment. The TravelingGeologist is a non-profit, web-based platform on which earth scientists share their experiences in the field with the expressed purpose of attracting and inspiring a new generation of scientists. The TravelingGeologist website is supplemented by various social media platforms that market the content on the main site. Because TravelingGeologist accepts contributions from a variety of earth scientists, it also provides an arena whereon research summaries and vignettes can be shared with the large lay- and expert audience. This gives contributing authors an additional opportunity to demonstrate to government institutions that fund their research projects that they are engaging in efforts to communicate their results to the wider public. Beyond the ability to inspire new students and communicate science to the general public, it is our intent that TravelingGeologist will foster communication and promote collaboration within the earth science community. We have demonstrated that through well-designed web-based media in a wide array of social media markets, earth scientists can disseminate their research to the public and inspire the next generation of earth scientists.

Data Generation in the Discovery Sciences—Learning from the Practices in an Advanced Research Laboratory

NASA Astrophysics Data System (ADS)

Roth, Wolff-Michael

2013-08-01

General scientific literacy includes understanding the grounds on which scientific claims are based. The measurements scientists make and the data that they produce from them generally constitute these grounds. However, the nature of data generation has received relatively little attention from those interested in teaching science through inquiry. To inform curriculum designers about the process of data generation and its relation to the understanding of patterns as these may arise from graphs, this 5-year ethnographic study in one advanced research laboratory was designed to investigate how natural scientists make decisions about the inclusion/exclusion of certain measurements in/from their data sources. The study shows that scientists exclude measurements from their data sources even before attempting to mathematize and interpret the data. The excluded measurements therefore never even enter the ground from and against which the scientific phenomenon emerges and therefore remain invisible to it. I conclude by encouraging science educators to squarely address this aspect of the discovery sciences in their teaching, which has both methodological and ethical implications.

The APECS Virtual Poster Session: a virtual platform for science communication and discussion

NASA Astrophysics Data System (ADS)

Renner, A.; Jochum, K.; Jullion, L.; Pavlov, A.; Liggett, D.; Fugmann, G.; Baeseman, J. L.; Apecs Virtual Poster Session Working Group, T.

2011-12-01

The Virtual Poster Session (VPS) of the Association of Polar Early Career Scientists (APECS) was developed by early career scientists as an online tool for communicating and discussing science and research beyond the four walls of a conference venue. Poster sessions often are the backbone of a conference where especially early career scientists get a chance to communicate their research, discuss ideas, data, and scientific problems with their peers and senior scientists. There, they can hone their 'elevator pitch', discussion skills and presentation skills. APECS has taken the poster session one step further and created the VPS - the same idea but independent from conferences, travel, and location. All that is needed is a computer with internet access. Instead of letting their posters collect dust on the computer's hard drive, scientists can now upload them to the APECS website. There, others have the continuous opportunity to comment, give feedback and discuss the work. Currently, about 200 posters are accessible contributed by authors and co-authors from 34 countries. Since January 2010, researchers can discuss their poster with a broad international audience including fellow researchers, community members, potential colleagues and collaborators, policy makers and educators during monthly conference calls via an internet platform. Recordings of the calls are available online afterwards. Calls so far have included topical sessions on e.g. marine biology, glaciology, or social sciences, and interdisciplinary calls on Arctic sciences or polar research activities in a specific country, e.g. India or Romania. They attracted audiences of scientists at all career stages and from all continents, with on average about 15 persons participating per call. Online tools like the VPS open up new ways for creating collaborations and new research ideas and sharing different methodologies for future projects, pushing aside the boundaries of countries and nations, conferences, offices, and disciplines, and provide early career scientists with easily accessible training opportunities for their communication and outreach skills, independent of their location and funding situation.

Achieving Operational Adaptability: Capacity Building Needs to Become a Warfighting Function

DTIC Science & Technology

2010-04-26

platypus effect as described by David Green in The Serendipity Machine: A Voyage of Discovery Through the Unexpected World of Computers. Early in...the 18th century, the discovery of the platypus challenged the categories of animal life recognized and utilized by scientists in Europe. Scientists...resisted changing their categories for years. At first, they believed the platypus was a fabrication. Later, they resisted change since they were

The dynamics of Brazilian protozoology over the past century.

PubMed

Elias, M Carolina; Floeter-Winter, Lucile M; Mena-Chalco, Jesus P

2016-01-01

Brazilian scientists have been contributing to the protozoology field for more than 100 years with important discoveries of new species such as Trypanosoma cruzi and Leishmania spp. In this work, we used a Brazilian thesis database (Coordination for the Improvement of Higher Education Personnel) covering the period from 1987-2011 to identify researchers who contributed substantially to protozoology. We selected 248 advisors by filtering to obtain researchers who supervised at least 10 theses. Based on a computational analysis of the thesis databases, we found students who were supervised by these scientists. A computational procedure was developed to determine the advisors' scientific ancestors using the Lattes Platform. These analyses provided a list of 1,997 researchers who were inspected through Lattes CV examination and allowed the identification of the pioneers of Brazilian protozoology. Moreover, we investigated the areas in which researchers who earned PhDs in protozoology are now working. We found that 68.4% of them are still in protozoology, while 16.7% have migrated to other fields. We observed that support for protozoology by national or international agencies is clearly correlated with the increase of scientists in the field. Finally, we described the academic genealogy of Brazilian protozoology by formalising the "forest" of Brazilian scientists involved in the study of protozoa and their vectors over the past century.

The dynamics of Brazilian protozoology over the past century

PubMed Central

Elias, M Carolina; Floeter-Winter, Lucile M; Mena-Chalco, Jesus P

2016-01-01

Brazilian scientists have been contributing to the protozoology field for more than 100 years with important discoveries of new species such asTrypanosoma cruzi and Leishmania spp. In this work, we used a Brazilian thesis database (Coordination for the Improvement of Higher Education Personnel) covering the period from 1987-2011 to identify researchers who contributed substantially to protozoology. We selected 248 advisors by filtering to obtain researchers who supervised at least 10 theses. Based on a computational analysis of the thesis databases, we found students who were supervised by these scientists. A computational procedure was developed to determine the advisors’ scientific ancestors using the Lattes Platform. These analyses provided a list of 1,997 researchers who were inspected through Lattes CV examination and allowed the identification of the pioneers of Brazilian protozoology. Moreover, we investigated the areas in which researchers who earned PhDs in protozoology are now working. We found that 68.4% of them are still in protozoology, while 16.7% have migrated to other fields. We observed that support for protozoology by national or international agencies is clearly correlated with the increase of scientists in the field. Finally, we described the academic genealogy of Brazilian protozoology by formalising the “forest” of Brazilian scientists involved in the study of protozoa and their vectors over the past century. PMID:26814646

Human Exploration Ethnography of the Haughton-Mars Project, 1998-1999

NASA Technical Reports Server (NTRS)

Clancey, William J.; Swanson, Keith (Technical Monitor)

1999-01-01

During the past two field seasons, July 1988 and 1999, we have conducted research about the field practices of scientists and engineers at Haughton Crater on Devon Island in the Canadian Arctic, with the objective of determining how people will live and work on Mars. This broad investigation of field life and work practice, part of the Haughton-Mars Project lead by Pascal Lee, spans social and cognitive anthropology, psychology, and computer science. Our approach involves systematic observation and description of activities, places, and concepts, constituting an ethnography of field science at Haughton. Our focus is on human behaviors-what people do, where, when, with whom, and why. By locating behavior in time and place-in contrast with a purely functional or "task oriented" description of work-we find patterns constituting the choreography of interaction between people, their habitat, and their tools. As such, we view the exploration process in terms of a total system comprising a social organization, facilities, terrain/climate, personal identities, artifacts, and computer tools. Because we are computer scientists seeking to develop new kinds of tools for living and working on Mars, we focus on the existing representational tools (such as documents and measuring devices), learning and improvization (such as use of the internet or informal assistance), and prototype computational systems brought to the field. Our research is based on partnership, by which field scientists and engineers actively contribute to our findings, just as we participate in their work and life.

Rice-Map: a new-generation rice genome browser.

PubMed

Wang, Jun; Kong, Lei; Zhao, Shuqi; Zhang, He; Tang, Liang; Li, Zhe; Gu, Xiaocheng; Luo, Jingchu; Gao, Ge

2011-03-30

The concurrent release of rice genome sequences for two subspecies (Oryza sativa L. ssp. japonica and Oryza sativa L. ssp. indica) facilitates rice studies at the whole genome level. Since the advent of high-throughput analysis, huge amounts of functional genomics data have been delivered rapidly, making an integrated online genome browser indispensable for scientists to visualize and analyze these data. Based on next-generation web technologies and high-throughput experimental data, we have developed Rice-Map, a novel genome browser for researchers to navigate, analyze and annotate rice genome interactively. More than one hundred annotation tracks (81 for japonica and 82 for indica) have been compiled and loaded into Rice-Map. These pre-computed annotations cover gene models, transcript evidences, expression profiling, epigenetic modifications, inter-species and intra-species homologies, genetic markers and other genomic features. In addition to these pre-computed tracks, registered users can interactively add comments and research notes to Rice-Map as User-Defined Annotation entries. By smoothly scrolling, dragging and zooming, users can browse various genomic features simultaneously at multiple scales. On-the-fly analysis for selected entries could be performed through dedicated bioinformatic analysis platforms such as WebLab and Galaxy. Furthermore, a BioMart-powered data warehouse "Rice Mart" is offered for advanced users to fetch bulk datasets based on complex criteria. Rice-Map delivers abundant up-to-date japonica and indica annotations, providing a valuable resource for both computational and bench biologists. Rice-Map is publicly accessible at http://www.ricemap.org/, with all data available for free downloading.

DNA methylation data analysis and its application to cancer research

PubMed Central

Ma, Xiaotu; Wang, Yi-Wei; Zhang, Michael Q; Gazdar, Adi F

2013-01-01

With the rapid development of genome-wide high-throughput technologies, including expression arrays, SNP arrays and next-generation sequencing platforms, enormous amounts of molecular data have been generated and deposited in the public domain. The application of computational approaches is required to yield biological insights from this enormous, ever-growing resource. A particularly interesting subset of these resources is related to epigenetic regulation, with DNA methylation being the most abundant data type. In this paper, we will focus on the analysis of DNA methylation data and its application to cancer studies. We first briefly review the molecular techniques that generate such data, much of which has been obtained with the use of the most recent version of Infinium HumanMethylation450 BeadChip® technology (Illumina, CA, USA). We describe the coverage of the methylome by this technique. Several examples of data mining are provided. However, it should be understood that reliance on a single aspect of epigenetics has its limitations. In the not too distant future, these defects may be rectified, providing scientists with previously unavailable opportunities to explore in detail the role of epigenetics in cancer and other disease states. PMID:23750645

Dynamic Collaboration Infrastructure for Hydrologic Science

NASA Astrophysics Data System (ADS)

Tarboton, D. G.; Idaszak, R.; Castillo, C.; Yi, H.; Jiang, F.; Jones, N.; Goodall, J. L.

