A Combined Eulerian-Lagrangian Data Representation for Large-Scale Applications.

PubMed

Sauer, Franz; Xie, Jinrong; Ma, Kwan-Liu

2017-10-01

The Eulerian and Lagrangian reference frames each provide a unique perspective when studying and visualizing results from scientific systems. As a result, many large-scale simulations produce data in both formats, and analysis tasks that simultaneously utilize information from both representations are becoming increasingly popular. However, due to their fundamentally different nature, drawing correlations between these data formats is a computationally difficult task, especially in a large-scale setting. In this work, we present a new data representation which combines both reference frames into a joint Eulerian-Lagrangian format. By reorganizing Lagrangian information according to the Eulerian simulation grid into a "unit cell" based approach, we can provide an efficient out-of-core means of sampling, querying, and operating with both representations simultaneously. We also extend this design to generate multi-resolution subsets of the full data to suit the viewer's needs and provide a fast flow-aware trajectory construction scheme. We demonstrate the effectiveness of our method using three large-scale real world scientific datasets and provide insight into the types of performance gains that can be achieved.

Data Intensive Scientific Workflows on a Federated Cloud: CRADA Final Report

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

Garzoglio, Gabriele

The Fermilab Scientific Computing Division and the KISTI Global Science Experimental Data Hub Center have built a prototypical large-scale infrastructure to handle scientific workflows of stakeholders to run on multiple cloud resources. The demonstrations have been in the areas of (a) Data-Intensive Scientific Workflows on Federated Clouds, (b) Interoperability and Federation of Cloud Resources, and (c) Virtual Infrastructure Automation to enable On-Demand Services.

Large-scale quarantine following biological terrorism in the United States: scientific examination, logistic and legal limits, and possible consequences.

PubMed

Barbera, J; Macintyre, A; Gostin, L; Inglesby, T; O'Toole, T; DeAtley, C; Tonat, K; Layton, M

2001-12-05

Concern for potential bioterrorist attacks causing mass casualties has increased recently. Particular attention has been paid to scenarios in which a biological agent capable of person-to-person transmission, such as smallpox, is intentionally released among civilians. Multiple public health interventions are possible to effect disease containment in this context. One disease control measure that has been regularly proposed in various settings is the imposition of large-scale or geographic quarantine on the potentially exposed population. Although large-scale quarantine has not been implemented in recent US history, it has been used on a small scale in biological hoaxes, and it has been invoked in federally sponsored bioterrorism exercises. This article reviews the scientific principles that are relevant to the likely effectiveness of quarantine, the logistic barriers to its implementation, legal issues that a large-scale quarantine raises, and possible adverse consequences that might result from quarantine action. Imposition of large-scale quarantine-compulsory sequestration of groups of possibly exposed persons or human confinement within certain geographic areas to prevent spread of contagious disease-should not be considered a primary public health strategy in most imaginable circumstances. In the majority of contexts, other less extreme public health actions are likely to be more effective and create fewer unintended adverse consequences than quarantine. Actions and areas for future research, policy development, and response planning efforts are provided.

In Defense of the National Labs and Big-Budget Science

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

Goodwin, J R

2008-07-29

The purpose of this paper is to present the unofficial and unsanctioned opinions of a Visiting Scientist at Lawrence Livermore National Laboratory on the values of LLNL and the other National Labs. The basic founding value and goal of the National Labs is big-budget scientific research, along with smaller-budget scientific research that cannot easily be done elsewhere. The most important example in the latter category is classified defense-related research. The historical guiding light here is the Manhattan Project. This endeavor was unique in human history, and might remain so. The scientific expertise and wealth of an entire nation was tappedmore » in a project that was huge beyond reckoning, with no advance guarantee of success. It was in many respects a clash of scientific titans, with a large supporting cast, collaborating toward a single well-defined goal. Never had scientists received so much respect, so much money, and so much intellectual freedom to pursue scientific progress. And never was the gap between theory and implementation so rapidly narrowed, with results that changed the world, completely. Enormous resources are spent at the national or international level on large-scale scientific projects. LLNL has the most powerful computer in the world, Blue Gene/L. (Oops, Los Alamos just seized the title with Roadrunner; such titles regularly change hands.) LLNL also has the largest laser in the world, the National Ignition Facility (NIF). Lawrence Berkeley National Lab (LBNL) has the most powerful microscope in the world. Not only is it beyond the resources of most large corporations to make such expenditures, but the risk exceeds the possible rewards for those corporations that could. Nor can most small countries afford to finance large scientific projects, and not even the richest can afford largess, especially if Congress is under major budget pressure. Some big-budget research efforts are funded by international consortiums, such as the Large Hadron Collider (LHC) at CERN, and the International Tokamak Experimental Reactor (ITER) in Cadarache, France, a magnetic-confinement fusion research project. The postWWII histories of particle and fusion physics contain remarkable examples of both international competition, with an emphasis on secrecy, and international cooperation, with an emphasis on shared knowledge and resources. Initiatives to share sometimes came from surprising directions. Most large-scale scientific projects have potential defense applications. NIF certainly does; it is primarily designed to create small-scale fusion explosions. Blue Gene/L operates in part in service to NIF, and in part to various defense projects. The most important defense projects include stewardship of the national nuclear weapons stockpile, and the proposed redesign and replacement of those weapons with fewer, safer, more reliable, longer-lived, and less apocalyptic warheads. Many well-meaning people will consider the optimal lifetime of a nuclear weapon to be zero, but most thoughtful people, when asked how much longer they think this nation will require them, will ask for some time to think. NIF is also designed to create exothermic small-scale fusion explosions. The malapropos 'exothermic' here is a convenience to cover a profusion of complexities, but the basic idea is that the explosions will create more recoverable energy than was used to create them. One can hope that the primary future benefits of success for NIF will be in cost-effective generation of electrical power through controlled small-scale fusion reactions, rather than in improved large-scale fusion explosions. Blue Gene/L also services climate research, genomic research, materials research, and a myriad of other computational problems that become more feasible, reliable, and precise the larger the number of computational nodes employed. Blue Gene/L has to be sited within a security complex for obvious reasons, but its value extends to the nation and the world. There is a duality here between large-scale scientific research machines and the supercomputers used to model them. An astounding example is illustrated in a graph released by EFDAJET, at Oxfordshire, UK, presently the largest operating magnetic-confinement fusion experiment. The graph shows plasma confinement times (an essential performance parameter) for all the major tokamaks in the international fusion program, over their existing lifetimes. The remarkable thing about the data is not so much confinement-time versus date or scale, but the fact that the data are given for both the computer model predictions and the actual experimental measurements, and the two are in phenomenal agreement over the extended range of scales. Supercomputer models, sometimes operating with the intricacy of Schroedinger's equation at quantum physical scales, have become a costly but enormously cost-saving tool.« less

The use of data from national and other large-scale user experience surveys in local quality work: a systematic review.

PubMed

Haugum, Mona; Danielsen, Kirsten; Iversen, Hilde Hestad; Bjertnaes, Oyvind

2014-12-01

An important goal for national and large-scale surveys of user experiences is quality improvement. However, large-scale surveys are normally conducted by a professional external surveyor, creating an institutionalized division between the measurement of user experiences and the quality work that is performed locally. The aim of this study was to identify and describe scientific studies related to the use of national and large-scale surveys of user experiences in local quality work. Ovid EMBASE, Ovid MEDLINE, Ovid PsycINFO and the Cochrane Database of Systematic Reviews. Scientific publications about user experiences and satisfaction about the extent to which data from national and other large-scale user experience surveys are used for local quality work in the health services. Themes of interest were identified and a narrative analysis was undertaken. Thirteen publications were included, all differed substantially in several characteristics. The results show that large-scale surveys of user experiences are used in local quality work. The types of follow-up activity varied considerably from conducting a follow-up analysis of user experience survey data to information sharing and more-systematic efforts to use the data as a basis for improving the quality of care. This review shows that large-scale surveys of user experiences are used in local quality work. However, there is a need for more, better and standardized research in this field. The considerable variation in follow-up activities points to the need for systematic guidance on how to use data in local quality work. © The Author 2014. Published by Oxford University Press in association with the International Society for Quality in Health Care; all rights reserved.

Avi Purkayastha | NREL

Science.gov Websites

Austin, from 2001 to 2007. There he was principal in HPC applications and user support, as well as in research and development in large-scale scientific applications and different HPC systems and technologies Interests HPC applications performance and optimizations|HPC systems and accelerator technologies|Scientific

On the contributions of astroparticle physics to cosmology

NASA Astrophysics Data System (ADS)

Falkenburg, Brigitte

2014-05-01

Studying astroparticle physics sheds new light on scientific explanation and on the ways in which cosmology is empirically underdetermined or not. Astroparticle physics extends the empirical domain of cosmology from purely astronomical data to "multi-messenger astrophysics", i.e., measurements of all kinds of cosmic rays including very high energetic gamma rays, neutrinos, and charged particles. My paper investigates the ways in which these measurements contribute to cosmology and compares them with philosophical views about scientific explanation, the relation between theory and data, and scientific realism. The "standard models" of cosmology and particle physics lack of unified foundations. Both are "piecemeal physics" in Cartwright's sense, but contrary to her metaphysics of a "dappled world" the work in both fields of research aims at unification. Cosmology proceeds "top-down", from models to data and from large scale to small-scale structures of the universe. Astroparticle physics proceeds "bottom-up", from data taking to models and from subatomic particles to large-scale structures of the universe. In order to reconstruct the causal stories of cosmic rays and the nature of their sources, several pragmatic unifying strategies are employed. Standard views about scientific explanation and scientific realism do not cope with these "bottom-up" strategies and the way in which they contribute to cosmology. In addition it has to be noted that the shift to "multi-messenger astrophysics" transforms the relation between cosmological theory and astrophysical data in a mutually holistic way.

A Game of Thrones: Organising and Legitimising Knowledge through PISA Research

ERIC Educational Resources Information Center

Mølstad, Christina E.; Pettersson, Daniel; Forsberg, Eva

2017-01-01

This study investigates knowledge structures and scientific communication using bibliometric methods to explore scientific knowledge production and dissemination. The aim is to develop knowledge about this growing field by investigating studies using international large-scale assessment (ILSA) data, with a specific focus on those using Programme…

A Rich Metadata Filesystem for Scientific Data

ERIC Educational Resources Information Center

Bui, Hoang

2012-01-01

As scientific research becomes more data intensive, there is an increasing need for scalable, reliable, and high performance storage systems. Such data repositories must provide both data archival services and rich metadata, and cleanly integrate with large scale computing resources. ROARS is a hybrid approach to distributed storage that provides…

Research and management issues in large-scale fire modeling

Treesearch

David L. Peterson; Daniel L. Schmoldt

2000-01-01

In 1996, a team of North American fire scientists and resource managers convened to assess the effects of fire disturbance on ecosystems and to develop scientific recommendations for future fire research and management activities. These recommendations - elicited with the Analytic Hierarchy Process - include numerically ranked scientific and managerial questions and...

Are large-scale flow experiments informing the science and management of freshwater ecosystems?

USGS Publications Warehouse

Olden, Julian D.; Konrad, Christopher P.; Melis, Theodore S.; Kennard, Mark J.; Freeman, Mary C.; Mims, Meryl C.; Bray, Erin N.; Gido, Keith B.; Hemphill, Nina P.; Lytle, David A.; McMullen, Laura E.; Pyron, Mark; Robinson, Christopher T.; Schmidt, John C.; Williams, John G.

2013-01-01

Greater scientific knowledge, changing societal values, and legislative mandates have emphasized the importance of implementing large-scale flow experiments (FEs) downstream of dams. We provide the first global assessment of FEs to evaluate their success in advancing science and informing management decisions. Systematic review of 113 FEs across 20 countries revealed that clear articulation of experimental objectives, while not universally practiced, was crucial for achieving management outcomes and changing dam-operating policies. Furthermore, changes to dam operations were three times less likely when FEs were conducted primarily for scientific purposes. Despite the recognized importance of riverine flow regimes, four-fifths of FEs involved only discrete flow events. Over three-quarters of FEs documented both abiotic and biotic outcomes, but only one-third examined multiple taxonomic responses, thus limiting how FE results can inform holistic dam management. Future FEs will present new opportunities to advance scientifically credible water policies.

An Investigation of the Large Scale Evolution and Topology of Coronal Mass Ejections in the Solar Wind

NASA Technical Reports Server (NTRS)

Riley, Peter

2000-01-01

This investigation is concerned with the large-scale evolution and topology of coronal mass ejections (CMEs) in the solar wind. During this reporting period we have focused on several aspects of CME properties, their identification and their evolution in the solar wind. The work included both analysis of Ulysses and ACE observations as well as fluid and magnetohydrodynamic simulations. In addition, we analyzed a series of "density holes" observed in the solar wind, that bear many similarities with CMEs. Finally, this work was communicated to the scientific community at three meetings and has led to three scientific papers that are in various stages of review.

Scientific management and implementation of the geophysical fluid flow cell for Spacelab missions

NASA Technical Reports Server (NTRS)

Hart, J.; Toomre, J.

1980-01-01

Scientific support for the spherical convection experiment to be flown on Spacelab 3 was developed. This experiment takes advantage of the zero gravity environment of the orbiting space laboratory to conduct fundamental fluid flow studies concerned with thermally driven motions inside a rotating spherical shell with radial gravity. Such a system is a laboratory analog of large scale atmospheric and solar circulations. The radial body force necessary to model gravity correctly is obtained by using dielectric polarization forces in a radially varying electric field to produce radial accelerations proportional to temperature. This experiment will answer fundamental questions concerned with establishing the preferred modes of large scale motion in planetary and stellar atmospheres.

The Explorer of Diffuse Galactic Emission (EDGE): Determining the Large-Scale Structure Evolution in the Universe

NASA Technical Reports Server (NTRS)

Silverberg, R. F.; Cheng, E. S.; Cottingham, D. A.; Fixsen, D. J.; Meyer, S. S.; Knox, L.; Timbie, P.; Wilson, G.

2003-01-01

Measurements of the large-scale anisotropy of the Cosmic Infared Background (CIB) can be used to determine the characteristics of the distribution of galaxies at the largest spatial scales. With this information important tests of galaxy evolution models and primordial structure growth are possible. In this paper, we describe the scientific goals, instrumentation, and operation of EDGE, a mission using an Antarctic Long Duration Balloon (LDB) platform. EDGE will osbserve the anisotropy in the CIB in 8 spectral bands from 270 GHz-1.5 THz with 6 arcminute angular resolution over a region -400 square degrees. EDGE uses a one-meter class off-axis telescope and an array of Frequency Selective Bololeters (FSB) to provide the compact and efficient multi-colar, high sensitivity radiometer required to achieve its scientific objectives.

Do large-scale assessments measure students' ability to integrate scientific knowledge?

NASA Astrophysics Data System (ADS)

Lee, Hee-Sun

2010-03-01

Large-scale assessments are used as means to diagnose the current status of student achievement in science and compare students across schools, states, and countries. For efficiency, multiple-choice items and dichotomously-scored open-ended items are pervasively used in large-scale assessments such as Trends in International Math and Science Study (TIMSS). This study investigated how well these items measure secondary school students' ability to integrate scientific knowledge. This study collected responses of 8400 students to 116 multiple-choice and 84 open-ended items and applied an Item Response Theory analysis based on the Rasch Partial Credit Model. Results indicate that most multiple-choice items and dichotomously-scored open-ended items can be used to determine whether students have normative ideas about science topics, but cannot measure whether students integrate multiple pieces of relevant science ideas. Only when the scoring rubric is redesigned to capture subtle nuances of student open-ended responses, open-ended items become a valid and reliable tool to assess students' knowledge integration ability.

Hydrological response of karst systems to large-scale climate variability for different catchments of the French karst observatory network INSU/CNRS SNO KARST

NASA Astrophysics Data System (ADS)

Massei, Nicolas; Labat, David; Jourde, Hervé; Lecoq, Nicolas; Mazzilli, Naomi

2017-04-01

The french karst observatory network SNO KARST is a national initiative from the National Institute for Earth Sciences and Astronomy (INSU) of the National Center for Scientific Research (CNRS). It is also part of the new french research infrastructure for the observation of the critical zone OZCAR. SNO KARST is composed by several karst sites distributed over conterminous France which are located in different physiographic and climatic contexts (Mediterranean, Pyrenean, Jura mountain, western and northwestern shore near the Atlantic or the English Channel). This allows the scientific community to develop advanced research and experiments dedicated to improve understanding of the hydrological functioning of karst catchments. Here we used several sites of SNO KARST in order to assess the hydrological response of karst catchments to long-term variation of large-scale atmospheric circulation. Using NCEP reanalysis products and karst discharge, we analyzed the links between large-scale circulation and karst water resources variability. As karst hydrosystems are highly heterogeneous media, they behave differently across different time-scales : we explore the large-scale/local-scale relationships according to time-scales using a wavelet multiresolution approach of both karst hydrological variables and large-scale climate fields such as sea level pressure (SLP). The different wavelet components of karst discharge in response to the corresponding wavelet component of climate fields are either 1) compared to physico-chemical/geochemical responses at karst springs, or 2) interpreted in terms of hydrological functioning by comparing discharge wavelet components to internal components obtained from precipitation/discharge models using the KARSTMOD conceptual modeling platform of SNO KARST.

Physical-Biological-Optics Model Development and Simulation for the Pacific Ocean and Monterey Bay, California

DTIC Science & Technology

2011-09-30

and easy to apply in large-scale physical-biogeochemical simulations. We also collaborate with Dr. Curt Mobley at Sequoia Scientific for the second...we are collaborating with Dr. Curtis Mobley of Sequoia Scientific on improving the link between the radiative transfer model (EcoLight) within the

"Scientifically-Based Research": The Art of Politics and the Distortion of Science

ERIC Educational Resources Information Center

Shaker, Paul; Ruitenberg, Claudia

2007-01-01

The US Federal Government is forcefully prescribing a narrow definition of "scientifically-based" educational research. US policy, emerging from contemporary neoliberal and technocratic viewpoints and funded and propagated on a large scale, has the potential to influence international thinking on educational research. In this article we continue a…

Electronic Scientific Data & Literature Aggregation: A Review for Librarians

ERIC Educational Resources Information Center

Losoff, Barbara

2009-01-01

The advent of large-scale digital repositories, along with the need for sharing useful data world-wide, demands change to the current information structure. The merging of digital scientific data with scholarly literature has the potential to fulfill the Semantic Web design principles. This paper will identify factors leading to integration of…

Large-scale, high-performance and cloud-enabled multi-model analytics experiments in the context of the Earth System Grid Federation

NASA Astrophysics Data System (ADS)

Fiore, S.; Płóciennik, M.; Doutriaux, C.; Blanquer, I.; Barbera, R.; Williams, D. N.; Anantharaj, V. G.; Evans, B. J. K.; Salomoni, D.; Aloisio, G.

2017-12-01

The increased models resolution in the development of comprehensive Earth System Models is rapidly leading to very large climate simulations output that pose significant scientific data management challenges in terms of data sharing, processing, analysis, visualization, preservation, curation, and archiving.Large scale global experiments for Climate Model Intercomparison Projects (CMIP) have led to the development of the Earth System Grid Federation (ESGF), a federated data infrastructure which has been serving the CMIP5 experiment, providing access to 2PB of data for the IPCC Assessment Reports. In such a context, running a multi-model data analysis experiment is very challenging, as it requires the availability of a large amount of data related to multiple climate models simulations and scientific data management tools for large-scale data analytics. To address these challenges, a case study on climate models intercomparison data analysis has been defined and implemented in the context of the EU H2020 INDIGO-DataCloud project. The case study has been tested and validated on CMIP5 datasets, in the context of a large scale, international testbed involving several ESGF sites (LLNL, ORNL and CMCC), one orchestrator site (PSNC) and one more hosting INDIGO PaaS services (UPV). Additional ESGF sites, such as NCI (Australia) and a couple more in Europe, are also joining the testbed. The added value of the proposed solution is summarized in the following: it implements a server-side paradigm which limits data movement; it relies on a High-Performance Data Analytics (HPDA) stack to address performance; it exploits the INDIGO PaaS layer to support flexible, dynamic and automated deployment of software components; it provides user-friendly web access based on the INDIGO Future Gateway; and finally it integrates, complements and extends the support currently available through ESGF. Overall it provides a new "tool" for climate scientists to run multi-model experiments. At the time this contribution is being written, the proposed testbed represents the first implementation of a distributed large-scale, multi-model experiment in the ESGF/CMIP context, joining together server-side approaches for scientific data analysis, HPDA frameworks, end-to-end workflow management, and cloud computing.

What makes computational open source software libraries successful?

NASA Astrophysics Data System (ADS)

Bangerth, Wolfgang; Heister, Timo

2013-01-01

Software is the backbone of scientific computing. Yet, while we regularly publish detailed accounts about the results of scientific software, and while there is a general sense of which numerical methods work well, our community is largely unaware of best practices in writing the large-scale, open source scientific software upon which our discipline rests. This is particularly apparent in the commonly held view that writing successful software packages is largely the result of simply ‘being a good programmer’ when in fact there are many other factors involved, for example the social skill of community building. In this paper, we consider what we have found to be the necessary ingredients for successful scientific software projects and, in particular, for software libraries upon which the vast majority of scientific codes are built today. In particular, we discuss the roles of code, documentation, communities, project management and licenses. We also briefly comment on the impact on academic careers of engaging in software projects.

Enabling large-scale next-generation sequence assembly with Blacklight

PubMed Central

Couger, M. Brian; Pipes, Lenore; Squina, Fabio; Prade, Rolf; Siepel, Adam; Palermo, Robert; Katze, Michael G.; Mason, Christopher E.; Blood, Philip D.

2014-01-01

Summary A variety of extremely challenging biological sequence analyses were conducted on the XSEDE large shared memory resource Blacklight, using current bioinformatics tools and encompassing a wide range of scientific applications. These include genomic sequence assembly, very large metagenomic sequence assembly, transcriptome assembly, and sequencing error correction. The data sets used in these analyses included uncategorized fungal species, reference microbial data, very large soil and human gut microbiome sequence data, and primate transcriptomes, composed of both short-read and long-read sequence data. A new parallel command execution program was developed on the Blacklight resource to handle some of these analyses. These results, initially reported previously at XSEDE13 and expanded here, represent significant advances for their respective scientific communities. The breadth and depth of the results achieved demonstrate the ease of use, versatility, and unique capabilities of the Blacklight XSEDE resource for scientific analysis of genomic and transcriptomic sequence data, and the power of these resources, together with XSEDE support, in meeting the most challenging scientific problems. PMID:25294974

Side effects of problem-solving strategies in large-scale nutrition science: towards a diversification of health.

PubMed

Penders, Bart; Vos, Rein; Horstman, Klasien

2009-11-01

Solving complex problems in large-scale research programmes requires cooperation and division of labour. Simultaneously, large-scale problem solving also gives rise to unintended side effects. Based upon 5 years of researching two large-scale nutrigenomic research programmes, we argue that problems are fragmented in order to be solved. These sub-problems are given priority for practical reasons and in the process of solving them, various changes are introduced in each sub-problem. Combined with additional diversity as a result of interdisciplinarity, this makes reassembling the original and overall goal of the research programme less likely. In the case of nutrigenomics and health, this produces a diversification of health. As a result, the public health goal of contemporary nutrition science is not reached in the large-scale research programmes we studied. Large-scale research programmes are very successful in producing scientific publications and new knowledge; however, in reaching their political goals they often are less successful.

Tritium

DTIC Science & Technology

2011-11-01

fusion energy -production processes of the particular type of reactor using a lithium (Li) blanket or related alloys such as the Pb-17Li eutectic. As such, tritium breeding is intimately connected with energy production, thermal management, radioactivity management, materials properties, and mechanical structures of any plausible future large-scale fusion power reactor. JASON is asked to examine the current state of scientific knowledge and engineering practice on the physical and chemical bases for large-scale tritium

Scientific Services on the Cloud

NASA Astrophysics Data System (ADS)

Chapman, David; Joshi, Karuna P.; Yesha, Yelena; Halem, Milt; Yesha, Yaacov; Nguyen, Phuong

Scientific Computing was one of the first every applications for parallel and distributed computation. To this date, scientific applications remain some of the most compute intensive, and have inspired creation of petaflop compute infrastructure such as the Oak Ridge Jaguar and Los Alamos RoadRunner. Large dedicated hardware infrastructure has become both a blessing and a curse to the scientific community. Scientists are interested in cloud computing for much the same reason as businesses and other professionals. The hardware is provided, maintained, and administrated by a third party. Software abstraction and virtualization provide reliability, and fault tolerance. Graduated fees allow for multi-scale prototyping and execution. Cloud computing resources are only a few clicks away, and by far the easiest high performance distributed platform to gain access to. There may still be dedicated infrastructure for ultra-scale science, but the cloud can easily play a major part of the scientific computing initiative.

Variations in University Students' Scientific Reasoning Skills across Majors, Years, and Types of Institutions

ERIC Educational Resources Information Center

Ding, Lin; Wei, Xin; Liu, Xiufeng

2016-01-01

This study investigates three aspects--university major, year, and institution type--in relation to student scientific reasoning. Students from three majors (science, engineering, and education), four year levels (years 1 through 4), and two tiers of Chinese universities (tiers 1 and 2) participated in the study. A large-scale written assessment…

Skin Friction Reduction Through Large-Scale Forcing

NASA Astrophysics Data System (ADS)

Bhatt, Shibani; Artham, Sravan; Gnanamanickam, Ebenezer

2017-11-01

Flow structures in a turbulent boundary layer larger than an integral length scale (δ), referred to as large-scales, interact with the finer scales in a non-linear manner. By targeting these large-scales and exploiting this non-linear interaction wall shear stress (WSS) reduction of over 10% has been achieved. The plane wall jet (PWJ), a boundary layer which has highly energetic large-scales that become turbulent independent of the near-wall finer scales, is the chosen model flow field. It's unique configuration allows for the independent control of the large-scales through acoustic forcing. Perturbation wavelengths from about 1 δ to 14 δ were considered with a reduction in WSS for all wavelengths considered. This reduction, over a large subset of the wavelengths, scales with both inner and outer variables indicating a mixed scaling to the underlying physics, while also showing dependence on the PWJ global properties. A triple decomposition of the velocity fields shows an increase in coherence due to forcing with a clear organization of the small scale turbulence with respect to the introduced large-scale. The maximum reduction in WSS occurs when the introduced large-scale acts in a manner so as to reduce the turbulent activity in the very near wall region. This material is based upon work supported by the Air Force Office of Scientific Research under Award Number FA9550-16-1-0194 monitored by Dr. Douglas Smith.

Pynamic: the Python Dynamic Benchmark

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

Lee, G L; Ahn, D H; de Supinksi, B R

2007-07-10

Python is widely used in scientific computing to facilitate application development and to support features such as computational steering. Making full use of some of Python's popular features, which improve programmer productivity, leads to applications that access extremely high numbers of dynamically linked libraries (DLLs). As a result, some important Python-based applications severely stress a system's dynamic linking and loading capabilities and also cause significant difficulties for most development environment tools, such as debuggers. Furthermore, using the Python paradigm for large scale MPI-based applications can create significant file IO and further stress tools and operating systems. In this paper, wemore » present Pynamic, the first benchmark program to support configurable emulation of a wide-range of the DLL usage of Python-based applications for large scale systems. Pynamic has already accurately reproduced system software and tool issues encountered by important large Python-based scientific applications on our supercomputers. Pynamic provided insight for our system software and tool vendors, and our application developers, into the impact of several design decisions. As we describe the Pynamic benchmark, we will highlight some of the issues discovered in our large scale system software and tools using Pynamic.« less

Moon-based Earth Observation for Large Scale Geoscience Phenomena

NASA Astrophysics Data System (ADS)

Guo, Huadong; Liu, Guang; Ding, Yixing

2016-07-01

The capability of Earth observation for large-global-scale natural phenomena needs to be improved and new observing platform are expected. We have studied the concept of Moon as an Earth observation in these years. Comparing with manmade satellite platform, Moon-based Earth observation can obtain multi-spherical, full-band, active and passive information,which is of following advantages: large observation range, variable view angle, long-term continuous observation, extra-long life cycle, with the characteristics of longevity ,consistency, integrity, stability and uniqueness. Moon-based Earth observation is suitable for monitoring the large scale geoscience phenomena including large scale atmosphere change, large scale ocean change,large scale land surface dynamic change,solid earth dynamic change,etc. For the purpose of establishing a Moon-based Earth observation platform, we already have a plan to study the five aspects as follows: mechanism and models of moon-based observing earth sciences macroscopic phenomena; sensors' parameters optimization and methods of moon-based Earth observation; site selection and environment of moon-based Earth observation; Moon-based Earth observation platform; and Moon-based Earth observation fundamental scientific framework.

Adding intelligence to scientific data management

NASA Technical Reports Server (NTRS)

Campbell, William J.; Short, Nicholas M., Jr.; Treinish, Lloyd A.

1989-01-01

NASA plans to solve some of the problems of handling large-scale scientific data bases by turning to artificial intelligence (AI) are discussed. The growth of the information glut and the ways that AI can help alleviate the resulting problems are reviewed. The employment of the Intelligent User Interface prototype, where the user will generate his own natural language query with the assistance of the system, is examined. Spatial data management, scientific data visualization, and data fusion are discussed.

Large-Scale Distributed Computational Fluid Dynamics on the Information Power Grid Using Globus

NASA Technical Reports Server (NTRS)

Barnard, Stephen; Biswas, Rupak; Saini, Subhash; VanderWijngaart, Robertus; Yarrow, Maurice; Zechtzer, Lou; Foster, Ian; Larsson, Olle

1999-01-01

This paper describes an experiment in which a large-scale scientific application development for tightly-coupled parallel machines is adapted to the distributed execution environment of the Information Power Grid (IPG). A brief overview of the IPG and a description of the computational fluid dynamics (CFD) algorithm are given. The Globus metacomputing toolkit is used as the enabling device for the geographically-distributed computation. Modifications related to latency hiding and Load balancing were required for an efficient implementation of the CFD application in the IPG environment. Performance results on a pair of SGI Origin 2000 machines indicate that real scientific applications can be effectively implemented on the IPG; however, a significant amount of continued effort is required to make such an environment useful and accessible to scientists and engineers.

Klamath Basin: A Watershed Approach to Support Habitat Restoration, Species Recovery, and Water Resource Planning

USGS Publications Warehouse

VanderKooi, S.P.; Thorsteinson, L.

2007-01-01

Water allocation among human and natural resource uses in the American West is challenging. Western rivers have been largely managed for hydropower, irrigation, drinking water, and navigation. Today land and water use practices have gained importance, particularly as aging dams are faced with re-licensing requirements and provisions of the Endangered Species and Clean Water Acts. Rising demand for scarce water heightens the need for scientific research to predict consequences of management actions on habitats, human resource use, and fish and wildlife. Climate change, introduction of invasive species, or restoration of fish passage can have large, landscape-scaled consequences - research must expand to encompass the appropriate scale and by applying multiple scientific disciplines to complex ecosystem challenges improve the adaptive management framework for decision-making.

Scientific opportunities using satellite surface wind stress measurements over the ocean

NASA Technical Reports Server (NTRS)

1982-01-01

Scientific opportunities that would be possible with the ability to collect wind data from space are highlighted. Minimum requirements for the space platform and ground data reduction system are assessed. The operational uses that may develop in government and commercial applications of these data are reviewed. The opportunity to predict the large-scale ocean anomaly called El Nino is highlighted.

Ecological foundations for fire management in North American forest and shrubland ecosystems

Treesearch

J.E. Keeley; G.H. Aplet; N.L. Christensen; S.G. Conard; E.A. Johnson; P.N. Omi; D.L. Peterson; T.W. Swetnam

2009-01-01

This synthesis provides an ecological foundation for management of the diverse ecosystems and fire regimes of North America based on scientific principles of fire interactions with vegetation, fuels, and biophysical processes. Although a large amount of scientific data on fire exists, most of those data have been collected at small spatial and temporal scales. Thus, it...

The Computing and Data Grid Approach: Infrastructure for Distributed Science Applications

NASA Technical Reports Server (NTRS)

Johnston, William E.

2002-01-01

With the advent of Grids - infrastructure for using and managing widely distributed computing and data resources in the science environment - there is now an opportunity to provide a standard, large-scale, computing, data, instrument, and collaboration environment for science that spans many different projects and provides the required infrastructure and services in a relatively uniform and supportable way. Grid technology has evolved over the past several years to provide the services and infrastructure needed for building 'virtual' systems and organizations. We argue that Grid technology provides an excellent basis for the creation of the integrated environments that can combine the resources needed to support the large- scale science projects located at multiple laboratories and universities. We present some science case studies that indicate that a paradigm shift in the process of science will come about as a result of Grids providing transparent and secure access to advanced and integrated information and technologies infrastructure: powerful computing systems, large-scale data archives, scientific instruments, and collaboration tools. These changes will be in the form of services that can be integrated with the user's work environment, and that enable uniform and highly capable access to these computers, data, and instruments, regardless of the location or exact nature of these resources. These services will integrate transient-use resources like computing systems, scientific instruments, and data caches (e.g., as they are needed to perform a simulation or analyze data from a single experiment); persistent-use resources. such as databases, data catalogues, and archives, and; collaborators, whose involvement will continue for the lifetime of a project or longer. While we largely address large-scale science in this paper, Grids, particularly when combined with Web Services, will address a broad spectrum of science scenarios. both large and small scale.

Scientific goals of the Cooperative Multiscale Experiment (CME)

NASA Technical Reports Server (NTRS)

Cotton, William

1993-01-01

Mesoscale Convective Systems (MCS) form the focus of CME. Recent developments in global climate models, the urgent need to improve the representation of the physics of convection, radiation, the boundary layer, and orography, and the surge of interest in coupling hydrologic, chemistry, and atmospheric models of various scales, have emphasized the need for a broad interdisciplinary and multi-scale approach to understanding and predicting MCS's and their interactions with processes at other scales. The role of mesoscale systems in the large-scale atmospheric circulation, the representation of organized convection and other mesoscale flux sources in terms of bulk properties, and the mutually consistent treatment of water vapor, clouds, radiation, and precipitation, are all key scientific issues concerning which CME will seek to increase understanding. The manner in which convective, mesoscale, and larger scale processes interact to produce and organize MCS's, the moisture cycling properties of MCS's, and the use of coupled cloud/mesoscale models to better understand these processes, are also major objectives of CME. Particular emphasis will be placed on the multi-scale role of MCS's in the hydrological cycle and in the production and transport of chemical trace constituents. The scientific goals of the CME consist of the following: understand how the large and small scales of motion influence the location, structure, intensity, and life cycles of MCS's; understand processes and conditions that determine the relative roles of balanced (slow manifold) and unbalanced (fast manifold) circulations in the dynamics of MCS's throughout their life cycles; assess the predictability of MCS's and improve the quantitative forecasting of precipitation and severe weather events; quantify the upscale feedback of MCS's to the large-scale environment and determine interrelationships between MCS occurrence and variations in the large-scale flow and surface forcing; provide a data base for initialization and verification of coupled regional, mesoscale/hydrologic, mesoscale/chemistry, and prototype mesoscale/cloud-resolving models for prediction of severe weather, ceilings, and visibility; provide a data base for initialization and validation of cloud-resolving models, and for assisting in the fabrication, calibration, and testing of cloud and MCS parameterization schemes; and provide a data base for validation of four dimensional data assimilation schemes and algorithms for retrieving cloud and state parameters from remote sensing instrumentation.

Modeling Change in Large-Scale Longitudinal Studies of Educational Growth: Four Decades of Contributions to the Assessment of Educational Growth. ETC R&D Scientific and Policy Contributions Series. ETS SPC-12-01. Research Report No. RR-12-04

ERIC Educational Resources Information Center

Rock, Donald A.

2012-01-01

This paper provides a history of ETS's role in developing assessment instruments and psychometric procedures for measuring change in large-scale national assessments funded by the Longitudinal Studies branch of the National Center for Education Statistics. It documents the innovations developed during more than 30 years of working with…

Modeling Change in Large-Scale Longitudinal Studies of Educational Growth: Four Decades of Contributions to the Assessment of Educational Growth. Research Report. ETS RR-12-04. ETS R&D Scientific and Policy Contributions Series. ETS SPC-12-01

ERIC Educational Resources Information Center

Rock, Donald A.

2012-01-01

This paper provides a history of ETS's role in developing assessment instruments and psychometric procedures for measuring change in large-scale national assessments funded by the Longitudinal Studies branch of the National Center for Education Statistics. It documents the innovations developed during more than 30 years of working with…

Trajectory Segmentation Map-Matching Approach for Large-Scale, High-Resolution GPS Data

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

Zhu, Lei; Holden, Jacob R.; Gonder, Jeffrey D.

With the development of smartphones and portable GPS devices, large-scale, high-resolution GPS data can be collected. Map matching is a critical step in studying vehicle driving activity and recognizing network traffic conditions from the data. A new trajectory segmentation map-matching algorithm is proposed to deal accurately and efficiently with large-scale, high-resolution GPS trajectory data. The new algorithm separated the GPS trajectory into segments. It found the shortest path for each segment in a scientific manner and ultimately generated a best-matched path for the entire trajectory. The similarity of a trajectory segment and its matched path is described by a similaritymore » score system based on the longest common subsequence. The numerical experiment indicated that the proposed map-matching algorithm was very promising in relation to accuracy and computational efficiency. Large-scale data set applications verified that the proposed method is robust and capable of dealing with real-world, large-scale GPS data in a computationally efficient and accurate manner.« less

Trajectory Segmentation Map-Matching Approach for Large-Scale, High-Resolution GPS Data

DOE PAGES

Zhu, Lei; Holden, Jacob R.; Gonder, Jeffrey D.

2017-01-01

With the development of smartphones and portable GPS devices, large-scale, high-resolution GPS data can be collected. Map matching is a critical step in studying vehicle driving activity and recognizing network traffic conditions from the data. A new trajectory segmentation map-matching algorithm is proposed to deal accurately and efficiently with large-scale, high-resolution GPS trajectory data. The new algorithm separated the GPS trajectory into segments. It found the shortest path for each segment in a scientific manner and ultimately generated a best-matched path for the entire trajectory. The similarity of a trajectory segment and its matched path is described by a similaritymore » score system based on the longest common subsequence. The numerical experiment indicated that the proposed map-matching algorithm was very promising in relation to accuracy and computational efficiency. Large-scale data set applications verified that the proposed method is robust and capable of dealing with real-world, large-scale GPS data in a computationally efficient and accurate manner.« less

Architectural Visualization of C/C++ Source Code for Program Comprehension

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

Panas, T; Epperly, T W; Quinlan, D

2006-09-01

Structural and behavioral visualization of large-scale legacy systems to aid program comprehension is still a major challenge. The challenge is even greater when applications are implemented in flexible and expressive languages such as C and C++. In this paper, we consider visualization of static and dynamic aspects of large-scale scientific C/C++ applications. For our investigation, we reuse and integrate specialized analysis and visualization tools. Furthermore, we present a novel layout algorithm that permits a compressive architectural view of a large-scale software system. Our layout is unique in that it allows traditional program visualizations, i.e., graph structures, to be seen inmore » relation to the application's file structure.« less

Robust Control of Multivariable and Large Scale Systems.

DTIC Science & Technology

1986-03-14

AD-A175 $5B ROBUST CONTROL OF MULTIVRRIALE AND LARG SCALE SYSTEMS V2 R75 (U) HONEYWELL SYSTEMS AND RESEARCH CENTER MINNEAPOLIS MN J C DOYLE ET AL...ONIJQ 86 R alFS ja ,.AMIECFOEPF:ORMING ORGANIZATION So OFFICE SYMBOL 7a NAME OF MONITORING ORGANIZATI ON jonevwell Systems & Research If 4000c" Air...Force Office of Scientific Research .~ C :AE S C.rv. Stare arma ZIP Code) 7C ADDRESS (Crty. Stare. am ZIP Code, *3660 Marshall Street NE Building 410

Photographic images captured while sampling for bald eagles near the Davis Pond freshwater diversion structure in Barataria Bay, Louisiana (2009-10)

USGS Publications Warehouse

Jenkins, Jill A.; Jeske, Clinton W.; Allain, Larry K.

2011-01-01

The implementation of freshwater diversions in large-scale coastal restoration schemes presents several scientific and management considerations. Large-scale environmental restructuring necessitates aquatic biomonitoring, and during such field studies, photographs that document animals and habitat may be captured. Among the biomonitoring studies performed in conjunction with the Davis Pond freshwater diversion structure south of New Orleans, Louisiana, only postdiversion study images are readily available, and these are presented here.

Toward server-side, high performance climate change data analytics in the Earth System Grid Federation (ESGF) eco-system

NASA Astrophysics Data System (ADS)

Fiore, Sandro; Williams, Dean; Aloisio, Giovanni

2016-04-01

In many scientific domains such as climate, data is often n-dimensional and requires tools that support specialized data types and primitives to be properly stored, accessed, analysed and visualized. Moreover, new challenges arise in large-scale scenarios and eco-systems where petabytes (PB) of data can be available and data can be distributed and/or replicated (e.g., the Earth System Grid Federation (ESGF) serving the Coupled Model Intercomparison Project, Phase 5 (CMIP5) experiment, providing access to 2.5PB of data for the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). Most of the tools currently available for scientific data analysis in the climate domain fail at large scale since they: (1) are desktop based and need the data locally; (2) are sequential, so do not benefit from available multicore/parallel machines; (3) do not provide declarative languages to express scientific data analysis tasks; (4) are domain-specific, which ties their adoption to a specific domain; and (5) do not provide a workflow support, to enable the definition of complex "experiments". The Ophidia project aims at facing most of the challenges highlighted above by providing a big data analytics framework for eScience. Ophidia provides declarative, server-side, and parallel data analysis, jointly with an internal storage model able to efficiently deal with multidimensional data and a hierarchical data organization to manage large data volumes ("datacubes"). The project relies on a strong background of high performance database management and OLAP systems to manage large scientific data sets. It also provides a native workflow management support, to define processing chains and workflows with tens to hundreds of data analytics operators to build real scientific use cases. With regard to interoperability aspects, the talk will present the contribution provided both to the RDA Working Group on Array Databases, and the Earth System Grid Federation (ESGF) Compute Working Team. Also highlighted will be the results of large scale climate model intercomparison data analysis experiments, for example: (1) defined in the context of the EU H2020 INDIGO-DataCloud project; (2) implemented in a real geographically distributed environment involving CMCC (Italy) and LLNL (US) sites; (3) exploiting Ophidia as server-side, parallel analytics engine; and (4) applied on real CMIP5 data sets available through ESGF.

Northwest Trajectory Analysis Capability: A Platform for Enhancing Computational Biophysics Analysis

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

Peterson, Elena S.; Stephan, Eric G.; Corrigan, Abigail L.

2008-07-30

As computational resources continue to increase, the ability of computational simulations to effectively complement, and in some cases replace, experimentation in scientific exploration also increases. Today, large-scale simulations are recognized as an effective tool for scientific exploration in many disciplines including chemistry and biology. A natural side effect of this trend has been the need for an increasingly complex analytical environment. In this paper, we describe Northwest Trajectory Analysis Capability (NTRAC), an analytical software suite developed to enhance the efficiency of computational biophysics analyses. Our strategy is to layer higher-level services and introduce improved tools within the user’s familiar environmentmore » without preventing researchers from using traditional tools and methods. Our desire is to share these experiences to serve as an example for effectively analyzing data intensive large scale simulation data.« less

Seismic safety in conducting large-scale blasts

NASA Astrophysics Data System (ADS)

Mashukov, I. V.; Chaplygin, V. V.; Domanov, V. P.; Semin, A. A.; Klimkin, M. A.

2017-09-01

In mining enterprises to prepare hard rocks for excavation a drilling and blasting method is used. With the approach of mining operations to settlements the negative effect of large-scale blasts increases. To assess the level of seismic impact of large-scale blasts the scientific staff of Siberian State Industrial University carried out expertise for coal mines and iron ore enterprises. Determination of the magnitude of surface seismic vibrations caused by mass explosions was performed using seismic receivers, an analog-digital converter with recording on a laptop. The registration results of surface seismic vibrations during production of more than 280 large-scale blasts at 17 mining enterprises in 22 settlements are presented. The maximum velocity values of the Earth’s surface vibrations are determined. The safety evaluation of seismic effect was carried out according to the permissible value of vibration velocity. For cases with exceedance of permissible values recommendations were developed to reduce the level of seismic impact.