2016-12-01

Data and modeling infrastructure is becoming increasingly accessible to water scientists. HydroShare is a collaborative environment that currently offers water scientists the ability to access modeling and data infrastructure in support of data intensive modeling and analysis. It supports the sharing of and collaboration around "resources" which are social objects defined to include both data and models in a structured standardized format. Users collaborate around these objects via comments, ratings, and groups. HydroShare also supports web services and cloud based computation for the execution of hydrologic models and analysis and visualization of hydrologic data. However, the quantity and variety of data and modeling infrastructure available that can be accessed from environments like HydroShare is increasing. Storage infrastructure can range from one's local PC to campus or organizational storage to storage in the cloud. Modeling or computing infrastructure can range from one's desktop to departmental clusters to national HPC resources to grid and cloud computing resources. How does one orchestrate this vast number of data and computing infrastructure without needing to correspondingly learn each new system? A common limitation across these systems is the lack of efficient integration between data transport mechanisms and the corresponding high-level services to support large distributed data and compute operations. A scientist running a hydrology model from their desktop may require processing a large collection of files across the aforementioned storage and compute resources and various national databases. To address these community challenges a proof-of-concept prototype was created integrating HydroShare with RADII (Resource Aware Data-centric collaboration Infrastructure) to provide software infrastructure to enable the comprehensive and rapid dynamic deployment of what we refer to as "collaborative infrastructure." In this presentation we discuss the results of this proof-of-concept prototype which enabled HydroShare users to readily instantiate virtual infrastructure marshaling arbitrary combinations, varieties, and quantities of distributed data and computing infrastructure in addressing big problems in hydrology.

Collaborative Learning: Cognitive and Computational Approaches. Advances in Learning and Instruction Series.

ERIC Educational Resources Information Center

Dillenbourg, Pierre, Ed.

Intended to illustrate the benefits of collaboration between scientists from psychology and computer science, namely machine learning, this book contains the following chapters, most of which are co-authored by scholars from both sides: (1) "Introduction: What Do You Mean by 'Collaborative Learning'?" (Pierre Dillenbourg); (2)…

RESEARCH STRATEGIES FOR THE APPLICATION OF THE TECHNIQUES OF COMPUTATIONAL BIOLOGICAL CHEMISTRY TO ENVIRONMENTAL PROBLEMS

EPA Science Inventory

On October 25 and 26, 1984, the U.S. EPA sponsored a workshop to consider the potential applications of the techniques of computational biological chemistry to problems in environmental health. Eleven extramural scientists from the various related disciplines and a similar number...

Debugging Geographers: Teaching Programming to Non-Computer Scientists

ERIC Educational Resources Information Center

Muller, Catherine L.; Kidd, Chris

2014-01-01

The steep learning curve associated with computer programming can be a daunting prospect, particularly for those not well aligned with this way of logical thinking. However, programming is a skill that is becoming increasingly important. Geography graduates entering careers in atmospheric science are one example of a particularly diverse group who…

Using Computers for Research into Social Relations.

ERIC Educational Resources Information Center

Holden, George W.

1988-01-01

Discusses computer-presented social situations (CPSS), i.e., microcomputer-based simulations developed to provide a new methodological tool for social scientists interested in the study of social relations. Two CPSSs are described: DaySim, used to help identify types of parenting; and DateSim, used to study interpersonal attraction. (21…

Brains--Computers--Machines: Neural Engineering in Science Classrooms

ERIC Educational Resources Information Center

Chudler, Eric H.; Bergsman, Kristen Clapper

2016-01-01

Neural engineering is an emerging field of high relevance to students, teachers, and the general public. This feature presents online resources that educators and scientists can use to introduce students to neural engineering and to integrate core ideas from the life sciences, physical sciences, social sciences, computer science, and engineering…

Computer Science Professionals and Greek Library Science

ERIC Educational Resources Information Center

Dendrinos, Markos N.

2008-01-01

This paper attempts to present the current state of computer science penetration into librarianship in terms of both workplace and education issues. The shift from material libraries into digital libraries is mirrored in the corresponding shift from librarians into information scientists. New library data and metadata, as well as new automated…

Describing the What and Why of Students' Difficulties in Boolean Logic

ERIC Educational Resources Information Center

Herman, Geoffrey L.; Loui, Michael C.; Kaczmarczyk, Lisa; Zilles, Craig

2012-01-01

The ability to reason with formal logic is a foundational skill for computer scientists and computer engineers that scaffolds the abilities to design, debug, and optimize. By interviewing students about their understanding of propositional logic and their ability to translate from English specifications to Boolean expressions, we characterized…

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.

Dawn: A Simulation Model for Evaluating Costs and Tradeoffs of Big Data Science Architectures

NASA Astrophysics Data System (ADS)

Cinquini, L.; Crichton, D. J.; Braverman, A. J.; Kyo, L.; Fuchs, T.; Turmon, M.

2014-12-01

In many scientific disciplines, scientists and data managers are bracing for an upcoming deluge of big data volumes, which will increase the size of current data archives by a factor of 10-100 times. For example, the next Climate Model Inter-comparison Project (CMIP6) will generate a global archive of model output of approximately 10-20 Peta-bytes, while the upcoming next generation of NASA decadal Earth Observing instruments are expected to collect tens of Giga-bytes/day. In radio-astronomy, the Square Kilometre Array (SKA) will collect data in the Exa-bytes/day range, of which (after reduction and processing) around 1.5 Exa-bytes/year will be stored. The effective and timely processing of these enormous data streams will require the design of new data reduction and processing algorithms, new system architectures, and new techniques for evaluating computation uncertainty. Yet at present no general software tool or framework exists that will allow system architects to model their expected data processing workflow, and determine the network, computational and storage resources needed to prepare their data for scientific analysis. In order to fill this gap, at NASA/JPL we have been developing a preliminary model named DAWN (Distributed Analytics, Workflows and Numerics) for simulating arbitrary complex workflows composed of any number of data processing and movement tasks. The model can be configured with a representation of the problem at hand (the data volumes, the processing algorithms, the available computing and network resources), and is able to evaluate tradeoffs between different possible workflows based on several estimators: overall elapsed time, separate computation and transfer times, resulting uncertainty, and others. So far, we have been applying DAWN to analyze architectural solutions for 4 different use cases from distinct science disciplines: climate science, astronomy, hydrology and a generic cloud computing use case. This talk will present preliminary results and discuss how DAWN can be evolved into a powerful tool for designing system architectures for data intensive science.

Novel 3-D Computer Model Can Help Predict Pathogens’ Roles in Cancer | Poster

Cancer.gov

To understand how bacterial and viral infections contribute to human cancers, four NCI at Frederick scientists turned not to the lab bench, but to a computer. The team has created the world’s first—and currently, only—3-D computational approach for studying interactions between pathogen proteins and human proteins based on a molecular adaptation known as interface mimicry.

Social and Personal Factors in Semantic Infusion Projects

NASA Astrophysics Data System (ADS)

West, P.; Fox, P. A.; McGuinness, D. L.

2009-12-01

As part of our semantic data framework activities across multiple, diverse disciplines we required the involvement of domain scientists, computer scientists, software engineers, data managers, and often, social scientists. This involvement from a cross-section of disciplines turns out to be a social exercise as much as it is a technical and methodical activity. Each member of the team is used to different modes of working, expectations, vocabularies, levels of participation, and incentive and reward systems. We will examine how both roles and personal responsibilities play in the development of semantic infusion projects, and how an iterative development cycle can contribute to the successful completion of such a project.

WATERS - Integrating Science and Education Through the Development of an Education & Outreach Program that Engages Scientists, Students and Citizens

NASA Astrophysics Data System (ADS)

Eschenbach, E. A.; Conklin, M. H.

2007-12-01

The need to train students in hydrologic science and environmental engineering is well established. Likewise, the public requires a raised awareness of the seriousness of water quality and availability problems. The WATERS Network (WATer and Environmental Research Systems Network ) has the potential to significantly change the way students, researchers, citizens, policy makers and industry members learn about environmental problems and solutions regarding water quality, quantity and distribution. This potential can be met if the efforts of water scientists, computer scientists, and educators are integrated appropriately. Successful pilot projects have found that cyberinfrastructure for education and outreach needs to be developed in parallel with research related cyberinfrastructure. We propose further integration of research, education and outreach activities. Through the use of technology that connects students, faculty, researchers, policy makers and others, WATERS Network can provide learning opportunities and teaching efficiencies that can revolutionize environmental science and engineering education. However, there are a plethora of existing environmental science and engineering educational programs. In this environment, WATERS can make a greater impact through careful selection of activities that build upon its unique strengths, that have high potential for engaging the members, and that meet identified needs: (i) modernizing curricula and pedagogy (ii) integrating science and education, (iii) sustainable professional development, and (iv) training the next generation of interdisciplinary water and social scientists and environmental engineers. National and observatory-based education facilities would establish the physical infrastructure necessary to coordinate education and outreach activities. Each observatory would partner with local educators and citizens to develop activities congruent with the scientific mission of the observatory. An unprecedented opportunity exists for educational research of both formal and informal environmental science and engineering education in order to understand how the Network can be efficiently used to create effective technology-based learning environments for all participants.

Preparing clinical pharmacy scientists for careers in clinical/translational research: can we meet the challenge?: ACCP Research Affairs Committee Commentary.

PubMed

Parker, Robert B; Ellingrod, Vicki; DiPiro, Joseph T; Bauman, Jerry L; Blouin, Robert A; Welage, Lynda S

2013-12-01

Developing clinical pharmacists' research skills and their ability to compete for extramural funding is an important component of the American College of Clinical Pharmacy's (ACCP) vision for pharmacists to play a prominent role in generating the new knowledge used to guide patient pharmacotherapy. Given the recent emphasis on clinical/translational research at the National Institutes of Health (NIH) and the key role of drug therapy in the management of many diseases, there is an unprecedented opportunity for the profession to contribute to this enterprise. A crucial question facing the profession is whether we can generate enough appropriately trained scientists to take advantage of these opportunities to generate the new knowledge to advance drug therapy. Since the 2009 publication of the ACCP Research Affairs Committee editorial recommending the Ph.D. degree (as opposed to fellowship training) as the optimal method for preparing pharmacists as clinical/translational scientists, significant changes have occurred in the economic, professional, political, and research environments. As a result, the 2012 ACCP Research Affairs Committee was charged with reexamining the college's position on training clinical pharmacy scientists in the context of these substantial environmental changes. In this commentary, the potential impact of these changes on opportunities for pharmacists in clinical/translational research are discussed as are strategies for ACCP, colleges of pharmacy, and the profession to increase the number and impact of clinical pharmacy scientists. Failure of our profession to take advantage of these opportunities risks our ability to contribute substantively to the biomedical research enterprise and ultimately improve the pharmacotherapy of our patients. © 2013 Pharmacotherapy Publications, Inc.