Profiling and Improving I/O Performance of a Large-Scale Climate Scientific Application

NASA Technical Reports Server (NTRS)

Liu, Zhuo; Wang, Bin; Wang, Teng; Tian, Yuan; Xu, Cong; Wang, Yandong; Yu, Weikuan; Cruz, Carlos A.; Zhou, Shujia; Clune, Tom;

Growing Your Career through Volunteering and Leadership

NASA Astrophysics Data System (ADS)

O'Riordan, C. A.; Meth, C.

2007-12-01

From giving your first paper at a scientific meeting to chairing committees that make multi-million dollar decisions, scientific organizations provide critical opportunities for growing your career. Many organizations support student activities by providing travel grants and fellowships - an important first step towards joining the larger scientific community. Beyond these standard opportunities, organizations also provide opportunities for students interested in gaining leadership experience, a skill not typically acquired in graduate science programs. For example, the Consortium for Leadership's Schlanger Ocean Drilling Fellowship provides research funds to graduate students, but also introduces the fellows to the communication skills needed to become successful members of their scientific community. Beyond student opportunities, volunteering provides mid-career and established scientists further experience in leadership. Opportunities exist in advising government science policy, guiding large-scale research programs, organizing large scientific meetings, and serving on non-profit boards. The variety of volunteer and leadership opportunities that are available give scientists at all stages of their career a chance to expand and diversify their experience, leading to new successes.

Subgrid-scale models for large-eddy simulation of rotating turbulent channel flows

NASA Astrophysics Data System (ADS)

Silvis, Maurits H.; Bae, Hyunji Jane; Trias, F. Xavier; Abkar, Mahdi; Moin, Parviz; Verstappen, Roel

2017-11-01

We aim to design subgrid-scale models for large-eddy simulation of rotating turbulent flows. Rotating turbulent flows form a challenging test case for large-eddy simulation due to the presence of the Coriolis force. The Coriolis force conserves the total kinetic energy while transporting it from small to large scales of motion, leading to the formation of large-scale anisotropic flow structures. The Coriolis force may also cause partial flow laminarization and the occurrence of turbulent bursts. Many subgrid-scale models for large-eddy simulation are, however, primarily designed to parametrize the dissipative nature of turbulent flows, ignoring the specific characteristics of transport processes. We, therefore, propose a new subgrid-scale model that, in addition to the usual dissipative eddy viscosity term, contains a nondissipative nonlinear model term designed to capture transport processes, such as those due to rotation. We show that the addition of this nonlinear model term leads to improved predictions of the energy spectra of rotating homogeneous isotropic turbulence as well as of the Reynolds stress anisotropy in spanwise-rotating plane-channel flows. This work is financed by the Netherlands Organisation for Scientific Research (NWO) under Project Number 613.001.212.

Recent developments in large-scale ozone generation with dielectric barrier discharges

NASA Astrophysics Data System (ADS)

Lopez, Jose L.

2014-10-01

Large-scale ozone generation for industrial applications has been entirely based on the creation of microplasmas or microdischarges created using dielectric barrier discharge (DBD) reactors. Although versions of DBD generated ozone have been in continuous use for over a hundred years especially in water treatment, recent changes in environmental awareness and sustainability have lead to a surge of ozone generating facilities throughout the world. As a result of this enhanced global usage of this environmental cleaning application various new discoveries have emerged in the science and technology of ozone generation. This presentation will describe some of the most recent breakthrough developments in large-scale ozone generation while further addressing some of the current scientific and engineering challenges of this technology.

The future of scientific workflows

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

Deelman, Ewa; Peterka, Tom; Altintas, Ilkay

Today’s computational, experimental, and observational sciences rely on computations that involve many related tasks. The success of a scientific mission often hinges on the computer automation of these workflows. In April 2015, the US Department of Energy (DOE) invited a diverse group of domain and computer scientists from national laboratories supported by the Office of Science, the National Nuclear Security Administration, from industry, and from academia to review the workflow requirements of DOE’s science and national security missions, to assess the current state of the art in science workflows, to understand the impact of emerging extreme-scale computing systems on thosemore » workflows, and to develop requirements for automated workflow management in future and existing environments. This article is a summary of the opinions of over 50 leading researchers attending this workshop. We highlight use cases, computing systems, workflow needs and conclude by summarizing the remaining challenges this community sees that inhibit large-scale scientific workflows from becoming a mainstream tool for extreme-scale science.« less

sbtools: A package connecting R to cloud-based data for collaborative online research

USGS Publications Warehouse

Winslow, Luke; Chamberlain, Scott; Appling, Alison P.; Read, Jordan S.

2016-01-01

The adoption of high-quality tools for collaboration and reproducible research such as R and Github is becoming more common in many research fields. While Github and other version management systems are excellent resources, they were originally designed to handle code and scale poorly to large text-based or binary datasets. A number of scientific data repositories are coming online and are often focused on dataset archival and publication. To handle collaborative workflows using large scientific datasets, there is increasing need to connect cloud-based online data storage to R. In this article, we describe how the new R package sbtools enables direct access to the advanced online data functionality provided by ScienceBase, the U.S. Geological Survey’s online scientific data storage platform.

The Classroom Sandbox: A Physical Model for Scientific Inquiry

ERIC Educational Resources Information Center

Feldman, Allan; Cooke, Michele L.; Ellsworth, Mary S.

2010-01-01

For scientists, the sandbox serves as an analog for faulting in Earth's crust. Here, the large, slow processes within the crust can be scaled to the size of a table, and time scales are directly observable. This makes it a useful tool for demonstrating the role of inquiry in science. For this reason, the sandbox is also helpful for learning…

Solution of matrix equations using sparse techniques

NASA Technical Reports Server (NTRS)

Baddourah, Majdi

1994-01-01

The solution of large systems of matrix equations is key to the solution of a large number of scientific and engineering problems. This talk describes the sparse matrix solver developed at Langley which can routinely solve in excess of 263,000 equations in 40 seconds on one Cray C-90 processor. It appears that for large scale structural analysis applications, sparse matrix methods have a significant performance advantage over other methods.

The Use of the Nature of Scientific Knowledge Scale as a Entrance Assessment in a Large, Online Citizen Science Project

NASA Astrophysics Data System (ADS)

Price, Aaron

2010-01-01

Citizen Sky is a new three-year, astronomical citizen science project launched in June, 2009 with funding from the National Science Foundation. This paper reports on early results of an assessment delivered to 1000 participants when they first joined the project. The goal of the assessment, based on the Nature of Scientific Knowledge Scale (NSKS), is to characterize their attitudes towards the nature of scientific knowledge. Our results are that the NSKS components of the assessment achieved high levels of reliability. Both reliability and overall scores fall within the range reported from other NSKS studies in the literature. Correlation analysis with other components of the assessment reveals some factors, such as age and understanding of scientific evidence, may be reflected in scores of subscales of NSKS items. Further work will be done using online discourse analysis and interviews. Overall, we find that the NSKS can be used as an entrance assessment for an online citizen science project.

A plea for a global natural history collection - online

USDA-ARS?s Scientific Manuscript database

Species are the currency of comparative biology: scientists from many biological disciplines, including community ecology, conservation biology, pest management, and biological control rely on scientifically sound, objective species data. However, large-scale species identifications are often not fe...

State of the Art in Large-Scale Soil Moisture Monitoring

NASA Technical Reports Server (NTRS)

Ochsner, Tyson E.; Cosh, Michael Harold; Cuenca, Richard H.; Dorigo, Wouter; Draper, Clara S.; Hagimoto, Yutaka; Kerr, Yan H.; Larson, Kristine M.; Njoku, Eni Gerald; Small, Eric E.;

Ontology-Driven Provenance Management in eScience: An Application in Parasite Research

NASA Astrophysics Data System (ADS)

Sahoo, Satya S.; Weatherly, D. Brent; Mutharaju, Raghava; Anantharam, Pramod; Sheth, Amit; Tarleton, Rick L.

Provenance, from the French word "provenir", describes the lineage or history of a data entity. Provenance is critical information in scientific applications to verify experiment process, validate data quality and associate trust values with scientific results. Current industrial scale eScience projects require an end-to-end provenance management infrastructure. This infrastructure needs to be underpinned by formal semantics to enable analysis of large scale provenance information by software applications. Further, effective analysis of provenance information requires well-defined query mechanisms to support complex queries over large datasets. This paper introduces an ontology-driven provenance management infrastructure for biology experiment data, as part of the Semantic Problem Solving Environment (SPSE) for Trypanosoma cruzi (T.cruzi). This provenance infrastructure, called T.cruzi Provenance Management System (PMS), is underpinned by (a) a domain-specific provenance ontology called Parasite Experiment ontology, (b) specialized query operators for provenance analysis, and (c) a provenance query engine. The query engine uses a novel optimization technique based on materialized views called materialized provenance views (MPV) to scale with increasing data size and query complexity. This comprehensive ontology-driven provenance infrastructure not only allows effective tracking and management of ongoing experiments in the Tarleton Research Group at the Center for Tropical and Emerging Global Diseases (CTEGD), but also enables researchers to retrieve the complete provenance information of scientific results for publication in literature.

Enabling large-scale viscoelastic calculations via neural network acceleration

NASA Astrophysics Data System (ADS)

Robinson DeVries, P.; Thompson, T. B.; Meade, B. J.

2017-12-01

One of the most significant challenges involved in efforts to understand the effects of repeated earthquake cycle activity are the computational costs of large-scale viscoelastic earthquake cycle models. Deep artificial neural networks (ANNs) can be used to discover new, compact, and accurate computational representations of viscoelastic physics. Once found, these efficient ANN representations may replace computationally intensive viscoelastic codes and accelerate large-scale viscoelastic calculations by more than 50,000%. This magnitude of acceleration enables the modeling of geometrically complex faults over thousands of earthquake cycles across wider ranges of model parameters and at larger spatial and temporal scales than have been previously possible. Perhaps most interestingly from a scientific perspective, ANN representations of viscoelastic physics may lead to basic advances in the understanding of the underlying model phenomenology. We demonstrate the potential of artificial neural networks to illuminate fundamental physical insights with specific examples.

Large-scale deep learning for robotically gathered imagery for science

NASA Astrophysics Data System (ADS)

Skinner, K.; Johnson-Roberson, M.; Li, J.; Iscar, E.

2016-12-01

With the explosion of computing power, the intelligence and capability of mobile robotics has dramatically increased over the last two decades. Today, we can deploy autonomous robots to achieve observations in a variety of environments ripe for scientific exploration. These platforms are capable of gathering a volume of data previously unimaginable. Additionally, optical cameras, driven by mobile phones and consumer photography, have rapidly improved in size, power consumption, and quality making their deployment cheaper and easier. Finally, in parallel we have seen the rise of large-scale machine learning approaches, particularly deep neural networks (DNNs), increasing the quality of the semantic understanding that can be automatically extracted from optical imagery. In concert this enables new science using a combination of machine learning and robotics. This work will discuss the application of new low-cost high-performance computing approaches and the associated software frameworks to enable scientists to rapidly extract useful science data from millions of robotically gathered images. The automated analysis of imagery on this scale opens up new avenues of inquiry unavailable using more traditional manual or semi-automated approaches. We will use a large archive of millions of benthic images gathered with an autonomous underwater vehicle to demonstrate how these tools enable new scientific questions to be posed.

The Snowmastodon Project: cutting-edge science on the blade of a bulldozer

USGS Publications Warehouse

Pigati, Jeffery S.; Miller, Ian M.; Johnson, Kirk R.

2015-01-01

Cutting-edge science happens at a variety of scales, from the individual and intimate to the large-scale and collaborative. The publication of a special issue of Quaternary Research in Nov. 2014 dedicated to the scientific findings of the “Snowmastodon Project” highlights what can be done when natural history museums, governmental agencies, and academic institutions work toward a common goal.

Interactive Visualization of Large-Scale Hydrological Data using Emerging Technologies in Web Systems and Parallel Programming

NASA Astrophysics Data System (ADS)

Demir, I.; Krajewski, W. F.

2013-12-01

As geoscientists are confronted with increasingly massive datasets from environmental observations to simulations, one of the biggest challenges is having the right tools to gain scientific insight from the data and communicate the understanding to stakeholders. Recent developments in web technologies make it easy to manage, visualize and share large data sets with general public. Novel visualization techniques and dynamic user interfaces allow users to interact with data, and modify the parameters to create custom views of the data to gain insight from simulations and environmental observations. This requires developing new data models and intelligent knowledge discovery techniques to explore and extract information from complex computational simulations or large data repositories. Scientific visualization will be an increasingly important component to build comprehensive environmental information platforms. This presentation provides an overview of the trends and challenges in the field of scientific visualization, and demonstrates information visualization and communication tools developed within the light of these challenges.

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

Towards large-scale, human-based, mesoscopic neurotechnologies.

PubMed

Chang, Edward F

2015-04-08

Direct human brain recordings have transformed the scope of neuroscience in the past decade. Progress has relied upon currently available neurophysiological approaches in the context of patients undergoing neurosurgical procedures for medical treatment. While this setting has provided precious opportunities for scientific research, it also has presented significant constraints on the development of new neurotechnologies. A major challenge now is how to achieve high-resolution spatiotemporal neural recordings at a large scale. By narrowing the gap between current approaches, new directions tailored to the mesoscopic (intermediate) scale of resolution may overcome the barriers towards safe and reliable human-based neurotechnology development, with major implications for advancing both basic research and clinical translation. Copyright © 2015 Elsevier Inc. All rights reserved.

Towards a Scalable and Adaptive Application Support Platform for Large-Scale Distributed E-Sciences in High-Performance Network Environments

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

Wu, Chase Qishi; Zhu, Michelle Mengxia

The advent of large-scale collaborative scientific applications has demonstrated the potential for broad scientific communities to pool globally distributed resources to produce unprecedented data acquisition, movement, and analysis. System resources including supercomputers, data repositories, computing facilities, network infrastructures, storage systems, and display devices have been increasingly deployed at national laboratories and academic institutes. These resources are typically shared by large communities of users over Internet or dedicated networks and hence exhibit an inherent dynamic nature in their availability, accessibility, capacity, and stability. Scientific applications using either experimental facilities or computation-based simulations with various physical, chemical, climatic, and biological models featuremore » diverse scientific workflows as simple as linear pipelines or as complex as a directed acyclic graphs, which must be executed and supported over wide-area networks with massively distributed resources. Application users oftentimes need to manually configure their computing tasks over networks in an ad hoc manner, hence significantly limiting the productivity of scientists and constraining the utilization of resources. The success of these large-scale distributed applications requires a highly adaptive and massively scalable workflow platform that provides automated and optimized computing and networking services. This project is to design and develop a generic Scientific Workflow Automation and Management Platform (SWAMP), which contains a web-based user interface specially tailored for a target application, a set of user libraries, and several easy-to-use computing and networking toolkits for application scientists to conveniently assemble, execute, monitor, and control complex computing workflows in heterogeneous high-performance network environments. SWAMP will enable the automation and management of the entire process of scientific workflows with the convenience of a few mouse clicks while hiding the implementation and technical details from end users. Particularly, we will consider two types of applications with distinct performance requirements: data-centric and service-centric applications. For data-centric applications, the main workflow task involves large-volume data generation, catalog, storage, and movement typically from supercomputers or experimental facilities to a team of geographically distributed users; while for service-centric applications, the main focus of workflow is on data archiving, preprocessing, filtering, synthesis, visualization, and other application-specific analysis. We will conduct a comprehensive comparison of existing workflow systems and choose the best suited one with open-source code, a flexible system structure, and a large user base as the starting point for our development. Based on the chosen system, we will develop and integrate new components including a black box design of computing modules, performance monitoring and prediction, and workflow optimization and reconfiguration, which are missing from existing workflow systems. A modular design for separating specification, execution, and monitoring aspects will be adopted to establish a common generic infrastructure suited for a wide spectrum of science applications. We will further design and develop efficient workflow mapping and scheduling algorithms to optimize the workflow performance in terms of minimum end-to-end delay, maximum frame rate, and highest reliability. We will develop and demonstrate the SWAMP system in a local environment, the grid network, and the 100Gpbs Advanced Network Initiative (ANI) testbed. The demonstration will target scientific applications in climate modeling and high energy physics and the functions to be demonstrated include workflow deployment, execution, steering, and reconfiguration. Throughout the project period, we will work closely with the science communities in the fields of climate modeling and high energy physics including Spallation Neutron Source (SNS) and Large Hadron Collider (LHC) projects to mature the system for production use.« less

Using learning networks to understand complex systems: a case study of biological, geophysical and social research in the Amazon.

PubMed

Barlow, Jos; Ewers, Robert M; Anderson, Liana; Aragao, Luiz E O C; Baker, Tim R; Boyd, Emily; Feldpausch, Ted R; Gloor, Emanuel; Hall, Anthony; Malhi, Yadvinder; Milliken, William; Mulligan, Mark; Parry, Luke; Pennington, Toby; Peres, Carlos A; Phillips, Oliver L; Roman-Cuesta, Rosa Maria; Tobias, Joseph A; Gardner, Toby A

2011-05-01

Developing high-quality scientific research will be most effective if research communities with diverse skills and interests are able to share information and knowledge, are aware of the major challenges across disciplines, and can exploit economies of scale to provide robust answers and better inform policy. We evaluate opportunities and challenges facing the development of a more interactive research environment by developing an interdisciplinary synthesis of research on a single geographic region. We focus on the Amazon as it is of enormous regional and global environmental importance and faces a highly uncertain future. To take stock of existing knowledge and provide a framework for analysis we present a set of mini-reviews from fourteen different areas of research, encompassing taxonomy, biodiversity, biogeography, vegetation dynamics, landscape ecology, earth-atmosphere interactions, ecosystem processes, fire, deforestation dynamics, hydrology, hunting, conservation planning, livelihoods, and payments for ecosystem services. Each review highlights the current state of knowledge and identifies research priorities, including major challenges and opportunities. We show that while substantial progress is being made across many areas of scientific research, our understanding of specific issues is often dependent on knowledge from other disciplines. Accelerating the acquisition of reliable and contextualized knowledge about the fate of complex pristine and modified ecosystems is partly dependent on our ability to exploit economies of scale in shared resources and technical expertise, recognise and make explicit interconnections and feedbacks among sub-disciplines, increase the temporal and spatial scale of existing studies, and improve the dissemination of scientific findings to policy makers and society at large. Enhancing interaction among research efforts is vital if we are to make the most of limited funds and overcome the challenges posed by addressing large-scale interdisciplinary questions. Bringing together a diverse scientific community with a single geographic focus can help increase awareness of research questions both within and among disciplines, and reveal the opportunities that may exist for advancing acquisition of reliable knowledge. This approach could be useful for a variety of globally important scientific questions. © 2010 The Authors. Biological Reviews © 2010 Cambridge Philosophical Society.

Information Power Grid Posters

NASA Technical Reports Server (NTRS)

Vaziri, Arsi

2003-01-01

This document is a summary of the accomplishments of the Information Power Grid (IPG). Grids are an emerging technology that provide seamless and uniform access to the geographically dispersed, computational, data storage, networking, instruments, and software resources needed for solving large-scale scientific and engineering problems. The goal of the NASA IPG is to use NASA's remotely located computing and data system resources to build distributed systems that can address problems that are too large or complex for a single site. The accomplishments outlined in this poster presentation are: access to distributed data, IPG heterogeneous computing, integration of large-scale computing node into distributed environment, remote access to high data rate instruments,and exploratory grid environment.

Global Behavior in Large Scale Systems

DTIC Science & Technology

2013-12-05

release. AIR FORCE RESEARCH LABORATORY AF OFFICE OF SCIENTIFIC RESEARCH (AFOSR)/RSL ARLINGTON, VIRGINIA 22203 AIR FORCE MATERIEL COMMAND AFRL-OSR-VA...and Research 875 Randolph Street, Suite 325 Room 3112, Arlington, VA 22203 December 3, 2013 1 Abstract This research attained two main achievements: 1...microscopic random interactions among the agents. 2 1 Introduction In this research we considered two main problems: 1) large deviation error performance in

Determination of the number of ψ(3686) events at BESIII

NASA Astrophysics Data System (ADS)

Ablikim, M.; Achasov, M. N.; Ai, X. C.; Ambrose, D. J.; Amoroso, A.; An, F. F.; An, Q.; Bai, J. Z.; Baldini Ferroli, R.; Ban, Y.; Bennett, J. V.; Bertani, M.; Bian, J. M.; Boger, E.; Bondarenko, O.; Boyko, I.; Briere, R. A.; Cai, H.; Cai, X.; Cakir, O.; Calcaterra, A.; Cao, G. F.; Cetin, S. A.; Chang, J. F.; Chelkov, G.; Chen, G.; Chen, H. S.; Chen, J. C.; Chen, M. L.; Chen, S. J.; Chen, X.; Chen, X. R.; Chen, Y. B.; Chu, X. K.; Chu, Y. P.; Cronin-Hennessy, D.; Dai, H. L.; Dai, J. P.; Dedovich, D.; Deng, Z. Y.; Denig, A.; Denysenko, I.; Destefanis, M.; Ding, Y.; Dong, C.; Dong, J.; Dong, L. Y.; Dong, M. Y.; Du, S. X.; Fan, J. Z.; Fang, J.; Fang, S. S.; Fang, Y.; Fava, L.; Feldbauer, F.; Feng, C. Q.; Fu, C. D.; Gao, Q.; Gao, Y.; Goetzen, K.; Gong, W. X.; Gradl, W.; Greco, M.; Gu, M. H.; Gu, Y. T.; Guan, Y. H.; Guo, A. Q.; Guo, Y. P.; Han, Y. L.; Harris, F. A.; He, K. L.; He, M.; Held, T.; Heng, Y. K.; Hou, Z. L.; Hu, H. M.; Hu, T.; Huang, G. S.; Huang, J. S.; Huang, L.; Huang, X. T.; Hussain, T.; Ji, Q.; Ji, Q. P.; Ji, X. B.; Ji, X. L.; Jiang, L. L.; Jiang, X. S.; Jiao, J. B.; Jiao, Z.; Jin, D. P.; Jin, S.; Johansson, T.; Kalantar-Nayestanaki, N.; Kang, X. L.; Kang, X. S.; Kavatsyuk, M.; Kloss, B.; Kopf, B.; Kornicer, M.; Kupsc, A.; Kühn, W.; Lai, W.; Lange, J. S.; Lara, M.; Larin, P.; Li, C. H.; Li, Cheng; Li, D. M.; Li, F.; Li, G.; Li, H. B.; Li, J. C.; Li, Kang; Li, Ke; Li, Lei; Li, P. R.; Li, Q. J.; Li, W. D.; Li, W. G.; Li, X. L.; Li, X. N.; Li, X. Q.; Li, X. R.; Li, Z. B.; Liang, H.; Liang, Y. F.; Liang, Y. T.; Liao, G. R.; Lin, D. X.; Liu, B. J.; Liu, C. X.; Liu, F. H.; Liu, Fang.; Liu, Feng.; Liu, H. B.; Liu, H. M.; Liu, Huihui.; Liu, J.; Liu, J. P.; Liu, K.; Liu, K. Y.; Liu, Q.; Liu, S. B.; Liu, X.; Liu, Y. B.; Liu, Z. A.; Liu, Zhiqiang.; Liu, Zhiqing.; Loehner, H.; Lou, X. C.; Lu, H. J.; Lu, H. L.; Lu, J. G.; Lu, Y.; Lu, Y. P.; Luo, C. L.; Luo, M. X.; Luo, T.; Luo, X. L.; Lv, M.; Lyu, X. R.; Ma, F. C.; Ma, H. L.; Ma, Q. M.; Ma, S.; Ma, T.; Ma, X. Y.; Maas, F. E.; Maggiora, M.; Mao, Y. J.; Mao, Z. P.; Messchendorp, J. G.; Min, J.; Min, T. J.; Mitchell, R. E.; Mo, X. H.; Mo, Y. J.; Morales Morales, C.; Moriya, K.; Muchnoi, N. Yu.; Muramatsu, H.; Nefedov, Y.; Nikolaev, I. B.; Ning, Z.; Nisar, S.; Niu, S. L.; Niu, X. Y.; Olsen, S. L.; Ouyang, Q.; Pacetti, S.; Pelizaeus, M.; Peng, H. P.; Peters, K.; Ping, J. L.; Ping, R. G.; Poling, R.; Qi, M.; Qian, S.; Qiao, C. F.; Qin, X. S.; Qin, Z. H.; Qiu, J. F.; Rashid, K. H.; Redmer, C. F.; Ripka, M.; Rong, G.; Sarantsev, A.; Schoenning, K.; Shan, W.; Shao, M.; Shen, C. P.; Shen, X. Y.; Sheng, H. Y.; Shepherd, M. R.; Song, W. M.; Song, X. Y.; Sosio, S.; Spataro, S.; Sun, G. X.; Sun, J. F.; Sun, S. S.; Sun, Y. J.; Sun, Y. Z.; Sun, Z. J.; Tang, C. J.; Tang, X.; Tapan, I.; Thorndike, E. H.; Toth, D.; Uman, I.; Varner, G. S.; Wang, B.; Wang, D.; Wang, D. Y.; Wang, K.; Wang, L. L.; Wang, L. S.; Wang, M.; Wang, P.; Wang, P. L.; Wang, Q. J.; Wang, W.; Wang, X. F.; Wang(Yadi, Y. D.; Wang, Y. F.; Wang, Y. Q.; Wang, Z.; Wang, Z. G.; Wang, Z. Y.; Wei, D. H.; Weidenkaff, P.; Wen, S. P.; Wiedner, U.; Wolke, M.; Wu, L. H.; Wu, Z.; Xia, L. G.; Xia, Y.; Xiao, D.; Xiao, Z. J.; Xie, Y. G.; Xiu, Q. L.; Xu, G. F.; Xu, L.; Xu, Q. J.; Xu, Q. N.; Xu, X. P.; Yan, W. B.; Yan, Y. H.; Yang, H. X.; Yang, Y.; Yang, Y. X.; Ye, H.; Ye, M.; Ye, M. H.; Yu, B. X.; Yu, C. X.; Yu, J. S.; Yuan, C. Z.; Yuan, Y.; Zafar, A. A.; Zeng, Y.; Zhang, B. X.; Zhang, B. Y.; Zhang, C. C.; Zhang, D. H.; Zhang, H. H.; Zhang, H. Y.; Zhang, J. J.; Zhang, J. Q.; Zhang, J. W.; Zhang, J. Y.; Zhang, J. Z.; Zhang, L.; Zhang, R.; Zhang, S. H.; Zhang, X. J.; Zhang, X. Y.; Zhang, Y. H.; Zhang, Yao.; Zhang, Z. H.; Zhang, Z. P.; Zhang, Z. Y.; Zhao, G.; Zhao, J. W.; Zhao, J. Z.; Zhao, Lei; Zhao, Ling.; Zhao, M. G.; Zhao, Q.; Zhao, Q. W.; Zhao, S. J.; Zhao, T. C.; Zhao, Y. B.; Zhao, Z. G.; Zhemchugov, A.; Zheng, B.; Zheng, J. P.; Zheng, Y. H.; Zhong, B.; Zhou, L.; Zhou, X.; Zhou, X. K.; Zhou, X. R.; Zhou, X. Y.; Zhu, K.; Zhu, K. J.; Zhu, X. L.; Zhu, Y. C.; Zhu, Y. S.; Zhu, Z. A.; Zhuang, J.; Zou, B. S.; Zou, J. H.; BESIII Collaboration

2018-02-01

The numbers of ψ(3686) events accumulated by the BESIII detector for the data taken during 2009 and 2012 are determined to be (107.0+/- 0.8)× {10}6 and (341.1+/- 2.1)× {10}6, respectively, by counting inclusive hadronic events, where the uncertainties are systematic and the statistical uncertainties are negligible. The number of events for the sample taken in 2009 is consistent with that of the previous measurement. The total number of ψ(3686) events for the two data taking periods is (448.1+/- 2.9)× {10}6. Supported by the Ministry of Science and Technology of China (2009CB825200), National Natural Science Foundation of China (NSFC) (11235011, 11322544, 11335008, 11425524, 11475207), the Chinese Academy of Sciences (CAS) Large-Scale Scientific Facility Program, the Collaborative Innovation Center for Particles and Interactions (CICPI), Joint Large-Scale Scientific Facility Funds of the NSFC and CAS (11179014), Joint Large-Scale Scientific Facility Funds of the NSFC and CAS (11179007, U1232201, U1532257, U1532258), Joint Funds of the National Natural Science Foundation of China (11079008), CAS (KJCX2-YW-N29, KJCX2-YW-N45), 100 Talents Program of CAS, National 1000 Talents Program of China, German Research Foundation DFG (Collaborative Research Center CRC 1044), Istituto Nazionale di Fisica Nucleare, Italy, Koninklijke Nederlandse Akademie van Wetenschappen (KNAW) (530-4CDP03), Ministry of Development of Turkey (DPT2006K-120470), National Natural Science Foundation of China (11205082), The Swedish Research Council, U. S. Department of Energy (DE-FG02-05ER41374, DE-SC-0010118, DE-SC-0010504), U.S. National Science Foundation, University of Groningen (RuG) and the Helmholtzzentrum fuer Schwerionenforschung GmbH (GSI), Darmstadt, WCU Program of National Research Foundation of Korea (R32-2008-000-10155-0).

Necessary Conditions for Intraplate Seismic Zones in North America

NASA Astrophysics Data System (ADS)

Thomas, William A.; Powell, Christine A.

2017-12-01

The cause of intraplate seismic zones persists as an important scientific and societal question. Most intraplate earthquakes are concentrated in specific seismic zones along or adjacent to large-scale basement structures (e.g., rifts or sutures at ancient plate boundaries) within continental crust. The major intraplate seismic zones are limited to specific segments and are not distributed along the lengths of the ancient structures. We present a new hypothesis that major intraplate seismic zones are restricted to places where concentrated crustal deformation (CCD) is overprinted on large-scale basement structures. Examples where CCD affects the stability of specific parts of large-scale structures in response to present-day stress conditions include the most active seismic zones in central and eastern North America: Charlevoix, Eastern Tennessee, and New Madrid. Our hypothesis has important implications for the assessment of seismic hazards.

Tigres Workflow Library: Supporting Scientific Pipelines on HPC Systems

DOE PAGES

Hendrix, Valerie; Fox, James; Ghoshal, Devarshi; ...

2016-07-21

The growth in scientific data volumes has resulted in the need for new tools that enable users to operate on and analyze data on large-scale resources. In the last decade, a number of scientific workflow tools have emerged. These tools often target distributed environments, and often need expert help to compose and execute the workflows. Data-intensive workflows are often ad-hoc, they involve an iterative development process that includes users composing and testing their workflows on desktops, and scaling up to larger systems. In this paper, we present the design and implementation of Tigres, a workflow library that supports the iterativemore » workflow development cycle of data-intensive workflows. Tigres provides an application programming interface to a set of programming templates i.e., sequence, parallel, split, merge, that can be used to compose and execute computational and data pipelines. We discuss the results of our evaluation of scientific and synthetic workflows showing Tigres performs with minimal template overheads (mean of 13 seconds over all experiments). We also discuss various factors (e.g., I/O performance, execution mechanisms) that affect the performance of scientific workflows on HPC systems.« less

Tigres Workflow Library: Supporting Scientific Pipelines on HPC Systems

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

Hendrix, Valerie; Fox, James; Ghoshal, Devarshi

The growth in scientific data volumes has resulted in the need for new tools that enable users to operate on and analyze data on large-scale resources. In the last decade, a number of scientific workflow tools have emerged. These tools often target distributed environments, and often need expert help to compose and execute the workflows. Data-intensive workflows are often ad-hoc, they involve an iterative development process that includes users composing and testing their workflows on desktops, and scaling up to larger systems. In this paper, we present the design and implementation of Tigres, a workflow library that supports the iterativemore » workflow development cycle of data-intensive workflows. Tigres provides an application programming interface to a set of programming templates i.e., sequence, parallel, split, merge, that can be used to compose and execute computational and data pipelines. We discuss the results of our evaluation of scientific and synthetic workflows showing Tigres performs with minimal template overheads (mean of 13 seconds over all experiments). We also discuss various factors (e.g., I/O performance, execution mechanisms) that affect the performance of scientific workflows on HPC systems.« less

Nuclear war effects studied

NASA Astrophysics Data System (ADS)

Widespread starvation resulting from changes in climate in the aftermath of a large-scale nuclear war could kill far more people than would the bombs themselves. That prediction was made in a recent study by the Scientific Committee on Problems of the Environment (SCOPE), an a rm of the International Council of Scientific Unions (ICSU). “Noncombatant and combatant countries alike” would risk mass starvation; SCOPE predicted that all told, 2.5 billion people could die as a result of crop failures and breakdowns in food distribution after a nuclear war.

Final Technical Report - Center for Technology for Advanced Scientific Component Software (TASCS)

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

Sussman, Alan

2014-10-21

This is a final technical report for the University of Maryland work in the SciDAC Center for Technology for Advanced Scientific Component Software (TASCS). The Maryland work focused on software tools for coupling parallel software components built using the Common Component Architecture (CCA) APIs. Those tools are based on the Maryland InterComm software framework that has been used in multiple computational science applications to build large-scale simulations of complex physical systems that employ multiple separately developed codes.

Advances in Multi-Sensor Scanning and Visualization of Complex Plants: the Utmost Case of a Reactor Building

NASA Astrophysics Data System (ADS)

Hullo, J.-F.; Thibault, G.; Boucheny, C.

2015-02-01

In a context of increased maintenance operations and workers generational renewal, a nuclear owner and operator like Electricité de France (EDF) is interested in the scaling up of tools and methods of "as-built virtual reality" for larger buildings and wider audiences. However, acquisition and sharing of as-built data on a large scale (large and complex multi-floored buildings) challenge current scientific and technical capacities. In this paper, we first present a state of the art of scanning tools and methods for industrial plants with very complex architecture. Then, we introduce the inner characteristics of the multi-sensor scanning and visualization of the interior of the most complex building of a power plant: a nuclear reactor building. We introduce several developments that made possible a first complete survey of such a large building, from acquisition, processing and fusion of multiple data sources (3D laser scans, total-station survey, RGB panoramic, 2D floor plans, 3D CAD as-built models). In addition, we present the concepts of a smart application developed for the painless exploration of the whole dataset. The goal of this application is to help professionals, unfamiliar with the manipulation of such datasets, to take into account spatial constraints induced by the building complexity while preparing maintenance operations. Finally, we discuss the main feedbacks of this large experiment, the remaining issues for the generalization of such large scale surveys and the future technical and scientific challenges in the field of industrial "virtual reality".

A survey of scientific literacy to provide a foundation for designing science communication in Japan.

PubMed

Kawamoto, Shishin; Nakayama, Minoru; Saijo, Miki

2013-08-01

There are various definitions and survey methods for scientific literacy. Taking into consideration the contemporary significance of scientific literacy, we have defined it with an emphasis on its social aspects. To acquire the insights needed to design a form of science communication that will enhance the scientific literacy of each individual, we conducted a large-scale random survey within Japan of individuals older than 18 years, using a printed questionnaire. The data thus acquired were analyzed using factor analysis and cluster analysis to create a 3-factor/4-cluster model of people's interest and attitude toward science, technology and society and their resulting tendencies. Differences were found among the four clusters in terms of the three factors: scientific factor, social factor, and science-appreciating factor. We propose a plan for designing a form of science communication that is appropriate to this current status of scientific literacy in Japan.

Do you kiss your mother with that mouth? An authentic large-scale undergraduate research experience in mapping the human oral microbiome.

PubMed

Wang, Jack T H; Daly, Joshua N; Willner, Dana L; Patil, Jayee; Hall, Roy A; Schembri, Mark A; Tyson, Gene W; Hugenholtz, Philip

2015-05-01

Clinical microbiology testing is crucial for the diagnosis and treatment of community and hospital-acquired infections. Laboratory scientists need to utilize technical and problem-solving skills to select from a wide array of microbial identification techniques. The inquiry-driven laboratory training required to prepare microbiology graduates for this professional environment can be difficult to replicate within undergraduate curricula, especially in courses that accommodate large student cohorts. We aimed to improve undergraduate scientific training by engaging hundreds of introductory microbiology students in an Authentic Large-Scale Undergraduate Research Experience (ALURE). The ALURE aimed to characterize the microorganisms that reside in the healthy human oral cavity-the oral microbiome-by analyzing hundreds of samples obtained from student volunteers within the course. Students were able to choose from selective and differential culture media, Gram-staining, microscopy, as well as polymerase chain reaction (PCR) and 16S rRNA gene sequencing techniques, in order to collect, analyze, and interpret novel data to determine the collective oral microbiome of the student cohort. Pre- and postsurvey analysis of student learning gains across two iterations of the course (2012-2013) revealed significantly higher student confidence in laboratory skills following the completion of the ALURE (p < 0.05 using the Mann-Whitney U-test). Learning objectives on effective scientific communication were also met through effective student performance in laboratory reports describing the research outcomes of the project. The integration of undergraduate research in clinical microbiology has the capacity to deliver authentic research experiences and improve scientific training for large cohorts of undergraduate students.

Improving Convection and Cloud Parameterization Using ARM Observations and NCAR Community Atmosphere Model CAM5

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

Zhang, Guang J.

2016-11-07

The fundamental scientific objectives of our research are to use ARM observations and the NCAR CAM5 to understand the large-scale control on convection, and to develop improved convection and cloud parameterizations for use in GCMs.

THE VIRTUAL INSTRUMENT: SUPPORT FOR GRID-ENABLED MCELL SIMULATIONS

PubMed Central

Casanova, Henri; Berman, Francine; Bartol, Thomas; Gokcay, Erhan; Sejnowski, Terry; Birnbaum, Adam; Dongarra, Jack; Miller, Michelle; Ellisman, Mark; Faerman, Marcio; Obertelli, Graziano; Wolski, Rich; Pomerantz, Stuart; Stiles, Joel

2010-01-01

Ensembles of widely distributed, heterogeneous resources, or Grids, have emerged as popular platforms for large-scale scientific applications. In this paper we present the Virtual Instrument project, which provides an integrated application execution environment that enables end-users to run and interact with running scientific simulations on Grids. This work is performed in the specific context of MCell, a computational biology application. While MCell provides the basis for running simulations, its capabilities are currently limited in terms of scale, ease-of-use, and interactivity. These limitations preclude usage scenarios that are critical for scientific advances. Our goal is to create a scientific “Virtual Instrument” from MCell by allowing its users to transparently access Grid resources while being able to steer running simulations. In this paper, we motivate the Virtual Instrument project and discuss a number of relevant issues and accomplishments in the area of Grid software development and application scheduling. We then describe our software design and report on the current implementation. We verify and evaluate our design via experiments with MCell on a real-world Grid testbed. PMID:20689618

The Power of Engaging Citizen Scientists for Scientific Progress

PubMed Central

Garbarino, Jeanne; Mason, Christopher E.

2016-01-01

Citizen science has become a powerful force for scientific inquiry, providing researchers with access to a vast array of data points while connecting nonscientists to the authentic process of science. This citizen-researcher relationship creates an incredible synergy, allowing for the creation, execution, and analysis of research projects that would otherwise prove impossible in traditional research settings, namely due to the scope of needed human or financial resources (or both). However, citizen-science projects are not without their challenges. For instance, as projects are scaled up, there is concern regarding the rigor and usability of data collected by citizens who are not formally trained in research science. While these concerns are legitimate, we have seen examples of highly successful citizen-science projects from multiple scientific disciplines that have enhanced our collective understanding of science, such as how RNA molecules fold or determining the microbial metagenomic snapshot of an entire public transportation system. These and other emerging citizen-science projects show how improved protocols for reliable, large-scale science can realize both an improvement of scientific understanding for the general public and novel views of the world around us. PMID:27047581

DOE High Performance Computing Operational Review (HPCOR): Enabling Data-Driven Scientific Discovery at HPC Facilities

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

Gerber, Richard; Allcock, William; Beggio, Chris

2014-10-17

U.S. Department of Energy (DOE) High Performance Computing (HPC) facilities are on the verge of a paradigm shift in the way they deliver systems and services to science and engineering teams. Research projects are producing a wide variety of data at unprecedented scale and level of complexity, with community-specific services that are part of the data collection and analysis workflow. On June 18-19, 2014 representatives from six DOE HPC centers met in Oakland, CA at the DOE High Performance Operational Review (HPCOR) to discuss how they can best provide facilities and services to enable large-scale data-driven scientific discovery at themore » DOE national laboratories. The report contains findings from that review.« less

Ionospheric Multi-Point Measurements Using Tethered Satellite Sensors

NASA Technical Reports Server (NTRS)

Gilchrist, B. E.; Heelis, R. A.; Raitt, W. J.

1998-01-01

Many scientific questions concerning the distribution of electromagnetic fields and plasma structures in the ionosphere require measurements over relatively small temporal and spatial scales with as little ambiguity as possible. It is also often necessary to differentiate several geophysical parameters between horizontal and vertical gradients unambiguously. The availability of multiple tethered satellites or sensors, so-called "pearls-on-a-string," may make the necessary measurements practical. In this report we provide two examples of scientific questions which could benefit from such measurements (1) high-latitude magnetospheric-ionospheric coupling; and, (2) plasma structure impact on large and small-scale electrodynamics. Space tether state-of-the-art and special technical considerations addressing mission lifetime, sensor pointing, and multi-stream telemetry are reviewed.

Large-scale forensic investigations into the missing: Challenges and considerations.

PubMed

Salado Puerto, Mercedes; Tuller, Hugh

2017-10-01

Large-scale forensic investigations may follow episodes of mass violence and disasters where hundreds or thousands of people have died or are missing. A number of unique challenges for forensic science, different from domestic investigations, arise in these contexts. The setting and situation of these investigations regularly force forensic scientists into practices not regularly encountered while working in a standard criminal justice system. These practices can entail activities not specific to a practitioner's particular field or necessarily be scientific in nature, but are still needed in order for the investigation to move forward. These activities can include (1) establishing the number of and who exactly is missing after mass violence and disaster, (2) the creation of working protocols to deal with the scale of the loss of life that often overwhelm domestic practices and institutions, (3) negotiating the form that the investigation will take with various stakeholders, (4) addressing cultural beliefs of the affected society regarding the dead and missing, and (5) working within prescribed economic, political, and time constraints, among others. Forensic scientific responses to these challenges have proven to be flexible, innovative, and continually evolving. Copyright © 2017 Elsevier B.V. All rights reserved.

Enabling Diverse Software Stacks on Supercomputers using High Performance Virtual Clusters.

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

Younge, Andrew J.; Pedretti, Kevin; Grant, Ryan

While large-scale simulations have been the hallmark of the High Performance Computing (HPC) community for decades, Large Scale Data Analytics (LSDA) workloads are gaining attention within the scientific community not only as a processing component to large HPC simulations, but also as standalone scientific tools for knowledge discovery. With the path towards Exascale, new HPC runtime systems are also emerging in a way that differs from classical distributed com- puting models. However, system software for such capabilities on the latest extreme-scale DOE supercomputing needs to be enhanced to more appropriately support these types of emerging soft- ware ecosystems. In thismore » paper, we propose the use of Virtual Clusters on advanced supercomputing resources to enable systems to support not only HPC workloads, but also emerging big data stacks. Specifi- cally, we have deployed the KVM hypervisor within Cray's Compute Node Linux on a XC-series supercomputer testbed. We also use libvirt and QEMU to manage and provision VMs directly on compute nodes, leveraging Ethernet-over-Aries network emulation. To our knowledge, this is the first known use of KVM on a true MPP supercomputer. We investigate the overhead our solution using HPC benchmarks, both evaluating single-node performance as well as weak scaling of a 32-node virtual cluster. Overall, we find single node performance of our solution using KVM on a Cray is very efficient with near-native performance. However overhead increases by up to 20% as virtual cluster size increases, due to limitations of the Ethernet-over-Aries bridged network. Furthermore, we deploy Apache Spark with large data analysis workloads in a Virtual Cluster, ef- fectively demonstrating how diverse software ecosystems can be supported by High Performance Virtual Clusters.« less

Science Partnerships Enabling Rapid Response: Designing a Strategy for Improving Scientific Collaboration during Crisis Response

NASA Astrophysics Data System (ADS)

Mease, L.; Gibbs, T.; Adiseshan, T.

2014-12-01

The 2010 Deepwater Horizon disaster required unprecedented engagement and collaboration with scientists from multiple disciplines across government, academia, and industry. Although this spurred the rapid advancement of valuable new scientific knowledge and tools, it also exposed weaknesses in the system of information dissemination and exchange among the scientists from those three sectors. Limited government communication with the broader scientific community complicated the rapid mobilization of the scientific community to assist with spill response, evaluation of impact, and public perceptions of the crisis. The lessons and new laws produced from prior spills such as Exxon Valdez were helpful, but ultimately did not lead to the actions necessary to prepare a suitable infrastructure that would support collaboration with non-governmental scientists. As oil demand pushes drilling into increasingly extreme environments, addressing the challenge of effective, science-based disaster response is an imperative. Our study employs a user-centered design process to 1) understand the obstacles to and opportunity spaces for effective scientific collaboration during environmental crises such as large oil spills, 2) identify possible tools and strategies to enable rapid information exchange between government responders and non-governmental scientists from multiple relevant disciplines, and 3) build a network of key influencers to secure sufficient buy-in for scaled implementation of appropriate tools and strategies. Our methods include user ethnography, complex system mapping, individual and system behavioral analysis, and large-scale system design to identify and prototype a solution to this crisis collaboration challenge. In this talk, we will present out insights gleaned from existing analogs of successful scientific collaboration during crises and our initial findings from the 60 targeted interviews we conducted that highlight key collaboration challenges that government agencies, academic research institutions, and industry scientists face during oil spill crises. We will also present a synthesis of leverage points in the system that may amplify the impact of an improved collaboration strategy among scientific stakeholders.

Load Balancing Scientific Applications

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

Pearce, Olga Tkachyshyn

2014-12-01

The largest supercomputers have millions of independent processors, and concurrency levels are rapidly increasing. For ideal efficiency, developers of the simulations that run on these machines must ensure that computational work is evenly balanced among processors. Assigning work evenly is challenging because many large modern parallel codes simulate behavior of physical systems that evolve over time, and their workloads change over time. Furthermore, the cost of imbalanced load increases with scale because most large-scale scientific simulations today use a Single Program Multiple Data (SPMD) parallel programming model, and an increasing number of processors will wait for the slowest one atmore » the synchronization points. To address load imbalance, many large-scale parallel applications use dynamic load balance algorithms to redistribute work evenly. The research objective of this dissertation is to develop methods to decide when and how to load balance the application, and to balance it effectively and affordably. We measure and evaluate the computational load of the application, and develop strategies to decide when and how to correct the imbalance. Depending on the simulation, a fast, local load balance algorithm may be suitable, or a more sophisticated and expensive algorithm may be required. We developed a model for comparison of load balance algorithms for a specific state of the simulation that enables the selection of a balancing algorithm that will minimize overall runtime.« less

Scalable Automated Model Search

DTIC Science & Technology

2014-05-20

ma- chines. Categories and Subject Descriptors Big Data [Distributed Computing]: Large scale optimization 1. INTRODUCTION Modern scientific and...from Continuum Analytics[1], and Apache Spark 0.8.1. Additionally, we made use of Hadoop 1.0.4 configured on local disks as our data store for the large...Borkar et al. Hyracks: A flexible and extensible foundation for data -intensive computing. In ICDE, 2011. [16] J. Canny and H. Zhao. Big data

Big Science vs. Little Science: How Scientific Impact Scales with Funding.

PubMed

Fortin, Jean-Michel; Currie, David J

2013-01-01

is it more effective to give large grants to a few elite researchers, or small grants to many researchers? Large grants would be more effective only if scientific impact increases as an accelerating function of grant size. Here, we examine the scientific impact of individual university-based researchers in three disciplines funded by the Natural Sciences and Engineering Research Council of Canada (NSERC). We considered four indices of scientific impact: numbers of articles published, numbers of citations to those articles, the most cited article, and the number of highly cited articles, each measured over a four-year period. We related these to the amount of NSERC funding received. Impact is positively, but only weakly, related to funding. Researchers who received additional funds from a second federal granting council, the Canadian Institutes for Health Research, were not more productive than those who received only NSERC funding. Impact was generally a decelerating function of funding. Impact per dollar was therefore lower for large grant-holders. This is inconsistent with the hypothesis that larger grants lead to larger discoveries. Further, the impact of researchers who received increases in funding did not predictably increase. We conclude that scientific impact (as reflected by publications) is only weakly limited by funding. We suggest that funding strategies that target diversity, rather than "excellence", are likely to prove to be more productive.

Reclamation with trees in Illinois

Treesearch

Brad Evilsizer

1980-01-01

Thru private initiative, Illinois citizens historically have invented and conducted large-scale tree planting programs, starting with hedgerow fences and farmstead windbreaks and continuing with surface mine reclamation and farm woodlands. With invaluable help from public and private scientific personnel, the old and new programs hold promise of enlargement and...

5 CFR 9301.7 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-01-01

... and that operates solely for the purpose of conducting scientific research the results of which are... employees who perform the work and costs of conducting large-scale computer searches. (c) Duplicate means to... education, that operates a program or programs of scholarly research. (e) Fee category means one of the...

5 CFR 9301.7 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-01-01

... and that operates solely for the purpose of conducting scientific research the results of which are... employees who perform the work and costs of conducting large-scale computer searches. (c) Duplicate means to... education, that operates a program or programs of scholarly research. (e) Fee category means one of the...

Designing next-generation platforms for evaluating scientific output: what scientists can learn from the social web

PubMed Central

Yarkoni, Tal

2012-01-01

Traditional pre-publication peer review of scientific output is a slow, inefficient, and unreliable process. Efforts to replace or supplement traditional evaluation models with open evaluation platforms that leverage advances in information technology are slowly gaining traction, but remain in the early stages of design and implementation. Here I discuss a number of considerations relevant to the development of such platforms. I focus particular attention on three core elements that next-generation evaluation platforms should strive to emphasize, including (1) open and transparent access to accumulated evaluation data, (2) personalized and highly customizable performance metrics, and (3) appropriate short-term incentivization of the userbase. Because all of these elements have already been successfully implemented on a large scale in hundreds of existing social web applications, I argue that development of new scientific evaluation platforms should proceed largely by adapting existing techniques rather than engineering entirely new evaluation mechanisms. Successful implementation of open evaluation platforms has the potential to substantially advance both the pace and the quality of scientific publication and evaluation, and the scientific community has a vested interest in shifting toward such models as soon as possible. PMID:23060783

Framing Psychology as a Discipline (1950-1999): A Large-Scale Term Co-Occurrence Analysis of Scientific Literature in Psychology.

PubMed

Flis, Ivan; van Eck, Nees Jan

2017-07-20

This study investigated the structure of psychological literature as represented by a corpus of 676,393 articles in the period from 1950 to 1999. The corpus was extracted from 1,269 journals indexed by PsycINFO. The data in our analysis consisted of the relevant terms mined from the titles and abstracts of all of the articles in the corpus. Based on the co-occurrences of these terms, we developed a series of chronological visualizations using a bibliometric software tool called VOSviewer. These visualizations produced a stable structure through the 5 decades under analysis, and this structure was analyzed as a data-mined proxy for the disciplinary formation of scientific psychology in the second part of the 20th century. Considering the stable structure uncovered by our term co-occurrence analysis and its visualization, we discuss it in the context of Lee Cronbach's "Two Disciplines of Scientific Psychology" (1957) and conventional history of 20th-century psychology's disciplinary formation and history of methods. Our aim was to provide a comprehensive digital humanities perspective on the large-scale structural development of research in English-language psychology from 1950 to 1999. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Recent Regional Climate State and Change - Derived through Downscaling Homogeneous Large-scale Components of Re-analyses

NASA Astrophysics Data System (ADS)

Von Storch, H.; Klehmet, K.; Geyer, B.; Li, D.; Schubert-Frisius, M.; Tim, N.; Zorita, E.

2015-12-01

Global re-analyses suffer from inhomogeneities, as they process data from networks under development. However, the large-scale component of such re-analyses is mostly homogeneous; additional observational data add in most cases to a better description of regional details and less so on large-scale states. Therefore, the concept of downscaling may be applied to homogeneously complementing the large-scale state of the re-analyses with regional detail - wherever the condition of homogeneity of the large-scales is fulfilled. Technically this can be done by using a regional climate model, or a global climate model, which is constrained on the large scale by spectral nudging. This approach has been developed and tested for the region of Europe, and a skillful representation of regional risks - in particular marine risks - was identified. While the data density in Europe is considerably better than in most other regions of the world, even here insufficient spatial and temporal coverage is limiting risk assessments. Therefore, downscaled data-sets are frequently used by off-shore industries. We have run this system also in regions with reduced or absent data coverage, such as the Lena catchment in Siberia, in the Yellow Sea/Bo Hai region in East Asia, in Namibia and the adjacent Atlantic Ocean. Also a global (large scale constrained) simulation has been. It turns out that spatially detailed reconstruction of the state and change of climate in the three to six decades is doable for any region of the world.The different data sets are archived and may freely by used for scientific purposes. Of course, before application, a careful analysis of the quality for the intended application is needed, as sometimes unexpected changes in the quality of the description of large-scale driving states prevail.

Big questions, big science: meeting the challenges of global ecology.

PubMed

Schimel, David; Keller, Michael

2015-04-01

Ecologists are increasingly tackling questions that require significant infrastucture, large experiments, networks of observations, and complex data and computation. Key hypotheses in ecology increasingly require more investment, and larger data sets to be tested than can be collected by a single investigator's or s group of investigator's labs, sustained for longer than a typical grant. Large-scale projects are expensive, so their scientific return on the investment has to justify the opportunity cost-the science foregone because resources were expended on a large project rather than supporting a number of individual projects. In addition, their management must be accountable and efficient in the use of significant resources, requiring the use of formal systems engineering and project management to mitigate risk of failure. Mapping the scientific method into formal project management requires both scientists able to work in the context, and a project implementation team sensitive to the unique requirements of ecology. Sponsoring agencies, under pressure from external and internal forces, experience many pressures that push them towards counterproductive project management but a scientific community aware and experienced in large project science can mitigate these tendencies. For big ecology to result in great science, ecologists must become informed, aware and engaged in the advocacy and governance of large ecological projects.

Managing large-scale workflow execution from resource provisioning to provenance tracking: The CyberShake example

USGS Publications Warehouse

Deelman, E.; Callaghan, S.; Field, E.; Francoeur, H.; Graves, R.; Gupta, N.; Gupta, V.; Jordan, T.H.; Kesselman, C.; Maechling, P.; Mehringer, J.; Mehta, G.; Okaya, D.; Vahi, K.; Zhao, L.

2006-01-01

This paper discusses the process of building an environment where large-scale, complex, scientific analysis can be scheduled onto a heterogeneous collection of computational and storage resources. The example application is the Southern California Earthquake Center (SCEC) CyberShake project, an analysis designed to compute probabilistic seismic hazard curves for sites in the Los Angeles area. We explain which software tools were used to build to the system, describe their functionality and interactions. We show the results of running the CyberShake analysis that included over 250,000 jobs using resources available through SCEC and the TeraGrid. ?? 2006 IEEE.

Approaching the exa-scale: a real-world evaluation of rendering extremely large data sets

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

Patchett, John M; Ahrens, James P; Lo, Li - Ta

2010-10-15

Extremely large scale analysis is becoming increasingly important as supercomputers and their simulations move from petascale to exascale. The lack of dedicated hardware acceleration for rendering on today's supercomputing platforms motivates our detailed evaluation of the possibility of interactive rendering on the supercomputer. In order to facilitate our understanding of rendering on the supercomputing platform, we focus on scalability of rendering algorithms and architecture envisioned for exascale datasets. To understand tradeoffs for dealing with extremely large datasets, we compare three different rendering algorithms for large polygonal data: software based ray tracing, software based rasterization and hardware accelerated rasterization. We presentmore » a case study of strong and weak scaling of rendering extremely large data on both GPU and CPU based parallel supercomputers using Para View, a parallel visualization tool. Wc use three different data sets: two synthetic and one from a scientific application. At an extreme scale, algorithmic rendering choices make a difference and should be considered while approaching exascale computing, visualization, and analysis. We find software based ray-tracing offers a viable approach for scalable rendering of the projected future massive data sizes.« less

Scalable Kernel Methods and Algorithms for General Sequence Analysis

ERIC Educational Resources Information Center

Kuksa, Pavel

2011-01-01

Analysis of large-scale sequential data has become an important task in machine learning and pattern recognition, inspired in part by numerous scientific and technological applications such as the document and text classification or the analysis of biological sequences. However, current computational methods for sequence comparison still lack…

In situ visualization for large-scale combustion simulations.

PubMed

Yu, Hongfeng; Wang, Chaoli; Grout, Ray W; Chen, Jacqueline H; Ma, Kwan-Liu

2010-01-01

As scientific supercomputing moves toward petascale and exascale levels, in situ visualization stands out as a scalable way for scientists to view the data their simulations generate. This full picture is crucial particularly for capturing and understanding highly intermittent transient phenomena, such as ignition and extinction events in turbulent combustion.

Evaluating Large-Scale Studies to Accurately Appraise Children's Performance

ERIC Educational Resources Information Center

Ernest, James M.

2012-01-01

Educational policy is often developed using a top-down approach. Recently, there has been a concerted shift in policy for educators to develop programs and research proposals that evolve from "scientific" studies and focus less on their intuition, aided by professional wisdom. This article analyzes several national and international…

General Purpose Sampling in the Domain of Higher Education.

ERIC Educational Resources Information Center

Creager, John A.

The experience of the American Council on Education's Cooperative Institutional Research Program indicates that large-scale national surveys in the domain of higher education can be performed with scientific integrity within the constraints of costs, logistics, and technical resources. The purposes of this report are to provide complete and…

Understanding Ocean Acidification

ERIC Educational Resources Information Center

National Oceanic and Atmospheric Administration, 2011

2011-01-01

This curriculum module is designed for students who are taking high school chemistry. Students should already have some experience with the following: (1) Understanding and reading the pH scale; (2) Knowledge of the carbon cycle; (3) Using scientific notation to express large and small values; and (4) Reading chemical equations. This curriculum…

Nonvolatile Resistive Switching and Physical Mechanism in LaCrO3 Thin Films

NASA Astrophysics Data System (ADS)

Hu, Wan-Jing; Hu, Ling; Wei, Ren-Huai; Tang, Xian-Wu; Song, Wen-Hai; Dai, Jian-Ming; Zhu, Xue-Bin; Sun, Yu-Ping

2018-04-01

Not Available Supported by the Joint Funds of the National Natural Science Foundation of China and the Chinese Academy of Sciences’ Large-Scale Scientific Facility under Grant No U1532149, and the National Basic Research Program of China under Grant No 2014CB931704.

Software Engineering for Scientific Computer Simulations

NASA Astrophysics Data System (ADS)

Post, Douglass E.; Henderson, Dale B.; Kendall, Richard P.; Whitney, Earl M.

2004-11-01

Computer simulation is becoming a very powerful tool for analyzing and predicting the performance of fusion experiments. Simulation efforts are evolving from including only a few effects to many effects, from small teams with a few people to large teams, and from workstations and small processor count parallel computers to massively parallel platforms. Successfully making this transition requires attention to software engineering issues. We report on the conclusions drawn from a number of case studies of large scale scientific computing projects within DOE, academia and the DoD. The major lessons learned include attention to sound project management including setting reasonable and achievable requirements, building a good code team, enforcing customer focus, carrying out verification and validation and selecting the optimum computational mathematics approaches.

Using blackmail, bribery, and guilt to address the tragedy of the virtual intellectual commons

NASA Astrophysics Data System (ADS)

Griffith, P. C.; Cook, R. B.; Wilson, B. E.; Gentry, M. J.; Horta, L. M.; McGroddy, M.; Morrell, A. L.; Wilcox, L. E.

2008-12-01

One goal of the NSF's vision for 21st Century Cyberinfrastructure is to create a virtual intellectual commons for the scientific community where advanced technologies perpetuate transformation of this community's productivity and capabilities. The metadata describing scientific observations, like the first paragraph of a news story, should answer the questions who? what? why? where? when? and how?, making them discoverable, comprehensible, contextualized, exchangeable, and machine-readable. Investigators who create good scientific metadata increase the scientific value of their observations within such a virtual intellectual commons. But the tragedy of this commons arises when investigators wish to receive without giving in return. The authors of this talk will describe how they have used combinations of blackmail, bribery, and guilt to motivate good behavior by investigators participating in two major scientific programs (NASA's component of the Large-scale Biosphere-Atmosphere Experiment in Amazonia; and the US Climate Change Science Program's North American Carbon Program).

Genomic Databases and Biobanks in Israel.

PubMed

Siegal, Gil

2015-01-01

Large-scale biobanks represents an important scientific and medical as well as a commercial opportunity. However, realizing these and other prospects requires social, legal, and regulatory conducive climate, as well as a capable scientific community and adequate infrastructure. Israel has been grappling with the appropriate approach to establishing such a repository, and debates over the governance, structure, finance, and mode of operation shed a bright light on the underlying social norms, civic engagement and scientific clout in steering a governmental response to pressing medical needs. The article presents the backdrop of the Israeli scene, and explores the reasons and forces at work behind the current formulation of the Israeli National Biobank, MIDGAM. © 2015 American Society of Law, Medicine & Ethics, Inc.

Physical habitat monitoring strategy (PHAMS) for reach-scale restoration effectiveness monitoring

USGS Publications Warehouse

Jones, Krista L.; O'Daniel, Scott J.; Beechie, Tim J.; Zakrajsek, John; Webster, John G.

2015-04-14

Habitat restoration efforts by the Confederated Tribes of the Umatilla Indian Reservation (CTUIR) have shifted from the site scale (1-10 meters) to the reach scale (100-1,000 meters). This shift was in response to the growing scientific emphasis on process-based restoration and to support from the 2007 Accords Agreement with the Bonneville Power Administration. With the increased size of restoration projects, the CTUIR and other agencies are in need of applicable monitoring methods for assessing large-scale changes in river and floodplain habitats following restoration. The goal of the Physical Habitat Monitoring Strategy is to outline methods that are useful for capturing reach-scale changes in surface and groundwater hydrology, geomorphology, hydrologic connectivity, and riparian vegetation at restoration projects. The Physical Habitat Monitoring Strategy aims to avoid duplication with existing regional effectiveness monitoring protocols by identifying complimentary reach-scale metrics and methods that may improve the ability of CTUIR and others to detect instream and riparian changes at large restoration projects.

Intensification and Structure Change of Super Typhoon Flo as Related to the Large-Scale Environment.

DTIC Science & Technology

1998-06-01

large dataset is a challenge. Schiavone and Papathomas (1990) summarize methods currently available for visualizing scientific 116 datasets. These...Prediction and Dynamic Meteorology, Second Edition. John Wiley and Sons, 477 pp. Hardy, R. L., 1971: Multiquadric equations of topography and other...Inter. Corp., Monterey CA, 40 pp. Sawyer, J. S., 1947: Notes on the theory of tropical cyclones. Quart. J. Roy. Meteor. Soc, 73, 101-126. Schiavone

Plowshare

DOE R&D Accomplishments Database

Teller, E.

1963-02-04

The purpose of this lecture is to give an impression of the main characteristic feature of Plowshare: its exceedingly wide applicability throughout fields of economic or scientific interest. If one wants to find the right applications, knowledge of the nuclear tool is not enough. One needs to have a thorough familiarity with the materials, with the processes, with all of science, with all the economics on our globe and maybe beyond. A survey is presented of all aspects of peaceful applications of nuclear explosives: earth moving, large-scale chemical and mining engineering, and scientific experiments. (D.L.C.)

Collaborative Problem-Solving Environments; Proceedings for the Workshop CPSEs for Scientific Research, San Diego, California, June 20 to July 1, 1999

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

Chin, George

1999-01-11

A workshop on collaborative problem-solving environments (CPSEs) was held June 29 through July 1, 1999, in San Diego, California. The workshop was sponsored by the U.S. Department of Energy and the High Performance Network Applications Team of the Large Scale Networking Working Group. The workshop brought together researchers and developers from industry, academia, and government to identify, define, and discuss future directions in collaboration and problem-solving technologies in support of scientific research.

NAS (Numerical Aerodynamic Simulation Program) technical summaries, March 1989 - February 1990

NASA Technical Reports Server (NTRS)

1990-01-01

Given here are selected scientific results from the Numerical Aerodynamic Simulation (NAS) Program's third year of operation. During this year, the scientific community was given access to a Cray-2 and a Cray Y-MP supercomputer. Topics covered include flow field analysis of fighter wing configurations, large-scale ocean modeling, the Space Shuttle flow field, advanced computational fluid dynamics (CFD) codes for rotary-wing airloads and performance prediction, turbulence modeling of separated flows, airloads and acoustics of rotorcraft, vortex-induced nonlinearities on submarines, and standing oblique detonation waves.

Blazing Signature Filter: a library for fast pairwise similarity comparisons

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

Lee, Joon-Yong; Fujimoto, Grant M.; Wilson, Ryan

Identifying similarities between datasets is a fundamental task in data mining and has become an integral part of modern scientific investigation. Whether the task is to identify co-expressed genes in large-scale expression surveys or to predict combinations of gene knockouts which would elicit a similar phenotype, the underlying computational task is often a multi-dimensional similarity test. As datasets continue to grow, improvements to the efficiency, sensitivity or specificity of such computation will have broad impacts as it allows scientists to more completely explore the wealth of scientific data. A significant practical drawback of large-scale data mining is the vast majoritymore » of pairwise comparisons are unlikely to be relevant, meaning that they do not share a signature of interest. It is therefore essential to efficiently identify these unproductive comparisons as rapidly as possible and exclude them from more time-intensive similarity calculations. The Blazing Signature Filter (BSF) is a highly efficient pairwise similarity algorithm which enables extensive data mining within a reasonable amount of time. The algorithm transforms datasets into binary metrics, allowing it to utilize the computationally efficient bit operators and provide a coarse measure of similarity. As a result, the BSF can scale to high dimensionality and rapidly filter unproductive pairwise comparison. Two bioinformatics applications of the tool are presented to demonstrate the ability to scale to billions of pairwise comparisons and the usefulness of this approach.« less

The Landscape Evolution Observatory: a large-scale controllable infrastructure to study coupled Earth-surface processes

USGS Publications Warehouse

Pangle, Luke A.; DeLong, Stephen B.; Abramson, Nate; Adams, John; Barron-Gafford, Greg A.; Breshears, David D.; Brooks, Paul D.; Chorover, Jon; Dietrich, William E.; Dontsova, Katerina; Durcik, Matej; Espeleta, Javier; Ferré, T.P.A.; Ferriere, Regis; Henderson, Whitney; Hunt, Edward A.; Huxman, Travis E.; Millar, David; Murphy, Brendan; Niu, Guo-Yue; Pavao-Zuckerman, Mitch; Pelletier, Jon D.; Rasmussen, Craig; Ruiz, Joaquin; Saleska, Scott; Schaap, Marcel; Sibayan, Michael; Troch, Peter A.; Tuller, Markus; van Haren, Joost; Zeng, Xubin

2015-01-01

Zero-order drainage basins, and their constituent hillslopes, are the fundamental geomorphic unit comprising much of Earth's uplands. The convergent topography of these landscapes generates spatially variable substrate and moisture content, facilitating biological diversity and influencing how the landscape filters precipitation and sequesters atmospheric carbon dioxide. In light of these significant ecosystem services, refining our understanding of how these functions are affected by landscape evolution, weather variability, and long-term climate change is imperative. In this paper we introduce the Landscape Evolution Observatory (LEO): a large-scale controllable infrastructure consisting of three replicated artificial landscapes (each 330 m2 surface area) within the climate-controlled Biosphere 2 facility in Arizona, USA. At LEO, experimental manipulation of rainfall, air temperature, relative humidity, and wind speed are possible at unprecedented scale. The Landscape Evolution Observatory was designed as a community resource to advance understanding of how topography, physical and chemical properties of soil, and biological communities coevolve, and how this coevolution affects water, carbon, and energy cycles at multiple spatial scales. With well-defined boundary conditions and an extensive network of sensors and samplers, LEO enables an iterative scientific approach that includes numerical model development and virtual experimentation, physical experimentation, data analysis, and model refinement. We plan to engage the broader scientific community through public dissemination of data from LEO, collaborative experimental design, and community-based model development.

Challenges in Managing Trustworthy Large-scale Digital Science

NASA Astrophysics Data System (ADS)

Evans, B. J. K.

2017-12-01

The increased use of large-scale international digital science has opened a number of challenges for managing, handling, using and preserving scientific information. The large volumes of information are driven by three main categories - model outputs including coupled models and ensembles, data products that have been processing to a level of usability, and increasingly heuristically driven data analysis. These data products are increasingly the ones that are usable by the broad communities, and far in excess of the raw instruments data outputs. The data, software and workflows are then shared and replicated to allow broad use at an international scale, which places further demands of infrastructure to support how the information is managed reliably across distributed resources. Users necessarily rely on these underlying "black boxes" so that they are productive to produce new scientific outcomes. The software for these systems depend on computational infrastructure, software interconnected systems, and information capture systems. This ranges from the fundamentals of the reliability of the compute hardware, system software stacks and libraries, and the model software. Due to these complexities and capacity of the infrastructure, there is an increased emphasis of transparency of the approach and robustness of the methods over the full reproducibility. Furthermore, with large volume data management, it is increasingly difficult to store the historical versions of all model and derived data. Instead, the emphasis is on the ability to access the updated products and the reliability by which both previous outcomes are still relevant and can be updated for the new information. We will discuss these challenges and some of the approaches underway that are being used to address these issues.

Methodological Problems of Nanotechnoscience

NASA Astrophysics Data System (ADS)

Gorokhov, V. G.

Recently, we have reported on the definitions of nanotechnology as a new type of NanoTechnoScience and on the nanotheory as a cluster of the different natural and engineering theories. Nanotechnology is not only a new type of scientific-engineering discipline, but it evolves also in a “nonclassical” way. Nanoontology or nano scientific world view has a function of the methodological orientation for the choice the theoretical means and methods toward a solution to the scientific and engineering problems. This allows to change from one explanation and scientific world view to another without any problems. Thus, nanotechnology is both a field of scientific knowledge and a sphere of engineering activity, in other words, NanoTechnoScience is similar to Systems Engineering as the analysis and design of large-scale, complex, man/machine systems but micro- and nanosystems. Nano systems engineering as well as Macro systems engineering includes not only systems design but also complex research. Design orientation has influence on the change of the priorities in the complex research and of the relation to the knowledge, not only to “the knowledge about something”, but also to the knowledge as the means of activity: from the beginning control and restructuring of matter at the nano-scale is a necessary element of nanoscience.

A dynamical systems approach to studying midlatitude weather extremes

NASA Astrophysics Data System (ADS)

Messori, Gabriele; Caballero, Rodrigo; Faranda, Davide

2017-04-01

Extreme weather occurrences carry enormous social and economic costs and routinely garner widespread scientific and media coverage. The ability to predict these events is therefore a topic of crucial importance. Here we propose a novel predictability pathway for extreme events, by building upon recent advances in dynamical systems theory. We show that simple dynamical systems metrics can be used to identify sets of large-scale atmospheric flow patterns with similar spatial structure and temporal evolution on time scales of several days to a week. In regions where these patterns favor extreme weather, they afford a particularly good predictability of the extremes. We specifically test this technique on the atmospheric circulation in the North Atlantic region, where it provides predictability of large-scale wintertime surface temperature extremes in Europe up to 1 week in advance.

Semantic Information Processing of Physical Simulation Based on Scientific Concept Vocabulary Model

NASA Astrophysics Data System (ADS)

Kino, Chiaki; Suzuki, Yoshio; Takemiya, Hiroshi

Scientific Concept Vocabulary (SCV) has been developed to actualize Cognitive methodology based Data Analysis System: CDAS which supports researchers to analyze large scale data efficiently and comprehensively. SCV is an information model for processing semantic information for physics and engineering. In the model of SCV, all semantic information is related to substantial data and algorisms. Consequently, SCV enables a data analysis system to recognize the meaning of execution results output from a numerical simulation. This method has allowed a data analysis system to extract important information from a scientific view point. Previous research has shown that SCV is able to describe simple scientific indices and scientific perceptions. However, it is difficult to describe complex scientific perceptions by currently-proposed SCV. In this paper, a new data structure for SCV has been proposed in order to describe scientific perceptions in more detail. Additionally, the prototype of the new model has been constructed and applied to actual data of numerical simulation. The result means that the new SCV is able to describe more complex scientific perceptions.

Scientific Discovery through Advanced Computing in Plasma Science

NASA Astrophysics Data System (ADS)

Tang, William

2005-03-01

Advanced computing is generally recognized to be an increasingly vital tool for accelerating progress in scientific research during the 21st Century. For example, the Department of Energy's ``Scientific Discovery through Advanced Computing'' (SciDAC) Program was motivated in large measure by the fact that formidable scientific challenges in its research portfolio could best be addressed by utilizing the combination of the rapid advances in super-computing technology together with the emergence of effective new algorithms and computational methodologies. The imperative is to translate such progress into corresponding increases in the performance of the scientific codes used to model complex physical systems such as those encountered in high temperature plasma research. If properly validated against experimental measurements and analytic benchmarks, these codes can provide reliable predictive capability for the behavior of a broad range of complex natural and engineered systems. This talk reviews recent progress and future directions for advanced simulations with some illustrative examples taken from the plasma science applications area. Significant recent progress has been made in both particle and fluid simulations of fine-scale turbulence and large-scale dynamics, giving increasingly good agreement between experimental observations and computational modeling. This was made possible by the combination of access to powerful new computational resources together with innovative advances in analytic and computational methods for developing reduced descriptions of physics phenomena spanning a huge range in time and space scales. In particular, the plasma science community has made excellent progress in developing advanced codes for which computer run-time and problem size scale well with the number of processors on massively parallel machines (MPP's). A good example is the effective usage of the full power of multi-teraflop (multi-trillion floating point computations per second) MPP's to produce three-dimensional, general geometry, nonlinear particle simulations which have accelerated progress in understanding the nature of plasma turbulence in magnetically-confined high temperature plasmas. These calculations, which typically utilized billions of particles for thousands of time-steps, would not have been possible without access to powerful present generation MPP computers and the associated diagnostic and visualization capabilities. In general, results from advanced simulations provide great encouragement for being able to include increasingly realistic dynamics to enable deeper physics insights into plasmas in both natural and laboratory environments. The associated scientific excitement should serve to stimulate improved cross-cutting collaborations with other fields and also to help attract bright young talent to the computational science area.

Web-based Visual Analytics for Extreme Scale Climate Science

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

Steed, Chad A; Evans, Katherine J; Harney, John F

In this paper, we introduce a Web-based visual analytics framework for democratizing advanced visualization and analysis capabilities pertinent to large-scale earth system simulations. We address significant limitations of present climate data analysis tools such as tightly coupled dependencies, ineffi- cient data movements, complex user interfaces, and static visualizations. Our Web-based visual analytics framework removes critical barriers to the widespread accessibility and adoption of advanced scientific techniques. Using distributed connections to back-end diagnostics, we minimize data movements and leverage HPC platforms. We also mitigate system dependency issues by employing a RESTful interface. Our framework embraces the visual analytics paradigm via newmore » visual navigation techniques for hierarchical parameter spaces, multi-scale representations, and interactive spatio-temporal data mining methods that retain details. Although generalizable to other science domains, the current work focuses on improving exploratory analysis of large-scale Community Land Model (CLM) and Community Atmosphere Model (CAM) simulations.« less

Anisotropy of the Cosmic Microwave Background Radiation on Large and Medium Angular Scales

NASA Technical Reports Server (NTRS)

Houghton, Anthony; Timbie, Peter

1998-01-01

This grant has supported work at Brown University on measurements of the 2.7 K Cosmic Microwave Background Radiation (CMB). The goal has been to characterize the spatial variations in the temperature of the CMB in order to understand the formation of large-scale structure in the universe. We have concurrently pursued two measurements using millimeter-wave telescopes carried aloft by scientific balloons. Both systems operate over a range of wavelengths, chosen to allow spectral removal of foreground sources such as the atmosphere, Galaxy, etc. The angular resolution of approx. 25 arcminutes is near the angular scale at which the most structure is predicted by current models to be visible in the CMB angular power spectrum. The main goal is to determine the angular scale of this structure; in turn we can infer the density parameter, Omega, for the universe as well as other cosmological parameters, such as the Hubble constant.

CERN and LHC - Their Place in Global Science

ScienceCinema

None

2018-01-09

The Large Hadron Collider (LHC) is the largest scientific instrument in the world. It brings into collision intense beams of protons and ions to explore the structure of matter and investigate the forces of nature at an unprecedented energy scale, thus serving a community of some 7,000 particle physicists from all over the world.

78 FR 25266 - An Assessment of Potential Mining Impacts on Salmon Ecosystems of Bristol Bay, Alaska

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-30

... information presented in the report, the realistic mining scenario used, the data and information used to... additional data or scientific or technical information about Bristol Bay resources or large-scale mining that... Potential Mining Impacts on Salmon Ecosystems of Bristol Bay, Alaska AGENCY: Environmental Protection Agency...

Uncertainty analysis in ecological studies: an overview

Treesearch

Harbin Li; Jianguo Wu

2006-01-01

Large-scale simulation models are essential tools for scientific research and environmental decision-making because they can be used to synthesize knowledge, predict consequences of potential scenarios, and develop optimal solutions (Clark et al. 2001, Berk et al. 2002, Katz 2002). Modeling is often the only means of addressing complex environmental problems that occur...

The End of School Reform

ERIC Educational Resources Information Center

Berube, Maurice R.; Berube, Clair T.

2006-01-01

Education as a major social movement is coming to an end. This book derives its theoretical framework from the ideas of Hegel, who perceived an end to history, and Thomas Kuhn, who theorized that history does not follow a linear path but that the scientific landscape changes through large-scale movements called "paradigm shifts". This book…

Java Performance for Scientific Applications on LLNL Computer Systems

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

Kapfer, C; Wissink, A

2002-05-10

Languages in use for high performance computing at the laboratory--Fortran (f77 and f90), C, and C++--have many years of development behind them and are generally considered the fastest available. However, Fortran and C do not readily extend to object-oriented programming models, limiting their capability for very complex simulation software. C++ facilitates object-oriented programming but is a very complex and error-prone language. Java offers a number of capabilities that these other languages do not. For instance it implements cleaner (i.e., easier to use and less prone to errors) object-oriented models than C++. It also offers networking and security as part ofmore » the language standard, and cross-platform executables that make it architecture neutral, to name a few. These features have made Java very popular for industrial computing applications. The aim of this paper is to explain the trade-offs in using Java for large-scale scientific applications at LLNL. Despite its advantages, the computational science community has been reluctant to write large-scale computationally intensive applications in Java due to concerns over its poor performance. However, considerable progress has been made over the last several years. The Java Grande Forum [1] has been promoting the use of Java for large-scale computing. Members have introduced efficient array libraries, developed fast just-in-time (JIT) compilers, and built links to existing packages used in high performance parallel computing.« less

A scientific program for infrared, submillimeter and radio astronomy from space: A report by the Management Operations Working Group

NASA Technical Reports Server (NTRS)

1989-01-01

Important and fundamental scientific progress can be attained through space observations in the wavelengths longward of 1 micron. The formation of galaxies, stars, and planets, the origin of quasars and the nature of active galactic nuclei, the large scale structure of the Universe, and the problem of the missing mass, are among the major scientific issues that can be addressed by these observations. Significant advances in many areas of astrophysics can be made over the next 20 years by implementing the outlined program. This program combines large observatories with smaller projects to create an overall scheme that emphasized complementarity and synergy, advanced technology, community support and development, and the training of the next generation of scientists. Key aspects of the program include: the Space Infrared Telescope Facility; the Stratospheric Observatory for Infrared Astronomy; a robust program of small missions; and the creation of the technology base for future major observatories.

Standardization of fluorine-18 manufacturing processes: new scientific challenges for PET.

PubMed

Hjelstuen, Ole K; Svadberg, Anders; Olberg, Dag E; Rosser, Mark

2011-08-01

In [(18)F]fluoride chemistry, the minute amounts of radioactivity taking part in a radiolabeling reaction are easily outnumbered by other reactants. Surface areas become comparably larger and more influential than in standard fluorine chemistry, while leachables, extractables, and other components that normally are considered small impurities can have a considerable influence on the efficiency of the reaction. A number of techniques exist to give sufficient (18)F-tracer for a study in a pre-clinical or clinical system, but the chemical and pharmaceutical understanding has significant gaps when it comes to scaling up or making the reaction more efficient. Automation and standardization of [(18)F]fluoride PET tracers is a prerequisite for reproducible manufacturing across multiple PET centers. So far, large-scale, multi-site manufacture has been established only for [(18)F]FDG, but several new tracers are emerging. In general terms, this transition from small- to large-scale production has disclosed several scientific challenges that need to be addressed. There are still areas of limited knowledge in the fundamental [(18)F]fluoride chemistry. The role of pharmaceutical factors that could influence the (18)F-radiosynthesis and the gaps in precise chemistry knowledge are discussed in this review based on a normal synthesis pattern. Copyright © 2011 Elsevier B.V. All rights reserved.

From catchment scale hydrologic processes to numerical models and robust predictions of climate change impacts at regional scales

NASA Astrophysics Data System (ADS)

Wagener, T.

2017-12-01

Current societal problems and questions demand that we increasingly build hydrologic models for regional or even continental scale assessment of global change impacts. Such models offer new opportunities for scientific advancement, for example by enabling comparative hydrology or connectivity studies, and for improved support of water management decision, since we might better understand regional impacts on water resources from large scale phenomena such as droughts. On the other hand, we are faced with epistemic uncertainties when we move up in scale. The term epistemic uncertainty describes those uncertainties that are not well determined by historical observations. This lack of determination can be because the future is not like the past (e.g. due to climate change), because the historical data is unreliable (e.g. because it is imperfectly recorded from proxies or missing), or because it is scarce (either because measurements are not available at the right scale or there is no observation network available at all). In this talk I will explore: (1) how we might build a bridge between what we have learned about catchment scale processes and hydrologic model development and evaluation at larger scales. (2) How we can understand the impact of epistemic uncertainty in large scale hydrologic models. And (3) how we might utilize large scale hydrologic predictions to understand climate change impacts, e.g. on infectious disease risk.

Science Diplomacy in Large International Collaborations

NASA Astrophysics Data System (ADS)

Barish, Barry C.

2011-04-01

What opportunities and challenges does the rapidly growing internationalization of science, especially large scale science and technology projects, present for US science policy? On one hand, the interchange of scientists, the sharing of technology and facilities and the working together on common scientific goals promotes better understanding and better science. On the other hand, challenges are presented, because the science cannot be divorced from government policies, and solutions must be found for issues varying from visas to making reliable international commitments.

White paper: A plan for cooperation between NASA and DARPA to establish a center for advanced architectures

NASA Technical Reports Server (NTRS)

Denning, P. J.; Adams, G. B., III; Brown, R. L.; Kanerva, P.; Leiner, B. M.; Raugh, M. R.

1986-01-01

Large, complex computer systems require many years of development. It is recognized that large scale systems are unlikely to be delivered in useful condition unless users are intimately involved throughout the design process. A mechanism is described that will involve users in the design of advanced computing systems and will accelerate the insertion of new systems into scientific research. This mechanism is embodied in a facility called the Center for Advanced Architectures (CAA). CAA would be a division of RIACS (Research Institute for Advanced Computer Science) and would receive its technical direction from a Scientific Advisory Board established by RIACS. The CAA described here is a possible implementation of a center envisaged in a proposed cooperation between NASA and DARPA.

An Illustrative Guide to the Minerva Framework

NASA Astrophysics Data System (ADS)

Flom, Erik; Leonard, Patrick; Hoeffel, Udo; Kwak, Sehyun; Pavone, Andrea; Svensson, Jakob; Krychowiak, Maciej; Wendelstein 7-X Team Collaboration

2017-10-01

Modern phsyics experiments require tracking and modelling data and their associated uncertainties on a large scale, as well as the combined implementation of multiple independent data streams for sophisticated modelling and analysis. The Minerva Framework offers a centralized, user-friendly method of large-scale physics modelling and scientific inference. Currently used by teams at multiple large-scale fusion experiments including the Joint European Torus (JET) and Wendelstein 7-X (W7-X), the Minerva framework provides a forward-model friendly architecture for developing and implementing models for large-scale experiments. One aspect of the framework involves so-called data sources, which are nodes in the graphical model. These nodes are supplied with engineering and physics parameters. When end-user level code calls a node, it is checked network-wide against its dependent nodes for changes since its last implementation and returns version-specific data. Here, a filterscope data node is used as an illustrative example of the Minerva Framework's data management structure and its further application to Bayesian modelling of complex systems. This work has been carried out within the framework of the EUROfusion Consortium and has received funding from the Euratom research and training programme 2014-2018 under Grant Agreement No. 633053.

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

Large-scale optimization-based non-negative computational framework for diffusion equations: Parallel implementation and performance studies

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

Chang, Justin; Karra, Satish; Nakshatrala, Kalyana B.

It is well-known that the standard Galerkin formulation, which is often the formulation of choice under the finite element method for solving self-adjoint diffusion equations, does not meet maximum principles and the non-negative constraint for anisotropic diffusion equations. Recently, optimization-based methodologies that satisfy maximum principles and the non-negative constraint for steady-state and transient diffusion-type equations have been proposed. To date, these methodologies have been tested only on small-scale academic problems. The purpose of this paper is to systematically study the performance of the non-negative methodology in the context of high performance computing (HPC). PETSc and TAO libraries are, respectively, usedmore » for the parallel environment and optimization solvers. For large-scale problems, it is important for computational scientists to understand the computational performance of current algorithms available in these scientific libraries. The numerical experiments are conducted on the state-of-the-art HPC systems, and a single-core performance model is used to better characterize the efficiency of the solvers. Furthermore, our studies indicate that the proposed non-negative computational framework for diffusion-type equations exhibits excellent strong scaling for real-world large-scale problems.« less

Large-scale optimization-based non-negative computational framework for diffusion equations: Parallel implementation and performance studies

DOE PAGES

Chang, Justin; Karra, Satish; Nakshatrala, Kalyana B.

2016-07-26

It is well-known that the standard Galerkin formulation, which is often the formulation of choice under the finite element method for solving self-adjoint diffusion equations, does not meet maximum principles and the non-negative constraint for anisotropic diffusion equations. Recently, optimization-based methodologies that satisfy maximum principles and the non-negative constraint for steady-state and transient diffusion-type equations have been proposed. To date, these methodologies have been tested only on small-scale academic problems. The purpose of this paper is to systematically study the performance of the non-negative methodology in the context of high performance computing (HPC). PETSc and TAO libraries are, respectively, usedmore » for the parallel environment and optimization solvers. For large-scale problems, it is important for computational scientists to understand the computational performance of current algorithms available in these scientific libraries. The numerical experiments are conducted on the state-of-the-art HPC systems, and a single-core performance model is used to better characterize the efficiency of the solvers. Furthermore, our studies indicate that the proposed non-negative computational framework for diffusion-type equations exhibits excellent strong scaling for real-world large-scale problems.« less

Implementation of a multi-threaded framework for large-scale scientific applications

DOE PAGES

Sexton-Kennedy, E.; Gartung, Patrick; Jones, C. D.; ...

2015-05-22

The CMS experiment has recently completed the development of a multi-threaded capable application framework. In this paper, we will discuss the design, implementation and application of this framework to production applications in CMS. For the 2015 LHC run, this functionality is particularly critical for both our online and offline production applications, which depend on faster turn-around times and a reduced memory footprint relative to before. These applications are complex codes, each including a large number of physics-driven algorithms. While the framework is capable of running a mix of thread-safe and 'legacy' modules, algorithms running in our production applications need tomore » be thread-safe for optimal use of this multi-threaded framework at a large scale. Towards this end, we discuss the types of changes, which were necessary for our algorithms to achieve good performance of our multithreaded applications in a full-scale application. Lastly performance numbers for what has been achieved for the 2015 run are presented.« less

Seismic and source characteristics of large chemical explosions. Final report

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

Adushkin, V.V.; Kostuchenko, V.N.; Pernik, L.M.