Building Capacity Through Hands-on Computational Internships to Assure Reproducible Results and Implementation of Digital Documentation in the ICERT REU Program

NASA Astrophysics Data System (ADS)

Gomez, R.; Gentle, J.

2015-12-01

Modern data pipelines and computational processes require that meticulous methodologies be applied in order to insure that the source data, algorithms, and results are properly curated, managed and retained while remaining discoverable, accessible, and reproducible. Given the complexity of understanding the scientific problem domain being researched, combined with the overhead of learning to use advanced computing technologies, it becomes paramount that the next generation of scientists and researchers learn to embrace best-practices. The Integrative Computational Education and Research Traineeship (ICERT) is a National Science Foundation (NSF) Research Experience for Undergraduates (REU) Site at the Texas Advanced Computing Center (TACC). During Summer 2015, two ICERT interns joined the 3DDY project. 3DDY converts geospatial datasets into file types that can take advantage of new formats, such as natural user interfaces, interactive visualization, and 3D printing. Mentored by TACC researchers for ten weeks, students with no previous background in computational science learned to use scripts to build the first prototype of the 3DDY application, and leveraged Wrangler, the newest high performance computing (HPC) resource at TACC. Test datasets for quadrangles in central Texas were used to assemble the 3DDY workflow and code. Test files were successfully converted into a stereo lithographic (STL) format, which is amenable for use with a 3D printers. Test files and the scripts were documented and shared using the Figshare site while metadata was documented for the 3DDY application using OntoSoft. These efforts validated a straightforward set of workflows to transform geospatial data and established the first prototype version of 3DDY. Adding the data and software management procedures helped students realize a broader set of tangible results (e.g. Figshare entries), better document their progress and the final state of their work for the research group and community, helped students and researchers follow a clear set of formats and fill in the necessary details that may be lost otherwise, and exposed the students to the next generation workflows and practices for digital scholarship and scientific inquiry for converting geospatial data into formats that are easy to reuse.

Data Prospecting Framework - a new approach to explore "big data" in Earth Science

NASA Astrophysics Data System (ADS)

Ramachandran, R.; Rushing, J.; Lin, A.; Kuo, K.

2012-12-01

Due to advances in sensors, computation and storage, cost and effort required to produce large datasets have been significantly reduced. As a result, we are seeing a proliferation of large-scale data sets being assembled in almost every science field, especially in geosciences. Opportunities to exploit the "big data" are enormous as new hypotheses can be generated by combining and analyzing large amounts of data. However, such a data-driven approach to science discovery assumes that scientists can find and isolate relevant subsets from vast amounts of available data. Current Earth Science data systems only provide data discovery through simple metadata and keyword-based searches and are not designed to support data exploration capabilities based on the actual content. Consequently, scientists often find themselves downloading large volumes of data, struggling with large amounts of storage and learning new analysis technologies that will help them separate the wheat from the chaff. New mechanisms of data exploration are needed to help scientists discover the relevant subsets We present data prospecting, a new content-based data analysis paradigm to support data-intensive science. Data prospecting allows the researchers to explore big data in determining and isolating data subsets for further analysis. This is akin to geo-prospecting in which mineral sites of interest are determined over the landscape through screening methods. The resulting "data prospects" only provide an interaction with and feel for the data through first-look analytics; the researchers would still have to download the relevant datasets and analyze them deeply using their favorite analytical tools to determine if the datasets will yield new hypotheses. Data prospecting combines two traditional categories of data analysis, data exploration and data mining within the discovery step. Data exploration utilizes manual/interactive methods for data analysis such as standard statistical analysis and visualization, usually on small datasets. On the other hand, data mining utilizes automated algorithms to extract useful information. Humans guide these automated algorithms and specify algorithm parameters (training samples, clustering size, etc.). Data Prospecting combines these two approaches using high performance computing and the new techniques for efficient distributed file access.

Connecting Scientists, College Students, Middle School Students & Elementary Students through Intergenerational Afterschool STEM Programming

NASA Astrophysics Data System (ADS)

Ali, N. A.; Paglierani, R.; Raftery, C. L.; Romero, V.; Harper, M. R.; Chilcott, C.; Peticolas, L. M.; Hauck, K.; Yan, D.; Ruderman, I.; Frappier, R.

2015-12-01

The Multiverse education group at UC Berkeley's Space Sciences Lab created the NASA-funded "Five Stars Pathway" model in which five "generations" of girls and women engage in science together in an afterschool setting, with each generation representing one stage in the pathway of pursuing a career in science, technology, engineering, or math (STEM). The five stages are: elementary-age students, middle-school-age students, undergraduate-level college students, graduate-level college students and professional scientists. This model was field-tested at two Girls Inc. afterschool locations in the San Francisco Bay Area and distributed to Girls Inc. affiliates and other afterschool program coordinators nationwide. This presentation will explore some of the challenges and success of implementing a multigenerational STEM model as well as distributing the free curriculum for interested scientists and college students to use with afterschool programs.

Workforce Challenges and Retention Success Stories

NASA Technical Reports Server (NTRS)

Donohue, John T.

2008-01-01

This viewgraph document discusses the current and future challenges in building and retaining the required workforce of scientist and engineers for NASA. Specifically, the talk reviews the current situation at the Goddard Space Flight Center in Greenbelt, Maryland. Several programs at NASA for high school and college students to assist in inspiring the next generation of scientist and engineers are reviewed. The issue of retention of the best of the young scientists and engineers is also reviewed, with a brief review of several young engineers and their success with and for NASA.

Exploring Women Community College Natural Scientists' Personal Experience Narratives through a Subjectivist Lens

ERIC Educational Resources Information Center

Woods, Nancy Anne

2010-01-01

The thrust in education today is to encourage young women to enter nontraditional fields of study such as chemistry, physics, and biology. In order to better prepare the next generation of women scientists, then, we should examine the experiences of women participants already working within these areas. We can learn from their experiences. What…

Technological Innovation and Technical Communications: Their Place in Aerospace Engineering Curricula. A Survey of European, Japanese and US Aerospace Engineers and Scientists.

ERIC Educational Resources Information Center

Pinelli, Thomas E.; And Others

1991-01-01

Reports on results from 260 aerospace engineers and scientists in United States, Europe, and Japan regarding their opinions about professional importance of technical communications; generation and utilization of technical communications; and relevant content of an undergraduate course in technical communications. The fields of cryogenics,…

Engineering Concepts: The Interplay between Concept Formation and Modeling Practices in Bioengineering Sciences

ERIC Educational Resources Information Center

Nersessian, Nancy J.

2012-01-01

As much research has demonstrated, novel scientific concepts do not arise fully formed in the head of a scientist but are created in problem-solving processes, which can extend for considerable periods and even span generations of scientists. To understand concept formation and conceptual change it is important to investigate these processes in…

The identification of cis-regulatory elements: A review from a machine learning perspective.

PubMed

Li, Yifeng; Chen, Chih-Yu; Kaye, Alice M; Wasserman, Wyeth W

2015-12-01

The majority of the human genome consists of non-coding regions that have been called junk DNA. However, recent studies have unveiled that these regions contain cis-regulatory elements, such as promoters, enhancers, silencers, insulators, etc. These regulatory elements can play crucial roles in controlling gene expressions in specific cell types, conditions, and developmental stages. Disruption to these regions could contribute to phenotype changes. Precisely identifying regulatory elements is key to deciphering the mechanisms underlying transcriptional regulation. Cis-regulatory events are complex processes that involve chromatin accessibility, transcription factor binding, DNA methylation, histone modifications, and the interactions between them. The development of next-generation sequencing techniques has allowed us to capture these genomic features in depth. Applied analysis of genome sequences for clinical genetics has increased the urgency for detecting these regions. However, the complexity of cis-regulatory events and the deluge of sequencing data require accurate and efficient computational approaches, in particular, machine learning techniques. In this review, we describe machine learning approaches for predicting transcription factor binding sites, enhancers, and promoters, primarily driven by next-generation sequencing data. Data sources are provided in order to facilitate testing of novel methods. The purpose of this review is to attract computational experts and data scientists to advance this field. Crown Copyright © 2015. Published by Elsevier Ireland Ltd. All rights reserved.

Using Rollback Avoidance to Mitigate Failures in Next-Generation Extreme-Scale Systems

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

Levy, Scott N.

2016-05-01

High-performance computing (HPC) systems enable scientists to numerically model complex phenomena in many important physical systems. The next major milestone in the development of HPC systems is the construction of the rst supercomputer capable executing more than an exa op, 10 18 oating point operations per second. On systems of this scale, failures will occur much more frequently than on current systems. As a result, resilience is a key obstacle to building next-generation extremescale systems. Coordinated checkpointing is currently the most widely-used mechanism for handling failures on HPC systems. Although coordinated checkpointing remains e ective on current systems, increasing themore » scale of today's systems to build next-generation systems will increase the cost of fault tolerance as more and more time is taken away from the application to protect against or recover from failure. Rollback avoidance techniques seek to mitigate the cost of checkpoint/restart by allowing an application to continue its execution rather than rolling back to an earlier checkpoint when failures occur. These techniqes include failure prediction and preventive migration, replicated computation, fault-tolerant algorithms, and softwarebased memory fault correction. In this thesis, we examine how rollback avoidance techniques can be used to address failures on extreme-scale systems. Using a combination of analytic modeling and simulation, we evaluate the potential impact of rollback avoidance on these systems. We then present a novel rollback avoidance technique that exploits similarities in application memory. Finally, we examine the feasibility of using this technique to protect against memory faults in kernel memory.« less

[Activities of Research Institute for Advanced Computer Science

NASA Technical Reports Server (NTRS)

Gross, Anthony R. (Technical Monitor); Leiner, Barry M.

2001-01-01

The Research Institute for Advanced Computer Science (RIACS) carries out basic research and technology development in computer science, in support of the National Aeronautics and Space Administrations missions. RIACS is located at the NASA Ames Research Center, Moffett Field, California. RIACS research focuses on the three cornerstones of IT research necessary to meet the future challenges of NASA missions: 1. Automated Reasoning for Autonomous Systems Techniques are being developed enabling spacecraft that will be self-guiding and self-correcting to the extent that they will require little or no human intervention. Such craft will be equipped to independently solve problems as they arise, and fulfill their missions with minimum direction from Earth. 2. Human-Centered Computing Many NASA missions require synergy between humans and computers, with sophisticated computational aids amplifying human cognitive and perceptual abilities. 3. High Performance Computing and Networking Advances in the performance of computing and networking continue to have major impact on a variety of NASA endeavors, ranging from modeling and simulation to analysis of large scientific datasets to collaborative engineering, planning and execution. In addition, RIACS collaborates with NASA scientists to apply IT research to a variety of NASA application domains. RIACS also engages in other activities, such as workshops, seminars, visiting scientist programs and student summer programs, designed to encourage and facilitate collaboration between the university and NASA IT research communities.