From the very beginning of its arrangement in 1947, the Institute for Dynamics of the Geospheres RAS (former Special Sector of the Institute for physics of the Earth, RAS) was providing scientific observations of effects of nuclear explosions, as well as large-scale detonations of HE, on environment. This report presents principal results of instrumental observations obtained from various large-scale chemical explosions conducted in the Former-Soviet Union in the period of time from 1957 to 1989. Considering principal aim of the work, tamped and equivalent chemical explosions have been selected with total weights from several hundreds to several thousands ton. Inmore » particular, the selected explosions were aimed to study scaling law from excavation explosions, seismic effect of tamped explosions, and for dam construction for hydropower stations and soil melioration. Instrumental data on surface explosions of total weight in the same range aimed to test military technics and special objects are not included.« less

Calculation methods for estimating the prospects of a space experiment by means of impact by asteroid Apophis on the Moon surface

NASA Astrophysics Data System (ADS)

Ostrik, A. V.; Kazantsev, A. M.

2018-01-01

The problem of principal change of asteroid 99952 (Apophis) orbit is formulated. Aim of this change is the termination of asteroid motion in Solar system. Instead of the passive rescue tactics from asteroid threat, an option is proposed for using the asteroid for setting up a large-scale space experiment on the impact interaction of the asteroid with the Moon. The scientific and methodical apparatus for calculating the possibility of realization, searching and justification the scientific uses of this space experiment is considered.

Pollutant Transport and Fate: Relations Between Flow-paths and Downstream Impacts of Human Activities

NASA Astrophysics Data System (ADS)

Thorslund, J.; Jarsjo, J.; Destouni, G.

2017-12-01

The quality of freshwater resources is increasingly impacted by human activities. Humans also extensively change the structure of landscapes, which may alter natural hydrological processes. To manage and maintain freshwater of good water quality, it is critical to understand how pollutants are released into, transported and transformed within the hydrological system. Some key scientific questions include: What are net downstream impacts of pollutants across different hydroclimatic and human disturbance conditions, and on different scales? What are the functions within and between components of the landscape, such as wetlands, on mitigating pollutant load delivery to downstream recipients? We explore these questions by synthesizing results from several relevant case study examples of intensely human-impacted hydrological systems. These case study sites have been specifically evaluated in terms of net impact of human activities on pollutant input to the aquatic system, as well as flow-path distributions trough wetlands as a potential ecosystem service of pollutant mitigation. Results shows that although individual wetlands have high retention capacity, efficient net retention effects were not always achieved at a larger landscape scale. Evidence suggests that the function of wetlands as mitigation solutions to pollutant loads is largely controlled by large-scale parallel and circular flow-paths, through which multiple wetlands are interconnected in the landscape. To achieve net mitigation effects at large scale, a large fraction of the polluted large-scale flows must be transported through multiple connected wetlands. Although such large-scale flow interactions are critical for assessing water pollution spreading and fate through the landscape, our synthesis shows a frequent lack of knowledge at such scales. We suggest ways forward for addressing the mismatch between the large scales at which key pollutant pressures and water quality changes take place and the relatively scale at which most studies and implementations are currently made. These suggestions can help bridge critical knowledge gaps, as needed for improving water quality predictions and mitigation solutions under human and environmental changes.

The compression–error trade-off for large gridded data sets

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

Silver, Jeremy D.; Zender, Charles S.

The netCDF-4 format is widely used for large gridded scientific data sets and includes several compression methods: lossy linear scaling and the non-lossy deflate and shuffle algorithms. Many multidimensional geoscientific data sets exhibit considerable variation over one or several spatial dimensions (e.g., vertically) with less variation in the remaining dimensions (e.g., horizontally). On such data sets, linear scaling with a single pair of scale and offset parameters often entails considerable loss of precision. We introduce an alternative compression method called "layer-packing" that simultaneously exploits lossy linear scaling and lossless compression. Layer-packing stores arrays (instead of a scalar pair) of scalemore » and offset parameters. An implementation of this method is compared with lossless compression, storing data at fixed relative precision (bit-grooming) and scalar linear packing in terms of compression ratio, accuracy and speed. When viewed as a trade-off between compression and error, layer-packing yields similar results to bit-grooming (storing between 3 and 4 significant figures). Bit-grooming and layer-packing offer significantly better control of precision than scalar linear packing. Relative performance, in terms of compression and errors, of bit-groomed and layer-packed data were strongly predicted by the entropy of the exponent array, and lossless compression was well predicted by entropy of the original data array. Layer-packed data files must be "unpacked" to be readily usable. The compression and precision characteristics make layer-packing a competitive archive format for many scientific data sets.« less

The compression–error trade-off for large gridded data sets

DOE PAGES

Silver, Jeremy D.; Zender, Charles S.

2017-01-27

The netCDF-4 format is widely used for large gridded scientific data sets and includes several compression methods: lossy linear scaling and the non-lossy deflate and shuffle algorithms. Many multidimensional geoscientific data sets exhibit considerable variation over one or several spatial dimensions (e.g., vertically) with less variation in the remaining dimensions (e.g., horizontally). On such data sets, linear scaling with a single pair of scale and offset parameters often entails considerable loss of precision. We introduce an alternative compression method called "layer-packing" that simultaneously exploits lossy linear scaling and lossless compression. Layer-packing stores arrays (instead of a scalar pair) of scalemore » and offset parameters. An implementation of this method is compared with lossless compression, storing data at fixed relative precision (bit-grooming) and scalar linear packing in terms of compression ratio, accuracy and speed. When viewed as a trade-off between compression and error, layer-packing yields similar results to bit-grooming (storing between 3 and 4 significant figures). Bit-grooming and layer-packing offer significantly better control of precision than scalar linear packing. Relative performance, in terms of compression and errors, of bit-groomed and layer-packed data were strongly predicted by the entropy of the exponent array, and lossless compression was well predicted by entropy of the original data array. Layer-packed data files must be "unpacked" to be readily usable. The compression and precision characteristics make layer-packing a competitive archive format for many scientific data sets.« less

An Anthropologist among the Psychometricians: Assessment Events, Ethnography, and Differential Item Functioning in the Mongolian Gobi

ERIC Educational Resources Information Center

Maddox, Bryan; Zumbo, Bruno D.; Tay-Lim, Brenda; Qu, Demin

2015-01-01

This article explores the potential for ethnographic observations to inform the analysis of test item performance. In 2010, a standardized, large-scale adult literacy assessment took place in Mongolia as part of the United Nations Educational, Scientific and Cultural Organization Literacy Assessment and Monitoring Programme (LAMP). In a novel form…

Recommendations for open data science.

PubMed

Gymrek, Melissa; Farjoun, Yossi

2016-01-01

Life science research increasingly relies on large-scale computational analyses. However, the code and data used for these analyses are often lacking in publications. To maximize scientific impact, reproducibility, and reuse, it is crucial that these resources are made publicly available and are fully transparent. We provide recommendations for improving the openness of data-driven studies in life sciences.

Evaluating Educational Programs. ETS R&D Scientific and Policy Contributions Series. ETS SPC-11-01. ETS Research Report No. RR-11-15

ERIC Educational Resources Information Center

Ball, Samuel

2011-01-01

Since its founding in 1947, ETS has conducted a significant and wide-ranging research program that has focused on, among other things, psychometric and statistical methodology; educational evaluation; performance assessment and scoring; large-scale assessment and evaluation; cognitive, developmental, personality, and social psychology; and…

Soil quality and productivity responses to watershed restoration in the Ouachita mountains of Arkansas, USA

Treesearch

John A. Stanturf; Daniel A. Marion; Martin Spetich; Kenneth Luckow; James M. Guldin; Hal O. Liechty; Calvin E. Meier

2000-01-01

The Ouachita Mountains Ecosystem Management Research Project (OEMP) is a large interdisciplinary research project designed to provide the scientific foundation for landscape management at the scale of watersheds. The OEMP has progressed through three phases: developing natural regeneration alternatives to clearcutting and planting; testing of these alternatives at the...

Recent activities of the physical society of Japan and the Japan society of applied physics gender equality promotion committees

NASA Astrophysics Data System (ADS)

Kaki, K.; Okiharu, F.; Tajima, S.; Takayama, H.; Watanabe, M. O.

2013-03-01

The results of a 2007 large-scale survey of gender equality in scientific and technological professions in Japan are reported. The activities of two Japanese physics societies in the three years since the 3rd IUPAP International Conference on Women in Physics was held in 2008 are reported.

The Role of Empathy in Preparing Teachers to Tackle Bullying

ERIC Educational Resources Information Center

Murphy, Helena; Tubritt, John; Norman, James O'Higgins

2018-01-01

Much research on bullying behaviour in schools among students has been carried out since the 1970's, when Olweus started a large-scale project in Norway which is now generally regarded as the first scientific study on bullying. Yet, there has been little research on how teachers respond to reports of bullying and tackle bullying behaviour in…

77 FR 11111 - Assessment of Potential Large-Scale Mining on the Bristol Bay Watershed of Alaska: Nomination of...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-24

... populations in the world. In February 2011, EPA began a scientific assessment of the Bristol Bay watershed to... on salmon and resident fish populations of the Kvichak and Nushagak River drainages, and if these effects are likely to affect wildlife and human populations in the region. Additional information...

Expanding Views of Creative Science: A Response to Ghassib's Productivist Industrial Model

ERIC Educational Resources Information Center

Ambrose, Don

2010-01-01

It was refreshing to read Hisham Ghassib's (2010) article outlining his model of scientific knowledge production. Too few scholarly writings in creative studies and gifted education deal with issues at the large-scale, panoramic level of analysis. Ghassib (2010) would not disappoint Albert Einstein who lamented that "I have little patience with…

Experimental effects of climate messages vary geographically

NASA Astrophysics Data System (ADS)

Zhang, Baobao; van der Linden, Sander; Mildenberger, Matto; Marlon, Jennifer R.; Howe, Peter D.; Leiserowitz, Anthony

2018-05-01

Social science scholars routinely evaluate the efficacy of diverse climate frames using local convenience or nationally representative samples1-5. For example, previous research has focused on communicating the scientific consensus on climate change, which has been identified as a `gateway' cognition to other key beliefs about the issue6-9. Importantly, although these efforts reveal average public responsiveness to particular climate frames, they do not describe variation in message effectiveness at the spatial and political scales relevant for climate policymaking. Here we use a small-area estimation method to map geographical variation in public responsiveness to information about the scientific consensus as part of a large-scale randomized national experiment (n = 6,301). Our survey experiment finds that, on average, public perception of the consensus increases by 16 percentage points after message exposure. However, substantial spatial variation exists across the United States at state and local scales. Crucially, responsiveness is highest in more conservative parts of the country, leading to national convergence in perceptions of the climate science consensus across diverse political geographies. These findings not only advance a geographical understanding of how the public engages with information about scientific agreement, but will also prove useful for policymakers, practitioners and scientists engaged in climate change mitigation and adaptation.

Measuring the perceived uncertainty of scientific evidence and its relationship to engagement with science.

PubMed

Retzbach, Joachim; Otto, Lukas; Maier, Michaela

2016-08-01

Many scholars have argued for the need to communicate openly not only scientific successes to the public but also limitations, such as the tentativeness of research findings, in order to enhance public trust and engagement. Yet, it has not been quantitatively assessed how the perception of scientific uncertainties relates to engagement with science on an individual level. In this article, we report the development and testing of a new questionnaire in English and German measuring the perceived uncertainty of scientific evidence. Results indicate that the scale is reliable and valid in both language versions and that its two subscales are differentially related to measures of engagement: Science-friendly attitudes were positively related only to 'subjectively' perceived uncertainty, whereas interest in science as well as behavioural engagement actions and intentions were largely uncorrelated. We conclude that perceiving scientific knowledge to be uncertain is only weakly, but positively related to engagement with science. © The Author(s) 2015.

Non-negative Tensor Factorization for Robust Exploratory Big-Data Analytics

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

Alexandrov, Boian; Vesselinov, Velimir Valentinov; Djidjev, Hristo Nikolov

Currently, large multidimensional datasets are being accumulated in almost every field. Data are: (1) collected by distributed sensor networks in real-time all over the globe, (2) produced by large-scale experimental measurements or engineering activities, (3) generated by high-performance simulations, and (4) gathered by electronic communications and socialnetwork activities, etc. Simultaneous analysis of these ultra-large heterogeneous multidimensional datasets is often critical for scientific discoveries, decision-making, emergency response, and national and global security. The importance of such analyses mandates the development of the next-generation of robust machine learning (ML) methods and tools for bigdata exploratory analysis.

IOPS advisor: Research in progress on knowledge-intensive methods for irregular operations airline scheduling

NASA Technical Reports Server (NTRS)

Borse, John E.; Owens, Christopher C.

1992-01-01

Our research focuses on the problem of recovering from perturbations in large-scale schedules, specifically on the ability of a human-machine partnership to dynamically modify an airline schedule in response to unanticipated disruptions. This task is characterized by massive interdependencies and a large space of possible actions. Our approach is to apply the following: qualitative, knowledge-intensive techniques relying on a memory of stereotypical failures and appropriate recoveries; and quantitative techniques drawn from the Operations Research community's work on scheduling. Our main scientific challenge is to represent schedules, failures, and repairs so as to make both sets of techniques applicable to the same data. This paper outlines ongoing research in which we are cooperating with United Airlines to develop our understanding of the scientific issues underlying the practicalities of dynamic, real-time schedule repair.

An Open, Large-Scale, Collaborative Effort to Estimate the Reproducibility of Psychological Science.

PubMed

2012-11-01

Reproducibility is a defining feature of science. However, because of strong incentives for innovation and weak incentives for confirmation, direct replication is rarely practiced or published. The Reproducibility Project is an open, large-scale, collaborative effort to systematically examine the rate and predictors of reproducibility in psychological science. So far, 72 volunteer researchers from 41 institutions have organized to openly and transparently replicate studies published in three prominent psychological journals in 2008. Multiple methods will be used to evaluate the findings, calculate an empirical rate of replication, and investigate factors that predict reproducibility. Whatever the result, a better understanding of reproducibility will ultimately improve confidence in scientific methodology and findings. © The Author(s) 2012.

GISpark: A Geospatial Distributed Computing Platform for Spatiotemporal Big Data

NASA Astrophysics Data System (ADS)

Wang, S.; Zhong, E.; Wang, E.; Zhong, Y.; Cai, W.; Li, S.; Gao, S.

2016-12-01

Geospatial data are growing exponentially because of the proliferation of cost effective and ubiquitous positioning technologies such as global remote-sensing satellites and location-based devices. Analyzing large amounts of geospatial data can provide great value for both industrial and scientific applications. Data- and compute- intensive characteristics inherent in geospatial big data increasingly pose great challenges to technologies of data storing, computing and analyzing. Such challenges require a scalable and efficient architecture that can store, query, analyze, and visualize large-scale spatiotemporal data. Therefore, we developed GISpark - a geospatial distributed computing platform for processing large-scale vector, raster and stream data. GISpark is constructed based on the latest virtualized computing infrastructures and distributed computing architecture. OpenStack and Docker are used to build multi-user hosting cloud computing infrastructure for GISpark. The virtual storage systems such as HDFS, Ceph, MongoDB are combined and adopted for spatiotemporal data storage management. Spark-based algorithm framework is developed for efficient parallel computing. Within this framework, SuperMap GIScript and various open-source GIS libraries can be integrated into GISpark. GISpark can also integrated with scientific computing environment (e.g., Anaconda), interactive computing web applications (e.g., Jupyter notebook), and machine learning tools (e.g., TensorFlow/Orange). The associated geospatial facilities of GISpark in conjunction with the scientific computing environment, exploratory spatial data analysis tools, temporal data management and analysis systems make up a powerful geospatial computing tool. GISpark not only provides spatiotemporal big data processing capacity in the geospatial field, but also provides spatiotemporal computational model and advanced geospatial visualization tools that deals with other domains related with spatial property. We tested the performance of the platform based on taxi trajectory analysis. Results suggested that GISpark achieves excellent run time performance in spatiotemporal big data applications.

Wayfinding in Social Networks

NASA Astrophysics Data System (ADS)

Liben-Nowell, David

With the recent explosion of popularity of commercial social-networking sites like Facebook and MySpace, the size of social networks that can be studied scientifically has passed from the scale traditionally studied by sociologists and anthropologists to the scale of networks more typically studied by computer scientists. In this chapter, I will highlight a recent line of computational research into the modeling and analysis of the small-world phenomenon - the observation that typical pairs of people in a social network are connected by very short chains of intermediate friends - and the ability of members of a large social network to collectively find efficient routes to reach individuals in the network. I will survey several recent mathematical models of social networks that account for these phenomena, with an emphasis on both the provable properties of these social-network models and the empirical validation of the models against real large-scale social-network data.

The Explorer of Diffuse Galactic Emission (EDGE): Determination of Large-Scale Structure Evolution from Measurement of the Anisotropy of the Cosmic Infrared Background

NASA Technical Reports Server (NTRS)

Silverberg, R. F.; Cheng, E. S.; Cottingham, D. A.; Fixsen, D. J.; Meyer, S. S.; Wilson, G. W.

2004-01-01

The formation of the first objects, stars and galaxies and their subsequent evolution remain a cosmological unknown. Few observational probes of these processes exist. The Cosmic Infrared Background (CIB) originates from this era, and can provide information to test models of both galaxy evolution and the growth of primordial structure. The Explorer of Diffuse Galactic Emission (EDGE) is a proposed balloon-borne mission designed to measure the spatial fluctuations in the CIB from 200 micrometers to 1 millimeter on 6' to 3 degree scales with 2 microKelvin sensitivity/resolution element. Such measurements would provide a sensitive probe of the large-scale variation in protogalaxy density at redshifts approximately 0.5-3. In this paper, we present the scientific justification for the mission and show a concept for the instrument and observations.

PetIGA: A framework for high-performance isogeometric analysis

DOE PAGES

Dalcin, Lisandro; Collier, Nathaniel; Vignal, Philippe; ...

2016-05-25

We present PetIGA, a code framework to approximate the solution of partial differential equations using isogeometric analysis. PetIGA can be used to assemble matrices and vectors which come from a Galerkin weak form, discretized with Non-Uniform Rational B-spline basis functions. We base our framework on PETSc, a high-performance library for the scalable solution of partial differential equations, which simplifies the development of large-scale scientific codes, provides a rich environment for prototyping, and separates parallelism from algorithm choice. We describe the implementation of PetIGA, and exemplify its use by solving a model nonlinear problem. To illustrate the robustness and flexibility ofmore » PetIGA, we solve some challenging nonlinear partial differential equations that include problems in both solid and fluid mechanics. Lastly, we show strong scaling results on up to 4096 cores, which confirm the suitability of PetIGA for large scale simulations.« less

Sea otters in captivity: applications and implications of husbandry development, public display, scientific research and management, and rescue and rehabilitation for sea otter conservation

USGS Publications Warehouse

VanBlaricom, Glenn R.; Belting, Traci F.; Triggs, Lisa H.

2015-01-01

Studies of sea otters in captivity began in 1932, producing important insights for conservation. Soviet (initiated in 1932) and United States (1951) studies provided information on captive otter husbandry, setting the stage for eventual large-scale translocations as tools for population restoration. Early studies also informed effective housing of animals in zoos and aquaria, with sea otters first publicly displayed in 1954. Surveys credited displayed otters in convincing the public of conservation values. After early studies, initial scientific data for captive sea otters in aquaria came from work initiated in 1956, and from dedicated research facilities beginning in 1968. Significant achievements have been made in studies of behavior, physiology, reproduction, and high-priority management issues. Larger-scale projects involving translocation and oil spill response provided extensive insights into stress reactions, water quality issues in captivity, and effects of oil spills.

Network bandwidth utilization forecast model on high bandwidth networks

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

Yoo, Wuchert; Sim, Alex

With the increasing number of geographically distributed scientific collaborations and the scale of the data size growth, it has become more challenging for users to achieve the best possible network performance on a shared network. We have developed a forecast model to predict expected bandwidth utilization for high-bandwidth wide area network. The forecast model can improve the efficiency of resource utilization and scheduling data movements on high-bandwidth network to accommodate ever increasing data volume for large-scale scientific data applications. Univariate model is developed with STL and ARIMA on SNMP path utilization data. Compared with traditional approach such as Box-Jenkins methodology,more » our forecast model reduces computation time by 83.2%. It also shows resilience against abrupt network usage change. The accuracy of the forecast model is within the standard deviation of the monitored measurements.« less

Network Bandwidth Utilization Forecast Model on High Bandwidth Network

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

Yoo, Wucherl; Sim, Alex

With the increasing number of geographically distributed scientific collaborations and the scale of the data size growth, it has become more challenging for users to achieve the best possible network performance on a shared network. We have developed a forecast model to predict expected bandwidth utilization for high-bandwidth wide area network. The forecast model can improve the efficiency of resource utilization and scheduling data movements on high-bandwidth network to accommodate ever increasing data volume for large-scale scientific data applications. Univariate model is developed with STL and ARIMA on SNMP path utilization data. Compared with traditional approach such as Box-Jenkins methodology,more » our forecast model reduces computation time by 83.2percent. It also shows resilience against abrupt network usage change. The accuracy of the forecast model is within the standard deviation of the monitored measurements.« less

Genetic analysis and molecular mapping of an Rf gene from Helianthus angustifolius for a new cytoplasmic male-sterile line

USDA-ARS?s Scientific Manuscript database

The combination of cytoplasmic male-sterile (CMS) and the corresponding fertility restoration genes (Rf) is a critical tool in large-scale hybrid seed production of sunflower. A new CMS line 514A, derived from H. tuberosus / 7718B, was obtained from a scientific exchange with the Liaoning Academy of...

Pathways--A Case of Large-Scale Implementation of Evidence-Based Practice in Scientific Inquiry-Based Science Education

ERIC Educational Resources Information Center

Sotiriou, Sofoklis; Bybee, Rodger W.; Bogner, Franz X.

2017-01-01

The fundamental pioneering ideas about student-centered, inquiry-based learning initiatives are differing in Europe and the US. The latter had initiated various top-down schemes that have led to well-defined standards, while in Europe, with its some 50 independent educational systems, a wide variety of approaches has been evolved. In this present…

Effects of Two Scientific Inquiry Professional Development Interventions on Teaching Practice

ERIC Educational Resources Information Center

Grigg, Jeffrey; Kelly, Kimberle A.; Gamoran, Adam; Borman, Geoffrey D.

2013-01-01

In this article, we examine classroom observations from a 3-year large-scale randomized trial in the Los Angeles Unified School District (LAUSD) to investigate the extent to which a professional development initiative in inquiry science influenced teaching practices in in 4th and 5th grade classrooms in 73 schools. During the course of the study,…

Large Scale Data Mining to Improve Usability of Data: An Intelligent Archive Testbed

NASA Technical Reports Server (NTRS)

Ramapriyan, Hampapuram; Isaac, David; Yang, Wenli; Morse, Steve

2005-01-01

Research in certain scientific disciplines - including Earth science, particle physics, and astrophysics - continually faces the challenge that the volume of data needed to perform valid scientific research can at times overwhelm even a sizable research community. The desire to improve utilization of this data gave rise to the Intelligent Archives project, which seeks to make data archives active participants in a knowledge building system capable of discovering events or patterns that represent new information or knowledge. Data mining can automatically discover patterns and events, but it is generally viewed as unsuited for large-scale use in disciplines like Earth science that routinely involve very high data volumes. Dozens of research projects have shown promising uses of data mining in Earth science, but all of these are based on experiments with data subsets of a few gigabytes or less, rather than the terabytes or petabytes typically encountered in operational systems. To bridge this gap, the Intelligent Archives project is establishing a testbed with the goal of demonstrating the use of data mining techniques in an operationally-relevant environment. This paper discusses the goals of the testbed and the design choices surrounding critical issues that arose during testbed implementation.

Software Engineering Support of the Third Round of Scientific Grand Challenge Investigations: Earth System Modeling Software Framework Survey

NASA Technical Reports Server (NTRS)

Talbot, Bryan; Zhou, Shu-Jia; Higgins, Glenn; Zukor, Dorothy (Technical Monitor)

2002-01-01

One of the most significant challenges in large-scale climate modeling, as well as in high-performance computing in other scientific fields, is that of effectively integrating many software models from multiple contributors. A software framework facilitates the integration task, both in the development and runtime stages of the simulation. Effective software frameworks reduce the programming burden for the investigators, freeing them to focus more on the science and less on the parallel communication implementation. while maintaining high performance across numerous supercomputer and workstation architectures. This document surveys numerous software frameworks for potential use in Earth science modeling. Several frameworks are evaluated in depth, including Parallel Object-Oriented Methods and Applications (POOMA), Cactus (from (he relativistic physics community), Overture, Goddard Earth Modeling System (GEMS), the National Center for Atmospheric Research Flux Coupler, and UCLA/UCB Distributed Data Broker (DDB). Frameworks evaluated in less detail include ROOT, Parallel Application Workspace (PAWS), and Advanced Large-Scale Integrated Computational Environment (ALICE). A host of other frameworks and related tools are referenced in this context. The frameworks are evaluated individually and also compared with each other.

Research ethics in the post-genomic era.

PubMed

Vähäkangas, Kirsi

2013-08-01

New high-throughput 'omics techniques are providing exciting opportunities in clinical medicine and toxicology, especially in the development of biomarkers. In health science research there are traditional ethical considerations that are reasonably obvious, like balancing health benefits and health risks, autonomy mainly pursued by informed consent, and protecting privacy. Epidemiological studies applying new large-scale approaches (e.g., high-throughput or high-content methods and global studies that utilize biobanking of samples and produce large-scale datasets) present new challenges that call for re-evaluation of standard ethical considerations. In this context, assessment of the ethics underlying study designs, bioinformatics, and statistics applied in the generation and clinical translation of research results should also be considered. Indeed, there are ethical considerations in the research process itself, in research objectives and how research is pursued (e.g., which methodologies are selected and how they are carried out). Maintaining research integrity is critical, as demonstrated by the relatively frequent retraction of scientific papers following violations of good scientific practice. Abiding by the laws is necessary but not sufficient for good research ethics, which is and remains in the hands of the scientific community at the level of both individual scientists and organizations. Senior scientists are responsible for the transfer of research tradition to the next generation of scientists through education, mentorship, and setting an example by their own behavior, as well as by creating systems in institutions that support good research ethics. Copyright © 2013 Wiley Periodicals, Inc.

Time-Series Forecast Modeling on High-Bandwidth Network Measurements

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

Yoo, Wucherl; Sim, Alex

With the increasing number of geographically distributed scientific collaborations and the growing sizes of scientific data, it has become challenging for users to achieve the best possible network performance on a shared network. In this paper, we have developed a model to forecast expected bandwidth utilization on high-bandwidth wide area networks. The forecast model can improve the efficiency of the resource utilization and scheduling of data movements on high-bandwidth networks to accommodate ever increasing data volume for large-scale scientific data applications. A univariate time-series forecast model is developed with the Seasonal decomposition of Time series by Loess (STL) and themore » AutoRegressive Integrated Moving Average (ARIMA) on Simple Network Management Protocol (SNMP) path utilization measurement data. Compared with the traditional approach such as Box-Jenkins methodology to train the ARIMA model, our forecast model reduces computation time up to 92.6 %. It also shows resilience against abrupt network usage changes. Finally, our forecast model conducts the large number of multi-step forecast, and the forecast errors are within the mean absolute deviation (MAD) of the monitored measurements.« less

Monitoring the fall of large atmospheric ice conglomerations: a multianalytical approach to the study of the Mejorada del Campo megacryometeor.

PubMed

Orellana, Francisco Alamilla; Alegre, José Ma Ramiro; Cordero Pérez, José Carlos; Martín Redondo, Ma Paz; Delgado Huertas, Antonio; Fernández Sampedro, Ma Teresa; Menor-Salván, César; Ruiz-Bermejo, Marta; López-Vera, Fernando; Rodríguez-Losada, José A; Martinez-Frias, Jesus

2008-04-01

Certain local atmospheric anomalies, such as the formation of unusually large ice conglomerations (megacryometeors), have been proposed to be a potential natural hazard for people and aviation, as well as geoindicators for fingerprinting larger-scale atmospheric environmental changes. On March 13th 2007, at approximately 10:15 am, an ice chunk weighing about 10 kg fell from the clear-sky and crashed through the roof (around 15 m) of an industrial storage house in Mejorada del Campo, a town located 20 km east from Madrid. The megacryometeor monitoring follow-up and the original investigation presented here includes, for the first time, both logistic and scientific collaboration between the Laboratory of the Environment, Criminalistic Service (SECRIM, the Spanish "Guardia Civil") and academic and scientific institutions (universities and the Spanish National Research Council). We propose that the management procedure of the incident, along with the detailed scientific research and combination of analytical methodologies in different laboratories, can serve as a protocol model for other similar events.

Time-Series Forecast Modeling on High-Bandwidth Network Measurements

DOE PAGES

Yoo, Wucherl; Sim, Alex

2016-06-24

With the increasing number of geographically distributed scientific collaborations and the growing sizes of scientific data, it has become challenging for users to achieve the best possible network performance on a shared network. In this paper, we have developed a model to forecast expected bandwidth utilization on high-bandwidth wide area networks. The forecast model can improve the efficiency of the resource utilization and scheduling of data movements on high-bandwidth networks to accommodate ever increasing data volume for large-scale scientific data applications. A univariate time-series forecast model is developed with the Seasonal decomposition of Time series by Loess (STL) and themore » AutoRegressive Integrated Moving Average (ARIMA) on Simple Network Management Protocol (SNMP) path utilization measurement data. Compared with the traditional approach such as Box-Jenkins methodology to train the ARIMA model, our forecast model reduces computation time up to 92.6 %. It also shows resilience against abrupt network usage changes. Finally, our forecast model conducts the large number of multi-step forecast, and the forecast errors are within the mean absolute deviation (MAD) of the monitored measurements.« less

Upscaling of U (VI) desorption and transport from decimeter‐scale heterogeneity to plume‐scale modeling

USGS Publications Warehouse

Curtis, Gary P.; Kohler, Matthias; Kannappan, Ramakrishnan; Briggs, Martin A.; Day-Lewis, Frederick D.

2015-01-01

Scientifically defensible predictions of field scale U(VI) transport in groundwater requires an understanding of key processes at multiple scales. These scales range from smaller than the sediment grain scale (less than 10 μm) to as large as the field scale which can extend over several kilometers. The key processes that need to be considered include both geochemical reactions in solution and at sediment surfaces as well as physical transport processes including advection, dispersion, and pore-scale diffusion. The research summarized in this report includes both experimental and modeling results in batch, column and tracer tests. The objectives of this research were to: (1) quantify the rates of U(VI) desorption from sediments acquired from a uranium contaminated aquifer in batch experiments;(2) quantify rates of U(VI) desorption in column experiments with variable chemical conditions, and(3) quantify nonreactive tracer and U(VI) transport in field tests.

A Lightweight I/O Scheme to Facilitate Spatial and Temporal Queries of Scientific Data Analytics

NASA Technical Reports Server (NTRS)

Tian, Yuan; Liu, Zhuo; Klasky, Scott; Wang, Bin; Abbasi, Hasan; Zhou, Shujia; Podhorszki, Norbert; Clune, Tom; Logan, Jeremy; Yu, Weikuan

2013-01-01

In the era of petascale computing, more scientific applications are being deployed on leadership scale computing platforms to enhance the scientific productivity. Many I/O techniques have been designed to address the growing I/O bottleneck on large-scale systems by handling massive scientific data in a holistic manner. While such techniques have been leveraged in a wide range of applications, they have not been shown as adequate for many mission critical applications, particularly in data post-processing stage. One of the examples is that some scientific applications generate datasets composed of a vast amount of small data elements that are organized along many spatial and temporal dimensions but require sophisticated data analytics on one or more dimensions. Including such dimensional knowledge into data organization can be beneficial to the efficiency of data post-processing, which is often missing from exiting I/O techniques. In this study, we propose a novel I/O scheme named STAR (Spatial and Temporal AggRegation) to enable high performance data queries for scientific analytics. STAR is able to dive into the massive data, identify the spatial and temporal relationships among data variables, and accordingly organize them into an optimized multi-dimensional data structure before storing to the storage. This technique not only facilitates the common access patterns of data analytics, but also further reduces the application turnaround time. In particular, STAR is able to enable efficient data queries along the time dimension, a practice common in scientific analytics but not yet supported by existing I/O techniques. In our case study with a critical climate modeling application GEOS-5, the experimental results on Jaguar supercomputer demonstrate an improvement up to 73 times for the read performance compared to the original I/O method.

Large-Scale Covariability Between Aerosol and Precipitation Over the 7-SEAS Region: Observations and Simulations

NASA Technical Reports Server (NTRS)

Huang, Jingfeng; Hsu, N. Christina; Tsay, Si-Chee; Zhang, Chidong; Jeong, Myeong Jae; Gautam, Ritesh; Bettenhausen, Corey; Sayer, Andrew M.; Hansell, Richard A.; Liu, Xiaohong;

Investigating large-scale secondary circulations within impact crater topographies in a refractive index-matched facility

NASA Astrophysics Data System (ADS)

Blois, Gianluca; Kim, Taehoon; Bristow, Nathan; Day, Mackenzie; Kocurek, Gary; Anderson, William; Christensen, Kenneth

2017-11-01

Impact craters, common large-scale topographic features on the surface of Mars, are circular depressions delimited by a sharp ridge. A variety of crater fill morphologies exist, suggesting that complex intracrater circulations affect their evolution. Some large craters (diameter >10 km), particularly at mid latitudes on Mars, exhibit a central mound surrounded by circular moat. Foremost among these examples is Gale crater, landing site of NASA's Curiosity rover, since large-scale climatic processes early in in the history of Mars are preserved in the stratigraphic record of the inner mound. Investigating the intracrater flow produced by large scale winds aloft Mars craters is key to a number of important scientific issues including ongoing research on Mars paleo-environmental reconstruction and the planning of future missions (these results must be viewed in conjunction with the affects of radial katabatibc flows, the importance of which is already established in preceding studies). In this work we consider a number of crater shapes inspired by Gale morphology, including idealized craters. Access to the flow field within such geometrically complex topography is achieved herein using a refractive index matched approach. Instantaneous velocity maps, using both planar and volumetric PIV techniques, are presented to elucidate complex three-dimensional flow within the crater. In addition, first- and second-order statistics will be discussed in the context of wind-driven (aeolian) excavation of crater fill.

Neural data science: accelerating the experiment-analysis-theory cycle in large-scale neuroscience.

PubMed

Paninski, L; Cunningham, J P

2018-06-01

Modern large-scale multineuronal recording methodologies, including multielectrode arrays, calcium imaging, and optogenetic techniques, produce single-neuron resolution data of a magnitude and precision that were the realm of science fiction twenty years ago. The major bottlenecks in systems and circuit neuroscience no longer lie in simply collecting data from large neural populations, but also in understanding this data: developing novel scientific questions, with corresponding analysis techniques and experimental designs to fully harness these new capabilities and meaningfully interrogate these questions. Advances in methods for signal processing, network analysis, dimensionality reduction, and optimal control-developed in lockstep with advances in experimental neurotechnology-promise major breakthroughs in multiple fundamental neuroscience problems. These trends are clear in a broad array of subfields of modern neuroscience; this review focuses on recent advances in methods for analyzing neural time-series data with single-neuronal precision. Copyright © 2018 Elsevier Ltd. All rights reserved.

Performance Analysis Tool for HPC and Big Data Applications on Scientific Clusters

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

Yoo, Wucherl; Koo, Michelle; Cao, Yu

Big data is prevalent in HPC computing. Many HPC projects rely on complex workflows to analyze terabytes or petabytes of data. These workflows often require running over thousands of CPU cores and performing simultaneous data accesses, data movements, and computation. It is challenging to analyze the performance involving terabytes or petabytes of workflow data or measurement data of the executions, from complex workflows over a large number of nodes and multiple parallel task executions. To help identify performance bottlenecks or debug the performance issues in large-scale scientific applications and scientific clusters, we have developed a performance analysis framework, using state-ofthe-more » art open-source big data processing tools. Our tool can ingest system logs and application performance measurements to extract key performance features, and apply the most sophisticated statistical tools and data mining methods on the performance data. It utilizes an efficient data processing engine to allow users to interactively analyze a large amount of different types of logs and measurements. To illustrate the functionality of the big data analysis framework, we conduct case studies on the workflows from an astronomy project known as the Palomar Transient Factory (PTF) and the job logs from the genome analysis scientific cluster. Our study processed many terabytes of system logs and application performance measurements collected on the HPC systems at NERSC. The implementation of our tool is generic enough to be used for analyzing the performance of other HPC systems and Big Data workows.« less

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.

The scientific data acquisition system of the GAMMA-400 space project

NASA Astrophysics Data System (ADS)

Bobkov, S. G.; Serdin, O. V.; Gorbunov, M. S.; Arkhangelskiy, A. I.; Topchiev, N. P.

2016-02-01

The description of scientific data acquisition system (SDAS) designed by SRISA for the GAMMA-400 space project is presented. We consider the problem of different level electronics unification: the set of reliable fault-tolerant integrated circuits fabricated on Silicon-on-Insulator 0.25 mkm CMOS technology and the high-speed interfaces and reliable modules used in the space instruments. The characteristics of reliable fault-tolerant very large scale integration (VLSI) technology designed by SRISA for the developing of computation systems for space applications are considered. The scalable net structure of SDAS based on Serial RapidIO interface including real-time operating system BAGET is described too.

Science of science.

PubMed

Fortunato, Santo; Bergstrom, Carl T; Börner, Katy; Evans, James A; Helbing, Dirk; Milojević, Staša; Petersen, Alexander M; Radicchi, Filippo; Sinatra, Roberta; Uzzi, Brian; Vespignani, Alessandro; Waltman, Ludo; Wang, Dashun; Barabási, Albert-László

2018-03-02

Identifying fundamental drivers of science and developing predictive models to capture its evolution are instrumental for the design of policies that can improve the scientific enterprise-for example, through enhanced career paths for scientists, better performance evaluation for organizations hosting research, discovery of novel effective funding vehicles, and even identification of promising regions along the scientific frontier. The science of science uses large-scale data on the production of science to search for universal and domain-specific patterns. Here, we review recent developments in this transdisciplinary field. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Fundamental research in artificial intelligence at NASA

NASA Technical Reports Server (NTRS)

Friedland, Peter

1990-01-01

This paper describes basic research at NASA in the field of artificial intelligence. The work is conducted at the Ames Research Center and the Jet Propulsion Laboratory, primarily under the auspices of the NASA-wide Artificial Intelligence Program in the Office of Aeronautics, Exploration and Technology. The research is aimed at solving long-term NASA problems in missions operations, spacecraft autonomy, preservation of corporate knowledge about NASA missions and vehicles, and management/analysis of scientific and engineering data. From a scientific point of view, the research is broken into the categories of: planning and scheduling; machine learning; and design of and reasoning about large-scale physical systems.

Particle acceleration, transport and turbulence in cosmic and heliospheric physics

NASA Technical Reports Server (NTRS)

Matthaeus, W.

1992-01-01

In this progress report, the long term goals, recent scientific progress, and organizational activities are described. The scientific focus of this annual report is in three areas: first, the physics of particle acceleration and transport, including heliospheric modulation and transport, shock acceleration and galactic propagation and reacceleration of cosmic rays; second, the development of theories of the interaction of turbulence and large scale plasma and magnetic field structures, as in winds and shocks; third, the elucidation of the nature of magnetohydrodynamic turbulence processes and the role such turbulence processes might play in heliospheric, galactic, cosmic ray physics, and other space physics applications.

Axiope tools for data management and data sharing.

PubMed

Goddard, Nigel H; Cannon, Robert C; Howell, Fred W

2003-01-01

Many areas of biological research generate large volumes of very diverse data. Managing this data can be a difficult and time-consuming process, particularly in an academic environment where there are very limited resources for IT support staff such as database administrators. The most economical and efficient solutions are those that enable scientists with minimal IT expertise to control and operate their own desktop systems. Axiope provides one such solution, Catalyzer, which acts as flexible cataloging system for creating structured records describing digital resources. The user is able specify both the content and structure of the information included in the catalog. Information and resources can be shared by a variety of means, including automatically generated sets of web pages. Federation and integration of this information, where needed, is handled by Axiope's Mercat server. Where there is a need for standardization or compatibility of the structures usedby different researchers this canbe achieved later by applying user-defined mappings in Mercat. In this way, large-scale data sharing can be achieved without imposing unnecessary constraints or interfering with the way in which individual scientists choose to record and catalog their work. We summarize the key technical issues involved in scientific data management and data sharing, describe the main features and functionality of Axiope Catalyzer and Axiope Mercat, and discuss future directions and requirements for an information infrastructure to support large-scale data sharing and scientific collaboration.

Studying Radiation Damage in Structural Materials by Using Ion Accelerators

NASA Astrophysics Data System (ADS)

Hosemann, Peter

2011-02-01

Radiation damage in structural materials is of major concern and a limiting factor for a wide range of engineering and scientific applications, including nuclear power production, medical applications, or components for scientific radiation sources. The usefulness of these applications is largely limited by the damage a material can sustain in the extreme environments of radiation, temperature, stress, and fatigue, over long periods of time. Although a wide range of materials has been extensively studied in nuclear reactors and neutron spallation sources since the beginning of the nuclear age, ion beam irradiations using particle accelerators are a more cost-effective alternative to study radiation damage in materials in a rather short period of time, allowing researchers to gain fundamental insights into the damage processes and to estimate the property changes due to irradiation. However, the comparison of results gained from ion beam irradiation, large-scale neutron irradiation, and a variety of experimental setups is not straightforward, and several effects have to be taken into account. It is the intention of this article to introduce the reader to the basic phenomena taking place and to point out the differences between classic reactor irradiations and ion irradiations. It will also provide an assessment of how accelerator-based ion beam irradiation is used today to gain insight into the damage in structural materials for large-scale engineering applications.

NASA's Arctic-Boreal Vulnerability Experiment: A large-scale study of environmental change in Western North America and its implications for ecological systems and society

NASA Astrophysics Data System (ADS)

Kasischke, E. S.; Hayes, D. J.; Griffith, P. C.; Larson, E. K.; Wickland, D. E.

2013-12-01

Climate change in high northern latitudes is unfolding faster than anywhere else on Earth, resulting in widespread changes in landscape structure and ecosystem function in the Arctic-Boreal Region (ABR). Recognizing its sensitivity, vulnerability and global importance, national- and international-level scientific efforts are now advancing our ability to observe, understand and model the complex, multi-scale processes that drive the ABR's natural and social systems. Long at the edge of our mental map of the world, environmental change in the ABR is increasingly becoming the focus of numerous policy discussions at the highest levels of decision-making. To improve our understanding of environmental change and its impacts in the ABR, the Terrestrial Ecology Program of the U.S. National Aeronautics and Space Administration (NASA) is planning its next major field campaign for Western Canada and Alaska. The field campaign will be based on the Arctic-Boreal Vulnerability Experiment (ABoVE) concept as described in the Revised Executive Summary from the ABoVE Scoping Study Report. The original Scoping Study Report provided the proof-of-concept demonstration of scientific importance and feasibility for this large-scale study. In early 2013, NASA announced the selection of the ABoVE Science Definition Team, which is charged with developing the Concise Experiment Plan for the campaign. Here, we outline the conceptual basis for ABoVE and present the compelling rationale explaining the scientific and societal importance of the study. We present the current status of the planning process, which includes development of the science questions to drive ABoVE research; the study design for the field campaign to address them; and the interagency and international collaborations necessary for implementation. The ABoVE study will focus on 1) developing a fuller understanding of ecosystem vulnerability to climate change in the ABR, and 2) providing the scientific information required to develop options for societal responses to the impacts of these changes. The field campaign will emphasize research that integrates data collected by airborne and spaceborne sensors with information obtained from field studies and ground-based observations. Other key components of ABoVE research include the process-level analyses, scientific syntheses, and modeling needed for understanding ecosystem responses and societal implications.

Development and Validation of Scientific Literacy Scale for College Preparedness in STEM with Freshmen from Diverse Institutions

ERIC Educational Resources Information Center

Benjamin, Thomas E.; Marks, Bryant; Demetrikopoulos, Melissa K.; Rose, Jordan; Pollard, Ethen; Thomas, Alicia; Muldrow, Lycurgus L.