An Innovative Approach to Bridge a Skill Gap and Grow a Workforce Pipeline: The Computer System, Cluster, and Networking Summer Institute

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

Connor, Carolyn Marie; Jacobson, Andree Lars; Bonnie, Amanda Marie

Sustainable and effective computing infrastructure depends critically on the skills and expertise of domain scientists and of committed and well-trained advanced computing professionals. But, in its ongoing High Performance Computing (HPC) work, Los Alamos National Laboratory noted a persistent shortage of well-prepared applicants, particularly for entry-level cluster administration, file systems administration, and high speed networking positions. Further, based upon recruiting efforts and interactions with universities graduating students in related majors of interest (e.g., computer science (CS)), there has been a long standing skillset gap, as focused training in HPC topics is typically lacking or absent in undergraduate and in evenmore » many graduate programs. Given that the effective operation and use of HPC systems requires specialized and often advanced training, that there is a recognized HPC skillset gap, and that there is intense global competition for computing and computational science talent, there is a long-standing and critical need for innovative approaches to help bridge the gap and create a well-prepared, next generation HPC workforce. Our paper places this need in the context of the HPC work and workforce requirements at Los Alamos National Laboratory (LANL) and presents one such innovative program conceived to address the need, bridge the gap, and grow an HPC workforce pipeline at LANL. The Computer System, Cluster, and Networking Summer Institute (CSCNSI) completed its 10th year in 2016. The story of the CSCNSI and its evolution is detailed below with a description of the design of its Boot Camp, and a summary of its success and some key factors that have enabled that success.« less

An Innovative Approach to Bridge a Skill Gap and Grow a Workforce Pipeline: The Computer System, Cluster, and Networking Summer Institute

DOE PAGES

Connor, Carolyn Marie; Jacobson, Andree Lars; Bonnie, Amanda Marie; ...

2016-11-01

Sustainable and effective computing infrastructure depends critically on the skills and expertise of domain scientists and of committed and well-trained advanced computing professionals. But, in its ongoing High Performance Computing (HPC) work, Los Alamos National Laboratory noted a persistent shortage of well-prepared applicants, particularly for entry-level cluster administration, file systems administration, and high speed networking positions. Further, based upon recruiting efforts and interactions with universities graduating students in related majors of interest (e.g., computer science (CS)), there has been a long standing skillset gap, as focused training in HPC topics is typically lacking or absent in undergraduate and in evenmore » many graduate programs. Given that the effective operation and use of HPC systems requires specialized and often advanced training, that there is a recognized HPC skillset gap, and that there is intense global competition for computing and computational science talent, there is a long-standing and critical need for innovative approaches to help bridge the gap and create a well-prepared, next generation HPC workforce. Our paper places this need in the context of the HPC work and workforce requirements at Los Alamos National Laboratory (LANL) and presents one such innovative program conceived to address the need, bridge the gap, and grow an HPC workforce pipeline at LANL. The Computer System, Cluster, and Networking Summer Institute (CSCNSI) completed its 10th year in 2016. The story of the CSCNSI and its evolution is detailed below with a description of the design of its Boot Camp, and a summary of its success and some key factors that have enabled that success.« less

Mission critical cloud computing in a week

NASA Astrophysics Data System (ADS)

George, B.; Shams, K.; Knight, D.; Kinney, J.

NASA's vision is to “ reach for new heights and reveal the unknown so that what we do and learn will benefit all humankind.” While our missions provide large volumes of unique and invaluable data to the scientific community, they also serve to inspire and educate the next generation of engineers and scientists. One critical aspect of “ benefiting all humankind” is to make our missions as visible and accessible as possible to facilitate the transfer of scientific knowledge to the public. The recent successful landing of the Curiosity rover on Mars exemplified this vision: we shared the landing event via live video streaming and web experiences with millions of people around the world. The video stream on Curiosity's website was delivered by a highly scalable stack of computing resources in the cloud to cache and distribute the video stream to our viewers. While this work was done in the context of public outreach, it has extensive implications for the development of mission critical, highly available, and elastic applications in the cloud for a diverse set of use cases across NASA.

Fusion interfaces for tactical environments: An application of virtual reality technology

NASA Technical Reports Server (NTRS)

Haas, Michael W.

1994-01-01

The term Fusion Interface is defined as a class of interface which integrally incorporates both virtual and nonvirtual concepts and devices across the visual, auditory, and haptic sensory modalities. A fusion interface is a multisensory virtually-augmented synthetic environment. A new facility has been developed within the Human Engineering Division of the Armstrong Laboratory dedicated to exploratory development of fusion interface concepts. This new facility, the Fusion Interfaces for Tactical Environments (FITE) Facility is a specialized flight simulator enabling efficient concept development through rapid prototyping and direct experience of new fusion concepts. The FITE Facility also supports evaluation of fusion concepts by operation fighter pilots in an air combat environment. The facility is utilized by a multidisciplinary design team composed of human factors engineers, electronics engineers, computer scientists, experimental psychologists, and oeprational pilots. The FITE computational architecture is composed of twenty-five 80486-based microcomputers operating in real-time. The microcomputers generate out-the-window visuals, in-cockpit and head-mounted visuals, localized auditory presentations, haptic displays on the stick and rudder pedals, as well as executing weapons models, aerodynamic models, and threat models.

Decision tree and ensemble learning algorithms with their applications in bioinformatics.

PubMed

Che, Dongsheng; Liu, Qi; Rasheed, Khaled; Tao, Xiuping

2011-01-01

Machine learning approaches have wide applications in bioinformatics, and decision tree is one of the successful approaches applied in this field. In this chapter, we briefly review decision tree and related ensemble algorithms and show the successful applications of such approaches on solving biological problems. We hope that by learning the algorithms of decision trees and ensemble classifiers, biologists can get the basic ideas of how machine learning algorithms work. On the other hand, by being exposed to the applications of decision trees and ensemble algorithms in bioinformatics, computer scientists can get better ideas of which bioinformatics topics they may work on in their future research directions. We aim to provide a platform to bridge the gap between biologists and computer scientists.

Supercomputing Sheds Light on the Dark Universe

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

Habib, Salman; Heitmann, Katrin

2012-11-15

At Argonne National Laboratory, scientists are using supercomputers to shed light on one of the great mysteries in science today, the Dark Universe. With Mira, a petascale supercomputer at the Argonne Leadership Computing Facility, a team led by physicists Salman Habib and Katrin Heitmann will run the largest, most complex simulation of the universe ever attempted. By contrasting the results from Mira with state-of-the-art telescope surveys, the scientists hope to gain new insights into the distribution of matter in the universe, advancing future investigations of dark energy and dark matter into a new realm. The team's research was named amore » finalist for the 2012 Gordon Bell Prize, an award recognizing outstanding achievement in high-performance computing.« less

International Conferences and Young Scientists Schools on Computational Information Technologies for Environmental Sciences (CITES) as a professional growth instrument

NASA Astrophysics Data System (ADS)

Gordov, E. P.; Lykosov, V. N.; Genina, E. Yu; Gordova, Yu E.

2017-11-01

The paper describes a regular events CITES consisting of young scientists school and international conference as a tool for training and professional growth. The events address the most pressing issues of application of information-computational technologies in environmental sciences and young scientists’ training, diminishing a gap between university graduates’ skill and concurrent challenges. The viability of the approach to the CITES organization is proved by the fact that single event organized in 2001 turned into a series, quite a few young participants successfully defended their PhD thesis and a number of researchers became Doctors of Science during these years. Young researchers from Russia and foreign countries show undiminishing interest to these events.

Analyzing prospective teachers' images of scientists using positive, negative and stereotypical images of scientists

NASA Astrophysics Data System (ADS)

Subramaniam, Karthigeyan; Esprívalo Harrell, Pamela; Wojnowski, David

2013-04-01

Background and purpose : This study details the use of a conceptual framework to analyze prospective teachers' images of scientists to reveal their context-specific conceptions of scientists. The conceptual framework consists of context-specific conceptions related to positive, stereotypical and negative images of scientists as detailed in the literature on the images, role and work of scientists. Sample, design and method : One hundred and ninety-six drawings of scientists, generated by prospective teachers, were analyzed using the Draw-A-Scientist-Test Checklist (DAST-C), a binary linear regression and the conceptual framework. Results : The results of the binary linear regression analysis revealed a statistically significant difference for two DAST-C elements: ethnicity differences with regard to drawing a scientist who was Caucasian and gender differences for indications of danger. Analysis using the conceptual framework helped to categorize the same drawings into positive, stereotypical, negative and composite images of a scientist. Conclusions : The conceptual framework revealed that drawings were focused on the physical appearance of the scientist, and to a lesser extent on the equipment, location and science-related practices that provided the context of a scientist's role and work. Implications for teacher educators include the need to understand that there is a need to provide tools, like the conceptual framework used in this study, to help prospective teachers to confront and engage with their multidimensional perspectives of scientists in light of the current trends on perceiving and valuing scientists. In addition, teacher educators need to use the conceptual framework, which yields qualitative perspectives about drawings, together with the DAST-C, which yields quantitative measure for drawings, to help prospective teachers to gain a holistic outlook on their drawings of scientists.

MATHEMATICAL ROUTINES FOR ENGINEERS AND SCIENTISTS

NASA Technical Reports Server (NTRS)

Kantak, A. V.

1994-01-01

The purpose of this package is to provide the scientific and engineering community with a library of programs useful for performing routine mathematical manipulations. This collection of programs will enable scientists to concentrate on their work without having to write their own routines for solving common problems, thus saving considerable amounts of time. This package contains sixteen subroutines. Each is separately documented with descriptions of the invoking subroutine call, its required parameters, and a sample test program. The functions available include: maxima, minima, and sort of vectors; factorials; random number generator (uniform or Gaussian distribution); complimentary error function; fast Fourier Transformation; Simpson's Rule integration; matrix determinate and inversion; Bessel function (J Bessel function for any order, and modified Bessel function for zero order); roots of a polynomial; roots of non-linear equation; and the solution of first order ordinary differential equations using Hamming's predictor-corrector method. There is also a subroutine for using a dot matrix printer to plot a given set of y values for a uniformly increasing x value. This package is written in FORTRAN 77 (Super Soft Small System FORTRAN compiler) for batch execution and has been implemented on the IBM PC computer series under MS-DOS with a central memory requirement of approximately 28K of 8 bit bytes for all subroutines. This program was developed in 1986.