2017-01-01

Although a major goal of Science, Technology, Engineering, and Mathematics (STEM) education is to develop scientific literacy, prior efforts at measuring scientific literacy have not attempted to link scientific literacy with success in STEM fields. The current Scientific Literacy Survey for College Preparedness in STEM (SLSCP-STEM) scale was…

The relevance of large scale environmental research infrastructures from the point of view of Ethics: the case of EMSO

NASA Astrophysics Data System (ADS)

Favali, Paolo; Beranzoli, Laura; Best, Mairi; Franceschini, PierLuigi; Materia, Paola; Peppoloni, Silvia; Picard, John

2014-05-01

EMSO (European Multidisciplinary Seafloor and Water Column Observatory) is a large-scale European Research Infrastructure (RI). It is a geographically distributed infrastructure composed of several deep-seafloor and water-column observatories, which will be deployed at key sites in European waters, spanning from the Arctic, through the Atlantic and Mediterranean, to the Black Sea, with the basic scientific objective of real-time, long-term monitoring of environmental processes related to the interaction between the geosphere, biosphere and hydrosphere. EMSO is one of the environmental RIs on the ESFRI roadmap. The ESRFI Roadmap identifies new RIs of pan-European importance that correspond to the long term needs of European research communities. EMSO will be the sub-sea segment of the EU's large-scale Earth Observation program, Copernicus (previously known as GMES - Global Monitoring for Environment and Security) and will significantly enhance the observational capabilities of European member states. An open data policy compliant with the recommendations being developed within the GEOSS initiative (Global Earth Observation System of Systems) will allow for shared use of the infrastructure and the exchange of scientific information and knowledge. The processes that occur in the oceans have a direct impact on human societies, therefore it is crucial to improve our understanding of how they operate and interact. To encompass the breadth of these major processes, sustained and integrated observations are required that appreciate the interconnectedness of atmospheric, surface ocean, biological pump, deep-sea, and solid-Earth dynamics and that can address: • natural and anthropogenic change; • interactions between ecosystem services, biodiversity, biogeochemistry, physics, and climate; • impacts of exploration and extraction of energy, minerals, and living resources; • geo-hazard early warning capability for earthquakes, tsunamis, gas-hydrate release, and slope instability and failure; • connecting scientific outcomes to stakeholders and policy makers, including to government decision-makers. The development of a large research infrastructure initiatives like EMSO must continuously take into account wide-reaching environmental and socio-economic implications and objectives. For this reason, an Ethics Commitee was established early in EMSO's initial Preparatory Phase with responsibility for overseeing the key ethical and social aspects of the project. These include: • promoting inclusive science communication and data dissemination services to civil society according to Open Access principles; • guaranteeing top quality scientific information and data as results of top quality research; • promoting the increased adoption of eco-friendly, sustainable technologies through the dissemination of advanced scientific knowledge and best practices to the private sector and to policy makers; • developing Education Strategies in cooperation with academia and industry aimed at informing and sensitizing the general public on the environmental and socio-economic implications and benefits of large research infrastructure initiatives such as EMSO; • carrying out Excellent Science following strict criteria of research integrity, as expressed in the Montreal Statement (2013); • promoting Geo-ethical awareness and innovation by spurring innovative approaches in the management of environmental aspects of large research projects; • supporting technological Innovation by working closely in support of SMEs; • providing a constant, qualified and authoritative one-stop-shopping Reference Point and Advisory for politicians and decision-makers. The paper shows how Geoethics is an essential tool for guiding methodological and operational choices, and management of an European project with great impact on the environment and society.

Data management strategies for multinational large-scale systems biology projects.

PubMed

Wruck, Wasco; Peuker, Martin; Regenbrecht, Christian R A

2014-01-01

Good accessibility of publicly funded research data is essential to secure an open scientific system and eventually becomes mandatory [Wellcome Trust will Penalise Scientists Who Don't Embrace Open Access. The Guardian 2012]. By the use of high-throughput methods in many research areas from physics to systems biology, large data collections are increasingly important as raw material for research. Here, we present strategies worked out by international and national institutions targeting open access to publicly funded research data via incentives or obligations to share data. Funding organizations such as the British Wellcome Trust therefore have developed data sharing policies and request commitment to data management and sharing in grant applications. Increased citation rates are a profound argument for sharing publication data. Pre-publication sharing might be rewarded by a data citation credit system via digital object identifiers (DOIs) which have initially been in use for data objects. Besides policies and incentives, good practice in data management is indispensable. However, appropriate systems for data management of large-scale projects for example in systems biology are hard to find. Here, we give an overview of a selection of open-source data management systems proved to be employed successfully in large-scale projects.

Data management strategies for multinational large-scale systems biology projects

PubMed Central

Peuker, Martin; Regenbrecht, Christian R.A.

2014-01-01

Good accessibility of publicly funded research data is essential to secure an open scientific system and eventually becomes mandatory [Wellcome Trust will Penalise Scientists Who Don’t Embrace Open Access. The Guardian 2012]. By the use of high-throughput methods in many research areas from physics to systems biology, large data collections are increasingly important as raw material for research. Here, we present strategies worked out by international and national institutions targeting open access to publicly funded research data via incentives or obligations to share data. Funding organizations such as the British Wellcome Trust therefore have developed data sharing policies and request commitment to data management and sharing in grant applications. Increased citation rates are a profound argument for sharing publication data. Pre-publication sharing might be rewarded by a data citation credit system via digital object identifiers (DOIs) which have initially been in use for data objects. Besides policies and incentives, good practice in data management is indispensable. However, appropriate systems for data management of large-scale projects for example in systems biology are hard to find. Here, we give an overview of a selection of open-source data management systems proved to be employed successfully in large-scale projects. PMID:23047157

Software engineering and automatic continuous verification of scientific software

NASA Astrophysics Data System (ADS)

Piggott, M. D.; Hill, J.; Farrell, P. E.; Kramer, S. C.; Wilson, C. R.; Ham, D.; Gorman, G. J.; Bond, T.

2011-12-01

Software engineering of scientific code is challenging for a number of reasons including pressure to publish and a lack of awareness of the pitfalls of software engineering by scientists. The Applied Modelling and Computation Group at Imperial College is a diverse group of researchers that employ best practice software engineering methods whilst developing open source scientific software. Our main code is Fluidity - a multi-purpose computational fluid dynamics (CFD) code that can be used for a wide range of scientific applications from earth-scale mantle convection, through basin-scale ocean dynamics, to laboratory-scale classic CFD problems, and is coupled to a number of other codes including nuclear radiation and solid modelling. Our software development infrastructure consists of a number of free tools that could be employed by any group that develops scientific code and has been developed over a number of years with many lessons learnt. A single code base is developed by over 30 people for which we use bazaar for revision control, making good use of the strong branching and merging capabilities. Using features of Canonical's Launchpad platform, such as code review, blueprints for designing features and bug reporting gives the group, partners and other Fluidity uers an easy-to-use platform to collaborate and allows the induction of new members of the group into an environment where software development forms a central part of their work. The code repositoriy are coupled to an automated test and verification system which performs over 20,000 tests, including unit tests, short regression tests, code verification and large parallel tests. Included in these tests are build tests on HPC systems, including local and UK National HPC services. The testing of code in this manner leads to a continuous verification process; not a discrete event performed once development has ceased. Much of the code verification is done via the "gold standard" of comparisons to analytical solutions via the method of manufactured solutions. By developing and verifying code in tandem we avoid a number of pitfalls in scientific software development and advocate similar procedures for other scientific code applications.

How can research on anthropogenic greenhouse gas flux quantification be better aligned with US climate change policy needs?

NASA Astrophysics Data System (ADS)

Gurney, K. R.

2014-12-01

Scientific research on quantification of anthropogenic greenhouse gas emissions at national and sub-national scales within the US has advanced considerably in the last decade. Large investment has been made in building systems capable of observing greenhouse gases in the atmosphere at multiple scales, measuring direct anthropogenic fluxes near sources and modeling the linkages between fluxes and observed concentrations. Much of this research has been focused at improving the "verification" component of "monitoring, reporting, and verification" and indeed, has achieved successes in recent years. However, there are opportunities for ongoing scientific research to contribute critical new information to policymakers. In order to realize this contribution, additional but complementary, research foci must be emphasized. Examples include more focus on anthropogenic emission drivers, quantification at scales relevant to human decision-making, and exploration of cost versus uncertainty in observing/modeling systems. I will review what I think are the opportunities to better align scientific research with current and emerging US climate change policymaking. I will then explore a few examples of where expansion or alteration of greenhouse gas flux quantification research focus could better align with current and emerging US climate change policymaking such as embodied in the proposed EPA rule aimed at reducing emissions from US power plants, California's ongoing emissions reduction policymaking and aspirational emission reduction efforts in multiple US cities.

Germany wide seasonal flood risk analysis for agricultural crops

NASA Astrophysics Data System (ADS)

Klaus, Stefan; Kreibich, Heidi; Kuhlmann, Bernd; Merz, Bruno; Schröter, Kai

2016-04-01

In recent years, large-scale flood risk analysis and mapping has gained attention. Regional to national risk assessments are needed, for example, for national risk policy developments, for large-scale disaster management planning and in the (re-)insurance industry. Despite increasing requests for comprehensive risk assessments some sectors have not received much scientific attention, one of these is the agricultural sector. In contrast to other sectors, agricultural crop losses depend strongly on the season. Also flood probability shows seasonal variation. Thus, the temporal superposition of high flood susceptibility of crops and high flood probability plays an important role for agricultural flood risk. To investigate this interrelation and provide a large-scale overview of agricultural flood risk in Germany, an agricultural crop loss model is used for crop susceptibility analyses and Germany wide seasonal flood-frequency analyses are undertaken to derive seasonal flood patterns. As a result, a Germany wide map of agricultural flood risk is shown as well as the crop type most at risk in a specific region. The risk maps may provide guidance for federal state-wide coordinated designation of retention areas.

An integrated network of Arabidopsis growth regulators and its use for gene prioritization.

PubMed

Sabaghian, Ehsan; Drebert, Zuzanna; Inzé, Dirk; Saeys, Yvan

2015-12-01

Elucidating the molecular mechanisms that govern plant growth has been an important topic in plant research, and current advances in large-scale data generation call for computational tools that efficiently combine these different data sources to generate novel hypotheses. In this work, we present a novel, integrated network that combines multiple large-scale data sources to characterize growth regulatory genes in Arabidopsis, one of the main plant model organisms. The contributions of this work are twofold: first, we characterized a set of carefully selected growth regulators with respect to their connectivity patterns in the integrated network, and, subsequently, we explored to which extent these connectivity patterns can be used to suggest new growth regulators. Using a large-scale comparative study, we designed new supervised machine learning methods to prioritize growth regulators. Our results show that these methods significantly improve current state-of-the-art prioritization techniques, and are able to suggest meaningful new growth regulators. In addition, the integrated network is made available to the scientific community, providing a rich data source that will be useful for many biological processes, not necessarily restricted to plant growth.

A worldwide analysis of the impact of forest cover change on annual runoff across multiple spatial scales

NASA Astrophysics Data System (ADS)

Zhang, M.; Liu, S.

2017-12-01

Despite extensive studies on hydrological responses to forest cover change in small watersheds, the hydrological responses to forest change and associated mechanisms across multiple spatial scales have not been fully understood. This review thus examined about 312 watersheds worldwide to provide a generalized framework to evaluate hydrological responses to forest cover change and to identify the contribution of spatial scale, climate, forest type and hydrological regime in determining the intensity of forest change related hydrological responses in small (<1000 km2) and large watersheds (≥1000 km2). Key findings include: 1) the increase in annual runoff associated with forest cover loss is statistically significant at multiple spatial scales whereas the effect of forest cover gain is statistically inconsistent; 2) the sensitivity of annual runoff to forest cover change tends to attenuate as watershed size increases only in large watersheds; 3) annual runoff is more sensitive to forest cover change in water-limited watersheds than in energy-limited watersheds across all spatial scales; and 4) small mixed forest-dominated watersheds or large snow-dominated watersheds are more hydrologically resilient to forest cover change. These findings improve the understanding of hydrological response to forest cover change at different spatial scales and provide a scientific underpinning to future watershed management in the context of climate change and increasing anthropogenic disturbances.

Prototype solar house. Study of the scientific evaluation and feasibility of a research and development project

NASA Astrophysics Data System (ADS)

Bundschuh, V.; Grueter, J. W.; Kleemann, M.; Melis, M.; Stein, H. J.; Wagner, H. J.; Dittrich, A.; Pohlmann, D.

1982-08-01

A preliminary study was undertaken before a large scale project for construction and survey of about a hundred solar houses was launched. The notion of solar house was defined and the use of solar energy (hot water preparation, heating of rooms, heating of swimming pool, or a combination of these possibilities) were examined. A coherent measuring program was set up. Advantages and inconveniences of the large scale project were reviewed. Production of hot water, evaluation of different concepts and different fabrications of solar systems, coverage of the different systems, conservation of energy, failure frequency and failures statistics, durability of the installation, investment maintenance and energy costs were retained as study parameters. Different solar hot water production systems and the heat counter used for measurements are described.

Chemical Warfare and Medical Response During World War I

PubMed Central

Fitzgerald, Gerard J.

2008-01-01

The first large-scale use of a traditional weapon of mass destruction (chemical, biological, or nuclear) involved the successful deployment of chemical weapons during World War I (1914–1918). Historians now refer to the Great War as the chemist’s war because of the scientific and engineering mobilization efforts by the major belligerents. The development, production, and deployment of war gases such as chlorine, phosgene, and mustard created a new and complex public health threat that endangered not only soldiers and civilians on the battlefield but also chemical workers on the home front involved in the large-scale manufacturing processes. The story of chemical weapons research and development during that war provides useful insights for current public health practitioners faced with a possible chemical weapons attack against civilian or military populations. PMID:18356568

Perspective: Markov models for long-timescale biomolecular dynamics.

PubMed

Schwantes, C R; McGibbon, R T; Pande, V S

2014-09-07

Molecular dynamics simulations have the potential to provide atomic-level detail and insight to important questions in chemical physics that cannot be observed in typical experiments. However, simply generating a long trajectory is insufficient, as researchers must be able to transform the data in a simulation trajectory into specific scientific insights. Although this analysis step has often been taken for granted, it deserves further attention as large-scale simulations become increasingly routine. In this perspective, we discuss the application of Markov models to the analysis of large-scale biomolecular simulations. We draw attention to recent improvements in the construction of these models as well as several important open issues. In addition, we highlight recent theoretical advances that pave the way for a new generation of models of molecular kinetics.

Chemical warfare and medical response during World War I.

PubMed

Fitzgerald, Gerard J

2008-04-01

The first large-scale use of a traditional weapon of mass destruction (chemical, biological, or nuclear) involved the successful deployment of chemical weapons during World War I (1914-1918). Historians now refer to the Great War as the chemist's war because of the scientific and engineering mobilization efforts by the major belligerents. The development, production, and deployment of war gases such as chlorine, phosgene, and mustard created a new and complex public health threat that endangered not only soldiers and civilians on the battlefield but also chemical workers on the home front involved in the large-scale manufacturing processes. The story of chemical weapons research and development during that war provides useful insights for current public health practitioners faced with a possible chemical weapons attack against civilian or military populations.

Mountain pine beetle, a major disturbance agent in US western coniferous forests: A synthesis of the state of knowledge

Treesearch

Jose F. Negron; Christopher J. Fettig

2014-01-01

It is well documented in the scientific and popular literature that large-scale bark beetle outbreaks are occurring across many coniferous forests in the western United States. One of the major species exhibiting extensive eruptive populations resulting in high levels of tree mortality is the mountain pine beetle, Dendroctonus ponderosae (Hopkins) (Negron et al. 2008...

Designing Leadership and Soft Skills in Educational Games: The e-Leadership and Soft Skills Educational Games Design Model (ELESS)

ERIC Educational Resources Information Center

Freitas, Sara; Routledge, Helen

2013-01-01

While the field of leadership studies includes a large corpus of literature and studies, the literature and scientific research in the field of e-leadership and soft skills used in learning game environments are at present small in scale. Towards contributing to this newly emerging field of literature and study, this research paper presents a new…

RELIABILITY, AVAILABILITY, AND SERVICEABILITY FOR PETASCALE HIGH-END COMPUTING AND BEYOND

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

Chokchai "Box" Leangsuksun

2011-05-31

Our project is a multi-institutional research effort that adopts interplay of RELIABILITY, AVAILABILITY, and SERVICEABILITY (RAS) aspects for solving resilience issues in highend scientific computing in the next generation of supercomputers. results lie in the following tracks: Failure prediction in a large scale HPC; Investigate reliability issues and mitigation techniques including in GPGPU-based HPC system; HPC resilience runtime & tools.

PETSc Users Manual Revision 3.7

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

Balay, Satish; Abhyankar, S.; Adams, M.

This manual describes the use of PETSc for the numerical solution of partial differential equations and related problems on high-performance computers. The Portable, Extensible Toolkit for Scientific Computation (PETSc) is a suite of data structures and routines that provide the building blocks for the implementation of large-scale application codes on parallel (and serial) computers. PETSc uses the MPI standard for all message-passing communication.

The Influence of Large-Scale Computing on Aircraft Structural Design.

DTIC Science & Technology

1986-04-01

the customer in the most cost- effective manner. Computer facility organizations became computer resource power brokers. A good data processing...capabilities generated on other processors can be easily used. This approach is easily implementable and provides a good strategy for using existing...assistance to member nations for the purpose of increasing their scientific and technical potential; - Recommending effective ways for the member nations to

PETSc Users Manual Revision 3.8

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

Balay, S.; Abhyankar, S.; Adams, M.

This manual describes the use of PETSc for the numerical solution of partial differential equations and related problems on high-performance computers. The Portable, Extensible Toolkit for Scientific Computation (PETSc) is a suite of data structures and routines that provide the building blocks for the implementation of large-scale application codes on parallel (and serial) computers. PETSc uses the MPI standard for all message-passing communication.

Cluster Randomized Trial of a Large-Scale Education Initiative in the Democratic Republic of Congo: Baseline Findings and Lessons

ERIC Educational Resources Information Center

Aber, John Lawrence; Torrente, Catalina; Annan, Jeannie; Bundervoet, Tom; Shivshanker, Anjuli

2012-01-01

The main purpose of the current paper is to describe and discuss the scientific and practical implications of pursuing rigorous developmental research in a low-income, war-afflicted country such as DRC. In addition, the paper aims to explore the individual, household and school correlates of children's academic performance and mental health and…

Evidence and AIDS activism: HIV scale-up and the contemporary politics of knowledge in global public health

PubMed Central

Colvin, Christopher J.

2014-01-01

The HIV epidemic is widely recognised as having prompted one of the most remarkable intersections ever of illness, science and activism. The production, circulation, use and evaluation of empirical scientific ‘evidence’ played a central part in activists’ engagement with AIDS science. Previous activist engagement with evidence focused on the social and biomedical responses to HIV in the global North as well as challenges around ensuring antiretroviral treatment (ART) was available in the global South. More recently, however, with the roll-out and scale-up of large public-sector ART programmes and new multi-dimensional prevention efforts, the relationships between evidence and activism have been changing. Scale-up of these large-scale treatment and prevention programmes represents an exciting new opportunity while bringing with it a host of new challenges. This paper examines what new forms of evidence and activism will be required to address the challenges of the scaling-up era of HIV treatment and prevention. It reviews some recent controversies around evidence and HIV scale-up and describes the different forms of evidence and activist strategies that will be necessary for a robust response to these new challenges. PMID:24498918

Using CyberShake Workflows to Manage Big Seismic Hazard Data on Large-Scale Open-Science HPC Resources

NASA Astrophysics Data System (ADS)

Callaghan, S.; Maechling, P. J.; Juve, G.; Vahi, K.; Deelman, E.; Jordan, T. H.

2015-12-01

The CyberShake computational platform, developed by the Southern California Earthquake Center (SCEC), is an integrated collection of scientific software and middleware that performs 3D physics-based probabilistic seismic hazard analysis (PSHA) for Southern California. CyberShake integrates large-scale and high-throughput research codes to produce probabilistic seismic hazard curves for individual locations of interest and hazard maps for an entire region. A recent CyberShake calculation produced about 500,000 two-component seismograms for each of 336 locations, resulting in over 300 million synthetic seismograms in a Los Angeles-area probabilistic seismic hazard model. CyberShake calculations require a series of scientific software programs. Early computational stages produce data used as inputs by later stages, so we describe CyberShake calculations using a workflow definition language. Scientific workflow tools automate and manage the input and output data and enable remote job execution on large-scale HPC systems. To satisfy the requests of broad impact users of CyberShake data, such as seismologists, utility companies, and building code engineers, we successfully completed CyberShake Study 15.4 in April and May 2015, calculating a 1 Hz urban seismic hazard map for Los Angeles. We distributed the calculation between the NSF Track 1 system NCSA Blue Waters, the DOE Leadership-class system OLCF Titan, and USC's Center for High Performance Computing. This study ran for over 5 weeks, burning about 1.1 million node-hours and producing over half a petabyte of data. The CyberShake Study 15.4 results doubled the maximum simulated seismic frequency from 0.5 Hz to 1.0 Hz as compared to previous studies, representing a factor of 16 increase in computational complexity. We will describe how our workflow tools supported splitting the calculation across multiple systems. We will explain how we modified CyberShake software components, including GPU implementations and migrating from file-based communication to MPI messaging, to greatly reduce the I/O demands and node-hour requirements of CyberShake. We will also present performance metrics from CyberShake Study 15.4, and discuss challenges that producers of Big Data on open-science HPC resources face moving forward.

Establishment of a National Wind Energy Center at University of Houston

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

Wang, Su Su

The DOE-supported project objectives are to: establish a national wind energy center (NWEC) at University of Houston and conduct research to address critical science and engineering issues for the development of future large MW-scale wind energy production systems, especially offshore wind turbines. The goals of the project are to: (1) establish a sound scientific/technical knowledge base of solutions to critical science and engineering issues for developing future MW-scale large wind energy production systems, (2) develop a state-of-the-art wind rotor blade research facility at the University of Houston, and (3) through multi-disciplinary research, introducing technology innovations on advanced wind-turbine materials, processing/manufacturingmore » technology, design and simulation, testing and reliability assessment methods related to future wind turbine systems for cost-effective production of offshore wind energy. To achieve the goals of the project, the following technical tasks were planned and executed during the period from April 15, 2010 to October 31, 2014 at the University of Houston: (1) Basic research on large offshore wind turbine systems (2) Applied research on innovative wind turbine rotors for large offshore wind energy systems (3) Integration of offshore wind-turbine design, advanced materials and manufacturing technologies (4) Integrity and reliability of large offshore wind turbine blades and scaled model testing (5) Education and training of graduate and undergraduate students and post- doctoral researchers (6) Development of a national offshore wind turbine blade research facility The research program addresses both basic science and engineering of current and future large wind turbine systems, especially offshore wind turbines, for MW-scale power generation. The results of the research advance current understanding of many important scientific issues and provide technical information for solving future large wind turbines with advanced design, composite materials, integrated manufacturing, and structural reliability and integrity. The educational program have trained many graduate and undergraduate students and post-doctoral level researchers to learn critical science and engineering of wind energy production systems through graduate-level courses and research, and participating in various projects in center’s large multi-disciplinary research. These students and researchers are now employed by the wind industry, national labs and universities to support the US and international wind energy industry. The national offshore wind turbine blade research facility developed in the project has been used to support the technical and training tasks planned in the program to accomplish their goals, and it is a national asset which is available for used by domestic and international researchers in the wind energy arena.« less

Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT)

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

Williams, Dean N.; Silva, Claudio

2013-09-30

For the past three years, a large analysis and visualization effort—funded by the Department of Energy’s Office of Biological and Environmental Research (BER), the National Aeronautics and Space Administration (NASA), and the National Oceanic and Atmospheric Administration (NOAA)—has brought together a wide variety of industry-standard scientific computing libraries and applications to create Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT) to serve the global climate simulation and observational research communities. To support interactive analysis and visualization, all components connect through a provenance application–programming interface to capture meaningful history and workflow. Components can be loosely coupled into the framework for fast integrationmore » or tightly coupled for greater system functionality and communication with other components. The overarching goal of UV-CDAT is to provide a new paradigm for access to and analysis of massive, distributed scientific data collections by leveraging distributed data architectures located throughout the world. The UV-CDAT framework addresses challenges in analysis and visualization and incorporates new opportunities, including parallelism for better efficiency, higher speed, and more accurate scientific inferences. Today, it provides more than 600 users access to more analysis and visualization products than any other single source.« less

An analysis of South African Grade 9 natural sciences textbooks for their representation of nature of science

NASA Astrophysics Data System (ADS)

Dewnarain Ramnarain, Umesh; Chanetsa, Tarisai

2016-04-01

This article reports on an analysis and comparison of three South African Grade 9 (13-14 years) Natural Sciences textbooks for the representation of nature of science (NOS). The analysis was framed by an analytical tool developed and validated by Abd-El-Khalick and a team of researchers in a large-scale study on the high school textbooks in the USA. The three textbooks were scored on targeted NOS aspects on a scale of -3 to +3 that reflected the explicitness with which these aspects were addressed. The analysis revealed that the textbooks poorly depict NOS, and in particular, there was scant attention given to the social dimension of science, science versus pseudoscience and the 'myth of the scientific method'. The findings of this study are incommensurate with the strong emphasis in a reformed school science curriculum that underlies the need for learners to understand the scientific enterprise, and how scientific knowledge develops. In view of this, the findings of this research reinforce the need for a review on the mandate given to textbook publishers and writers so that a stronger focus be placed on the development of materials that better represent the tenets of NOS.

MicroEcos: Micro-Scale Explorations of Large-Scale Late Pleistocene Ecosystems

NASA Astrophysics Data System (ADS)

Gellis, B. S.

2017-12-01

Pollen data can inform the reconstruction of early-floral environments by providing data for artistic representations of what early-terrestrial ecosystems looked like, and how existing terrestrial landscapes have evolved. For example, what did the Bighorn Basin look like when large ice sheets covered modern Canada, the Yellowstone Plateau had an ice cap, and the Bighorn Mountains were mantled with alpine glaciers? MicroEcos is an immersive, multimedia project that aims to strengthen human-nature connections through the understanding and appreciation of biological ecosystems. Collected pollen data elucidates flora that are visible in the fossil record - associated with the Late-Pleistocene - and have been illustrated and described in botanical literature. It aims to make scientific data accessible and interesting to all audiences through a series of interactive-digital sculptures, large-scale photography and field-based videography. While this project is driven by scientific data, it is rooted in deeply artistic and outreach-based practices, which include broad artistic practices, e.g.: digital design, illustration, photography, video and sound design. Using 3D modeling and printing technology MicroEcos centers around a series of 3D-printed models of the Last Canyon rock shelter on the Wyoming and Montana border, Little Windy Hill pond site in Wyoming's Medicine Bow National Forest, and Natural Trap Cave site in Wyoming's Big Horn Basin. These digital, interactive-3D sculpture provide audiences with glimpses of three-dimensional Late-Pleistocene environments, and helps create dialogue of how grass, sagebrush, and spruce based ecosystems form. To help audiences better contextualize how MicroEcos bridges notions of time, space, and place, modern photography and videography of the Last Canyon, Little Windy Hill and Natural Trap Cave sites surround these 3D-digital reconstructions.

John R. Delaney Receives 2012 Athelstan Spilhaus Award: Response

NASA Astrophysics Data System (ADS)

Delaney, John R.

2013-01-01

It is humbling and exhilarating to be honored as this year's recipient of the Spilhaus Award. Humbling because Athelstan himself set the standard as a highly productive scientific innovator with a gift for making science not just accessible but engaging to the public at large. Exhilarating because we are all now poised on the threshold of being able to achieve universal scientific engagement with a global audience. Rapidly emerging technologies, global societal problems, shifting international attitudes, and novel social media are converging to power a new paradigm of scientific inquiry and engagement. Scientists are now enabled to operate transparently on a stage of planetary to microscopic scale. The boundaries between research and education begin to blur as this convergence embraces scientific investigation, the arts, the environment, the economy, ethics, energy, health, and entertainment. It is into this complex cultural tapestry that we scientists must weave our stories of struggle and success to engage entire communities in the essential roles that science, technology, and people play.

Big data analytics workflow management for eScience

NASA Astrophysics Data System (ADS)

Fiore, Sandro; D'Anca, Alessandro; Palazzo, Cosimo; Elia, Donatello; Mariello, Andrea; Nassisi, Paola; Aloisio, Giovanni

2015-04-01

In many domains such as climate and astrophysics, scientific data is often n-dimensional and requires tools that support specialized data types and primitives if it is to be properly stored, accessed, analysed and visualized. Currently, scientific data analytics relies on domain-specific software and libraries providing a huge set of operators and functionalities. However, most of these software fail at large scale since they: (i) are desktop based, rely on local computing capabilities and need the data locally; (ii) cannot benefit from available multicore/parallel machines since they are based on sequential codes; (iii) do not provide declarative languages to express scientific data analysis tasks, and (iv) do not provide newer or more scalable storage models to better support the data multidimensionality. Additionally, most of them: (v) are domain-specific, which also means they support a limited set of data formats, and (vi) do not provide a workflow support, to enable the construction, execution and monitoring of more complex "experiments". The Ophidia project aims at facing most of the challenges highlighted above by providing a big data analytics framework for eScience. Ophidia provides several parallel operators to manipulate large datasets. Some relevant examples include: (i) data sub-setting (slicing and dicing), (ii) data aggregation, (iii) array-based primitives (the same operator applies to all the implemented UDF extensions), (iv) data cube duplication, (v) data cube pivoting, (vi) NetCDF-import and export. Metadata operators are available too. Additionally, the Ophidia framework provides array-based primitives to perform data sub-setting, data aggregation (i.e. max, min, avg), array concatenation, algebraic expressions and predicate evaluation on large arrays of scientific data. Bit-oriented plugins have also been implemented to manage binary data cubes. Defining processing chains and workflows with tens, hundreds of data analytics operators is the real challenge in many practical scientific use cases. This talk will specifically address the main needs, requirements and challenges regarding data analytics workflow management applied to large scientific datasets. Three real use cases concerning analytics workflows for sea situational awareness, fire danger prevention, climate change and biodiversity will be discussed in detail.

Darwin the scientist.

PubMed

Browne, J

2009-01-01

Charles Darwin's experimental investigations show him to have been a superb practical researcher. These skills are often underestimated today when assessing Darwin's achievement in the Origin of Species and his other books. Supported by a private income, he turned his house and gardens into a Victorian equivalent of a modern research station. Darwin participated actively in the exchange of scientific information via letters and much of his research was also carried out through correspondence. Although this research was relatively small scale in practice, it was large scale in intellectual scope. Darwin felt he had a strong desire to understand or explain whatever he observed.

Approaches for advancing scientific understanding of macrosystems

USGS Publications Warehouse

Levy, Ofir; Ball, Becky A.; Bond-Lamberty, Ben; Cheruvelil, Kendra S.; Finley, Andrew O.; Lottig, Noah R.; Surangi W. Punyasena,; Xiao, Jingfeng; Zhou, Jizhong; Buckley, Lauren B.; Filstrup, Christopher T.; Keitt, Tim H.; Kellner, James R.; Knapp, Alan K.; Richardson, Andrew D.; Tcheng, David; Toomey, Michael; Vargas, Rodrigo; Voordeckers, James W.; Wagner, Tyler; Williams, John W.

2014-01-01

The emergence of macrosystems ecology (MSE), which focuses on regional- to continental-scale ecological patterns and processes, builds upon a history of long-term and broad-scale studies in ecology. Scientists face the difficulty of integrating the many elements that make up macrosystems, which consist of hierarchical processes at interacting spatial and temporal scales. Researchers must also identify the most relevant scales and variables to be considered, the required data resources, and the appropriate study design to provide the proper inferences. The large volumes of multi-thematic data often associated with macrosystem studies typically require validation, standardization, and assimilation. Finally, analytical approaches need to describe how cross-scale and hierarchical dynamics and interactions relate to macroscale phenomena. Here, we elaborate on some key methodological challenges of MSE research and discuss existing and novel approaches to meet them.

Beowulf Distributed Processing and the United States Geological Survey

USGS Publications Warehouse

Maddox, Brian G.

2002-01-01

Introduction In recent years, the United States Geological Survey's (USGS) National Mapping Discipline (NMD) has expanded its scientific and research activities. Work is being conducted in areas such as emergency response research, scientific visualization, urban prediction, and other simulation activities. Custom-produced digital data have become essential for these types of activities. High-resolution, remotely sensed datasets are also seeing increased use. Unfortunately, the NMD is also finding that it lacks the resources required to perform some of these activities. Many of these projects require large amounts of computer processing resources. Complex urban-prediction simulations, for example, involve large amounts of processor-intensive calculations on large amounts of input data. This project was undertaken to learn and understand the concepts of distributed processing. Experience was needed in developing these types of applications. The idea was that this type of technology could significantly aid the needs of the NMD scientific and research programs. Porting a numerically intensive application currently being used by an NMD science program to run in a distributed fashion would demonstrate the usefulness of this technology. There are several benefits that this type of technology can bring to the USGS's research programs. Projects can be performed that were previously impossible due to a lack of computing resources. Other projects can be performed on a larger scale than previously possible. For example, distributed processing can enable urban dynamics research to perform simulations on larger areas without making huge sacrifices in resolution. The processing can also be done in a more reasonable amount of time than with traditional single-threaded methods (a scaled version of Chester County, Pennsylvania, took about fifty days to finish its first calibration phase with a single-threaded program). This paper has several goals regarding distributed processing technology. It will describe the benefits of the technology. Real data about a distributed application will be presented as an example of the benefits that this technology can bring to USGS scientific programs. Finally, some of the issues with distributed processing that relate to USGS work will be discussed.

Optimizing CyberShake Seismic Hazard Workflows for Large HPC Resources

NASA Astrophysics Data System (ADS)

Callaghan, S.; Maechling, P. J.; Juve, G.; Vahi, K.; Deelman, E.; Jordan, T. H.

2014-12-01

The CyberShake computational platform is a well-integrated collection of scientific software and middleware that calculates 3D simulation-based probabilistic seismic hazard curves and hazard maps for the Los Angeles region. Currently each CyberShake model comprises about 235 million synthetic seismograms from about 415,000 rupture variations computed at 286 sites. CyberShake integrates large-scale parallel and high-throughput serial seismological research codes into a processing framework in which early stages produce files used as inputs by later stages. Scientific workflow tools are used to manage the jobs, data, and metadata. The Southern California Earthquake Center (SCEC) developed the CyberShake platform using USC High Performance Computing and Communications systems and open-science NSF resources.CyberShake calculations were migrated to the NSF Track 1 system NCSA Blue Waters when it became operational in 2013, via an interdisciplinary team approach including domain scientists, computer scientists, and middleware developers. Due to the excellent performance of Blue Waters and CyberShake software optimizations, we reduced the makespan (a measure of wallclock time-to-solution) of a CyberShake study from 1467 to 342 hours. We will describe the technical enhancements behind this improvement, including judicious introduction of new GPU software, improved scientific software components, increased workflow-based automation, and Blue Waters-specific workflow optimizations.Our CyberShake performance improvements highlight the benefits of scientific workflow tools. The CyberShake workflow software stack includes the Pegasus Workflow Management System (Pegasus-WMS, which includes Condor DAGMan), HTCondor, and Globus GRAM, with Pegasus-mpi-cluster managing the high-throughput tasks on the HPC resources. The workflow tools handle data management, automatically transferring about 13 TB back to SCEC storage.We will present performance metrics from the most recent CyberShake study, executed on Blue Waters. We will compare the performance of CPU and GPU versions of our large-scale parallel wave propagation code, AWP-ODC-SGT. Finally, we will discuss how these enhancements have enabled SCEC to move forward with plans to increase the CyberShake simulation frequency to 1.0 Hz.

PREDON Scientific Data Preservation 2014

NASA Astrophysics Data System (ADS)

Diaconu, C.; Kraml, S.; Surace, C.; Chateigner, D.; Libourel, T.; Laurent, A.; Lin, Y.; Schaming, M.; Benbernou, S.; Lebbah, M.; Boucon, D.; Cérin, C.; Azzag, H.; Mouron, P.; Nief, J.-Y.; Coutin, S.; Beckmann, V.

Scientific data collected with modern sensors or dedicated detectors exceed very often the perimeter of the initial scientific design. These data are obtained more and more frequently with large material and human efforts. A large class of scientific experiments are in fact unique because of their large scale, with very small chances to be repeated and to superseded by new experiments in the same domain: for instance high energy physics and astrophysics experiments involve multi-annual developments and a simple duplication of efforts in order to reproduce old data is simply not affordable. Other scientific experiments are in fact unique by nature: earth science, medical sciences etc. since the collected data is "time-stamped" and thereby non-reproducible by new experiments or observations. In addition, scientific data collection increased dramatically in the recent years, participating to the so-called "data deluge" and inviting for common reflection in the context of "big data" investigations. The new knowledge obtained using these data should be preserved long term such that the access and the re-use are made possible and lead to an enhancement of the initial investment. Data observatories, based on open access policies and coupled with multi-disciplinary techniques for indexing and mining may lead to truly new paradigms in science. It is therefore of outmost importance to pursue a coherent and vigorous approach to preserve the scientific data at long term. The preservation remains nevertheless a challenge due to the complexity of the data structure, the fragility of the custom-made software environments as well as the lack of rigorous approaches in workflows and algorithms. To address this challenge, the PREDON project has been initiated in France in 2012 within the MASTODONS program: a Big Data scientific challenge, initiated and supported by the Interdisciplinary Mission of the National Centre for Scientific Research (CNRS). PREDON is a study group formed by researchers from different disciplines and institutes. Several meetings and workshops lead to a rich exchange in ideas, paradigms and methods. The present document includes contributions of the participants to the PREDON Study Group, as well as invited papers, related to the scientific case, methodology and technology. This document should be read as a "facts finding" resource pointing to a concrete and significant scientific interest for long term research data preservation, as well as to cutting edge methods and technologies to achieve this goal. A sustained, coherent and long term action in the area of scientific data preservation would be highly beneficial.

Mathematical and Computational Challenges in Population Biology and Ecosystems Science

NASA Technical Reports Server (NTRS)

Levin, Simon A.; Grenfell, Bryan; Hastings, Alan; Perelson, Alan S.

1997-01-01

Mathematical and computational approaches provide powerful tools in the study of problems in population biology and ecosystems science. The subject has a rich history intertwined with the development of statistics and dynamical systems theory, but recent analytical advances, coupled with the enhanced potential of high-speed computation, have opened up new vistas and presented new challenges. Key challenges involve ways to deal with the collective dynamics of heterogeneous ensembles of individuals, and to scale from small spatial regions to large ones. The central issues-understanding how detail at one scale makes its signature felt at other scales, and how to relate phenomena across scales-cut across scientific disciplines and go to the heart of algorithmic development of approaches to high-speed computation. Examples are given from ecology, genetics, epidemiology, and immunology.

Uvf - Unified Volume Format: A General System for Efficient Handling of Large Volumetric Datasets.

PubMed

Krüger, Jens; Potter, Kristin; Macleod, Rob S; Johnson, Christopher

2008-01-01

With the continual increase in computing power, volumetric datasets with sizes ranging from only a few megabytes to petascale are generated thousands of times per day. Such data may come from an ordinary source such as simple everyday medical imaging procedures, while larger datasets may be generated from cluster-based scientific simulations or measurements of large scale experiments. In computer science an incredible amount of work worldwide is put into the efficient visualization of these datasets. As researchers in the field of scientific visualization, we often have to face the task of handling very large data from various sources. This data usually comes in many different data formats. In medical imaging, the DICOM standard is well established, however, most research labs use their own data formats to store and process data. To simplify the task of reading the many different formats used with all of the different visualization programs, we present a system for the efficient handling of many types of large scientific datasets (see Figure 1 for just a few examples). While primarily targeted at structured volumetric data, UVF can store just about any type of structured and unstructured data. The system is composed of a file format specification with a reference implementation of a reader. It is not only a common, easy to implement format but also allows for efficient rendering of most datasets without the need to convert the data in memory.

Demonstration-Scale High-Cell-Density Fermentation of Pichia pastoris.

PubMed

Liu, Wan-Cang; Zhu, Ping

2018-01-01

Pichia pastoris has been one of the most successful heterologous overexpression systems in generating proteins for large-scale production through high-cell-density fermentation. However, optimizing conditions of the large-scale high-cell-density fermentation for biochemistry and industrialization is usually a laborious and time-consuming process. Furthermore, it is often difficult to produce authentic proteins in large quantities, which is a major obstacle for functional and structural features analysis and industrial application. For these reasons, we have developed a protocol for efficient demonstration-scale high-cell-density fermentation of P. pastoris, which employs a new methanol-feeding strategy-biomass-stat strategy and a strategy of increased air pressure instead of pure oxygen supplement. The protocol included three typical stages of glycerol batch fermentation (initial culture phase), glycerol fed-batch fermentation (biomass accumulation phase), and methanol fed-batch fermentation (induction phase), which allows direct online-monitoring of fermentation conditions, including broth pH, temperature, DO, anti-foam generation, and feeding of glycerol and methanol. Using this protocol, production of the recombinant β-xylosidase of Lentinula edodes origin in 1000-L scale fermentation can be up to ~900 mg/L or 9.4 mg/g cells (dry cell weight, intracellular expression), with the specific production rate and average specific production of 0.1 mg/g/h and 0.081 mg/g/h, respectively. The methodology described in this protocol can be easily transferred to other systems, and eligible to scale up for a large number of proteins used in either the scientific studies or commercial purposes.

The Ophidia Stack: Toward Large Scale, Big Data Analytics Experiments for Climate Change

NASA Astrophysics Data System (ADS)

Fiore, S.; Williams, D. N.; D'Anca, A.; Nassisi, P.; Aloisio, G.

2015-12-01

The Ophidia project is a research effort on big data analytics facing scientific data analysis challenges in multiple domains (e.g. climate change). It provides a "datacube-oriented" framework responsible for atomically processing and manipulating scientific datasets, by providing a common way to run distributive tasks on large set of data fragments (chunks). Ophidia provides declarative, server-side, and parallel data analysis, jointly with an internal storage model able to efficiently deal with multidimensional data and a hierarchical data organization to manage large data volumes. The project relies on a strong background on high performance database management and On-Line Analytical Processing (OLAP) systems to manage large scientific datasets. The Ophidia analytics platform provides several data operators to manipulate datacubes (about 50), and array-based primitives (more than 100) to perform data analysis on large scientific data arrays. To address interoperability, Ophidia provides multiple server interfaces (e.g. OGC-WPS). From a client standpoint, a Python interface enables the exploitation of the framework into Python-based eco-systems/applications (e.g. IPython) and the straightforward adoption of a strong set of related libraries (e.g. SciPy, NumPy). The talk will highlight a key feature of the Ophidia framework stack: the "Analytics Workflow Management System" (AWfMS). The Ophidia AWfMS coordinates, orchestrates, optimises and monitors the execution of multiple scientific data analytics and visualization tasks, thus supporting "complex analytics experiments". Some real use cases related to the CMIP5 experiment will be discussed. In particular, with regard to the "Climate models intercomparison data analysis" case study proposed in the EU H2020 INDIGO-DataCloud project, workflows related to (i) anomalies, (ii) trend, and (iii) climate change signal analysis will be presented. Such workflows will be distributed across multiple sites - according to the datasets distribution - and will include intercomparison, ensemble, and outlier analysis. The two-level workflow solution envisioned in INDIGO (coarse grain for distributed tasks orchestration, and fine grain, at the level of a single data analytics cluster instance) will be presented and discussed.

Connecting Humans and Water: The Case for Coordinated Data Collection

NASA Astrophysics Data System (ADS)

Braden, J. B.; Brown, D. G.; Jolejole-Foreman, C.; Maidment, D. R.; Marquart-Pyatt, S. T.; Schneider, D. W.

2012-12-01

"Water problems" are fundamentally human problems -- aligning water quality and quantity with human aspirations. In the U.S., however, the few ongoing efforts to repeatedly observe humans in relation to water at large scale are disjointed both with each other and with observing systems for water quality and quantity. This presentation argues for the systematic, coordinated, and on-going collection of primary data on humans, spanning beliefs, perceptions, behaviors, and institutions, alongside the water environments in which they are embedded. Such an enterprise would advance not only water science and related policy and management decisions, but also generate basic insights into human cognition, decision making, and institutional development as they relate to the science of sustainability. In support of this argument, two types of original analyses are presented. First, two case studies using existing data sets illustrate methodological issues involved in integrating natural system data with social data at large scale: one concerns the influence of water quality conditions on personal efforts to conserve water and contribute financially to environmental protection; the other explores relationships between recreation behavior and water quality. Both case studies show how methodological differences between data programs seriously undercut the potential to draw inference about human responses to water quality while also illustrating the scientific potential that could be realized from linking human and scientific surveys of the water environment. Second, the results of a survey of water scientists concerning important scientific and policy questions around humans and water provide insight into data collection priorities for a coordinated program of observation.