Accelerating Astronomy & Astrophysics in the New Era of Parallel Computing: GPUs, Phi and Cloud Computing

NASA Astrophysics Data System (ADS)

Ford, Eric B.; Dindar, Saleh; Peters, Jorg

2015-08-01

The realism of astrophysical simulations and statistical analyses of astronomical data are set by the available computational resources. Thus, astronomers and astrophysicists are constantly pushing the limits of computational capabilities. For decades, astronomers benefited from massive improvements in computational power that were driven primarily by increasing clock speeds and required relatively little attention to details of the computational hardware. For nearly a decade, increases in computational capabilities have come primarily from increasing the degree of parallelism, rather than increasing clock speeds. Further increases in computational capabilities will likely be led by many-core architectures such as Graphical Processing Units (GPUs) and Intel Xeon Phi. Successfully harnessing these new architectures, requires significantly more understanding of the hardware architecture, cache hierarchy, compiler capabilities and network network characteristics.I will provide an astronomer's overview of the opportunities and challenges provided by modern many-core architectures and elastic cloud computing. The primary goal is to help an astronomical audience understand what types of problems are likely to yield more than order of magnitude speed-ups and which problems are unlikely to parallelize sufficiently efficiently to be worth the development time and/or costs.I will draw on my experience leading a team in developing the Swarm-NG library for parallel integration of large ensembles of small n-body systems on GPUs, as well as several smaller software projects. I will share lessons learned from collaborating with computer scientists, including both technical and soft skills. Finally, I will discuss the challenges of training the next generation of astronomers to be proficient in this new era of high-performance computing, drawing on experience teaching a graduate class on High-Performance Scientific Computing for Astrophysics and organizing a 2014 advanced summer school on Bayesian Computing for Astronomical Data Analysis with support of the Penn State Center for Astrostatistics and Institute for CyberScience.

Software Carpentry and the Hydrological Sciences

NASA Astrophysics Data System (ADS)

Ahmadia, A. J.; Kees, C. E.; Farthing, M. W.

2013-12-01

Scientists are spending an increasing amount of time building and using hydrology software. However, most scientists are never taught how to do this efficiently. As a result, many are unaware of tools and practices that would allow them to write more reliable and maintainable code with less effort. As hydrology models increase in capability and enter use by a growing number of scientists and their communities, it is important that the scientific software development practices scale up to meet the challenges posed by increasing software complexity, lengthening software lifecycles, a growing number of stakeholders and contributers, and a broadened developer base that extends from application domains to high performance computing centers. Many of these challenges in complexity, lifecycles, and developer base have been successfully met by the open source community, and there are many lessons to be learned from their experiences and practices. Additionally, there is much wisdom to be found in the results of research studies conducted on software engineering itself. Software Carpentry aims to bridge the gap between the current state of software development and these known best practices for scientific software development, with a focus on hands-on exercises and practical advice based on the following principles: 1. Write programs for people, not computers. 2. Automate repetitive tasks 3. Use the computer to record history 4. Make incremental changes 5. Use version control 6. Don't repeat yourself (or others) 7. Plan for mistakes 8. Optimize software only after it works 9. Document design and purpose, not mechanics 10. Collaborate We discuss how these best practices, arising from solid foundations in research and experience, have been shown to help improve scientist's productivity and the reliability of their software.

CompNanoTox2015: novel perspectives from a European conference on computational nanotoxicology on predictive nanotoxicology.

PubMed

Bañares, Miguel A; Haase, Andrea; Tran, Lang; Lobaskin, Vladimir; Oberdörster, Günter; Rallo, Robert; Leszczynski, Jerzy; Hoet, Peter; Korenstein, Rafi; Hardy, Barry; Puzyn, Tomasz

2017-09-01

A first European Conference on Computational Nanotoxicology, CompNanoTox, was held in November 2015 in Benahavís, Spain with the objectives to disseminate and integrate results from the European modeling and database projects (NanoPUZZLES, ModENPTox, PreNanoTox, MembraneNanoPart, MODERN, eNanoMapper and EU COST TD1204 MODENA) as well as to create synergies within the European NanoSafety Cluster. This conference was supported by the COST Action TD1204 MODENA on developing computational methods for toxicological risk assessment of engineered nanoparticles and provided a unique opportunity for cross fertilization among complementary disciplines. The efforts to develop and validate computational models crucially depend on high quality experimental data and relevant assays which will be the basis to identify relevant descriptors. The ambitious overarching goal of this conference was to promote predictive nanotoxicology, which can only be achieved by a close collaboration between the computational scientists (e.g. database experts, modeling experts for structure, (eco) toxicological effects, performance and interaction of nanomaterials) and experimentalists from different areas (in particular toxicologists, biologists, chemists and material scientists, among others). The main outcome and new perspectives of this conference are summarized here.

Tools and techniques for computational reproducibility.

PubMed

Piccolo, Stephen R; Frampton, Michael B

2016-07-11

When reporting research findings, scientists document the steps they followed so that others can verify and build upon the research. When those steps have been described in sufficient detail that others can retrace the steps and obtain similar results, the research is said to be reproducible. Computers play a vital role in many research disciplines and present both opportunities and challenges for reproducibility. Computers can be programmed to execute analysis tasks, and those programs can be repeated and shared with others. The deterministic nature of most computer programs means that the same analysis tasks, applied to the same data, will often produce the same outputs. However, in practice, computational findings often cannot be reproduced because of complexities in how software is packaged, installed, and executed-and because of limitations associated with how scientists document analysis steps. Many tools and techniques are available to help overcome these challenges; here we describe seven such strategies. With a broad scientific audience in mind, we describe the strengths and limitations of each approach, as well as the circumstances under which each might be applied. No single strategy is sufficient for every scenario; thus we emphasize that it is often useful to combine approaches.

CompNanoTox2015: novel perspectives from a European conference on computational nanotoxicology on predictive nanotoxicology

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

Bañares, Miguel A.; Haase, Andrea; Tran, Lang

A first European Conference on Computational Nanotoxicology, CompNanoTox, was held in November 2015 in Benahavís, Spain with the objectives to disseminate and integrate results from the European modeling and database projects (NanoPUZZLES, ModENPTox, PreNanoTox, MembraneNanoPart, MODERN, eNanoMapper and EU COST TD1204 MODENA) as well as to create synergies within the European NanoSafety Cluster. This conference was supported by the COST Action TD1204 MODENA on developing computational methods for toxicological risk assessment of engineered nanoparticles and provided a unique opportunity for crossfertilization among complementary disciplines. The efforts to develop and validate computational models crucially depend on high quality experimental data andmore » relevant assays which will be the basis to identify relevant descriptors. The ambitious overarching goal of this conference was to promote predictive nanotoxicology, which can only be achieved by a close collaboration between the computational scientists (e.g. database experts, modeling experts for structure, (eco) toxicological effects, performance and interaction of nanomaterials) and experimentalists from different areas (in particular toxicologists, biologists, chemists and material scientists, among others). The main outcome and new perspectives of this conference are summarized here.« less

Reflections on the current and future roles of clinician-scientists.

PubMed

Baumal, Reuben; Benbassat, Jochanan; Van, Julie A D

2014-08-01

"Clinician-scientists" is an all-inclusive term for board-certified specialists who engage in patient care and laboratory-based (biomedical) research, patient-based (clinical) research, or population-based (epidemiological) research. In recent years, the number of medical graduates who choose to combine patient care and research has declined, generating concerns about the future of medical research. This paper reviews: a) the various current categories of clinician-scientists, b) the reasons proposed for the declining number of medical graduates who opt for a career as clinician-scientists, c) the various interventions aimed at reversing this trend, and d) the projections for the future role of clinician-scientists. Efforts to encourage students to combine patient care and research include providing financial and institutional support, and reducing the duration of the training of clinician-scientists. However, recent advances in clinical and biomedical knowledge have increased the difficulties in maintaining the dual role of care-providers and scientists. It was therefore suggested that rather than expecting clinician-scientists to compete with full-time clinicians in providing patient care, and with full-time investigators in performing research, clinician-scientists will increasingly assume the role of leading/coordinating interdisciplinary teams. Such teams would focus either on patient-based research or on the clinical, biomedical and epidemiological aspects of specific clinical disorders, such as hypertension and diabetes.

Generating Southern Africa Precipitation Forecast Using the FEWS Engine, a New Application for the Google Earth Engine

NASA Astrophysics Data System (ADS)

Landsfeld, M. F.; Hegewisch, K.; Daudert, B.; Morton, C.; Husak, G. J.; Friedrichs, M.; Funk, C. C.; Huntington, J. L.; Abatzoglou, J. T.; Verdin, J. P.

2016-12-01

The Famine Early Warning Systems Network (FEWS NET) focuses on food insecurity in developing nations and provides objective, evidence-based analysis to help government decision-makers and relief agencies plan for and respond to humanitarian emergencies. The network of FEWS NET analysts and scientists require flexible, interactive tools to aid in their monitoring and research efforts. Because they often work in bandwidth-limited regions, lightweight Internet tools and services that bypass the need for downloading massive datasets are preferred for their work. To support food security analysis FEWS NET developed a custom interface for the Google Earth Engine (GEE). GEE is a platform developed by Google to support scientific analysis of environmental data in their cloud computing environment. This platform allows scientists and independent researchers to mine massive collections of environmental data, leveraging Google's vast computational resources for purposes of detecting changes and monitoring the Earth's surface and climate. GEE hosts an enormous amount of satellite imagery and climate archives, one of which is the Climate Hazards Group Infrared Precipitation with Stations dataset (CHIRPS). CHIRPS precipitation dataset is a key input for FEWS NET monitoring and forecasting efforts. In this talk we introduce the FEWS Engine interface. We present an application that highlights the utility of FEWS Engine for forecasting the upcoming seasonal precipitation of southern Africa. Specifically, the current state of ENSO is assessed and used to identify similar historical seasons. The FEWS Engine compositing tool is used to examine rainfall and other environmental data for these analog seasons. The application illustrates the unique benefits of using FEWS Engine for on-the-fly food security scenario development.

HydroShare: An online, collaborative environment for the sharing of hydrologic data and models (Invited)

NASA Astrophysics Data System (ADS)

Tarboton, D. G.; Idaszak, R.; Horsburgh, J. S.; Ames, D.; Goodall, J. L.; Band, L. E.; Merwade, V.; Couch, A.; Arrigo, J.; Hooper, R. P.; Valentine, D. W.; Maidment, D. R.