The prospect of modern thermomechanics in structural integrity calculations of large-scale pressure vessels

NASA Astrophysics Data System (ADS)

Fekete, Tamás

2018-05-01

Structural integrity calculations play a crucial role in designing large-scale pressure vessels. Used in the electric power generation industry, these kinds of vessels undergo extensive safety analyses and certification procedures before deemed feasible for future long-term operation. The calculations are nowadays directed and supported by international standards and guides based on state-of-the-art results of applied research and technical development. However, their ability to predict a vessel's behavior under accidental circumstances after long-term operation is largely limited by the strong dependence of the analysis methodology on empirical models that are correlated to the behavior of structural materials and their changes during material aging. Recently a new scientific engineering paradigm, structural integrity has been developing that is essentially a synergistic collaboration between a number of scientific and engineering disciplines, modeling, experiments and numerics. Although the application of the structural integrity paradigm highly contributed to improving the accuracy of safety evaluations of large-scale pressure vessels, the predictive power of the analysis methodology has not yet improved significantly. This is due to the fact that already existing structural integrity calculation methodologies are based on the widespread and commonly accepted 'traditional' engineering thermal stress approach, which is essentially based on the weakly coupled model of thermomechanics and fracture mechanics. Recently, a research has been initiated in MTA EK with the aim to review and evaluate current methodologies and models applied in structural integrity calculations, including their scope of validity. The research intends to come to a better understanding of the physical problems that are inherently present in the pool of structural integrity problems of reactor pressure vessels, and to ultimately find a theoretical framework that could serve as a well-grounded theoretical foundation for a new modeling framework of structural integrity. This paper presents the first findings of the research project.

The roles of integration in molecular systems biology.

PubMed

O'Malley, Maureen A; Soyer, Orkun S

2012-03-01

A common way to think about scientific practice involves classifying it as hypothesis- or data-driven. We argue that although such distinctions might illuminate scientific practice very generally, they are not sufficient to understand the day-to-day dynamics of scientific activity and the development of programmes of research. One aspect of everyday scientific practice that is beginning to gain more attention is integration. This paper outlines what is meant by this term and how it has been discussed from scientific and philosophical points of view. We focus on methodological, data and explanatory integration, and show how they are connected. Then, using some examples from molecular systems biology, we will show how integration works in a range of inquiries to generate surprising insights and even new fields of research. From these examples we try to gain a broader perspective on integration in relation to the contexts of inquiry in which it is implemented. In today's environment of data-intensive large-scale science, integration has become both a practical and normative requirement with corresponding implications for meta-methodological accounts of scientific practice. We conclude with a discussion of why an understanding of integration and its dynamics is useful for philosophy of science and scientific practice in general. Copyright © 2011 Elsevier Ltd. All rights reserved.

Biomedical Scientific and Professional Social Networks in the Service of the Development of Modern Scientific Publishing.

PubMed

Masic, Izet; Begic, Edin

2016-12-01

Information technologies have found their application in virtually every branch of health care. In recent years they have demonstrated their potential in the development of online library, where scientists and researchers can share their latest findings. Academia.edu, ResearchGate, Mendeley, Kudos, with the support of platform GoogleScholar, have indeed increased the visibility of scientific work of one author, and enable a much greater availability of the scientific work to the broader audience. Online libraries have allowed free access to the scientific content to the countries that could not follow the economic costs of getting access to certain scientific bases. Especially great benefit occurred in countries in transition and developing countries. Online libraries have great potential in terms of expanding knowledge, but they also present a major problem for many publishers, because their rights can be violated, which are signed by the author when publishing the paper. In the future it will lead to a major conflict of the author, the editorial board and online database, about the right to scientific content This question certainly represents one of the most pressing issues of publishing, whose future in printed form is already in the past, and the future of the online editions will be a problem of large-scale.

Biomedical Scientific and Professional Social Networks in the Service of the Development of Modern Scientific Publishing

PubMed Central

Masic, Izet; Begic, Edin

2016-01-01

Information technologies have found their application in virtually every branch of health care. In recent years they have demonstrated their potential in the development of online library, where scientists and researchers can share their latest findings. Academia.edu, ResearchGate, Mendeley, Kudos, with the support of platform GoogleScholar, have indeed increased the visibility of scientific work of one author, and enable a much greater availability of the scientific work to the broader audience. Online libraries have allowed free access to the scientific content to the countries that could not follow the economic costs of getting access to certain scientific bases. Especially great benefit occurred in countries in transition and developing countries. Online libraries have great potential in terms of expanding knowledge, but they also present a major problem for many publishers, because their rights can be violated, which are signed by the author when publishing the paper. In the future it will lead to a major conflict of the author, the editorial board and online database, about the right to scientific content This question certainly represents one of the most pressing issues of publishing, whose future in printed form is already in the past, and the future of the online editions will be a problem of large-scale. PMID:28077905

RIKEN BNL Research Center

NASA Astrophysics Data System (ADS)

Samios, Nicholas

2014-09-01

Since its inception in 1997, the RIKEN BNL Research Center (RBRC) has been a major force in the realms of Spin Physics, Relativistic Heavy Ion Physics, large scale Computing Physics and the training of a new generation of extremely talented physicists. This has been accomplished through the recruitment of an outstanding non-permanent staff of Fellows and Research associates in theory and experiment. RBRC is now a mature organization that has reached a steady level in the size of scientific and support staff while at the same time retaining its vibrant youth. A brief history of the scientific accomplishments and contributions of the RBRC physicists will be presented as well as a discussion of the unique RBRC management structure.

The "DGPPN-Cohort": A national collaboration initiative by the German Association for Psychiatry and Psychotherapy (DGPPN) for establishing a large-scale cohort of psychiatric patients.

PubMed

Anderson-Schmidt, Heike; Adler, Lothar; Aly, Chadiga; Anghelescu, Ion-George; Bauer, Michael; Baumgärtner, Jessica; Becker, Joachim; Bianco, Roswitha; Becker, Thomas; Bitter, Cosima; Bönsch, Dominikus; Buckow, Karoline; Budde, Monika; Bührig, Martin; Deckert, Jürgen; Demiroglu, Sara Y; Dietrich, Detlef; Dümpelmann, Michael; Engelhardt, Uta; Fallgatter, Andreas J; Feldhaus, Daniel; Figge, Christian; Folkerts, Here; Franz, Michael; Gade, Katrin; Gaebel, Wolfgang; Grabe, Hans-Jörgen; Gruber, Oliver; Gullatz, Verena; Gusky, Linda; Heilbronner, Urs; Helbing, Krister; Hegerl, Ulrich; Heinz, Andreas; Hensch, Tilman; Hiemke, Christoph; Jäger, Markus; Jahn-Brodmann, Anke; Juckel, Georg; Kandulski, Franz; Kaschka, Wolfgang P; Kircher, Tilo; Koller, Manfred; Konrad, Carsten; Kornhuber, Johannes; Krause, Marina; Krug, Axel; Lee, Mahsa; Leweke, Markus; Lieb, Klaus; Mammes, Mechthild; Meyer-Lindenberg, Andreas; Mühlbacher, Moritz; Müller, Matthias J; Nieratschker, Vanessa; Nierste, Barbara; Ohle, Jacqueline; Pfennig, Andrea; Pieper, Marlenna; Quade, Matthias; Reich-Erkelenz, Daniela; Reif, Andreas; Reitt, Markus; Reininghaus, Bernd; Reininghaus, Eva Z; Riemenschneider, Matthias; Rienhoff, Otto; Roser, Patrik; Rujescu, Dan; Schennach, Rebecca; Scherk, Harald; Schmauss, Max; Schneider, Frank; Schosser, Alexandra; Schott, Björn H; Schwab, Sybille G; Schwanke, Jens; Skrowny, Daniela; Spitzer, Carsten; Stierl, Sebastian; Stöckel, Judith; Stübner, Susanne; Thiel, Andreas; Volz, Hans-Peter; von Hagen, Martin; Walter, Henrik; Witt, Stephanie H; Wobrock, Thomas; Zielasek, Jürgen; Zimmermann, Jörg; Zitzelsberger, Antje; Maier, Wolfgang; Falkai, Peter G; Rietschel, Marcella; Schulze, Thomas G

2013-12-01

The German Association for Psychiatry and Psychotherapy (DGPPN) has committed itself to establish a prospective national cohort of patients with major psychiatric disorders, the so-called DGPPN-Cohort. This project will enable the scientific exploitation of high-quality data and biomaterial from psychiatric patients for research. It will be set up using harmonised data sets and procedures for sample generation and guided by transparent rules for data access and data sharing regarding the central research database. While the main focus lies on biological research, it will be open to all kinds of scientific investigations, including epidemiological, clinical or health-service research.

The Ophidia framework: toward cloud-based data analytics for climate change

NASA Astrophysics Data System (ADS)

Fiore, Sandro; D'Anca, Alessandro; Elia, Donatello; Mancini, Marco; Mariello, Andrea; Mirto, Maria; Palazzo, Cosimo; Aloisio, Giovanni

2015-04-01

The Ophidia project is a research effort on big data analytics facing scientific data analysis challenges in the climate change domain. It provides parallel (server-side) data analysis, an internal storage model and a hierarchical data organization to manage large amount of multidimensional scientific data. The Ophidia analytics platform provides several MPI-based parallel operators to manipulate large datasets (data cubes) and array-based primitives to perform data analysis on large arrays of scientific data. The most relevant data analytics use cases implemented in national and international projects target fire danger prevention (OFIDIA), interactions between climate change and biodiversity (EUBrazilCC), climate indicators and remote data analysis (CLIP-C), sea situational awareness (TESSA), large scale data analytics on CMIP5 data in NetCDF format, Climate and Forecast (CF) convention compliant (ExArch). Two use cases regarding the EU FP7 EUBrazil Cloud Connect and the INTERREG OFIDIA projects will be presented during the talk. In the former case (EUBrazilCC) the Ophidia framework is being extended to integrate scalable VM-based solutions for the management of large volumes of scientific data (both climate and satellite data) in a cloud-based environment to study how climate change affects biodiversity. In the latter one (OFIDIA) the data analytics framework is being exploited to provide operational support regarding processing chains devoted to fire danger prevention. To tackle the project challenges, data analytics workflows consisting of about 130 operators perform, among the others, parallel data analysis, metadata management, virtual file system tasks, maps generation, rolling of datasets, import/export of datasets in NetCDF format. Finally, the entire Ophidia software stack has been deployed at CMCC on 24-nodes (16-cores/node) of the Athena HPC cluster. Moreover, a cloud-based release tested with OpenNebula is also available and running in the private cloud infrastructure of the CMCC Supercomputing Centre.

Web-based visualization of very large scientific astronomy imagery

NASA Astrophysics Data System (ADS)

Bertin, E.; Pillay, R.; Marmo, C.

2015-04-01

Visualizing and navigating through large astronomy images from a remote location with current astronomy display tools can be a frustrating experience in terms of speed and ergonomics, especially on mobile devices. In this paper, we present a high performance, versatile and robust client-server system for remote visualization and analysis of extremely large scientific images. Applications of this work include survey image quality control, interactive data query and exploration, citizen science, as well as public outreach. The proposed software is entirely open source and is designed to be generic and applicable to a variety of datasets. It provides access to floating point data at terabyte scales, with the ability to precisely adjust image settings in real-time. The proposed clients are light-weight, platform-independent web applications built on standard HTML5 web technologies and compatible with both touch and mouse-based devices. We put the system to the test and assess the performance of the system and show that a single server can comfortably handle more than a hundred simultaneous users accessing full precision 32 bit astronomy data.

Unpacking the Paradox of Chinese Science Learners: Insights from Research into Asian Chinese School Students' Attitudes towards Learning Science, Science Learning Strategies, and Scientific Epistemological Views

ERIC Educational Resources Information Center

Cheng, May Hung May; Wan, Zhi Hong

2016-01-01

Chinese students' excellent science performance in large-scale international comparisons contradicts the stereotype of the Chinese non-productive classroom learning environment and learners. Most of the existing explanations of this paradox are provided from the perspective of teaching and learning in a general sense, but little work can be found…

Plentern mit Kiefern--Ergebnisse aus den USA [Plentering with pines--results from the United States

Treesearch

James M. Guldin; Don C. Bragg; Andreas Zingg

2017-01-01

Until now, scientifically reliable data on plentering of light-demanding tree species in Europe have been lacking. This gap is filled with long-term trials from the USA, among others with southern yellow pines. In the southern state of Arkansas, two plots of 16 hectares were installed in 1936, in the context of a large-scale trial of mixed loblolly pine (...

JPRS Report, Soviet Union, Economic Affairs

DTIC Science & Technology

1988-10-18

34Commodities—The Mirror of Cost Accounting"] [Text] A number of large-scale decisions directed toward increasing the production of high-quality...suitable in the sphere of scientific research and experimental design work. It is known, for example, that the number of blueprints , specifications, or...the situation, Yu. Kozyrev , deputy chief of the Department for Problems of the Machine Building Complex of the USSR State Committee for Science and

The Tomographic Ionized-Carbon Mapping Experiment (TIME) CII Imaging Spectrometer

NASA Astrophysics Data System (ADS)

Staniszewski, Z.; Bock, J. J.; Bradford, C. M.; Brevik, J.; Cooray, A.; Gong, Y.; Hailey-Dunsheath, S.; O'Brient, R.; Santos, M.; Shirokoff, E.; Silva, M.; Zemcov, M.

2014-09-01

The Tomographic Ionized-Carbon Mapping Experiment (TIME) and TIME-Pilot are proposed imaging spectrometers to measure reionization and large scale structure at redshifts 5-9. We seek to exploit the 158 restframe emission of [CII], which becomes measurable at 200-300 GHz at reionization redshifts. Here we describe the scientific motivation, give an overview of the proposed instrument, and highlight key technological developments underway to enable these measurements.

SparkText: Biomedical Text Mining on Big Data Framework.

PubMed

Ye, Zhan; Tafti, Ahmad P; He, Karen Y; Wang, Kai; He, Max M

Many new biomedical research articles are published every day, accumulating rich information, such as genetic variants, genes, diseases, and treatments. Rapid yet accurate text mining on large-scale scientific literature can discover novel knowledge to better understand human diseases and to improve the quality of disease diagnosis, prevention, and treatment. In this study, we designed and developed an efficient text mining framework called SparkText on a Big Data infrastructure, which is composed of Apache Spark data streaming and machine learning methods, combined with a Cassandra NoSQL database. To demonstrate its performance for classifying cancer types, we extracted information (e.g., breast, prostate, and lung cancers) from tens of thousands of articles downloaded from PubMed, and then employed Naïve Bayes, Support Vector Machine (SVM), and Logistic Regression to build prediction models to mine the articles. The accuracy of predicting a cancer type by SVM using the 29,437 full-text articles was 93.81%. While competing text-mining tools took more than 11 hours, SparkText mined the dataset in approximately 6 minutes. This study demonstrates the potential for mining large-scale scientific articles on a Big Data infrastructure, with real-time update from new articles published daily. SparkText can be extended to other areas of biomedical research.

Intraseasonal and Interannual Variability of Mars Present Climate

NASA Astrophysics Data System (ADS)

Hollingsworth, Jeffery L.; Bridger, Alison F. C.; Haberle, Robert M.

1996-01-01

This is a Final Report for a Joint Research Interchange (JRI) between NASA Ames Research Center and San Jose State University, Department of Meteorology. The focus of this JRI has been to investigate the nature of intraseasonal and interannual variability of Mars'present climate. We have applied a three-dimensional climate model based on the full hydrostatic primitive equations to determine the spatial, but primarily, the temporal structures of the planet's large-scale circulation as it evolves during a given seasonal advance, and, over multi-annual cycles. The particular climate model applies simplified physical parameterizations and is computationally efficient. It could thus easily be integrated in a perpetual season or advancing season configuration, as well as over many Mars years. We have assessed both high and low-frequency components of the circulation (i.e., motions having periods of Omicron(2-10 days) or greater than Omicron(10 days), respectively). Results from this investigation have explored the basic issue whether Mars' climate system is naturally 'chaotic' associated with nonlinear interactions of the large-scale circulation-regardless of any allowance for year-to-year variations in external forcing mechanisms. Titles of papers presented at scientific conferences and a manuscript to be submitted to the scientific literature are provided. An overview of a areas for further investigation is also presented.

Investigation of the Large Scale Evolution and Topology of Coronal Mass Ejections in the Solar Wind

NASA Technical Reports Server (NTRS)

Riley, Pete

2001-01-01

This investigation is concerned with the large-scale evolution and topology of coronal mass ejections (CMEs) in the solar wind. During the course of this three-year investigation, we have undertaken a number of studies that are discussed in more detail in this report. For example, we conducted an analysis of all CMEs observed by the Ulysses spacecraft during its in-ecliptic phase between 1 and 5 AU. In addition to studying the properties of the ejecta, we also analyzed the shocks that could be unambiguously associated with the fast CMEs. We also analyzed a series of 'density holes' observed in the solar wind that bear many similarities with CMEs. To complement this analysis, we conducted a series of 1-D and 2 1/2-D fluid, MHD, and hybrid simulations to address a number of specific issues related to CME evolution in the solar wind. For example, we used fluid simulations to address the interpretation of negative electron temperature-density relationships often observed within CME/cloud intervals. As part of this investigation, a number of fruitful international collaborations were forged. Finally, the results of this work were presented at nine scientific meetings and communicated in eight scientific, refereed papers.

SparkText: Biomedical Text Mining on Big Data Framework

PubMed Central

He, Karen Y.; Wang, Kai

2016-01-01

Background Many new biomedical research articles are published every day, accumulating rich information, such as genetic variants, genes, diseases, and treatments. Rapid yet accurate text mining on large-scale scientific literature can discover novel knowledge to better understand human diseases and to improve the quality of disease diagnosis, prevention, and treatment. Results In this study, we designed and developed an efficient text mining framework called SparkText on a Big Data infrastructure, which is composed of Apache Spark data streaming and machine learning methods, combined with a Cassandra NoSQL database. To demonstrate its performance for classifying cancer types, we extracted information (e.g., breast, prostate, and lung cancers) from tens of thousands of articles downloaded from PubMed, and then employed Naïve Bayes, Support Vector Machine (SVM), and Logistic Regression to build prediction models to mine the articles. The accuracy of predicting a cancer type by SVM using the 29,437 full-text articles was 93.81%. While competing text-mining tools took more than 11 hours, SparkText mined the dataset in approximately 6 minutes. Conclusions This study demonstrates the potential for mining large-scale scientific articles on a Big Data infrastructure, with real-time update from new articles published daily. SparkText can be extended to other areas of biomedical research. PMID:27685652

'Sciencenet'--towards a global search and share engine for all scientific knowledge.

PubMed

Lütjohann, Dominic S; Shah, Asmi H; Christen, Michael P; Richter, Florian; Knese, Karsten; Liebel, Urban

2011-06-15

Modern biological experiments create vast amounts of data which are geographically distributed. These datasets consist of petabytes of raw data and billions of documents. Yet to the best of our knowledge, a search engine technology that searches and cross-links all different data types in life sciences does not exist. We have developed a prototype distributed scientific search engine technology, 'Sciencenet', which facilitates rapid searching over this large data space. By 'bringing the search engine to the data', we do not require server farms. This platform also allows users to contribute to the search index and publish their large-scale data to support e-Science. Furthermore, a community-driven method guarantees that only scientific content is crawled and presented. Our peer-to-peer approach is sufficiently scalable for the science web without performance or capacity tradeoff. The free to use search portal web page and the downloadable client are accessible at: http://sciencenet.kit.edu. The web portal for index administration is implemented in ASP.NET, the 'AskMe' experiment publisher is written in Python 2.7, and the backend 'YaCy' search engine is based on Java 1.6.

Making sense scientific claims in advertising. A study of scientifically aware consumers.

PubMed

Dodds, Rachel E; Tseëlon, Efrat; Weitkamp, Emma L C

2008-04-01

Evidence that science is becoming increasingly embedded in culture comes from the proliferation of discourses of ethical consumption, sustainability, and environmental awareness. Al Gore's recent award, along with UN's Inter-governmental Panel on Climate Change (IPCC) of the Nobel peace prize-- provided a recent high profile linking of consumption and science. It is not clear to what extent the public at large engages in evaluating the scientific merits of the arguments about the link between human consumption and global environmental catastrophes. But on a local scale, we are routinely required to evaluate, scientific and pseudoscientific claims in advertising. Since advertising is used to sell products, the discourse of scientifically framed claims is being used to persuade consumers of the benefits of these products. In the case of functional foods and cosmetics, such statements are deployed to promote the health benefits and effectiveness of their products. This exploratory study examines the views of British consumers about the scientific and pseudoscientific claims made in advertisements for foods, with particular reference to functional foods, and cosmetics. The participants in the study all worked in scientific environments, though they were not all scientists. The study found that scientific arguments that were congruent with existing health knowledge tended to be accepted while pseudoscientific knowledge was regarded skeptically and concerns were raised over the accuracy and believability of the pseudoscientific claims. It appears that scientific awareness may play a part in consumers' ability to critically examine scientifically and pseudoscientifically based advertising claims.

Machine learning for large-scale wearable sensor data in Parkinson's disease: Concepts, promises, pitfalls, and futures.

PubMed

Kubota, Ken J; Chen, Jason A; Little, Max A

2016-09-01

For the treatment and monitoring of Parkinson's disease (PD) to be scientific, a key requirement is that measurement of disease stages and severity is quantitative, reliable, and repeatable. The last 50 years in PD research have been dominated by qualitative, subjective ratings obtained by human interpretation of the presentation of disease signs and symptoms at clinical visits. More recently, "wearable," sensor-based, quantitative, objective, and easy-to-use systems for quantifying PD signs for large numbers of participants over extended durations have been developed. This technology has the potential to significantly improve both clinical diagnosis and management in PD and the conduct of clinical studies. However, the large-scale, high-dimensional character of the data captured by these wearable sensors requires sophisticated signal processing and machine-learning algorithms to transform it into scientifically and clinically meaningful information. Such algorithms that "learn" from data have shown remarkable success in making accurate predictions for complex problems in which human skill has been required to date, but they are challenging to evaluate and apply without a basic understanding of the underlying logic on which they are based. This article contains a nontechnical tutorial review of relevant machine-learning algorithms, also describing their limitations and how these can be overcome. It discusses implications of this technology and a practical road map for realizing the full potential of this technology in PD research and practice. © 2016 International Parkinson and Movement Disorder Society. © 2016 International Parkinson and Movement Disorder Society.

Rediscovery of the doldrums in storm-resolving simulations over the tropical Atlantic

NASA Astrophysics Data System (ADS)

Klocke, Daniel; Brueck, Matthias; Hohenegger, Cathy; Stevens, Bjorn

2017-12-01

The doldrums — a zone of calm and variable winds in the deep tropics between the trades — were of key importance to nineteenth century maritime travel. As a result, the region was a focus in atmospheric science at that time. However, as sailing ships were replaced by steamboats, scientific interest shifted to the heavy precipitating storms within the doldrums: the deep convective systems of the intertropical convergence zone. Now, in storm-system-resolving simulations over a period of two months that cover a large part of the tropical Atlantic, the doldrums are one of the most prominent features. The doldrums are substantially less pronounced in coarser-resolution simulations that use a parameterization for convection, despite their large-scale extent. We conclude that explicitly representing the storm scale dynamics and their coupling to the surface wind on the storm-system scales helps to maintain the systems of winds that define the doldrums. We suggest that the lack of these wind systems could explain the persistent tropical precipitation biases in climate models.

The connection-set algebra--a novel formalism for the representation of connectivity structure in neuronal network models.

PubMed

Djurfeldt, Mikael

2012-07-01

The connection-set algebra (CSA) is a novel and general formalism for the description of connectivity in neuronal network models, from small-scale to large-scale structure. The algebra provides operators to form more complex sets of connections from simpler ones and also provides parameterization of such sets. CSA is expressive enough to describe a wide range of connection patterns, including multiple types of random and/or geometrically dependent connectivity, and can serve as a concise notation for network structure in scientific writing. CSA implementations allow for scalable and efficient representation of connectivity in parallel neuronal network simulators and could even allow for avoiding explicit representation of connections in computer memory. The expressiveness of CSA makes prototyping of network structure easy. A C+ + version of the algebra has been implemented and used in a large-scale neuronal network simulation (Djurfeldt et al., IBM J Res Dev 52(1/2):31-42, 2008b) and an implementation in Python has been publicly released.

Matching traditional and scientific observations to detect environmental change: a discussion on Arctic terrestrial ecosystems.

PubMed

Huntington, Henry; Callaghan, Terry; Fox, Shari; Krupnik, Igor

2004-11-01

Recent environmental changes are having, and are expected to continue to have, significant impacts in the Arctic as elsewhere in the world. Detecting those changes and determining the mechanisms that cause them are far from trivial problems. The use of multiple methods of observation can increase confidence in individual observations, broaden the scope of information available about environmental change, and contribute to insights concerning mechanisms of change. In this paper, we examine the ways that using traditional ecological knowledge (TEK) together with scientific observations can achieve these objectives. A review of TEK observations in comparison with scientific observations demonstrates the promise of this approach, while also revealing several challenges to putting it into practice on a large scale. Further efforts are suggested, particularly in undertaking collaborative projects designed to produce parallel observations that can be readily compared and analyzed in greater detail than is possible in an opportunistic sample.

Parallel computing works

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

Not Available

An account of the Caltech Concurrent Computation Program (C{sup 3}P), a five year project that focused on answering the question: Can parallel computers be used to do large-scale scientific computations '' As the title indicates, the question is answered in the affirmative, by implementing numerous scientific applications on real parallel computers and doing computations that produced new scientific results. In the process of doing so, C{sup 3}P helped design and build several new computers, designed and implemented basic system software, developed algorithms for frequently used mathematical computations on massively parallel machines, devised performance models and measured the performance of manymore » computers, and created a high performance computing facility based exclusively on parallel computers. While the initial focus of C{sup 3}P was the hypercube architecture developed by C. Seitz, many of the methods developed and lessons learned have been applied successfully on other massively parallel architectures.« less

The joint cardiovascular research profile of the university medical centres in the Netherlands.

PubMed

van Welie, S D; van Leeuwen, T N; Bouma, C J; Klaassen, A B M

2016-05-01

Biomedical scientific research in the Netherlands has a good reputation worldwide. Quantitatively, the university medical centres (UMCs) deliver about 40 % of the total number of scientific publications of this research. Analysis of the bibliometric output data of the UMCs shows that their research is highly cited. These output-based analyses also indicate the high impact of cardiovascular scientific research in these centres, illustrating the strength of this research in the Netherlands. A set of six joint national cardiovascular research topics selected by the UMCs can be recognised. At the top are heart failure, rhythm disorder research and atherosclerosis. National collaboration of top scientists in consortia in these three areas is successful in acquiring funding of large-scale programs. Our observations suggest that funding national consortia of experts focused on a few selected research topics may increase the international competitiveness of cardiovascular research in the Netherlands.

Upscaling of U(VI) Desorption and Transport from Decimeter-Scale Heterogeneity to Plume-Scale Modeling

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

Curtis, Gary P.; Kohler, Matthias; Kannappan, Ramakrishnan

2015-02-24

Scientifically defensible predictions of field scale U(VI) transport in groundwater requires an understanding of key processes at multiple scales. These scales range from smaller than the sediment grain scale (less than 10 μm) to as large as the field scale which can extend over several kilometers. The key processes that need to be considered include both geochemical reactions in solution and at sediment surfaces as well as physical transport processes including advection, dispersion, and pore-scale diffusion. The research summarized in this report includes both experimental and modeling results in batch, column and tracer tests. The objectives of this research weremore » to: (1) quantify the rates of U(VI) desorption from sediments acquired from a uranium contaminated aquifer in batch experiments;(2) quantify rates of U(VI) desorption in column experiments with variable chemical conditions, and(3) quantify nonreactive tracer and U(VI) transport in field tests.« less

A uniform approach for programming distributed heterogeneous computing systems

PubMed Central

Grasso, Ivan; Pellegrini, Simone; Cosenza, Biagio; Fahringer, Thomas

2014-01-01

Large-scale compute clusters of heterogeneous nodes equipped with multi-core CPUs and GPUs are getting increasingly popular in the scientific community. However, such systems require a combination of different programming paradigms making application development very challenging. In this article we introduce libWater, a library-based extension of the OpenCL programming model that simplifies the development of heterogeneous distributed applications. libWater consists of a simple interface, which is a transparent abstraction of the underlying distributed architecture, offering advanced features such as inter-context and inter-node device synchronization. It provides a runtime system which tracks dependency information enforced by event synchronization to dynamically build a DAG of commands, on which we automatically apply two optimizations: collective communication pattern detection and device-host-device copy removal. We assess libWater’s performance in three compute clusters available from the Vienna Scientific Cluster, the Barcelona Supercomputing Center and the University of Innsbruck, demonstrating improved performance and scaling with different test applications and configurations. PMID:25844015

NASA's Global Hawk

NASA Image and Video Library

2014-09-23

View from a Chase Plane; HS3 Science Flight 8 Wraps Up The chase plane accompanying NASA's Global Hawk No. 872 captured this picture on Sept. 19 after the Global Hawk completed science flight #8 where it gathered data from a weakening Tropical Storm Edouard over the North Atlantic Ocean. Credit: NASA -- The Hurricane and Severe Storm Sentinel (HS3) is a five-year mission specifically targeted to investigate the processes that underlie hurricane formation and intensity change in the Atlantic Ocean basin. HS3 is motivated by hypotheses related to the relative roles of the large-scale environment and storm-scale internal processes. Read more: espo.nasa.gov/missions/hs3/mission-gallery NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Parallel Computation of the Regional Ocean Modeling System (ROMS)

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

Wang, P; Song, Y T; Chao, Y

2005-04-05

The Regional Ocean Modeling System (ROMS) is a regional ocean general circulation modeling system solving the free surface, hydrostatic, primitive equations over varying topography. It is free software distributed world-wide for studying both complex coastal ocean problems and the basin-to-global scale ocean circulation. The original ROMS code could only be run on shared-memory systems. With the increasing need to simulate larger model domains with finer resolutions and on a variety of computer platforms, there is a need in the ocean-modeling community to have a ROMS code that can be run on any parallel computer ranging from 10 to hundreds ofmore » processors. Recently, we have explored parallelization for ROMS using the MPI programming model. In this paper, an efficient parallelization strategy for such a large-scale scientific software package, based on an existing shared-memory computing model, is presented. In addition, scientific applications and data-performance issues on a couple of SGI systems, including Columbia, the world's third-fastest supercomputer, are discussed.« less

A Component Approach to Collaborative Scientific Software Development: Tools and Techniques Utilized by the Quantum Chemistry Science Application Partnership

DOE PAGES

Kenny, Joseph P.; Janssen, Curtis L.; Gordon, Mark S.; ...

2008-01-01

Cutting-edge scientific computing software is complex, increasingly involving the coupling of multiple packages to combine advanced algorithms or simulations at multiple physical scales. Component-based software engineering (CBSE) has been advanced as a technique for managing this complexity, and complex component applications have been created in the quantum chemistry domain, as well as several other simulation areas, using the component model advocated by the Common Component Architecture (CCA) Forum. While programming models do indeed enable sound software engineering practices, the selection of programming model is just one building block in a comprehensive approach to large-scale collaborative development which must also addressmore » interface and data standardization, and language and package interoperability. We provide an overview of the development approach utilized within the Quantum Chemistry Science Application Partnership, identifying design challenges, describing the techniques which we have adopted to address these challenges and highlighting the advantages which the CCA approach offers for collaborative development.« less

A uniform approach for programming distributed heterogeneous computing systems.

PubMed

Grasso, Ivan; Pellegrini, Simone; Cosenza, Biagio; Fahringer, Thomas

2014-12-01

Large-scale compute clusters of heterogeneous nodes equipped with multi-core CPUs and GPUs are getting increasingly popular in the scientific community. However, such systems require a combination of different programming paradigms making application development very challenging. In this article we introduce libWater, a library-based extension of the OpenCL programming model that simplifies the development of heterogeneous distributed applications. libWater consists of a simple interface, which is a transparent abstraction of the underlying distributed architecture, offering advanced features such as inter-context and inter-node device synchronization. It provides a runtime system which tracks dependency information enforced by event synchronization to dynamically build a DAG of commands, on which we automatically apply two optimizations: collective communication pattern detection and device-host-device copy removal. We assess libWater's performance in three compute clusters available from the Vienna Scientific Cluster, the Barcelona Supercomputing Center and the University of Innsbruck, demonstrating improved performance and scaling with different test applications and configurations.

Porting the AVS/Express scientific visualization software to Cray XT4.

PubMed

Leaver, George W; Turner, Martin J; Perrin, James S; Mummery, Paul M; Withers, Philip J

2011-08-28

Remote scientific visualization, where rendering services are provided by larger scale systems than are available on the desktop, is becoming increasingly important as dataset sizes increase beyond the capabilities of desktop workstations. Uptake of such services relies on access to suitable visualization applications and the ability to view the resulting visualization in a convenient form. We consider five rules from the e-Science community to meet these goals with the porting of a commercial visualization package to a large-scale system. The application uses message-passing interface (MPI) to distribute data among data processing and rendering processes. The use of MPI in such an interactive application is not compatible with restrictions imposed by the Cray system being considered. We present details, and performance analysis, of a new MPI proxy method that allows the application to run within the Cray environment yet still support MPI communication required by the application. Example use cases from materials science are considered.

Scientific, technological, and economic aspects of rapid tooling by electric arc spray forming

NASA Astrophysics Data System (ADS)

Grant, P. S.; Duncan, S. R.; Roche, A.; Johnson, C. F.

2006-12-01

For the last seven years, Oxford University and Ford Motor Company personnel have been researching jointly the development of the large-scale spray forming of steel tooling capable for use in mass production, particularly for the pressing of sheet metal in automotive applications. These investigations have involved: the comprehensive microstructure and property studies, modeling of shape evolution and heat flow, realtime feedback control of tool temperature to eliminate tool distortion, high-speed imaging and particle image velocimetry of droplet deposition on three-dimensional (3D) shapes, testing of full-scale tools for different applications in the production environment, and detailed studies of the cost and time savings realized for different tooling applications. This paper provides an overview of the scientific and technical progress to date, presents the latest results, and describes the current state-of-the-art. Many of the insights described have relevance and applicability across the family of thermal spray processes and applications.

The scientific targets of the SCOPE mission

NASA Astrophysics Data System (ADS)

Fujimoto, M.; Saito, Y.; Tsuda, Y.; Shinohara, I.; Kojima, H.

Future Japanese magnetospheric mission "SCOPE" is now under study (planned to be launched in 2012). The main purpose of this mission is to investigate the dynamic behaviors of plasmas in the Earth's magnetosphere from the view-point of cross-scale coupling. Dynamical collisionless space plasma phenomena, be they large scale as a whole, are chracterized by coupling over various time and spatial scales. The best example would be the magnetic reconnection process, which is a large scale energy conversion process but has a small key region at the heart of its engine. Inside the key region, electron scale dynamics plays the key role in liberating the frozen-in constraint, by which reconnection is allowed to proceed. The SCOPE mission is composed of one large mother satellite and four small daughter satellites. The mother spacecraft will be equiped with the electron detector that has 10 msec time resolution so that scales down to the electron's will be resolved. Three of the four daughter satellites surround the mother satellite 3-dimensionally with the mutual distances between several km and several thousand km, which are varied during the mission. Plasma measurements on these spacecrafts will have 1 sec resolution and will provide information on meso-scale plasma structure. The fourth daughter satellite stays near the mother satellite with the distance less than 100km. By correlation between the two plasma wave instruments on the daughter and the mother spacecrafts, propagation of the waves and the information on the electron scale dynamics will be obtained. By this strategy, both meso- and micro-scale information on dynamics are obtained, that will enable us to investigate the physics of the space plasma from the cross-scale coupling point of view.

Scaling laws and fluctuations in the statistics of word frequencies

NASA Astrophysics Data System (ADS)

Gerlach, Martin; Altmann, Eduardo G.

2014-11-01

In this paper, we combine statistical analysis of written texts and simple stochastic models to explain the appearance of scaling laws in the statistics of word frequencies. The average vocabulary of an ensemble of fixed-length texts is known to scale sublinearly with the total number of words (Heaps’ law). Analyzing the fluctuations around this average in three large databases (Google-ngram, English Wikipedia, and a collection of scientific articles), we find that the standard deviation scales linearly with the average (Taylor's law), in contrast to the prediction of decaying fluctuations obtained using simple sampling arguments. We explain both scaling laws (Heaps’ and Taylor) by modeling the usage of words using a Poisson process with a fat-tailed distribution of word frequencies (Zipf's law) and topic-dependent frequencies of individual words (as in topic models). Considering topical variations lead to quenched averages, turn the vocabulary size a non-self-averaging quantity, and explain the empirical observations. For the numerous practical applications relying on estimations of vocabulary size, our results show that uncertainties remain large even for long texts. We show how to account for these uncertainties in measurements of lexical richness of texts with different lengths.

Assessing Student Status and Progress in Science Reasoning and Quantitative Literacy at a Very Large Undergraduate Institution

NASA Astrophysics Data System (ADS)

Donahue, Megan; Kaplan, J.; Ebert-May, D.; Ording, G.; Melfi, V.; Gilliland, D.; Sikorski, A.; Johnson, N.

2009-01-01

The typical large liberal-arts, tier-one research university requires all of its graduates to achieve some minimal standards of quantitative literacy and scientific reasoning skills. But how do we know what we are doing, as instructors and as a university, is working the way we think it should? At Michigan State University, a cross-disciplinary team of scientists, statisticians, and teacher education experts have begun a large-scale investigation about student mastery of quantitative and scientific skills, beginning with an assessment of 3,000 freshmen before they start their university careers. We will describe the process we used for developing and testing an instrument, for expanding faculty involvement and input on high-level goals. For this limited presentation, we will limit the discussion mainly to the scientific reasoning perspective, but we will briefly mention some intriguing observations regarding quantitative literacy as well. This project represents the beginning of long-term, longitudinal tracking of the progress of students at our institution. We will discuss preliminary results our 2008 assessment of incoming freshman at Michigan State, and where we plan to go from here. We acknowledge local support from the Quality Fund from the Office of the Provost at MSU. We also acknowledge the Center for Assessment at James Madison University and the NSF for their support at the very beginning of our work.

Delensing CMB polarization with external datasets

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

Smith, Kendrick M.; Hanson, Duncan; LoVerde, Marilena

2012-06-01

One of the primary scientific targets of current and future CMB polarization experiments is the search for a stochastic background of gravity waves in the early universe. As instrumental sensitivity improves, the limiting factor will eventually be B-mode power generated by gravitational lensing, which can be removed through use of so-called ''delensing'' algorithms. We forecast prospects for delensing using lensing maps which are obtained externally to CMB polarization: either from large-scale structure observations, or from high-resolution maps of CMB temperature. We conclude that the forecasts in either case are not encouraging, and that significantly delensing large-scale CMB polarization requires high-resolutionmore » polarization maps with sufficient sensitivity to measure the lensing B-mode. We also present a simple formalism for including delensing in CMB forecasts which is computationally fast and agrees well with Monte Carlos.« less

Study of Travelling Interplanetary Phenomena Report

NASA Astrophysics Data System (ADS)

Dryer, Murray

1987-09-01

Scientific progress on the topic of energy, mass, and momentum transport from the Sun into the heliosphere is contingent upon interdisciplinary and international cooperative efforts on the part of many workers. Summarized here is a report of some highlights of research carried out during the SMY/SMA by the STIP (Study of Travelling Interplanetary Phenomena) Project that included solar and interplanetary scientists around the world. These highlights are concerned with coronal mass ejections from solar flares or erupting prominences (sometimes together); their large-scale consequences in interplanetary space (such as shocks and magnetic 'bubbles'); and energetic particles and their relationship to these large-scale structures. It is concluded that future progress is contingent upon similar international programs assisted by real-time (or near-real-time) warnings of solar activity by cooperating agencies along the lines experienced during the SMY/SMA.

CO2 Emissions in an Oil Palm Plantation on Tropical Peat in Malaysia

NASA Astrophysics Data System (ADS)

Leclerc, M.; Zhang, G.; Jantan, N. M.; Harun, M. H.; Kamarudin, N.; Choo, Y. M.

2016-12-01

Tropical peats are large contributors to greenhouse gas emissions and differ markedly from their counterparts at temperate latitudes. The rapid deforestation and subsequent land conversion of tropical virgin forests in Southeast Asia have been decried by environmental groups worldwide even though there is currently little robust scientific evidence to ascertain the net amount of greenhouse gas released to the atmosphere. The conversion to oil palm plantation at a large scale further exacerbates the situation. This paper shows preliminary data on CO2 emissions in a converted oil palm plantation grown on tropical peat in northeast Malaysia.

Inner-outer predictive wall model for wall-bounded turbulence in hypersonic flow

NASA Astrophysics Data System (ADS)

Martin, M. Pino; Helm, Clara M.

2017-11-01

The inner-outer predictive wall model of Mathis et al. is modified for hypersonic turbulent boundary layers. The model is based on a modulation of the energized motions in the inner layer by large scale momentum fluctuations in the logarithmic layer. Using direct numerical simulation (DNS) data of turbulent boundary layers with free stream Mach number 3 to 10, it is shown that the variation of the fluid properties in the compressible flows leads to large Reynolds number (Re) effects in the outer layer and facilitate the modulation observed in high Re incompressible flows. The modulation effect by the large scale increases with increasing free-stream Mach number. The model is extended to include spanwise and wall-normal velocity fluctuations and is generalized through Morkovin scaling. Temperature fluctuations are modeled using an appropriate Reynolds Analogy. Density fluctuations are calculated using an equation of state and a scaling with Mach number. DNS data are used to obtain the universal signal and parameters. The model is tested by using the universal signal to reproduce the flow conditions of Mach 3 and Mach 7 turbulent boundary layer DNS data and comparing turbulence statistics between the modeled flow and the DNS data. This work is supported by the Air Force Office of Scientific Research under Grant FA9550-17-1-0104.

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

Visualizing the Big (and Large) Data from an HPC Resource

NASA Astrophysics Data System (ADS)

Sisneros, R.

2015-10-01

Supercomputers are built to endure painfully large simulations and contend with resulting outputs. These are characteristics that scientists are all too willing to test the limits of in their quest for science at scale. The data generated during a scientist's workflow through an HPC center (large data) is the primary target for analysis and visualization. However, the hardware itself is also capable of generating volumes of diagnostic data (big data); this presents compelling opportunities to deploy analogous analytic techniques. In this paper we will provide a survey of some of the many ways in which visualization and analysis may be crammed into the scientific workflow as well as utilized on machine-specific data.

Architectural Strategies for Enabling Data-Driven Science at Scale

NASA Astrophysics Data System (ADS)

Crichton, D. J.; Law, E. S.; Doyle, R. J.; Little, M. M.

2017-12-01

The analysis of large data collections from NASA or other agencies is often executed through traditional computational and data analysis approaches, which require users to bring data to their desktops and perform local data analysis. Alternatively, data are hauled to large computational environments that provide centralized data analysis via traditional High Performance Computing (HPC). Scientific data archives, however, are not only growing massive, but are also becoming highly distributed. Neither traditional approach provides a good solution for optimizing analysis into the future. Assumptions across the NASA mission and science data lifecycle, which historically assume that all data can be collected, transmitted, processed, and archived, will not scale as more capable instruments stress legacy-based systems. New paradigms are needed to increase the productivity and effectiveness of scientific data analysis. This paradigm must recognize that architectural and analytical choices are interrelated, and must be carefully coordinated in any system that aims to allow efficient, interactive scientific exploration and discovery to exploit massive data collections, from point of collection (e.g., onboard) to analysis and decision support. The most effective approach to analyzing a distributed set of massive data may involve some exploration and iteration, putting a premium on the flexibility afforded by the architectural framework. The framework should enable scientist users to assemble workflows efficiently, manage the uncertainties related to data analysis and inference, and optimize deep-dive analytics to enhance scalability. In many cases, this "data ecosystem" needs to be able to integrate multiple observing assets, ground environments, archives, and analytics, evolving from stewardship of measurements of data to using computational methodologies to better derive insight from the data that may be fused with other sets of data. This presentation will discuss architectural strategies, including a 2015-2016 NASA AIST Study on Big Data, for evolving scientific research towards massively distributed data-driven discovery. It will include example use cases across earth science, planetary science, and other disciplines.