2013-12-01

HydroShare is an online, collaborative system being developed for sharing hydrologic data and models. The goal of HydroShare is to enable scientists to easily discover and access data and models, retrieve them to their desktop or perform analyses in a distributed computing environment that may include grid, cloud or high performance computing model instances as necessary. Scientists may also publish outcomes (data, results or models) into HydroShare, using the system as a collaboration platform for sharing data, models and analyses. HydroShare is expanding the data sharing capability of the CUAHSI Hydrologic Information System by broadening the classes of data accommodated, creating new capability to share models and model components, and taking advantage of emerging social media functionality to enhance information about and collaboration around hydrologic data and models. One of the fundamental concepts in HydroShare is that of a Resource. All content is represented using a Resource Data Model that separates system and science metadata and has elements common to all resources as well as elements specific to the types of resources HydroShare will support. These will include different data types used in the hydrology community and models and workflows that require metadata on execution functionality. HydroShare will use the integrated Rule-Oriented Data System (iRODS) to manage federated data content and perform rule-based background actions on data and model resources, including parsing to generate metadata catalog information and the execution of models and workflows. This presentation will introduce the HydroShare functionality developed to date, describe key elements of the Resource Data Model and outline the roadmap for future development.

NASA Earth Exchange (NEX) Supporting Analyses for National Climate Assessments

NASA Astrophysics Data System (ADS)

Nemani, R. R.; Thrasher, B. L.; Wang, W.; Lee, T. J.; Melton, F. S.; Dungan, J. L.; Michaelis, A.

2015-12-01

The NASA Earth Exchange (NEX) is a collaborative computing platform that has been developed with the objective of bringing scientists together with the software tools, massive global datasets, and supercomputing resources necessary to accelerate research in Earth systems science and global change. NEX supports several research projects that are closely related with the National Climate Assessment including the generation of high-resolution climate projections, identification of trends and extremes in climate variables and the evaluation of their impacts on regional carbon/water cycles and biodiversity, the development of land-use management and adaptation strategies for climate-change scenarios, and even the exploration of climate mitigation through geo-engineering. Scientists also use the large collection of satellite data on NEX to conduct research on quantifying spatial and temporal changes in land surface processes in response to climate and land-cover-land-use changes. Researchers, leveraging NEX's massive compute/storage resources, have used statistical techniques to downscale the coarse-resolution CMIP5 projections to fulfill the demands of the community for a wide range of climate change impact analyses. The DCP-30 (Downscaled Climate Projections at 30 arcsecond) for the conterminous US at monthly, ~1km resolution and the GDDP (Global Daily Downscaled Projections) for the entire world at daily, 25km resolution are now widely used in climate research and applications, as well as for communicating climate change. In order to serve a broader community, the NEX team in collaboration with Amazon, Inc, created the OpenNEX platform. OpenNEX provides ready access to NEX data holdings, including the NEX-DCP30 and GDDP datasets along with a number of pertinent analysis tools and workflows on the AWS infrastructure in the form of publicly available, self contained, fully functional Amazon Machine Images (AMI's) for anyone interested in global climate change.

Stereotyping in Relation to the Gender Gap in Participation in Computing.

ERIC Educational Resources Information Center

Siann, Gerda; And Others

1988-01-01

A questionnaire completed by 928 postsecondary students asked subjects to rate one of two computer scientists on 16 personal attributes. Aside from gender of the ratee, questionnaires were identical. Results indicate that on eight attributes the female was rated significantly more positively than the male. Implications are discussed. (Author/CH)

Constructing Contracts: Making Discrete Mathematics Relevant to Beginning Programmers

ERIC Educational Resources Information Center

Gegg-Harrison, Timothy S.

2005-01-01

Although computer scientists understand the importance of discrete mathematics to the foundations of their field, computer science (CS) students do not always see the relevance. Thus, it is important to find a way to show students its relevance. The concept of program correctness is generally taught as an activity independent of the programming…

Communication for Scientists and Engineers: A "Computer Model" in the Basic Course.

ERIC Educational Resources Information Center

Haynes, W. Lance

Successful speech should rest not on prepared notes and outlines but on genuine oral discourse based on "data" fed into the "software" in the computer which already exists within each person. Writing cannot speak for itself, nor can it continually adjust itself to accommodate diverse response. Moreover, no matter how skillfully…

Identification of Factors That Affect Software Complexity.

ERIC Educational Resources Information Center

Kaiser, Javaid

A survey of computer scientists was conducted to identify factors that affect software complexity. A total of 160 items were selected from the literature to include in a questionnaire sent to 425 individuals who were employees of computer-related businesses in Lawrence and Kansas City. The items were grouped into nine categories called system…

Synthetic Biology: Knowledge Accessed by Everyone (Open Sources)

ERIC Educational Resources Information Center

Sánchez Reyes, Patricia Margarita

2016-01-01

Using the principles of biology, along with engineering and with the help of computer, scientists manage to copy. DNA sequences from nature and use them to create new organisms. DNA is created through engineering and computer science managing to create life inside a laboratory. We cannot dismiss the role that synthetic biology could lead in…

The Multiple Pendulum Problem via Maple[R

ERIC Educational Resources Information Center

Salisbury, K. L.; Knight, D. G.

2002-01-01

The way in which computer algebra systems, such as Maple, have made the study of physical problems of some considerable complexity accessible to mathematicians and scientists with modest computational skills is illustrated by solving the multiple pendulum problem. A solution is obtained for four pendulums with no restriction on the size of the…

Computers and the Future of Skill Demand. Educational Research and Innovation Series

ERIC Educational Resources Information Center

Elliott, Stuart W.

2017-01-01

Computer scientists are working on reproducing all human skills using artificial intelligence, machine learning and robotics. Unsurprisingly then, many people worry that these advances will dramatically change work skills in the years ahead and perhaps leave many workers unemployable. This report develops a new approach to understanding these…

Symposium on Parallel Computational Methods for Large-scale Structural Analysis and Design, 2nd, Norfolk, VA, US

NASA Technical Reports Server (NTRS)

Storaasli, Olaf O. (Editor); Housner, Jerrold M. (Editor)

1993-01-01

Computing speed is leaping forward by several orders of magnitude each decade. Engineers and scientists gathered at a NASA Langley symposium to discuss these exciting trends as they apply to parallel computational methods for large-scale structural analysis and design. Among the topics discussed were: large-scale static analysis; dynamic, transient, and thermal analysis; domain decomposition (substructuring); and nonlinear and numerical methods.

A cyber-linked undergraduate research experience in computational biomolecular structure prediction and design

PubMed Central

Alford, Rebecca F.; Dolan, Erin L.

2017-01-01

Computational biology is an interdisciplinary field, and many computational biology research projects involve distributed teams of scientists. To accomplish their work, these teams must overcome both disciplinary and geographic barriers. Introducing new training paradigms is one way to facilitate research progress in computational biology. Here, we describe a new undergraduate program in biomolecular structure prediction and design in which students conduct research at labs located at geographically-distributed institutions while remaining connected through an online community. This 10-week summer program begins with one week of training on computational biology methods development, transitions to eight weeks of research, and culminates in one week at the Rosetta annual conference. To date, two cohorts of students have participated, tackling research topics including vaccine design, enzyme design, protein-based materials, glycoprotein modeling, crowd-sourced science, RNA processing, hydrogen bond networks, and amyloid formation. Students in the program report outcomes comparable to students who participate in similar in-person programs. These outcomes include the development of a sense of community and increases in their scientific self-efficacy, scientific identity, and science values, all predictors of continuing in a science research career. Furthermore, the program attracted students from diverse backgrounds, which demonstrates the potential of this approach to broaden the participation of young scientists from backgrounds traditionally underrepresented in computational biology. PMID:29216185

A cyber-linked undergraduate research experience in computational biomolecular structure prediction and design.

PubMed

Alford, Rebecca F; Leaver-Fay, Andrew; Gonzales, Lynda; Dolan, Erin L; Gray, Jeffrey J

2017-12-01

Computational biology is an interdisciplinary field, and many computational biology research projects involve distributed teams of scientists. To accomplish their work, these teams must overcome both disciplinary and geographic barriers. Introducing new training paradigms is one way to facilitate research progress in computational biology. Here, we describe a new undergraduate program in biomolecular structure prediction and design in which students conduct research at labs located at geographically-distributed institutions while remaining connected through an online community. This 10-week summer program begins with one week of training on computational biology methods development, transitions to eight weeks of research, and culminates in one week at the Rosetta annual conference. To date, two cohorts of students have participated, tackling research topics including vaccine design, enzyme design, protein-based materials, glycoprotein modeling, crowd-sourced science, RNA processing, hydrogen bond networks, and amyloid formation. Students in the program report outcomes comparable to students who participate in similar in-person programs. These outcomes include the development of a sense of community and increases in their scientific self-efficacy, scientific identity, and science values, all predictors of continuing in a science research career. Furthermore, the program attracted students from diverse backgrounds, which demonstrates the potential of this approach to broaden the participation of young scientists from backgrounds traditionally underrepresented in computational biology.

Computer Model Predicts the Movement of Dust

NASA Technical Reports Server (NTRS)

2002-01-01

A new computer model of the atmosphere can now actually pinpoint where global dust events come from, and can project where they're going. The model may help scientists better evaluate the impact of dust on human health, climate, ocean carbon cycles, ecosystems, and atmospheric chemistry. Also, by seeing where dust originates and where it blows people with respiratory problems can get advanced warning of approaching dust clouds. 'The model is physically more realistic than previous ones,' said Mian Chin, a co-author of the study and an Earth and atmospheric scientist at Georgia Tech and the Goddard Space Flight Center (GSFC) in Greenbelt, Md. 'It is able to reproduce the short term day-to-day variations and long term inter-annual variations of dust concentrations and distributions that are measured from field experiments and observed from satellites.' The above images show both aerosols measured from space (left) and the movement of aerosols predicted by computer model for the same date (right). For more information, read New Computer Model Tracks and Predicts Paths Of Earth's Dust Images courtesy Paul Giroux, Georgia Tech/NASA Goddard Space Flight Center

Next-Generation Genomics Facility at C-CAMP: Accelerating Genomic Research in India

PubMed Central

S, Chandana; Russiachand, Heikham; H, Pradeep; S, Shilpa; M, Ashwini; S, Sahana; B, Jayanth; Atla, Goutham; Jain, Smita; Arunkumar, Nandini; Gowda, Malali

2014-01-01

Next-Generation Sequencing (NGS; http://www.genome.gov/12513162) is a recent life-sciences technological revolution that allows scientists to decode genomes or transcriptomes at a much faster rate with a lower cost. Genomic-based studies are in a relatively slow pace in India due to the non-availability of genomics experts, trained personnel and dedicated service providers. Using NGS there is a lot of potential to study India's national diversity (of all kinds). We at the Centre for Cellular and Molecular Platforms (C-CAMP) have launched the Next Generation Genomics Facility (NGGF) to provide genomics service to scientists, to train researchers and also work on national and international genomic projects. We have HiSeq1000 from Illumina and GS-FLX Plus from Roche454. The long reads from GS FLX Plus, and high sequence depth from HiSeq1000, are the best and ideal hybrid approaches for de novo and re-sequencing of genomes and transcriptomes. At our facility, we have sequenced around 70 different organisms comprising of more than 388 genomes and 615 transcriptomes – prokaryotes and eukaryotes (fungi, plants and animals). In addition we have optimized other unique applications such as small RNA (miRNA, siRNA etc), long Mate-pair sequencing (2 to 20 Kb), Coding sequences (Exome), Methylome (ChIP-Seq), Restriction Mapping (RAD-Seq), Human Leukocyte Antigen (HLA) typing, mixed genomes (metagenomes) and target amplicons, etc. Translating DNA sequence data from NGS sequencer into meaningful information is an important exercise. Under NGGF, we have bioinformatics experts and high-end computing resources to dissect NGS data such as genome assembly and annotation, gene expression, target enrichment, variant calling (SSR or SNP), comparative analysis etc. Our services (sequencing and bioinformatics) have been utilized by more than 45 organizations (academia and industry) both within India and outside, resulting several publications in peer-reviewed journals and several genomic/transcriptomic data is available at NCBI.