MEMO2 - MEthane goes MObile - MEasurements and Modelling - Part 2

NASA Astrophysics Data System (ADS)

Röckmann, Thomas; Walter, Sylvia

2017-04-01

As mitigation of climate change is a key scientific and societal challenge, the 2015 United Nations Climate Change Conference in Paris (COP21) agreed to limit global warming "well below" 2˚ C and, if possible, below 1.5˚ C. Reaching this target requires massive reductions of greenhouse gas emissions, and achieving significant reduction of greenhouse gas emissions is a logical headline targets of the EU climate action and of the H2020 strategy. CH4 emissions are a major contributor to Europe's global warming impact and emissions are not well quantified yet. There are significant discrepancies between official inventories of emissions and estimates derived from direct atmospheric measurement. Effective emission reduction can only be achieved if sources are properly quantified, and mitigation efforts are verified. New advanced combinations of measurement and modelling are needed to archive such quantification. MEMO2 will contribute to the targets of the EU with a focus on methane (CH4). The project will bridge the gap between large-scale scientific estimates from in situ monitoring programs and the 'bottom-up' estimates of emissions from local sources that are used in the national reporting by I) developing new and advanced mobile methane (CH4) measurements tools and networks, II) isotopic source identification, and III) modelling at different scales. Within the project qualified scientists will be educated in the use and implementation of interdisciplinary knowledge and techniques that are essential to meet and verify emission reduction goals. MEMO2 will facilitate intensive collaboration between the largely academic greenhouse gas monitoring community and non-academic partners who are responsible for evaluating and reporting greenhouse gas emissions to policy makers. MEMO2 is a European Training Network with more than 20 collaborators from 7 countries. It is a 4-years project and we will present the project and its objectives to the scientific community to foster collaboration and scientific exchange from the beginning.

HEPCloud, a New Paradigm for HEP Facilities: CMS Amazon Web Services Investigation

DOE PAGES

Holzman, Burt; Bauerdick, Lothar A. T.; Bockelman, Brian; ...

2017-09-29

Historically, high energy physics computing has been performed on large purpose-built computing systems. These began as single-site compute facilities, but have evolved into the distributed computing grids used today. Recently, there has been an exponential increase in the capacity and capability of commercial clouds. Cloud resources are highly virtualized and intended to be able to be flexibly deployed for a variety of computing tasks. There is a growing interest among the cloud providers to demonstrate the capability to perform large-scale scientific computing. In this paper, we discuss results from the CMS experiment using the Fermilab HEPCloud facility, which utilized bothmore » local Fermilab resources and virtual machines in the Amazon Web Services Elastic Compute Cloud. We discuss the planning, technical challenges, and lessons learned involved in performing physics workflows on a large-scale set of virtualized resources. Additionally, we will discuss the economics and operational efficiencies when executing workflows both in the cloud and on dedicated resources.« less

Dynamical systems proxies of atmospheric predictability and mid-latitude extremes

NASA Astrophysics Data System (ADS)

Messori, Gabriele; Faranda, Davide; Caballero, Rodrigo; Yiou, Pascal

2017-04-01

Extreme weather ocurrences carry enormous social and economic costs and routinely garner widespread scientific and media coverage. Many extremes (for e.g. storms, heatwaves, cold spells, heavy precipitation) are tied to specific patterns of midlatitude atmospheric circulation. The ability to identify these patterns and use them to enhance the predictability of the extremes is therefore a topic of crucial societal and economic value. We propose a novel predictability pathway for extreme events, by building upon recent advances in dynamical systems theory. We use two simple dynamical systems metrics - local dimension and persistence - to identify sets of similar large-scale atmospheric flow patterns which present a coherent temporal evolution. When these patterns correspond to weather extremes, they therefore afford a particularly good forward predictability. We specifically test this technique on European winter temperatures, whose variability largely depends on the atmospheric circulation in the North Atlantic region. We find that our dynamical systems approach provides predictability of large-scale temperature extremes up to one week in advance.

HEPCloud, a New Paradigm for HEP Facilities: CMS Amazon Web Services Investigation

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

Holzman, Burt; Bauerdick, Lothar A. T.; Bockelman, Brian

Historically, high energy physics computing has been performed on large purpose-built computing systems. These began as single-site compute facilities, but have evolved into the distributed computing grids used today. Recently, there has been an exponential increase in the capacity and capability of commercial clouds. Cloud resources are highly virtualized and intended to be able to be flexibly deployed for a variety of computing tasks. There is a growing interest among the cloud providers to demonstrate the capability to perform large-scale scientific computing. In this paper, we discuss results from the CMS experiment using the Fermilab HEPCloud facility, which utilized bothmore » local Fermilab resources and virtual machines in the Amazon Web Services Elastic Compute Cloud. We discuss the planning, technical challenges, and lessons learned involved in performing physics workflows on a large-scale set of virtualized resources. Additionally, we will discuss the economics and operational efficiencies when executing workflows both in the cloud and on dedicated resources.« less

Intercomparison Project on Parameterizations of Large-Scale Dynamics for Simulations of Tropical Convection

NASA Astrophysics Data System (ADS)

Sobel, A. H.; Wang, S.; Bellon, G.; Sessions, S. L.; Woolnough, S.

2013-12-01

Parameterizations of large-scale dynamics have been developed in the past decade for studying the interaction between tropical convection and large-scale dynamics, based on our physical understanding of the tropical atmosphere. A principal advantage of these methods is that they offer a pathway to attack the key question of what controls large-scale variations of tropical deep convection. These methods have been used with both single column models (SCMs) and cloud-resolving models (CRMs) to study the interaction of deep convection with several kinds of environmental forcings. While much has been learned from these efforts, different groups' efforts are somewhat hard to compare. Different models, different versions of the large-scale parameterization methods, and experimental designs that differ in other ways are used. It is not obvious which choices are consequential to the scientific conclusions drawn and which are not. The methods have matured to the point that there is value in an intercomparison project. In this context, the Global Atmospheric Systems Study - Weak Temperature Gradient (GASS-WTG) project was proposed at the Pan-GASS meeting in September 2012. The weak temperature gradient approximation is one method to parameterize large-scale dynamics, and is used in the project name for historical reasons and simplicity, but another method, the damped gravity wave (DGW) method, will also be used in the project. The goal of the GASS-WTG project is to develop community understanding of the parameterization methods currently in use. Their strengths, weaknesses, and functionality in models with different physics and numerics will be explored in detail, and their utility to improve our understanding of tropical weather and climate phenomena will be further evaluated. This presentation will introduce the intercomparison project, including background, goals, and overview of the proposed experimental design. Interested groups will be invited to join (it will not be too late), and preliminary results will be presented.

Interactive Exploration and Analysis of Large-Scale Simulations Using Topology-Based Data Segmentation.

PubMed

Bremer, Peer-Timo; Weber, Gunther; Tierny, Julien; Pascucci, Valerio; Day, Marcus S; Bell, John B

2011-09-01

Large-scale simulations are increasingly being used to study complex scientific and engineering phenomena. As a result, advanced visualization and data analysis are also becoming an integral part of the scientific process. Often, a key step in extracting insight from these large simulations involves the definition, extraction, and evaluation of features in the space and time coordinates of the solution. However, in many applications, these features involve a range of parameters and decisions that will affect the quality and direction of the analysis. Examples include particular level sets of a specific scalar field, or local inequalities between derived quantities. A critical step in the analysis is to understand how these arbitrary parameters/decisions impact the statistical properties of the features, since such a characterization will help to evaluate the conclusions of the analysis as a whole. We present a new topological framework that in a single-pass extracts and encodes entire families of possible features definitions as well as their statistical properties. For each time step we construct a hierarchical merge tree a highly compact, yet flexible feature representation. While this data structure is more than two orders of magnitude smaller than the raw simulation data it allows us to extract a set of features for any given parameter selection in a postprocessing step. Furthermore, we augment the trees with additional attributes making it possible to gather a large number of useful global, local, as well as conditional statistic that would otherwise be extremely difficult to compile. We also use this representation to create tracking graphs that describe the temporal evolution of the features over time. Our system provides a linked-view interface to explore the time-evolution of the graph interactively alongside the segmentation, thus making it possible to perform extensive data analysis in a very efficient manner. We demonstrate our framework by extracting and analyzing burning cells from a large-scale turbulent combustion simulation. In particular, we show how the statistical analysis enabled by our techniques provides new insight into the combustion process.

Tools for Observation: Art and the Scientific Process

NASA Astrophysics Data System (ADS)

Pettit, E. C.; Coryell-Martin, M.; Maisch, K.

2015-12-01

Art can support the scientific process during different phases of a scientific discovery. Art can help explain and extend the scientific concepts for the general public; in this way art is a powerful tool for communication. Art can aid the scientist in processing and interpreting the data towards an understanding of the concepts and processes; in this way art is powerful - if often subconscious - tool to inform the process of discovery. Less often acknowledged, art can help engage students and inspire scientists during the initial development of ideas, observations, and questions; in this way art is a powerful tool to develop scientific questions and hypotheses. When we use art as a tool for communication of scientific discoveries, it helps break down barriers and makes science concepts less intimidating and more accessible and understandable for the learner. Scientists themselves use artistic concepts and processes - directly or indirectly - to help deepen their understanding. Teachers are following suit by using art more to stimulate students' creative thinking and problem solving. We show the value of teaching students to use the artistic "way of seeing" to develop their skills in observation, questioning, and critical thinking. In this way, art can be a powerful tool to engage students (from elementary to graduate) in the beginning phase of a scientific discovery, which is catalyzed by inquiry and curiosity. Through qualitative assessment of the Girls on Ice program, we show that many of the specific techniques taught by art teachers are valuable for science students to develop their observation skills. In particular, the concepts of contour drawing, squinting, gesture drawing, inverted drawing, and others can provide valuable training for student scientists. These art techniques encourage students to let go of preconceptions and "see" the world (the "data") in new ways they help students focus on both large-scale patterns and small-scale details.

An imperative need for global change research in tropical forests.

PubMed

Zhou, Xuhui; Fu, Yuling; Zhou, Lingyan; Li, Bo; Luo, Yiqi

2013-09-01

Tropical forests play a crucial role in regulating regional and global climate dynamics, and model projections suggest that rapid climate change may result in forest dieback or savannization. However, these predictions are largely based on results from leaf-level studies. How tropical forests respond and feedback to climate change is largely unknown at the ecosystem level. Several complementary approaches have been used to evaluate the effects of climate change on tropical forests, but the results are conflicting, largely due to confounding effects of multiple factors. Although altered precipitation and nitrogen deposition experiments have been conducted in tropical forests, large-scale warming and elevated carbon dioxide (CO2) manipulations are completely lacking, leaving many hypotheses and model predictions untested. Ecosystem-scale experiments to manipulate temperature and CO2 concentration individually or in combination are thus urgently needed to examine their main and interactive effects on tropical forests. Such experiments will provide indispensable data and help gain essential knowledge on biogeochemical, hydrological and biophysical responses and feedbacks of tropical forests to climate change. These datasets can also inform regional and global models for predicting future states of tropical forests and climate systems. The success of such large-scale experiments in natural tropical forests will require an international framework to coordinate collaboration so as to meet the challenges in cost, technological infrastructure and scientific endeavor.

Analysis of temporal-longitudinal-latitudinal characteristics in the global ionosphere based on tensor rank-1 decomposition

NASA Astrophysics Data System (ADS)

Lu, Shikun; Zhang, Hao; Li, Xihai; Li, Yihong; Niu, Chao; Yang, Xiaoyun; Liu, Daizhi

2018-03-01

Combining analyses of spatial and temporal characteristics of the ionosphere is of great significance for scientific research and engineering applications. Tensor decomposition is performed to explore the temporal-longitudinal-latitudinal characteristics in the ionosphere. Three-dimensional tensors are established based on the time series of ionospheric vertical total electron content maps obtained from the Centre for Orbit Determination in Europe. To obtain large-scale characteristics of the ionosphere, rank-1 decomposition is used to obtain U^{(1)}, U^{(2)}, and U^{(3)}, which are the resulting vectors for the time, longitude, and latitude modes, respectively. Our initial finding is that the correspondence between the frequency spectrum of U^{(1)} and solar variation indicates that rank-1 decomposition primarily describes large-scale temporal variations in the global ionosphere caused by the Sun. Furthermore, the time lags between the maxima of the ionospheric U^{(2)} and solar irradiation range from 1 to 3.7 h without seasonal dependence. The differences in time lags may indicate different interactions between processes in the magnetosphere-ionosphere-thermosphere system. Based on the dataset displayed in the geomagnetic coordinates, the position of the barycenter of U^{(3)} provides evidence for north-south asymmetry (NSA) in the large-scale ionospheric variations. The daily variation in such asymmetry indicates the influences of solar ionization. The diurnal geomagnetic coordinate variations in U^{(3)} show that the large-scale EIA (equatorial ionization anomaly) variations during the day and night have similar characteristics. Considering the influences of geomagnetic disturbance on ionospheric behavior, we select the geomagnetic quiet GIMs to construct the ionospheric tensor. The results indicate that the geomagnetic disturbances have little effect on large-scale ionospheric characteristics.

Large scale and cloud-based multi-model analytics experiments on climate change data in the Earth System Grid Federation

NASA Astrophysics Data System (ADS)

Fiore, Sandro; Płóciennik, Marcin; Doutriaux, Charles; Blanquer, Ignacio; Barbera, Roberto; Donvito, Giacinto; Williams, Dean N.; Anantharaj, Valentine; Salomoni, Davide D.; Aloisio, Giovanni

2017-04-01

In many scientific domains such as climate, data is often n-dimensional and requires tools that support specialized data types and primitives to be properly stored, accessed, analysed and visualized. Moreover, new challenges arise in large-scale scenarios and eco-systems where petabytes (PB) of data can be available and data can be distributed and/or replicated, such as the Earth System Grid Federation (ESGF) serving the Coupled Model Intercomparison Project, Phase 5 (CMIP5) experiment, providing access to 2.5PB of data for the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). A case study on climate models intercomparison data analysis addressing several classes of multi-model experiments is being implemented in the context of the EU H2020 INDIGO-DataCloud project. Such experiments require the availability of large amount of data (multi-terabyte order) related to the output of several climate models simulations as well as the exploitation of scientific data management tools for large-scale data analytics. More specifically, the talk discusses in detail a use case on precipitation trend analysis in terms of requirements, architectural design solution, and infrastructural implementation. The experiment has been tested and validated on CMIP5 datasets, in the context of a large scale distributed testbed across EU and US involving three ESGF sites (LLNL, ORNL, and CMCC) and one central orchestrator site (PSNC). The general "environment" of the case study relates to: (i) multi-model data analysis inter-comparison challenges; (ii) addressed on CMIP5 data; and (iii) which are made available through the IS-ENES/ESGF infrastructure. The added value of the solution proposed in the INDIGO-DataCloud project are summarized in the following: (i) it implements a different paradigm (from client- to server-side); (ii) it intrinsically reduces data movement; (iii) it makes lightweight the end-user setup; (iv) it fosters re-usability (of data, final/intermediate products, workflows, sessions, etc.) since everything is managed on the server-side; (v) it complements, extends and interoperates with the ESGF stack; (vi) it provides a "tool" for scientists to run multi-model experiments, and finally; and (vii) it can drastically reduce the time-to-solution for these experiments from weeks to hours. At the time the contribution is being written, the proposed testbed represents the first concrete implementation of a distributed multi-model experiment in the ESGF/CMIP context joining server-side and parallel processing, end-to-end workflow management and cloud computing. As opposed to the current scenario based on search & discovery, data download, and client-based data analysis, the INDIGO-DataCloud architectural solution described in this contribution addresses the scientific computing & analytics requirements by providing a paradigm shift based on server-side and high performance big data frameworks jointly with two-level workflow management systems realized at the PaaS level via a cloud infrastructure.

Orthographic and Phonological Neighborhood Databases across Multiple Languages.

PubMed

Marian, Viorica

2017-01-01

The increased globalization of science and technology and the growing number of bilinguals and multilinguals in the world have made research with multiple languages a mainstay for scholars who study human function and especially those who focus on language, cognition, and the brain. Such research can benefit from large-scale databases and online resources that describe and measure lexical, phonological, orthographic, and semantic information. The present paper discusses currently-available resources and underscores the need for tools that enable measurements both within and across multiple languages. A general review of language databases is followed by a targeted introduction to databases of orthographic and phonological neighborhoods. A specific focus on CLEARPOND illustrates how databases can be used to assess and compare neighborhood information across languages, to develop research materials, and to provide insight into broad questions about language. As an example of how using large-scale databases can answer questions about language, a closer look at neighborhood effects on lexical access reveals that not only orthographic, but also phonological neighborhoods can influence visual lexical access both within and across languages. We conclude that capitalizing upon large-scale linguistic databases can advance, refine, and accelerate scientific discoveries about the human linguistic capacity.

Quantifying expert consensus against the existence of a secret, large-scale atmospheric spraying program

NASA Astrophysics Data System (ADS)

Shearer, Christine; West, Mick; Caldeira, Ken; Davis, Steven J.

2016-08-01

Nearly 17% of people in an international survey said they believed the existence of a secret large-scale atmospheric program (SLAP) to be true or partly true. SLAP is commonly referred to as ‘chemtrails’ or ‘covert geoengineering’, and has led to a number of websites purported to show evidence of widespread chemical spraying linked to negative impacts on human health and the environment. To address these claims, we surveyed two groups of experts—atmospheric chemists with expertize in condensation trails and geochemists working on atmospheric deposition of dust and pollution—to scientifically evaluate for the first time the claims of SLAP theorists. Results show that 76 of the 77 scientists (98.7%) that took part in this study said they had not encountered evidence of a SLAP, and that the data cited as evidence could be explained through other factors, including well-understood physics and chemistry associated with aircraft contrails and atmospheric aerosols. Our goal is not to sway those already convinced that there is a secret, large-scale spraying program—who often reject counter-evidence as further proof of their theories—but rather to establish a source of objective science that can inform public discourse.

[Research and application: scale of knowledge, attitude, and behavior of lifestyle intervention in a diabetes high-risk population].

PubMed

Wang, W J

2016-07-06

There is a large population at high risk for diabetes in China, and there has been a dramatic increase in the incidence of diabetes in the country over the past 30 years. Interventions targeting the individual risk factors of diabetes can effectively prevent diabetes; these include factors such as an unhealthy diet, lack of physical activity, overweight, and obesity, among others. Evaluation of related knowledge, attitudes, and behaviors before and after intervention using appropriate scales can measure population demands and the effectiveness of interventions. Scientificity and practicability are basic requirements of scale development. The theoretical basis and measuring items of a scale should be consistent with the theory of behavior change and should measure the content of interventions in a standardized and detailed manner to produce good validity, reliability, and acceptability. The scale of knowledge, attitude, and behavior of lifestyle intervention in a diabetes high-risk population is a tool for demand evaluation and effect evaluation of lifestyle intervention that has good validity and reliability. Established by the National Center for Chronic and Noncommunicable Disease Control and Prevention, its use can help to decrease the Chinese population at high risk for diabetes through targeted and scientifically sound lifestyle interventions. Future development of intervention evaluation scales for useing in high-risk populations should consider new factors and characteristics of the different populations, to develop new scales and modify or simplify existing ones, as well as to extend the measurement dimensions to barriers and supporting environment for behaviors change.

Effects of pore-scale physics on uranium geochemistry in Hanford sediments

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

Hu, Qinhong; Ewing, Robert P.

Overall, this work examines a key scientific issue, mass transfer limitations at the pore-scale, using both new instruments with high spatial resolution, and new conceptual and modeling paradigms. The complementary laboratory and numerical approaches connect pore-scale physics to macroscopic measurements, providing a previously elusive scale integration. This Exploratory research project produced five peer-reviewed journal publications and eleven scientific presentations. This work provides new scientific understanding, allowing the DOE to better incorporate coupled physical and chemical processes into decision making for environmental remediation and long-term stewardship.

The Pilot Lunar Geologic Mapping Project: Summary Results and Recommendations from the Copernicus Quadrangle

NASA Technical Reports Server (NTRS)

Skinner, J. A., Jr.; Gaddis, L. R.; Hagerty, J. J.

2010-01-01

The first systematic lunar geologic maps were completed at 1:1M scale for the lunar near side during the 1960s using telescopic and Lunar Orbiter (LO) photographs [1-3]. The program under which these maps were completed established precedents for map base, scale, projection, and boundaries in order to avoid widely discrepant products. A variety of geologic maps were subsequently produced for various purposes, including 1:5M scale global maps [4-9] and large scale maps of high scientific interest (including the Apollo landing sites) [10]. Since that time, lunar science has benefitted from an abundance of surface information, including high resolution images and diverse compositional data sets, which have yielded a host of topical planetary investigations. The existing suite of lunar geologic maps and topical studies provide exceptional context in which to unravel the geologic history of the Moon. However, there has been no systematic approach to lunar geologic mapping since the flight of post-Apollo scientific orbiters. Geologic maps provide a spatial and temporal framework wherein observations can be reliably benchmarked and compared. As such, a lack of a systematic mapping program means that modern (post- Apollo) data sets, their scientific ramifications, and the lunar scientists who investigate these data, are all marginalized in regard to geologic mapping. Marginalization weakens the overall understanding of the geologic evolution of the Moon and unnecessarily partitions lunar research. To bridge these deficiencies, we began a pilot geologic mapping project in 2005 as a means to assess the interest, relevance, and technical methods required for a renewed lunar geologic mapping program [11]. Herein, we provide a summary of the pilot geologic mapping project, which focused on the geologic materials and stratigraphic relationships within the Copernicus quadrangle (0-30degN, 0-45degW).

Topology and evolution of technology innovation networks

NASA Astrophysics Data System (ADS)

Valverde, Sergi; Solé, Ricard V.; Bedau, Mark A.; Packard, Norman

2007-11-01

The web of relations linking technological innovation can be fairly described in terms of patent citations. The resulting patent citation network provides a picture of the large-scale organization of innovations and its time evolution. Here we study the patterns of change of patents registered by the U.S. Patent and Trademark Office. We show that the scaling behavior exhibited by this network is consistent with a preferential attachment mechanism together with a Weibull-shaped aging term. Such an attachment kernel is shared by scientific citation networks, thus indicating a universal type of mechanism linking ideas and designs and their evolution. The implications for evolutionary theory of innovation are discussed.

Report of the Working Group on Large-Scale Computing in Aeronautics.

DTIC Science & Technology

1984-06-01

incompressible approximations that are presently made in the lifting line or lifting surface representations of rotor blades. Finally, viscous effects in the forms... Effects of Rotor Model Degradation in the Accuracy of Rotocraft Real-Time Simulation, NASA TN D-8378;1977. 20. Gullen, R. K., Cattell, C. S., and Overton...assistance to member nations for the purpose of increasing their scientific and technical potential; - Recommending effective ways for the member nations

Assessing a Science Graduate School Recruitment Symposium.

PubMed

González-Espada, Wilson; Díaz-Muñoz, Greetchen; Feliú-Mójer, Mónica; Flores-Otero, Jacqueline; Fortis-Santiago, Yaihara; Guerrero-Medina, Giovanna; López-Casillas, Marcos; Colón-Ramos, Daniel A; Fernández-Repollet, Emma

2015-12-01

Ciencia Puerto Rico, a non-profit organization dedicated to promoting science, research and scientific education among Latinos, organized an educational symposium to provide college science majors the tools, opportunities and advice to pursue graduate degrees and succeed in the STEM disciplines. In this article we share our experiences and lessons learned, for others interested in developing large-scale events to recruit underrepresented minorities to STEM and in evaluating the effectiveness of these efforts.

Control Circuitry for High Speed VLSI (Very Large Scale Integration) Winograd Fourier Transform Processors.

DTIC Science & Technology

1985-12-01

Office of Scientific Research , and Air Force Space Division are sponsoring research for the development of a high speed DFT processor. This DFT...to the arithmetic circuitry through a master/slave 11-15 %v OPR ONESHOT OUTPUT OUTPUT .., ~ INITIALIZATION COLUMN’ 00 N DONE CUTRPLANE PLAtNE Figure...Since the TSP is an NP-complete problem, many mathematicians, operations researchers , computer scientists and the like have proposed heuristic

Assessing a Science Graduate School Recruitment Symposium

PubMed Central

González-Espada, Wilson; Díaz-Muñoz, Greetchen; Feliú-Mójer, Mónica; Flores-Otero, Jacqueline; Fortis-Santiago, Yaihara; Guerrero-Medina, Giovanna; López-Casillas, Marcos; Colón-Ramos, Daniel A.; Fernández-Repollet, Emma

2015-01-01

Ciencia Puerto Rico, a non-profit organization dedicated to promoting science, research and scientific education among Latinos, organized an educational symposium to provide college science majors the tools, opportunities and advice to pursue graduate degrees and succeed in the STEM disciplines. In this article we share our experiences and lessons learned, for others interested in developing large-scale events to recruit underrepresented minorities to STEM and in evaluating the effectiveness of these efforts. PMID:26770074

IAHS/WMO Working Group for GEWEX Progress Report

NASA Astrophysics Data System (ADS)

Schultz, Gert; Colenbrander, H.

The International Council of Scientific Unions (ICSU) and the World Meteorological Organization (WMO) undertook the Global Energy and Water Cycle Experiment (GEWEX). In early 1989 in Pasadena, Calif., the Scientific Steering Group (SSG) for GEWEX of the Joint Scientific Committee (JSC) for the World Climate Research Program (WCRP) held its first meeting. GEWEX objectives were formulated and documented in the “Report of the First Session of the JSC-Scientific Steering Group for GEWEX,” published as WCRP-25, WMO/TD-No. 321.Vit Klemes, Victoria, B.C., Canada, who represented the International Association of Hydrological Sciences (IAHS) at the SSG meeting, stated the IAHS intention to play an active role in GEWEX. IAHS described GEWEX as “the development, validation and use of large-scale hydrological models, coupled with general circulation models, which make use of data from space observing systems.” IAHS then established the IAHS/WMO Working Group for GEWEX, which held its first meeting during the IAHS Third Scientific Assembly in Baltimore, May 19, 1989. Klemes was the first working group chairman, and passed the title to Gert A. Schultz, Ruhr University, Bochum, Germany, in the fall of 1989.

Interactive Scripting for Analysis and Visualization of Arbitrarily Large, Disparately Located Climate Data Ensembles Using a Progressive Runtime Server

NASA Astrophysics Data System (ADS)

Christensen, C.; Summa, B.; Scorzelli, G.; Lee, J. W.; Venkat, A.; Bremer, P. T.; Pascucci, V.

2017-12-01

Massive datasets are becoming more common due to increasingly detailed simulations and higher resolution acquisition devices. Yet accessing and processing these huge data collections for scientific analysis is still a significant challenge. Solutions that rely on extensive data transfers are increasingly untenable and often impossible due to lack of sufficient storage at the client side as well as insufficient bandwidth to conduct such large transfers, that in some cases could entail petabytes of data. Large-scale remote computing resources can be useful, but utilizing such systems typically entails some form of offline batch processing with long delays, data replications, and substantial cost for any mistakes. Both types of workflows can severely limit the flexible exploration and rapid evaluation of new hypotheses that are crucial to the scientific process and thereby impede scientific discovery. In order to facilitate interactivity in both analysis and visualization of these massive data ensembles, we introduce a dynamic runtime system suitable for progressive computation and interactive visualization of arbitrarily large, disparately located spatiotemporal datasets. Our system includes an embedded domain-specific language (EDSL) that allows users to express a wide range of data analysis operations in a simple and abstract manner. The underlying runtime system transparently resolves issues such as remote data access and resampling while at the same time maintaining interactivity through progressive and interruptible processing. Computations involving large amounts of data can be performed remotely in an incremental fashion that dramatically reduces data movement, while the client receives updates progressively thereby remaining robust to fluctuating network latency or limited bandwidth. This system facilitates interactive, incremental analysis and visualization of massive remote datasets up to petabytes in size. Our system is now available for general use in the community through both docker and anaconda.

National Laboratory for Advanced Scientific Visualization at UNAM - Mexico

NASA Astrophysics Data System (ADS)

Manea, Marina; Constantin Manea, Vlad; Varela, Alfredo

2016-04-01

In 2015, the National Autonomous University of Mexico (UNAM) joined the family of Universities and Research Centers where advanced visualization and computing plays a key role to promote and advance missions in research, education, community outreach, as well as business-oriented consulting. This initiative provides access to a great variety of advanced hardware and software resources and offers a range of consulting services that spans a variety of areas related to scientific visualization, among which are: neuroanatomy, embryonic development, genome related studies, geosciences, geography, physics and mathematics related disciplines. The National Laboratory for Advanced Scientific Visualization delivers services through three main infrastructure environments: the 3D fully immersive display system Cave, the high resolution parallel visualization system Powerwall, the high resolution spherical displays Earth Simulator. The entire visualization infrastructure is interconnected to a high-performance-computing-cluster (HPCC) called ADA in honor to Ada Lovelace, considered to be the first computer programmer. The Cave is an extra large 3.6m wide room with projected images on the front, left and right, as well as floor walls. Specialized crystal eyes LCD-shutter glasses provide a strong stereo depth perception, and a variety of tracking devices allow software to track the position of a user's hand, head and wand. The Powerwall is designed to bring large amounts of complex data together through parallel computing for team interaction and collaboration. This system is composed by 24 (6x4) high-resolution ultra-thin (2 mm) bezel monitors connected to a high-performance GPU cluster. The Earth Simulator is a large (60") high-resolution spherical display used for global-scale data visualization like geophysical, meteorological, climate and ecology data. The HPCC-ADA, is a 1000+ computing core system, which offers parallel computing resources to applications that requires large quantity of memory as well as large and fast parallel storage systems. The entire system temperature is controlled by an energy and space efficient cooling solution, based on large rear door liquid cooled heat exchangers. This state-of-the-art infrastructure will boost research activities in the region, offer a powerful scientific tool for teaching at undergraduate and graduate levels, and enhance association and cooperation with business-oriented organizations.

A Study about the 3S-based Great Ruins Monitoring and Early-warning System

NASA Astrophysics Data System (ADS)

Xuefeng, W.; Zhongyuan, H.; Gongli, L.; Li, Z.

2015-08-01

Large-scale urbanization construction and new countryside construction, frequent natural disasters, and natural corrosion pose severe threat to the great ruins. It is not uncommon that the cultural relics are damaged and great ruins are occupied. Now the ruins monitoring mainly adopt general monitoring data processing system which can not effectively exert management, display, excavation analysis and data sharing of the relics monitoring data. Meanwhile those general software systems require layout of large number of devices or apparatuses, but they are applied to small-scope relics monitoring only. Therefore, this paper proposes a method to make use of the stereoscopic cartographic satellite technology to improve and supplement the great ruins monitoring index system and combine GIS and GPS to establish a highly automatic, real-time and intelligent great ruins monitoring and early-warning system in order to realize collection, processing, updating, spatial visualization, analysis, distribution and sharing of the monitoring data, and provide scientific and effective data for the relics protection, scientific planning, reasonable development and sustainable utilization.

On humanity's role in space

NASA Technical Reports Server (NTRS)

Von Puttkamer, J.

1978-01-01

Manned spaceflight is considered within the framework of two broad categories: human exploitation of space for economic or scientific gain, and human habitation of space as a place where man may live, grow, and actualize himself. With the advent of the Space Shuttle, exploitation of space will take the form of new product development. This will continue during the 1990s as the new products are manufactured on a scale large enough to be profitable. The turn of the century should see major industries in space, and large space habitats. Thus, the question of mankind's existential needs arises. In addition to basic physical needs, the spiritual and cultural requirements of human beings must be considered. The impact of man's presence in space upon human culture in general is discussed with reference to international cooperation, public interest in space programs, scientific advancement, the basic urge to explore, and the density of mankind as a whole; which will become free of external constraints as we step into the cosmos.

Cross-Identification of Astronomical Catalogs on Multiple GPUs

NASA Astrophysics Data System (ADS)

Lee, M. A.; Budavári, T.

2013-10-01

One of the most fundamental problems in observational astronomy is the cross-identification of sources. Observations are made in different wavelengths, at different times, and from different locations and instruments, resulting in a large set of independent observations. The scientific outcome is often limited by our ability to quickly perform meaningful associations between detections. The matching, however, is difficult scientifically, statistically, as well as computationally. The former two require detailed physical modeling and advanced probabilistic concepts; the latter is due to the large volumes of data and the problem's combinatorial nature. In order to tackle the computational challenge and to prepare for future surveys, whose measurements will be exponentially increasing in size past the scale of feasible CPU-based solutions, we developed a new implementation which addresses the issue by performing the associations on multiple Graphics Processing Units (GPUs). Our implementation utilizes up to 6 GPUs in combination with the Thrust library to achieve an over 40x speed up verses the previous best implementation running on a multi-CPU SQL Server.

Remote experimental site concept development

NASA Astrophysics Data System (ADS)

Casper, Thomas A.; Meyer, William; Butner, David

1995-01-01

Scientific research is now often conducted on large and expensive experiments that utilize collaborative efforts on a national or international scale to explore physics and engineering issues. This is particularly true for the current US magnetic fusion energy program where collaboration on existing facilities has increased in importance and will form the basis for future efforts. As fusion energy research approaches reactor conditions, the trend is towards fewer large and expensive experimental facilities, leaving many major institutions without local experiments. Since the expertise of various groups is a valuable resource, it is important to integrate these teams into an overall scientific program. To sustain continued involvement in experiments, scientists are now often required to travel frequently, or to move their families, to the new large facilities. This problem is common to many other different fields of scientific research. The next-generation tokamaks, such as the Tokamak Physics Experiment (TPX) or the International Thermonuclear Experimental Reactor (ITER), will operate in steady-state or long pulse mode and produce fluxes of fusion reaction products sufficient to activate the surrounding structures. As a direct consequence, remote operation requiring robotics and video monitoring will become necessary, with only brief and limited access to the vessel area allowed. Even the on-site control room, data acquisition facilities, and work areas will be remotely located from the experiment, isolated by large biological barriers, and connected with fiber-optics. Current planning for the ITER experiment includes a network of control room facilities to be located in the countries of the four major international partners; USA, Russian Federation, Japan, and the European Community.

Metadata Management on the SCEC PetaSHA Project: Helping Users Describe, Discover, Understand, and Use Simulation Data in a Large-Scale Scientific Collaboration

NASA Astrophysics Data System (ADS)

Okaya, D.; Deelman, E.; Maechling, P.; Wong-Barnum, M.; Jordan, T. H.; Meyers, D.

2007-12-01

Large scientific collaborations, such as the SCEC Petascale Cyberfacility for Physics-based Seismic Hazard Analysis (PetaSHA) Project, involve interactions between many scientists who exchange ideas and research results. These groups must organize, manage, and make accessible their community materials of observational data, derivative (research) results, computational products, and community software. The integration of scientific workflows as a paradigm to solve complex computations provides advantages of efficiency, reliability, repeatability, choices, and ease of use. The underlying resource needed for a scientific workflow to function and create discoverable and exchangeable products is the construction, tracking, and preservation of metadata. In the scientific workflow environment there is a two-tier structure of metadata. Workflow-level metadata and provenance describe operational steps, identity of resources, execution status, and product locations and names. Domain-level metadata essentially define the scientific meaning of data, codes and products. To a large degree the metadata at these two levels are separate. However, between these two levels is a subset of metadata produced at one level but is needed by the other. This crossover metadata suggests that some commonality in metadata handling is needed. SCEC researchers are collaborating with computer scientists at SDSC, the USC Information Sciences Institute, and Carnegie Mellon Univ. in order to perform earthquake science using high-performance computational resources. A primary objective of the "PetaSHA" collaboration is to perform physics-based estimations of strong ground motion associated with real and hypothetical earthquakes located within Southern California. Construction of 3D earth models, earthquake representations, and numerical simulation of seismic waves are key components of these estimations. Scientific workflows are used to orchestrate the sequences of scientific tasks and to access distributed computational facilities such as the NSF TeraGrid. Different types of metadata are produced and captured within the scientific workflows. One workflow within PetaSHA ("Earthworks") performs a linear sequence of tasks with workflow and seismological metadata preserved. Downstream scientific codes ingest these metadata produced by upstream codes. The seismological metadata uses attribute-value pairing in plain text; an identified need is to use more advanced handling methods. Another workflow system within PetaSHA ("Cybershake") involves several complex workflows in order to perform statistical analysis of ground shaking due to thousands of hypothetical but plausible earthquakes. Metadata management has been challenging due to its construction around a number of legacy scientific codes. We describe difficulties arising in the scientific workflow due to the lack of this metadata and suggest corrective steps, which in some cases include the cultural shift of domain science programmers coding for metadata.

Unified Performance and Power Modeling of Scientific Workloads

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

Song, Shuaiwen; Barker, Kevin J.; Kerbyson, Darren J.

2013-11-17

It is expected that scientific applications executing on future large-scale HPC must be optimized not only in terms of performance, but also in terms of power consumption. As power and energy become increasingly constrained resources, researchers and developers must have access to tools that will allow for accurate prediction of both performance and power consumption. Reasoning about performance and power consumption in concert will be critical for achieving maximum utilization of limited resources on future HPC systems. To this end, we present a unified performance and power model for the Nek-Bone mini-application developed as part of the DOE's CESAR Exascalemore » Co-Design Center. Our models consider the impact of computation, point-to-point communication, and collective communication« less

NASA/MSFC FY92 Earth Science and Applications Program Research Review

NASA Technical Reports Server (NTRS)

Arnold, James E. (Editor); Leslie, Fred W. (Editor)

1993-01-01

A large amount of attention has recently been given to global issues such as the ozone hole, tropospheric temperature variability, etc. A scientific challenge is to better understand atmospheric processes on a variety of spatial and temporal scales in order to predict environmental changes. Measurement of geophysical parameters such as wind, temperature, and moisture are needed to validate theories, provide analyzed data sets, and initialize or constrain numerical models. One of NASA's initiatives is the Mission to Planet Earth Program comprised of an Earth Observation System (EOS) and the scientific strategy to analyze these data. This work describes these efforts in the context of satellite data analysis and fundamental studies of atmospheric dynamics which examine selected processes important to the global circulation.

U.S. Geological Survey coastal and marine geology research; recent highlights and achievements

USGS Publications Warehouse

Williams, S. Jeffress; Barnes, Peter W.; Prager, Ellen J.

2000-01-01

The USGS Coastal and Marine Geology Program has large-scale national and regional research projects that focus on environmental quality, geologic hazards, natural resources, and information transfer. This Circular highlights recent scientific findings of the program, which play a vital role in the USGS endeavor to understand human interactions with the natural environment and to determine how the fundamental geologic processes controlling the Earth work. The scientific knowledge acquired through USGS research and monitoring is critically needed by planners, government agencies, and the public. Effective communication of the results of this research will enable the USGS Coastal and Marine Geology Program to play an integral part in assisting the Nation in responding the pressing Earth science challenges of the 21st century.

Lakeside: Merging Urban Design with Scientific Analysis

ScienceCinema

Guzowski, Leah; Catlett, Charlie; Woodbury, Ed

2018-01-16

Researchers at the U.S. Department of Energy's Argonne National Laboratory and the University of Chicago are developing tools that merge urban design with scientific analysis to improve the decision-making process associated with large-scale urban developments. One such tool, called LakeSim, has been prototyped with an initial focus on consumer-driven energy and transportation demand, through a partnership with the Chicago-based architectural and engineering design firm Skidmore, Owings & Merrill, Clean Energy Trust and developer McCaffery Interests. LakeSim began with the need to answer practical questions about urban design and planning, requiring a better understanding about the long-term impact of design decisions on energy and transportation demand for a 600-acre development project on Chicago's South Side - the Chicago Lakeside Development project.

The European perspective for LSST

NASA Astrophysics Data System (ADS)

Gangler, Emmanuel

2017-06-01

LSST is a next generation telescope that will produce an unprecedented data flow. The project goal is to deliver data products such as images and catalogs thus enabling scientific analysis for a wide community of users. As a large scale survey, LSST data will be complementary with other facilities in a wide range of scientific domains, including data from ESA or ESO. European countries have invested in LSST since 2007, in the construction of the camera as well as in the computing effort. This latter will be instrumental in designing the next step: how to distribute LSST data to Europe. Astroinformatics challenges for LSST indeed includes not only the analysis of LSST big data, but also the practical efficiency of the data access.

The efficacy of student-centered instruction in supporting science learning.

PubMed

Granger, E M; Bevis, T H; Saka, Y; Southerland, S A; Sampson, V; Tate, R L

2012-10-05

Transforming science learning through student-centered instruction that engages students in a variety of scientific practices is central to national science-teaching reform efforts. Our study employed a large-scale, randomized-cluster experimental design to compare the effects of student-centered and teacher-centered approaches on elementary school students' understanding of space-science concepts. Data included measures of student characteristics and learning and teacher characteristics and fidelity to the instructional approach. Results reveal that learning outcomes were higher for students enrolled in classrooms engaging in scientific practices through a student-centered approach; two moderators were identified. A statistical search for potential causal mechanisms for the observed outcomes uncovered two potential mediators: students' understanding of models and evidence and the self-efficacy of teachers.

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

PubMed

Bicer, Tekin; Gürsoy, Doğa; Andrade, Vincent De; Kettimuthu, Rajkumar; Scullin, William; Carlo, Francesco De; Foster, Ian T

2017-01-01

Modern synchrotron light sources and detectors produce data at such scale and complexity that large-scale computation is required to unleash their full power. One of the widely used imaging techniques that generates data at tens of gigabytes per second is computed tomography (CT). Although CT experiments result in rapid data generation, the analysis and reconstruction of the collected data may require hours or even days of computation time with a medium-sized workstation, which hinders the scientific progress that relies on the results of analysis. We present Trace, a data-intensive computing engine that we have developed to enable high-performance implementation of iterative tomographic reconstruction algorithms for parallel computers. Trace 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 that we apply to the replicated reconstruction objects and evaluate them using tomography datasets collected at the Advanced Photon Source. Our experimental evaluations show that our optimizations and parallelization techniques can provide 158× speedup using 32 compute nodes (384 cores) over a single-core configuration and decrease the end-to-end processing time of a large sinogram (with 4501 × 1 × 22,400 dimensions) from 12.5 h to <5 min per iteration. The proposed tomographic reconstruction engine can efficiently process large-scale tomographic data using many compute nodes and minimize reconstruction times.

High performance computing and communications: Advancing the frontiers of information technology

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

NONE

1997-12-31

This report, which supplements the President`s Fiscal Year 1997 Budget, describes the interagency High Performance Computing and Communications (HPCC) Program. The HPCC Program will celebrate its fifth anniversary in October 1996 with an impressive array of accomplishments to its credit. Over its five-year history, the HPCC Program has focused on developing high performance computing and communications technologies that can be applied to computation-intensive applications. Major highlights for FY 1996: (1) High performance computing systems enable practical solutions to complex problems with accuracies not possible five years ago; (2) HPCC-funded research in very large scale networking techniques has been instrumental inmore » the evolution of the Internet, which continues exponential growth in size, speed, and availability of information; (3) The combination of hardware capability measured in gigaflop/s, networking technology measured in gigabit/s, and new computational science techniques for modeling phenomena has demonstrated that very large scale accurate scientific calculations can be executed across heterogeneous parallel processing systems located thousands of miles apart; (4) Federal investments in HPCC software R and D support researchers who pioneered the development of parallel languages and compilers, high performance mathematical, engineering, and scientific libraries, and software tools--technologies that allow scientists to use powerful parallel systems to focus on Federal agency mission applications; and (5) HPCC support for virtual environments has enabled the development of immersive technologies, where researchers can explore and manipulate multi-dimensional scientific and engineering problems. Educational programs fostered by the HPCC Program have brought into classrooms new science and engineering curricula designed to teach computational science. This document contains a small sample of the significant HPCC Program accomplishments in FY 1996.« less

Evaluating non-relational storage technology for HEP metadata and meta-data catalog

NASA Astrophysics Data System (ADS)

Grigorieva, M. A.; Golosova, M. V.; Gubin, M. Y.; Klimentov, A. A.; Osipova, V. V.; Ryabinkin, E. A.