Automating CapCom: Pragmatic Operations and Technology Research for Human Exploration of Mars

NASA Technical Reports Server (NTRS)

Clancey, William J.

2003-01-01

During the Apollo program, NASA and the scientific community used terrestrial analog sites for understanding planetary features and for training astronauts to be scientists. More recently, computer scientists and human factors specialists have followed geologists and biologists into the field, learning how science is actually done on expeditions in extreme environments. Research stations have been constructed by the Mars Society in the Arctic and American southwest, providing facilities for hundreds of researchers to investigate how small crews might live and work on Mars. Combining these interests-science, operations, and technology-in Mars analog field expeditions provides tremendous synergy and authenticity to speculations about Mars missions. By relating historical analyses of Apollo and field science, engineers are creating experimental prototypes that provide significant new capabilities, such as a computer system that automates some of the functions of Apollo s CapCom. Thus, analog studies have created a community of practice-a new collaboration between scientists and engineers-so that technology begins with real human needs and works incrementally towards the challenges of the human exploration of Mars.

Developing the next generation of nurse scientists.

PubMed

Burkhart, Patricia V; Hall, Lynne A

2015-01-01

This article describes an undergraduate nursing research internship program in which students are engaged in research with a faculty mentor. Since 2002, more than 130 undergraduate nursing students have participated. Interns coauthored publications, presented papers and posters at conferences, and received awards. This highly successful program provides a model that can be easily replicated to foster the development of future nurse scientists.

Preparing a New Generation of Citizens and Scientists to Face Earth's Future

ERIC Educational Resources Information Center

Bralower, Timothy J.; Feiss, P. Geoffrey; Manduca, Cathryn A.

2008-01-01

As the research interests and the focus of traditional earth scientists are transformed, so too must education in earth system science at colleges and universities across the country change. The required change involves not only the methods used to teach this new science, but also the essential place of the earth sciences in the panoply of…

Interface between Physics and Biology: Training a New Generation of Creative Bilingual Scientists.

PubMed

Riveline, Daniel; Kruse, Karsten

2017-08-01

Whereas physics seeks for universal laws underlying natural phenomena, biology accounts for complexity and specificity of molecular details. Contemporary biological physics requires people capable of working at this interface. New programs prepare scientists who transform respective disciplinary views into innovative approaches for solving outstanding problems in the life sciences. Copyright © 2017 Elsevier Ltd. All rights reserved.

C2M: Configurable Chemical Middleware

PubMed Central

Roosendaal, Hans E.; Geurts, Peter A. T. M.

2001-01-01

One of the vexing problems that besets concurrent use of multiple, heterogeneous resources is format multiplicity. C2M aims to equip scientists with a wrapper generator on their desktop. The wrapper generator can build wrappers, or converters that can convert data from or into different formats, from a high-level description of the formats. The language in which such a high-level description is expressed is easy enough for scientists to be able to write format descriptions at minimal cost. In C2M, wrappers and documentation for human reading are automatically obtained from the same user-supplied specifications. Initial experiments demonstrate that the idea can, indeed, lead to the advent of usergoverned wrapper generators. Future research will consolidate the code and extend the approach to a realistic variety of formats. PMID:18628869

What should a climate scientist advocate for? The intersection of expertise and values in a politicized world (Invited)

NASA Astrophysics Data System (ADS)

Schmidt, G. A.

2013-12-01

Stephen Schneider was a science communicator who understood intimately the roles of expertise and values in raising public awareness and in discussing both problems and solutions to issues of public concern. With a new generation of climate scientists stepping up to the microphone, what are the lessons to be learned from his experiences? I will discuss the ethical issues associated with being both a scientist and a human being, the importance of honesty - to oneself and to ones audience - and how this can be effective. I will also discuss how scientists can find a role for themselves in advocating what they feel strongly about and how to avoid some common pitfalls and problems. Above all, I will present a picture of how one can try to be both a public voice and a good scientist, and how these roles, in the end, reinforce one another.

A Micro-Level Data-Calibrated Agent-Based Model: The Synergy between Microsimulation and Agent-Based Modeling.

PubMed

Singh, Karandeep; Ahn, Chang-Won; Paik, Euihyun; Bae, Jang Won; Lee, Chun-Hee

2018-01-01

Artificial life (ALife) examines systems related to natural life, its processes, and its evolution, using simulations with computer models, robotics, and biochemistry. In this article, we focus on the computer modeling, or "soft," aspects of ALife and prepare a framework for scientists and modelers to be able to support such experiments. The framework is designed and built to be a parallel as well as distributed agent-based modeling environment, and does not require end users to have expertise in parallel or distributed computing. Furthermore, we use this framework to implement a hybrid model using microsimulation and agent-based modeling techniques to generate an artificial society. We leverage this artificial society to simulate and analyze population dynamics using Korean population census data. The agents in this model derive their decisional behaviors from real data (microsimulation feature) and interact among themselves (agent-based modeling feature) to proceed in the simulation. The behaviors, interactions, and social scenarios of the agents are varied to perform an analysis of population dynamics. We also estimate the future cost of pension policies based on the future population structure of the artificial society. The proposed framework and model demonstrates how ALife techniques can be used by researchers in relation to social issues and policies.

Understanding the Performance and Potential of Cloud Computing for Scientific Applications

DOE PAGES

Sadooghi, Iman; Martin, Jesus Hernandez; Li, Tonglin; ...

2015-02-19

In this paper, commercial clouds bring a great opportunity to the scientific computing area. Scientific applications usually require significant resources, however not all scientists have access to sufficient high-end computing systems, may of which can be found in the Top500 list. Cloud Computing has gained the attention of scientists as a competitive resource to run HPC applications at a potentially lower cost. But as a different infrastructure, it is unclear whether clouds are capable of running scientific applications with a reasonable performance per money spent. This work studies the performance of public clouds and places this performance in context tomore » price. We evaluate the raw performance of different services of AWS cloud in terms of the basic resources, such as compute, memory, network and I/O. We also evaluate the performance of the scientific applications running in the cloud. This paper aims to assess the ability of the cloud to perform well, as well as to evaluate the cost of the cloud running scientific applications. We developed a full set of metrics and conducted a comprehensive performance evlauation over the Amazon cloud. We evaluated EC2, S3, EBS and DynamoDB among the many Amazon AWS services. We evaluated the memory sub-system performance with CacheBench, the network performance with iperf, processor and network performance with the HPL benchmark application, and shared storage with NFS and PVFS in addition to S3. We also evaluated a real scientific computing application through the Swift parallel scripting system at scale. Armed with both detailed benchmarks to gauge expected performance and a detailed monetary cost analysis, we expect this paper will be a recipe cookbook for scientists to help them decide where to deploy and run their scientific applications between public clouds, private clouds, or hybrid clouds.« less

Understanding the Performance and Potential of Cloud Computing for Scientific Applications

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

Sadooghi, Iman; Martin, Jesus Hernandez; Li, Tonglin

In this paper, commercial clouds bring a great opportunity to the scientific computing area. Scientific applications usually require significant resources, however not all scientists have access to sufficient high-end computing systems, may of which can be found in the Top500 list. Cloud Computing has gained the attention of scientists as a competitive resource to run HPC applications at a potentially lower cost. But as a different infrastructure, it is unclear whether clouds are capable of running scientific applications with a reasonable performance per money spent. This work studies the performance of public clouds and places this performance in context tomore » price. We evaluate the raw performance of different services of AWS cloud in terms of the basic resources, such as compute, memory, network and I/O. We also evaluate the performance of the scientific applications running in the cloud. This paper aims to assess the ability of the cloud to perform well, as well as to evaluate the cost of the cloud running scientific applications. We developed a full set of metrics and conducted a comprehensive performance evlauation over the Amazon cloud. We evaluated EC2, S3, EBS and DynamoDB among the many Amazon AWS services. We evaluated the memory sub-system performance with CacheBench, the network performance with iperf, processor and network performance with the HPL benchmark application, and shared storage with NFS and PVFS in addition to S3. We also evaluated a real scientific computing application through the Swift parallel scripting system at scale. Armed with both detailed benchmarks to gauge expected performance and a detailed monetary cost analysis, we expect this paper will be a recipe cookbook for scientists to help them decide where to deploy and run their scientific applications between public clouds, private clouds, or hybrid clouds.« less

Semantic knowledge for histopathological image analysis: from ontologies to processing portals and deep learning

NASA Astrophysics Data System (ADS)

Kergosien, Yannick L.; Racoceanu, Daniel

2017-11-01

This article presents our vision about the next generation of challenges in computational/digital pathology. The key role of the domain ontology, developed in a sustainable manner (i.e. using reference checklists and protocols, as the living semantic repositories), opens the way to effective/sustainable traceability and relevance feedback concerning the use of existing machine learning algorithms, proven to be very performant in the latest digital pathology challenges (i.e. convolutional neural networks). Being able to work in an accessible web-service environment, with strictly controlled issues regarding intellectual property (image and data processing/analysis algorithms) and medical data/image confidentiality is essential for the future. Among the web-services involved in the proposed approach, the living yellow pages in the area of computational pathology seems to be very important in order to reach an operational awareness, validation, and feasibility. This represents a very promising way to go to the next generation of tools, able to bring more guidance to the computer scientists and confidence to the pathologists, towards an effective/efficient daily use. Besides, a consistent feedback and insights will be more likely to emerge in the near future - from these sophisticated machine learning tools - back to the pathologists-, strengthening, therefore, the interaction between the different actors of a sustainable biomedical ecosystem (patients, clinicians, biologists, engineers, scientists etc.). Beside going digital/computational - with virtual slide technology demanding new workflows-, Pathology must prepare for another coming revolution: semantic web technologies now enable the knowledge of experts to be stored in databases, shared through the Internet, and accessible by machines. Traceability, disambiguation of reports, quality monitoring, interoperability between health centers are some of the associated benefits that pathologists were seeking. However, major changes are also to be expected for the relation of human diagnosis to machine based procedures. Improving on a former imaging platform which used a local knowledge base and a reasoning engine to combine image processing modules into higher level tasks, we propose a framework where different actors of the histopathology imaging world can cooperate using web services - exchanging knowledge as well as imaging services - and where the results of such collaborations on diagnostic related tasks can be evaluated in international challenges such as those recently organized for mitosis detection, nuclear atypia, or tissue architecture in the context of cancer grading. This framework is likely to offer an effective context-guidance and traceability to Deep Learning approaches, with an interesting promising perspective given by the multi-task learning (MTL) paradigm, distinguished by its applicability to several different learning algorithms, its non- reliance on specialized architectures and the promising results demonstrated, in particular towards the problem of weak supervision-, an issue found when direct links from pathology terms in reports to corresponding regions within images are missing.

Construction of an advanced software tool for planetary atmospheric modeling

NASA Technical Reports Server (NTRS)

Friedland, Peter; Keller, Richard M.; Mckay, Christopher P.; Sims, Michael H.; Thompson, David E.

1993-01-01

Scientific model-building can be a time intensive and painstaking process, often involving the development of large complex computer programs. Despite the effort involved, scientific models cannot be distributed easily and shared with other scientists. In general, implemented scientific models are complicated, idiosyncratic, and difficult for anyone but the original scientist/programmer to understand. We propose to construct a scientific modeling software tool that serves as an aid to the scientist in developing, using and sharing models. The proposed tool will include an interactive intelligent graphical interface and a high-level domain-specific modeling language. As a testbed for this research, we propose to develop a software prototype in the domain of planetary atmospheric modeling.

HERCULES: A Pattern Driven Code Transformation System

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

Kartsaklis, Christos; Hernandez, Oscar R; Hsu, Chung-Hsing

2012-01-01

New parallel computers are emerging, but developing efficient scientific code for them remains difficult. A scientist must manage not only the science-domain complexity but also the performance-optimization complexity. HERCULES is a code transformation system designed to help the scientist to separate the two concerns, which improves code maintenance, and facilitates performance optimization. The system combines three technologies, code patterns, transformation scripts and compiler plugins, to provide the scientist with an environment to quickly implement code transformations that suit his needs. Unlike existing code optimization tools, HERCULES is unique in its focus on user-level accessibility. In this paper we discuss themore » design, implementation and an initial evaluation of HERCULES.« less

Construction of an advanced software tool for planetary atmospheric modeling

NASA Technical Reports Server (NTRS)

Friedland, Peter; Keller, Richard M.; Mckay, Christopher P.; Sims, Michael H.; Thompson, David E.

1992-01-01

Scientific model-building can be a time intensive and painstaking process, often involving the development of large complex computer programs. Despite the effort involved, scientific models cannot be distributed easily and shared with other scientists. In general, implemented scientific models are complicated, idiosyncratic, and difficult for anyone but the original scientist/programmer to understand. We propose to construct a scientific modeling software tool that serves as an aid to the scientist in developing, using and sharing models. The proposed tool will include an interactive intelligent graphical interface and a high-level domain-specific modeling language. As a test bed for this research, we propose to develop a software prototype in the domain of planetary atmospheric modeling.

Establishment of an Undergraduate Research and Training Program in Radiochemistry at Florida Memorial University, a Historically Black College or University (HBCU)

NASA Astrophysics Data System (ADS)

Tamalis, Dimitri; Stiffin, Rose; Elliott, Michael; Huisso, Ayivi; Biegalski, Steven; Landsberger, Sheldon

2009-08-01

With the passing of the Energy Policy Act of 2005, the United States is experiencing for the first time in over two decades, what some refer to as the "Nuclear Renaissance". The US Nuclear Regulatory Commission (NRC) recognizes this surge in application submissions and is committed to reviewing these applications in a timely manner to support the country's growing energy demands. Notwithstanding these facts, it is understood that the nuclear industry requires appropriately trained and educated personnel to support the growing needs of the nuclear industry and the US NRC. Equally important is the need to educate the next generation of students in nuclear non-proliferation, nuclear forensics and various aspects of homeland security for the national laboratories and the Department of Defense. From mechanical engineers educated and experienced in materials, thermal/fluid dynamics, and component failure analysis, to physicists using advanced computing techniques to design the next generation of nuclear reactor fuel elements, the need for new engineers, scientists, and health physicist has never been greater.

A downloadable meshed human canine tooth model with PDL and bone for finite element simulations.

PubMed

Boryor, Andrew; Hohmann, Ansgar; Geiger, Martin; Wolfram, Uwe; Sander, Christian; Sander, Franz Günter

2009-09-01

The aim of this study is to relieve scientists from the complex and time-consuming task of model generation by providing a model of a canine tooth and its periradicular tissues for Finite Element Method (FEM) simulations. This was achieved with diverse commercial software, based on a micro-computed tomography of the specimen. The Finite Element (FE) Model consists of enamel, dentin, nerve (innervation), periodontal ligament (PDL), and the surrounding cortical bone with trabecular structure. The area and volume meshes are of a very high quality in order to represent the model in a detailed form. Material properties are to be set individually by every user. The tooth model is provided for Abaqus, Ansys, HyperMesh, Nastran and as STL files, in an ASCII format for free download. This can help reduce the cost and effort of generating a tooth model for some research institutions, and may encourage other research groups to provide their high quality models for other researchers. By providing FE models, research results, especially FEM simulations, could be easily verified by others.

Scaffolding Students' Online Critiquing of Expert- and Peer-generated Molecular Models of Chemical Reactions

NASA Astrophysics Data System (ADS)

Chang, Hsin-Yi; Chang, Hsiang-Chi

2013-08-01

In this study, we developed online critiquing activities using an open-source computer learning environment. We investigated how well the activities scaffolded students to critique molecular models of chemical reactions made by scientists, peers, and a fictitious peer, and whether the activities enhanced the students' understanding of science models and chemical reactions. The activities were implemented in an eighth-grade class with 28 students in a public junior high school in southern Taiwan. The study employed mixed research methods. Data collected included pre- and post-instructional assessments, post-instructional interviews, and students' electronic written responses and oral discussions during the critiquing activities. The results indicated that these activities guided the students to produce overall quality critiques. Also, the students developed a more sophisticated understanding of chemical reactions and scientific models as a result of the intervention. Design considerations for effective model critiquing activities are discussed based on observational results, including the use of peer-generated artefacts for critiquing to promote motivation and collaboration, coupled with critiques of scientific models to enhance students' epistemological understanding of model purpose and communication.

The species translation challenge—A systems biology perspective on human and rat bronchial epithelial cells

PubMed Central

Poussin, Carine; Mathis, Carole; Alexopoulos, Leonidas G; Messinis, Dimitris E; Dulize, Rémi H J; Belcastro, Vincenzo; Melas, Ioannis N; Sakellaropoulos, Theodore; Rhrissorrakrai, Kahn; Bilal, Erhan; Meyer, Pablo; Talikka, Marja; Boué, Stéphanie; Norel, Raquel; Rice, John J; Stolovitzky, Gustavo; Ivanov, Nikolai V; Peitsch, Manuel C; Hoeng, Julia

2014-01-01

The biological responses to external cues such as drugs, chemicals, viruses and hormones, is an essential question in biomedicine and in the field of toxicology, and cannot be easily studied in humans. Thus, biomedical research has continuously relied on animal models for studying the impact of these compounds and attempted to ‘translate’ the results to humans. In this context, the SBV IMPROVER (Systems Biology Verification for Industrial Methodology for PROcess VErification in Research) collaborative initiative, which uses crowd-sourcing techniques to address fundamental questions in systems biology, invited scientists to deploy their own computational methodologies to make predictions on species translatability. A multi-layer systems biology dataset was generated that was comprised of phosphoproteomics, transcriptomics and cytokine data derived from normal human (NHBE) and rat (NRBE) bronchial epithelial cells exposed in parallel to more than 50 different stimuli under identical conditions. The present manuscript describes in detail the experimental settings, generation, processing and quality control analysis of the multi-layer omics dataset accessible in public repositories for further intra- and inter-species translation studies. PMID:25977767

The species translation challenge-a systems biology perspective on human and rat bronchial epithelial cells.

PubMed

Poussin, Carine; Mathis, Carole; Alexopoulos, Leonidas G; Messinis, Dimitris E; Dulize, Rémi H J; Belcastro, Vincenzo; Melas, Ioannis N; Sakellaropoulos, Theodore; Rhrissorrakrai, Kahn; Bilal, Erhan; Meyer, Pablo; Talikka, Marja; Boué, Stéphanie; Norel, Raquel; Rice, John J; Stolovitzky, Gustavo; Ivanov, Nikolai V; Peitsch, Manuel C; Hoeng, Julia

2014-01-01

The biological responses to external cues such as drugs, chemicals, viruses and hormones, is an essential question in biomedicine and in the field of toxicology, and cannot be easily studied in humans. Thus, biomedical research has continuously relied on animal models for studying the impact of these compounds and attempted to 'translate' the results to humans. In this context, the SBV IMPROVER (Systems Biology Verification for Industrial Methodology for PROcess VErification in Research) collaborative initiative, which uses crowd-sourcing techniques to address fundamental questions in systems biology, invited scientists to deploy their own computational methodologies to make predictions on species translatability. A multi-layer systems biology dataset was generated that was comprised of phosphoproteomics, transcriptomics and cytokine data derived from normal human (NHBE) and rat (NRBE) bronchial epithelial cells exposed in parallel to more than 50 different stimuli under identical conditions. The present manuscript describes in detail the experimental settings, generation, processing and quality control analysis of the multi-layer omics dataset accessible in public repositories for further intra- and inter-species translation studies.

A visiting scientist program in atmospheric sciences for the Goddard Space Flight Center

NASA Technical Reports Server (NTRS)

Davis, M. H.

1989-01-01

A visiting scientist program was conducted in the atmospheric sciences and related areas at the Goddard Laboratory for Atmospheres. Research was performed in mathematical analysis as applied to computer modeling of the atmospheres; development of atmospheric modeling programs; analysis of remotely sensed atmospheric, surface, and oceanic data and its incorporation into atmospheric models; development of advanced remote sensing instrumentation; and related research areas. The specific research efforts are detailed by tasks.