2016-10-01

Large-scale scientific experiments produce vast volumes of data. These data are stored, processed and analyzed in a distributed computing environment. The life cycle of experiment is managed by specialized software like Distributed Data Management and Workload Management Systems. In order to be interpreted and mined, experimental data must be accompanied by auxiliary metadata, which are recorded at each data processing step. Metadata describes scientific data and represent scientific objects or results of scientific experiments, allowing them to be shared by various applications, to be recorded in databases or published via Web. Processing and analysis of constantly growing volume of auxiliary metadata is a challenging task, not simpler than the management and processing of experimental data itself. Furthermore, metadata sources are often loosely coupled and potentially may lead to an end-user inconsistency in combined information queries. To aggregate and synthesize a range of primary metadata sources, and enhance them with flexible schema-less addition of aggregated data, we are developing the Data Knowledge Base architecture serving as the intelligence behind GUIs and APIs.

Tracking Provenance of Earth Science Data

NASA Technical Reports Server (NTRS)

Tilmes, Curt; Yesha, Yelena; Halem, Milton

2010-01-01

Tremendous volumes of data have been captured, archived and analyzed. Sensors, algorithms and processing systems for transforming and analyzing the data are evolving over time. Web Portals and Services can create transient data sets on-demand. Data are transferred from organization to organization with additional transformations at every stage. Provenance in this context refers to the source of data and a record of the process that led to its current state. It encompasses the documentation of a variety of artifacts related to particular data. Provenance is important for understanding and using scientific datasets, and critical for independent confirmation of scientific results. Managing provenance throughout scientific data processing has gained interest lately and there are a variety of approaches. Large scale scientific datasets consisting of thousands to millions of individual data files and processes offer particular challenges. This paper uses the analogy of art history provenance to explore some of the concerns of applying provenance tracking to earth science data. It also illustrates some of the provenance issues with examples drawn from the Ozone Monitoring Instrument (OMI) Data Processing System (OMIDAPS) run at NASA's Goddard Space Flight Center by the first author.

Testing the robustness of Citizen Science projects: Evaluating the results of pilot project COMBER.

PubMed

Chatzigeorgiou, Giorgos; Faulwetter, Sarah; Dailianis, Thanos; Smith, Vincent Stuart; Koulouri, Panagiota; Dounas, Costas; Arvanitidis, Christos

2016-01-01

Citizen Science (CS) as a term implies a great deal of approaches and scopes involving many different fields of science. The number of the relevant projects globally has been increased significantly in the recent years. Large scale ecological questions can be answered only through extended observation networks and CS projects can support this effort. Although the need of such projects is apparent, an important part of scientific community cast doubt on the reliability of CS data sets. The pilot CS project COMBER has been created in order to provide evidence to answer the aforementioned question in the coastal marine biodiversity monitoring. The results of the current analysis show that a carefully designed CS project with clear hypotheses, wide participation and data sets validation, can be a valuable tool for the large scale and long term changes in marine biodiversity pattern change and therefore for relevant management and conservation issues.

Workplan for Catalyzing Collaboration with Amazonian Universities in the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA)

NASA Technical Reports Server (NTRS)

Brown, I. Foster; Moreira, Adriana

1997-01-01

Success of the Large-Scale Biosphere-Atmospheric Experiment in Amazonia (LBA) program depends on several critical factors, the most important being the effective participation of Amazonian researchers and institutions. Without host-county counterparts, particularly in Amazonia, many important studies cannot he undertaken due either to lack of qualified persons or to legal constraints. No less important, the acceptance of the LBA program in Amazonia is also dependent on what LBA can do for improving the scientific expertise in Amazonia. Gaining the active investment of Amazonian scientists in a comprehensive research program is not a trivial task. Potential collaborators are few, particularly where much of the research was to be originally focused - the southern arc of Brazilian Amazonia. The mid-term goals of the LBA Committee on Training and Education are to increase the number of collaborators and to demonstrate that LBA will be of benefit to the region.

Can a science-based definition of acupuncture improve clinical outcomes?

PubMed

Priebe, Ted; Stumpf, Steven H; Zalunardo, Rod

2017-05-01

Research on acupuncture has been muddled by attempts to bridge the ancient with the modern. Barriers to effectiveness research are reflected in recurring conflicts that include disagreement on use of the most basic terms, lack of standard intervention controls, and the absence of functional measures for assessing treatment effect. Acupuncture research has stalled at the "placebo barrier" wherein acupuncture is "no better than placebo." The most widely recognized comparative effectiveness research in acupuncture does not compare acupuncture treatment protocols within groups, thereby, mutating large scale effectiveness studies into large scale efficacy trials. Too often research in acupuncture attempts to tie outcomes to traditional belief systems thereby limiting usefulness of the research. The acupuncture research paradigm needs to focus more closely on a scientific definition of treatments and outcomes that compare protocols in terms of prevalent clinical issues such as relative effectiveness for treating pain.

Scalable parallel distance field construction for large-scale applications

DOE PAGES

Yu, Hongfeng; Xie, Jinrong; Ma, Kwan -Liu; ...

2015-10-01

Computing distance fields is fundamental to many scientific and engineering applications. Distance fields can be used to direct analysis and reduce data. In this paper, we present a highly scalable method for computing 3D distance fields on massively parallel distributed-memory machines. Anew distributed spatial data structure, named parallel distance tree, is introduced to manage the level sets of data and facilitate surface tracking overtime, resulting in significantly reduced computation and communication costs for calculating the distance to the surface of interest from any spatial locations. Our method supports several data types and distance metrics from real-world applications. We demonstrate itsmore » efficiency and scalability on state-of-the-art supercomputers using both large-scale volume datasets and surface models. We also demonstrate in-situ distance field computation on dynamic turbulent flame surfaces for a petascale combustion simulation. In conclusion, our work greatly extends the usability of distance fields for demanding applications.« less

Scalable Parallel Distance Field Construction for Large-Scale Applications.

PubMed

Yu, Hongfeng; Xie, Jinrong; Ma, Kwan-Liu; Kolla, Hemanth; Chen, Jacqueline H

2015-10-01

Computing distance fields is fundamental to many scientific and engineering applications. Distance fields can be used to direct analysis and reduce data. In this paper, we present a highly scalable method for computing 3D distance fields on massively parallel distributed-memory machines. A new distributed spatial data structure, named parallel distance tree, is introduced to manage the level sets of data and facilitate surface tracking over time, resulting in significantly reduced computation and communication costs for calculating the distance to the surface of interest from any spatial locations. Our method supports several data types and distance metrics from real-world applications. We demonstrate its efficiency and scalability on state-of-the-art supercomputers using both large-scale volume datasets and surface models. We also demonstrate in-situ distance field computation on dynamic turbulent flame surfaces for a petascale combustion simulation. Our work greatly extends the usability of distance fields for demanding applications.

Listening to the Deep: live monitoring of ocean noise and cetacean acoustic signals.

PubMed

André, M; van der Schaar, M; Zaugg, S; Houégnigan, L; Sánchez, A M; Castell, J V

2011-01-01

The development and broad use of passive acoustic monitoring techniques have the potential to help assessing the large-scale influence of artificial noise on marine organisms and ecosystems. Deep-sea observatories have the potential to play a key role in understanding these recent acoustic changes. LIDO (Listening to the Deep Ocean Environment) is an international project that is allowing the real-time long-term monitoring of marine ambient noise as well as marine mammal sounds at cabled and standalone observatories. Here, we present the overall development of the project and the use of passive acoustic monitoring (PAM) techniques to provide the scientific community with real-time data at large spatial and temporal scales. Special attention is given to the extraction and identification of high frequency cetacean echolocation signals given the relevance of detecting target species, e.g. beaked whales, in mitigation processes, e.g. during military exercises. Copyright © 2011. Published by Elsevier Ltd.

Scientific Visualization Tools for Enhancement of Undergraduate Research

NASA Astrophysics Data System (ADS)

Rodriguez, W. J.; Chaudhury, S. R.

2001-05-01

Undergraduate research projects that utilize remote sensing satellite instrument data to investigate atmospheric phenomena pose many challenges. A significant challenge is processing large amounts of multi-dimensional data. Remote sensing data initially requires mining; filtering of undesirable spectral, instrumental, or environmental features; and subsequently sorting and reformatting to files for easy and quick access. The data must then be transformed according to the needs of the investigation(s) and displayed for interpretation. These multidimensional datasets require views that can range from two-dimensional plots to multivariable-multidimensional scientific visualizations with animations. Science undergraduate students generally find these data processing tasks daunting. Generally, researchers are required to fully understand the intricacies of the dataset and write computer programs or rely on commercially available software, which may not be trivial to use. In the time that undergraduate researchers have available for their research projects, learning the data formats, programming languages, and/or visualization packages is impractical. When dealing with large multi-dimensional data sets appropriate Scientific Visualization tools are imperative in allowing students to have a meaningful and pleasant research experience, while producing valuable scientific research results. The BEST Lab at Norfolk State University has been creating tools for multivariable-multidimensional analysis of Earth Science data. EzSAGE and SAGE4D have been developed to sort, analyze and visualize SAGE II (Stratospheric Aerosol and Gas Experiment) data with ease. Three- and four-dimensional visualizations in interactive environments can be produced. EzSAGE provides atmospheric slices in three-dimensions where the researcher can change the scales in the three-dimensions, color tables and degree of smoothing interactively to focus on particular phenomena. SAGE4D provides a navigable four-dimensional interactive environment. These tools allow students to make higher order decisions based on large multidimensional sets of data while diminishing the level of frustration that results from dealing with the details of processing large data sets.

Luminosity measurements for the R scan experiment at BESIII

NASA Astrophysics Data System (ADS)

Ablikim, M.; Achasov, M. N.; Ahmed, S.; Ai, X. C.; Albayrak, O.; Albrecht, M.; Ambrose, D. J.; Amoroso, A.; An, F. F.; An, Q.; Bai, J. Z.; Bakina, O.; Baldini Ferroli, R.; Ban, Y.; Bennett, D. W.; Bennett, J. V.; Berger, N.; Bertani, M.; Bettoni, D.; Bian, J. M.; Bianchi, F.; Boger, E.; Boyko, I.; Briere, R. A.; Cai, H.; Cai, X.; Cakir, O.; Calcaterra, A.; Cao, G. F.; Cetin, S. A.; Chai, J.; Chang, J. F.; Chelkov, G.; Chen, G.; Chen, H. S.; Chen, J. C.; Chen, M. L.; Chen, S.; Chen, S. J.; Chen, X.; Chen, X. R.; Chen, Y. B.; Chu, X. K.; Cibinetto, G.; Dai, H. L.; Dai, J. P.; Dbeyssi, A.; Dedovich, D.; Deng, Z. Y.; Denig, A.; Denysenko, I.; Destefanis, M.; De Mori, F.; Ding, Y.; Dong, C.; Dong, J.; Dong, L. Y.; Dong, M. Y.; Dou, Z. L.; Du, S. X.; Duan, P. F.; Fan, J. Z.; Fang, J.; Fang, S. S.; Fang, X.; Fang, Y.; Farinelli, R.; Fava, L.; Feldbauer, F.; Felici, G.; Feng, C. Q.; Fioravanti, E.; Fritsch, M.; Fu, C. D.; Gao, Q.; Gao, X. L.; Gao, Y.; Gao, Z.; Garzia, I.; Goetzen, K.; Gong, L.; Gong, W. X.; Gradl, W.; Greco, M.; Gu, M. H.; Gu, Y. T.; Guan, Y. H.; Guo, A. Q.; Guo, L. B.; Guo, R. P.; Guo, Y.; Guo, Y. P.; Haddadi, Z.; Hafner, A.; Han, S.; Hao, X. Q.; Harris, F. A.; He, K. L.; Heinsius, F. H.; Held, T.; Heng, Y. K.; Holtmann, T.; Hou, Z. L.; Hu, C.; Hu, H. M.; Hu, J. F.; Hu, T.; Hu, Y.; Huang, G. S.; Huang, J. S.; Huang, X. T.; Huang, X. Z.; Huang, Z. L.; Hussain, T.; Ikegami Andersson, W.; Ji, Q.; Ji, Q. P.; Ji, X. B.; Ji, X. L.; Jiang, L. W.; Jiang, X. S.; Jiang, X. Y.; Jiao, J. B.; Jiao, Z.; Jin, D. P.; Jin, S.; Johansson, T.; Julin, A.; Kalantar-Nayestanaki, N.; Kang, X. L.; Kang, X. S.; Kavatsyuk, M.; Ke, B. C.; Kiese, P.; Kliemt, R.; Kloss, B.; Kolcu, O. B.; Kopf, B.; Kornicer, M.; Kupsc, A.; Kühn, W.; Lange, J. S.; Lara, M.; Larin, P.; Leithoff, H.; Leng, C.; Li, C.; Li, Cheng; Li, D. M.; Li, F.; Li, F. Y.; Li, G.; Li, H. B.; Li, H. J.; Li, J. C.; Li, Jin; Li, K.; Li, K.; Li, Lei; Li, P. R.; Li, Q. Y.; Li, T.; Li, W. D.; Li, W. G.; Li, X. L.; Li, X. N.; Li, X. Q.; Li, Y. B.; Li, Z. B.; Liang, H.; Liang, Y. F.; Liang, Y. T.; Liao, G. R.; Lin, D. X.; Liu, B.; Liu, B. J.; Liu, C. X.; Liu, D.; Liu, F. H.; Liu, Fang; Liu, Feng; Liu, H. B.; Liu, H. H.; Liu, H. H.; Liu, H. M.; Liu, J.; Liu, J. B.; Liu, J. P.; Liu, J. Y.; Liu, K.; Liu, K. Y.; Liu, L. D.; Liu, P. L.; Liu, Q.; Liu, S. B.; Liu, X.; Liu, Y. B.; Liu, Y. Y.; Liu, Z. A.; Liu, Zhiqing; Loehner, H.; Lou, X. C.; Lu, H. J.; Lu, J. G.; Lu, Y.; Lu, Y. P.; Luo, C. L.; Luo, M. X.; Luo, T.; Luo, X. L.; Lyu, X. R.; Ma, F. C.; Ma, H. L.; Ma, L. L.; Ma, M. M.; Ma, Q. M.; Ma, T.; Ma, X. N.; Ma, X. Y.; Ma, Y. M.; Maas, F. E.; Maggiora, M.; Malik, Q. A.; Mao, Y. J.; Mao, Z. P.; Marcello, S.; Messchendorp, J. G.; Mezzadri, G.; Min, J.; Min, T. J.; Mitchell, R. E.; Mo, X. H.; Mo, Y. J.; Morales Morales, C.; Muchnoi, N. Yu.; Muramatsu, H.; Musiol, P.; Nefedov, Y.; Nerling, F.; Nikolaev, I. B.; Ning, Z.; Nisar, S.; Niu, S. L.; Niu, X. Y.; Olsen, S. L.; Ouyang, Q.; Pacetti, S.; Pan, Y.; Patteri, P.; Pelizaeus, M.; Peng, H. P.; Peters, K.; Pettersson, J.; Ping, J. L.; Ping, R. G.; Poling, R.; Prasad, V.; Qi, H. R.; Qi, M.; Qian, S.; Qiao, C. F.; Qin, L. Q.; Qin, N.; Qin, X. S.; Qin, Z. H.; Qiu, J. F.; Rashid, K. H.; Redmer, C. F.; Ripka, M.; Rong, G.; Rosner, Ch.; Ruan, X. D.; Sarantsev, A.; Savrié, M.; Schnier, C.; Schoenning, K.; Shan, W.; Shao, M.; Shen, C. P.; Shen, P. X.; Shen, X. Y.; Sheng, H. Y.; Song, W. M.; Song, X. Y.; Sosio, S.; Spataro, S.; Sun, G. X.; Sun, J. F.; Sun, S. S.; Sun, X. H.; Sun, Y. J.; Sun, Y. Z.; Sun, Z. J.; Sun, Z. T.; Tang, C. J.; Tang, X.; Tapan, I.; Thorndike, E. H.; Tiemens, M.; Uman, I.; Varner, G. S.; Wang, B.; Wang, B. L.; Wang, D.; Wang, D. Y.; Wang, K.; Wang, L. L.; Wang, L. S.; Wang, M.; Wang, P.; Wang, P. L.; Wang, W.; Wang, W. P.; Wang, X. F.; Wang, Y.; Wang, Y. D.; Wang, Y. F.; Wang, Y. Q.; Wang, Z.; Wang, Z. G.; Wang, Z. H.; Wang, Z. Y.; Wang, Z. Y.; Weber, T.; Wei, D. H.; Weidenkaff, P.; Wen, S. P.; Wiedner, U.; Wolke, M.; Wu, L. H.; Wu, L. J.; Wu, Z.; Xia, L.; Xia, L. G.; Xia, Y.; Xiao, D.; Xiao, H.; Xiao, Z. J.; Xie, Y. G.; Xie, Y. H.; Xiu, Q. L.; Xu, G. F.; Xu, J. J.; Xu, L.; Xu, Q. J.; Xu, Q. N.; Xu, X. P.; Yan, L.; Yan, W. B.; Yan, W. C.; Yan, Y. H.; Yang, H. J.; Yang, H. X.; Yang, L.; Yang, Y. X.; Ye, M.; Ye, M. H.; Yin, J. H.; You, Z. Y.; Yu, B. X.; Yu, C. X.; Yu, J. S.; Yuan, C. Z.; Yuan, Y.; Yuncu, A.; Zafar, A. A.; Zeng, Y.; Zeng, Z.; Zhang, B. X.; Zhang, B. Y.; Zhang, C. C.; Zhang, D. H.; Zhang, H. H.; Zhang, H. Y.; Zhang, J.; Zhang, J. J.; Zhang, J. L.; Zhang, J. Q.; Zhang, J. W.; Zhang, J. Y.; Zhang, J. Z.; Zhang, K.; Zhang, L.; Zhang, S. Q.; Zhang, X. Y.; Zhang, Y.; Zhang, Y.; Zhang, Y. H.; Zhang, Y. N.; Zhang, Y. T.; Zhang, Yu; Zhang, Z. H.; Zhang, Z. P.; Zhang, Z. Y.; Zhao, G.; Zhao, J. W.; Zhao, J. Y.; Zhao, J. Z.; Zhao, Lei; Zhao, Ling; Zhao, M. G.; Zhao, Q.; Zhao, Q. W.; Zhao, S. J.; Zhao, T. C.; Zhao, Y. B.; Zhao, Z. G.; Zhemchugov, A.; Zheng, B.; Zheng, J. P.; Zheng, W. J.; Zheng, Y. H.; Zhong, B.; Zhou, L.; Zhou, X.; Zhou, X. K.; Zhou, X. R.; Zhou, X. Y.; Zhu, K.; Zhu, K. J.; Zhu, S.; Zhu, S. H.; Zhu, X. L.; Zhu, Y. C.; Zhu, Y. S.; Zhu, Z. A.; Zhuang, J.; Zotti, L.; Zou, B. S.; Zou, J. H.; BESIII Collaboration

2017-06-01

By analyzing the large-angle Bhabha scattering events e+e- → (γ)e+e- and diphoton events e+e- → (γ)γγ for the data sets collected at center-of-mass (c.m.) energies between 2.2324 and 4.5900 GeV (131 energy points in total) with the upgraded Beijing Spectrometer (BESIII) at the Beijing Electron-Positron Collider (BEPCII), the integrated luminosities have been measured at the different c.m. energies, individually. The results are important inputs for the R value and J/ψ resonance parameter measurements. Supported by National Key Basic Research Program of China (2015CB856700), National Natural Science Foundation of China (NSFC) (10935007, 11121092, 11125525, 11235011, 11322544, 11335008, 11375170, 11275189, 11079030, 11475164, 11475169, 11005109, 10979095, 11275211), Chinese Academy of Sciences (CAS) Large-Scale Scientific Facility Program; Joint Large-Scale Scientific Facility Funds of the NSFC and CAS (11179007, U1232201, U1332201, U1532102). (KJCX2-YW-N29, KJCX2-YW-N45). 100 Talents Program of CAS, INPAC and Shanghai Key Laboratory for Particle Physics and Cosmology, German Research Foundation DFG (Collaborative Research Center CRC-1044), Istituto Nazionale di Fisica Nucleare, Italy, Ministry of Development of Turkey (DPT2006K-120470), Russian Foundation for Basic Research (14-07-91152), U. S. Department of Energy (DE-FG02-04ER41291, DE-FG02-05ER41374, DE-FG02-94ER40823, DESC0010118), U.S. National Science Foundation, University of Groningen (RuG) and the Helmholtzzentrum fuer Schwerionenforschung GmbH (GSI), Darmstadt, WCU Program of National Research Foundation of Korea (R32-2008-000-10155-0)

Towards Building a High Performance Spatial Query System for Large Scale Medical Imaging Data.

PubMed

Aji, Ablimit; Wang, Fusheng; Saltz, Joel H

2012-11-06

Support of high performance queries on large volumes of scientific spatial data is becoming increasingly important in many applications. This growth is driven by not only geospatial problems in numerous fields, but also emerging scientific applications that are increasingly data- and compute-intensive. For example, digital pathology imaging has become an emerging field during the past decade, where examination of high resolution images of human tissue specimens enables more effective diagnosis, prediction and treatment of diseases. Systematic analysis of large-scale pathology images generates tremendous amounts of spatially derived quantifications of micro-anatomic objects, such as nuclei, blood vessels, and tissue regions. Analytical pathology imaging provides high potential to support image based computer aided diagnosis. One major requirement for this is effective querying of such enormous amount of data with fast response, which is faced with two major challenges: the "big data" challenge and the high computation complexity. In this paper, we present our work towards building a high performance spatial query system for querying massive spatial data on MapReduce. Our framework takes an on demand index building approach for processing spatial queries and a partition-merge approach for building parallel spatial query pipelines, which fits nicely with the computing model of MapReduce. We demonstrate our framework on supporting multi-way spatial joins for algorithm evaluation and nearest neighbor queries for microanatomic objects. To reduce query response time, we propose cost based query optimization to mitigate the effect of data skew. Our experiments show that the framework can efficiently support complex analytical spatial queries on MapReduce.

Precision measurement of the integrated luminosity of the data taken by BESIII at center-of-mass energies between 3.810 GeV and 4.600 GeV

NASA Astrophysics Data System (ADS)

Ablikim, M.; N. Achasov, M.; Ai, X. C.; Albayrak, O.; Albrecht, M.; J. Ambrose, D.; Amoroso, A.; An, F. F.; An, Q.; Bai, J. Z.; R. Baldini, Ferroli; Ban, Y.; W. Bennett, D.; V. Bennett, J.; Bertani, M.; Bettoni, D.; Bian, J. M.; Bianchi, F.; Boger, E.; Bondarenko, O.; Boyko, I.; A. Briere, R.; Cai, H.; Cai, X.; Cakir, O.; Calcaterra, A.; Cao, G. F.; A. Cetin, S.; Chang, J. F.; Chelkov, G.; Chen, G.; Chen, H. S.; Chen, H. Y.; Chen, J. C.; Chen, M. L.; Chen, S. J.; Chen, X.; Chen, X. R.; Chen, Y. B.; Cheng, H. P.; Chu, X. K.; Cibinetto, G.; Cronin-Hennessy, D.; Dai, H. L.; Dai, J. P.; Dbeyssi, A.; Dedovich, D.; Deng, Z. Y.; Denig, A.; Denysenko, I.; Destefanis, M.; F. De, Mori; Ding, Y.; Dong, C.; Dong, J.; Dong, L. Y.; Dong, M. Y.; Du, S. X.; Duan, P. F.; Fan, J. Z.; Fang, J.; Fang, S. S.; Fang, X.; Fang, Y.; Fava, L.; Feldbauer, F.; Felici, G.; Feng, C. Q.; Fioravanti, E.; Fritsch, M.; Fu, C. D.; Gao, Q.; Gao, Y.; Gao, Z.; Garzia, I.; Geng, C.; Goetzen, K.; Gong, W. X.; Gradl, W.; Greco, M.; Gu, M. H.; Gu, Y. T.; Guan, Y. H.; Guo, A. Q.; Guo, L. B.; Guo, Y.; P. Guo, Y.; Haddadi, Z.; Hafner, A.; Han, S.; Han, Y. L.; Hao, X. Q.; A. Harris, F.; He, K. L.; He, Z. Y.; Held, T.; Heng, Y. K.; Hou, Z. L.; Hu, C.; Hu, H. M.; Hu, J. F.; Hu, T.; Hu, Y.; Huang, G. M.; Huang, G. S.; Huang, H. P.; Huang, J. S.; Huang, X. T.; Huang, Y.; Hussain, T.; Ji, Q.; Ji, Q. P.; Ji, X. B.; Ji, X. L.; Jiang, L. L.; Jiang, L. W.; Jiang, X. S.; Jiao, J. B.; Jiao, Z.; Jin, D. P.; Jin, S.; Johansson, T.; Julin, A.; Kalantar-Nayestanaki, N.; Kang, X. L.; Kang, X. S.; Kavatsyuk, M.; C. Ke, B.; Kliemt, R.; Kloss, B.; B. Kolcu, O.; Kopf, B.; Kornicer, M.; Kuehn, W.; Kupsc, A.; Lai, W.; S. Lange, J.; M., Lara; Larin, P.; Leng, C.; Li, C. H.; Li, Cheng; Li, D. M.; Li, F.; Li, G.; Li, H. B.; Li, J. C.; Li, Jin; Li, K.; Li, K.; Li, Lei; Li, P. R.; Li, T.; Li, W. D.; Li, W. G.; Li, X. L.; Li, X. M.; Li, X. N.; Li, X. Q.; Li, Z. B.; Liang, H.; Liang, Y. F.; Liang, Y. T.; Liao, G. R.; X. Lin(Lin, D.; Liu, B. J.; Liu, C. X.; Liu, F. H.; Liu, Fang; Liu, Feng; Liu, H. B.; Liu, H. H.; Liu, H. H.; Liu, H. M.; Liu, J.; Liu, J. P.; Liu, J. Y.; Liu, K.; Liu, K. Y.; Liu, L. D.; Liu, P. L.; Liu, Q.; Liu, S. B.; Liu, X.; Liu, X. X.; Liu, Y. B.; Liu, Z. A.; Liu, Zhiqiang; Zhiqing, Liu; Loehner, H.; Lou, X. C.; Lu, H. J.; Lu, J. G.; Lu, R. Q.; Lu, Y.; Lu, Y. P.; Luo, C. L.; Luo, M. X.; Luo, T.; Luo, X. L.; Lv, M.; Lyu, X. R.; Ma, F. C.; Ma, H. L.; Ma, L. L.; Ma, Q. M.; Ma, S.; Ma, T.; Ma, X. N.; Ma, X. Y.; E. Maas, F.; Maggiora, M.; A. Malik, Q.; Mao, Y. J.; Mao, Z. P.; Marcello, S.; G. Messchendorp, J.; Min, J.; Min, T. J.; E. Mitchell, R.; Mo, X. H.; Mo, Y. J.; C. Morales, Morales; Moriya, K.; Yu. Muchnoi, N.; Muramatsu, H.; Nefedov, Y.; Nerling, F.; B. Nikolaev, I.; Ning, Z.; Nisar, S.; Niu, S. L.; Niu, X. Y.; Olsen, S. L.; Ouyang, Q.; Pacetti, S.; Patteri, P.; Pelizaeus, M.; Peng, H. P.; Peters, K.; Ping, J. L.; Ping, R. G.; Poling, R.; Pu, Y. N.; Qi, M.; Qian, S.; Qiao, C. F.; Qin, L. Q.; Qin, N.; Qin, X. S.; Qin, Y.; Qin, Z. H.; Qiu, J. F.; H. Rashid, K.; F. Redmer, C.; Ren, H. L.; Ripka, M.; Rong, G.; Ruan, X. D.; Santoro, V.; Sarantsev, A.; Savrié, M.; Schoenning, K.; Schumann, S.; Shan, W.; Shao, M.; Shen, C. P.; Shen, P. X.; Shen, X. Y.; Sheng, H. Y.; Song, W. M.; Song, X. Y.; Sosio, S.; Spataro, S.; Sun, G. X.; Sun, J. F.; Sun, S. S.; Sun, Y. J.; Sun, Y. Z.; Sun, Z. J.; Sun, Z. T.; Tang, C. J.; Tang, X.; Tapan, I.; H. Thorndike, E.; Tiemens, M.; Toth, D.; Ullrich, M.; Uman, I.; S. Varner, G.; Wang, B.; Wang, B. L.; Wang, D.; Wang, D. Y.; Wang, K.; Wang, L. L.; Wang, L. S.; Wang, M.; Wang, P.; Wang, P. L.; Wang, Q. J.; Wang, S. G.; Wang, W.; Wang, X. F.; Yadi, Wang; Wang, Y. F.; Wang, Y. Q.; Wang, Z.; Wang, Z. G.; Wang, Z. H.; Wang, Z. Y.; Weber, T.; Wei, D. H.; Wei, J. B.; Weidenkaff, P.; Wen, S. P.; Wiedner, U.; Wolke, M.; Wu, L. H.; Wu, Z.; Xia, L. G.; Xia, Y.; Xiao, D.; Xiao, Z. J.; Xie, Y. G.; Xiu, Q. L.; Xu, G. F.; Xu, L.; Xu, Q. J.; Xu, Q. N.; Xu, X. P.; Yan, L.; Yan, W. B.; Yan, W. C.; Yan, Y. H.; Yang, H. X.; Yang, L.; Yang, Y.; Yang, Y. X.; Ye, H.; Ye, M.; Ye, M. H.; Yin, J. H.; Yu, B. X.; Yu, C. X.; Yu, H. W.; Yu, J. S.; Yuan, C. Z.; Yuan, W. L.; Yuan, Y.; Yuncu, A.; A. Zafar, A.; Zallo, A.; Zeng, Y.; Zhang, B. X.; Zhang, B. Y.; Zhang, C.; Zhang, C. C.; Zhang, D. H.; Zhang, H. H.; Zhang, H. Y.; Zhang, J. J.; Zhang, J. L.; Zhang, J. Q.; Zhang, J. W.; Zhang, J. Y.; Zhang, J. Z.; Zhang, K.; Zhang, L.; Zhang, S. H.; Zhang, X. Y.; Zhang, Y.; Zhang, Y. H.; Zhang, Y. T.; Zhang, Z. H.; Zhang, Z. P.; Zhang, Z. Y.; Zhao, G.; Zhao, J. W.; Zhao, J. Y.; Zhao, J. Z.; Zhao, Lei; Zhao, Ling; Zhao, M. G.; Zhao, Q.; Zhao, Q. W.; Zhao, S. J.; Zhao, T. C.; Zhao, Y. B.; Zhao, Z. G.; Zhemchugov, A.; Zheng, B.; Zheng, J. P.; Zheng, W. J.; Zheng, Y. H.; Zhong, B.; Zhou, L.; Zhou, Li; Zhou, X.; Zhou, X. K.; Zhou, X. R.; Zhou, X. Y.; Zhu, K.; Zhu, K. J.; Zhu, S.; Zhu, X. L.; Zhu, Y. C.; Zhu, Y. S.; Zhu, Z. A.; Zhuang, J.; Zotti, L.; Zou, B. S.; Zou, J. H.; BESIII Collaboration

2015-09-01

From December 2011 to May 2014, about 5 fb-1 of data were taken with the BESIII detector at center-of-mass energies between 3.810 GeV and 4.600 GeV to study the charmonium-like states and higher excited charmonium states. The time-integrated luminosity of the collected data sample is measured to a precision of 1% by analyzing events produced by the large-angle Bhabha scattering process. Supported by National Key Basic Research Program of China (2015CB856700), National Natural Science Foundation of China (NSFC) (11125525, 11235011, 11322544, 11335008, 11425524), Chinese Academy of Sciences (CAS) Large-Scale Scientific Facility Program, Joint Large-Scale Scientific Facility Funds of the NSFC and CAS (11179007, U1232201, U1332201) CAS (KJCX2-YW-N29, KJCX2-YW-N45), 100 Talents Program of CAS, INPAC and Shanghai Key Laboratory for Particle Physics and Cosmology, German Research Foundation DFG (Collaborative Research Center CRC-1044), Istituto Nazionale di Fisica Nucleare, Italy; Ministry of Development of Turkey (DPT2006K-120470), Russian Foundation for Basic Research (14-07-91152), U.S. Department of Energy (DE-FG02-04ER41291, DE-FG02-05ER41374, DE-FG02-94ER40823, DESC0010118), U.S. National Science Foundation, University of Groningen (RuG) and the Helmholtzzentrum fuer Schwerionenforschung GmbH (GSI), Darmstadt and WCU Program of National Research Foundation of Korea (R32-2008-000-10155-0)

Towards Building a High Performance Spatial Query System for Large Scale Medical Imaging Data

PubMed Central

Aji, Ablimit; Wang, Fusheng; Saltz, Joel H.

2013-01-01

Support of high performance queries on large volumes of scientific spatial data is becoming increasingly important in many applications. This growth is driven by not only geospatial problems in numerous fields, but also emerging scientific applications that are increasingly data- and compute-intensive. For example, digital pathology imaging has become an emerging field during the past decade, where examination of high resolution images of human tissue specimens enables more effective diagnosis, prediction and treatment of diseases. Systematic analysis of large-scale pathology images generates tremendous amounts of spatially derived quantifications of micro-anatomic objects, such as nuclei, blood vessels, and tissue regions. Analytical pathology imaging provides high potential to support image based computer aided diagnosis. One major requirement for this is effective querying of such enormous amount of data with fast response, which is faced with two major challenges: the “big data” challenge and the high computation complexity. In this paper, we present our work towards building a high performance spatial query system for querying massive spatial data on MapReduce. Our framework takes an on demand index building approach for processing spatial queries and a partition-merge approach for building parallel spatial query pipelines, which fits nicely with the computing model of MapReduce. We demonstrate our framework on supporting multi-way spatial joins for algorithm evaluation and nearest neighbor queries for microanatomic objects. To reduce query response time, we propose cost based query optimization to mitigate the effect of data skew. Our experiments show that the framework can efficiently support complex analytical spatial queries on MapReduce. PMID:24501719

WOMEN’S SUFFRAGE, POLITICAL RESPONSIVENESS, AND CHILD SURVIVAL IN AMERICAN HISTORY*

PubMed Central

Miller, Grant

2010-01-01

Women’s choices appear to emphasize child welfare more than those of men. This paper presents new evidence on how suffrage rights for American women helped children to benefit from the scientific breakthroughs of the bacteriological revolution. Consistent with standard models of electoral competition, suffrage laws were followed by immediate shifts in legislative behavior and large, sudden increases in local public health spending. This growth in public health spending fueled large-scale door-to-door hygiene campaigns, and child mortality declined by 8-15% (or 20,000 annual child deaths nationwide) as cause-specific reductions occurred exclusively among infectious childhood killers sensitive to hygienic conditions. PMID:21373369

Characterizing Temperature Variability and Associated Large Scale Meteorological Patterns Across South America

NASA Astrophysics Data System (ADS)

Detzer, J.; Loikith, P. C.; Mechoso, C. R.; Barkhordarian, A.; Lee, H.

2017-12-01

South America's climate varies considerably owing to its large geographic range and diverse topographical features. Spanning the tropics to the mid-latitudes and from high peaks to tropical rainforest, the continent experiences an array of climate and weather patterns. Due to this considerable spatial extent, assessing temperature variability at the continent scale is particularly challenging. It is well documented in the literature that temperatures have been increasing across portions of South America in recent decades, and while there have been many studies that have focused on precipitation variability and change, temperature has received less scientific attention. Therefore, a more thorough understanding of the drivers of temperature variability is critical for interpreting future change. First, k-means cluster analysis is used to identify four primary modes of temperature variability across the continent, stratified by season. Next, composites of large scale meteorological patterns (LSMPs) are calculated for months assigned to each cluster. Initial results suggest that LSMPs, defined using meteorological variables such as sea level pressure (SLP), geopotential height, and wind, are able to identify synoptic scale mechanisms important for driving temperature variability at the monthly scale. Some LSMPs indicate a relationship with known recurrent modes of climate variability. For example, composites of geopotential height suggest that the Southern Annular Mode is an important, but not necessarily dominant, component of temperature variability over southern South America. This work will be extended to assess the drivers of temperature extremes across South America.

Conceiving processes in atmospheric models-General equations, subscale parameterizations, and 'superparameterizations'

NASA Astrophysics Data System (ADS)

Gramelsberger, Gabriele

The scientific understanding of atmospheric processes has been rooted in the mechanical and physical view of nature ever since dynamic meteorology gained ground in the late 19th century. Conceiving the atmosphere as a giant 'air mass circulation engine' entails applying hydro- and thermodynamical theory to the subject in order to describe the atmosphere's behaviour on small scales. But when it comes to forecasting, it turns out that this view is far too complex to be computed. The limitation of analytical methods precludes an exact solution, forcing scientists to make use of numerical simulation. However, simulation introduces two prerequisites to meteorology: First, the partitioning of the theoretical view into two parts-the large-scale behaviour of the atmosphere, and the effects of smaller-scale processes on this large-scale behaviour, so-called parametrizations; and second, the dependency on computational power in order to achieve a higher resolution. The history of today's atmospheric circulation modelling can be reconstructed as the attempt to improve the handling of these basic constraints. It can be further seen as the old schism between theory and application under new circumstances, which triggers a new discussion about the question of how processes may be conceived in atmospheric modelling.

The Multi-Scale Network Landscape of Collaboration.

PubMed

Bae, Arram; Park, Doheum; Ahn, Yong-Yeol; Park, Juyong

2016-01-01

Propelled by the increasing availability of large-scale high-quality data, advanced data modeling and analysis techniques are enabling many novel and significant scientific understanding of a wide range of complex social, natural, and technological systems. These developments also provide opportunities for studying cultural systems and phenomena--which can be said to refer to all products of human creativity and way of life. An important characteristic of a cultural product is that it does not exist in isolation from others, but forms an intricate web of connections on many levels. In the creation and dissemination of cultural products and artworks in particular, collaboration and communication of ideas play an essential role, which can be captured in the heterogeneous network of the creators and practitioners of art. In this paper we propose novel methods to analyze and uncover meaningful patterns from such a network using the network of western classical musicians constructed from a large-scale comprehensive Compact Disc recordings data. We characterize the complex patterns in the network landscape of collaboration between musicians across multiple scales ranging from the macroscopic to the mesoscopic and microscopic that represent the diversity of cultural styles and the individuality of the artists.

The Multi-Scale Network Landscape of Collaboration

PubMed Central

Ahn, Yong-Yeol; Park, Juyong

2016-01-01

Propelled by the increasing availability of large-scale high-quality data, advanced data modeling and analysis techniques are enabling many novel and significant scientific understanding of a wide range of complex social, natural, and technological systems. These developments also provide opportunities for studying cultural systems and phenomena—which can be said to refer to all products of human creativity and way of life. An important characteristic of a cultural product is that it does not exist in isolation from others, but forms an intricate web of connections on many levels. In the creation and dissemination of cultural products and artworks in particular, collaboration and communication of ideas play an essential role, which can be captured in the heterogeneous network of the creators and practitioners of art. In this paper we propose novel methods to analyze and uncover meaningful patterns from such a network using the network of western classical musicians constructed from a large-scale comprehensive Compact Disc recordings data. We characterize the complex patterns in the network landscape of collaboration between musicians across multiple scales ranging from the macroscopic to the mesoscopic and microscopic that represent the diversity of cultural styles and the individuality of the artists. PMID:26990088

BlazeDEM3D-GPU A Large Scale DEM simulation code for GPUs

NASA Astrophysics Data System (ADS)

Govender, Nicolin; Wilke, Daniel; Pizette, Patrick; Khinast, Johannes

2017-06-01

Accurately predicting the dynamics of particulate materials is of importance to numerous scientific and industrial areas with applications ranging across particle scales from powder flow to ore crushing. Computational discrete element simulations is a viable option to aid in the understanding of particulate dynamics and design of devices such as mixers, silos and ball mills, as laboratory scale tests comes at a significant cost. However, the computational time required to simulate an industrial scale simulation which consists of tens of millions of particles can take months to complete on large CPU clusters, making the Discrete Element Method (DEM) unfeasible for industrial applications. Simulations are therefore typically restricted to tens of thousands of particles with highly detailed particle shapes or a few million of particles with often oversimplified particle shapes. However, a number of applications require accurate representation of the particle shape to capture the macroscopic behaviour of the particulate system. In this paper we give an overview of the recent extensions to the open source GPU based DEM code, BlazeDEM3D-GPU, that can simulate millions of polyhedra and tens of millions of spheres on a desktop computer with a single or multiple GPUs.

Research, monitoring and evaluation of fish and wildlife restoration projects in the Columbia River Basin: Lessons learned and suggestions for large-scale monitoring programs.

Treesearch

Lyman L. McDonald; Robert Bilby; Peter A. Bisson; Charles C. Coutant; John M. Epifanio; Daniel Goodman; Susan Hanna; Nancy Huntly; Erik Merrill; Brian Riddell; William Liss; Eric J. Loudenslager; David P. Philipp; William Smoker; Richard R. Whitney; Richard N. Williams

2007-01-01

The year 2006 marked two milestones in the Columbia River Basin and the Pacific Northwest region's efforts to rebuild its once great salmon and steelhead runs: the 25th anniversary of the creation of the Northwest Power and Conservation Council and the 10th anniversary of an amendment to the Northwest Power Act that formalized scientific peer review of the council...

Limnological surveys of the Great Lakes--early and recent

USGS Publications Warehouse

Smith, Stanford H.

1957-01-01

Early explorations on the Great Lakes were concerned largely with things easily collected or observed—common organisms, water levels, surface temperatures … Even when more scientific studies were undertaken, they were at first scattered and small-scale. Effective surveys became possible only through inter-agency cooperation which permits a pooling of facilities, staff, and equipment. Expansion of limnological research on the Great Lakes has been rapid in later years and the outlook for the future is good.

To simulate or not to simulate: what are the questions?

PubMed

Dudai, Yadin; Evers, Kathinka

2014-10-22

Simulation is a powerful method in science and engineering. However, simulation is an umbrella term, and its meaning and goals differ among disciplines. Rapid advances in neuroscience and computing draw increasing attention to large-scale brain simulations. What is the meaning of simulation, and what should the method expect to achieve? We discuss the concept of simulation from an integrated scientific and philosophical vantage point and pinpoint selected issues that are specific to brain simulation.

Concepts for a global resources information system

NASA Technical Reports Server (NTRS)

Billingsley, F. C.; Urena, J. L.

1984-01-01

The objective of the Global Resources Information System (GRIS) is to establish an effective and efficient information management system to meet the data access requirements of NASA and NASA-related scientists conducting large-scale, multi-disciplinary, multi-mission scientific investigations. Using standard interfaces and operating guidelines, diverse data systems can be integrated to provide the capabilities to access and process multiple geographically dispersed data sets and to develop the necessary procedures and algorithms to derive global resource information.

Shake, Rattle and Roles: Lessons from Experimental Earthquake Engineering for Incorporating Remote Users in Large-Scale E-Science Experiments

DTIC Science & Technology

2007-01-01

Mechanical Turk: Artificial Artificial Intelligence . Retrieved May 15, 2006 from http://www.mturk.com/ mturk/welcome Atkins, D. E., Droegemeier, K. K...Turk (Amazon, 2006) site goes beyond volunteers and pays people to do Human Intelligence Tasks, those that are difficult for computers but relatively...geographically distributed scientific collaboration, and the use of videogame technology for training. Address: U.S. Army Research Institute, 2511 Jefferson

Convective phenomena at high resolution over Europe and the Mediterranean. The join EURO-CORDEX and Med-CORDEX flagship pilot study

NASA Astrophysics Data System (ADS)

Coppola, Erika; Sobolowski, Stefan

2017-04-01

The join EURO-CORDEX and Med-CORDEX Flagship Pilot Study dedicated to the frontier research of using convective permitting models to address the impact of human induced climate change on convection, has been recently approved and the scientific community behind the project is made of 30 different scientific institutes distributed all around Europe. The motivations for such a challenge is the availability of large field campaigns dedicated to the study of heavy precipitation events such as HyMeX and high resolution dense observation networks like WegnerNet, RdisaggH (CH),COMEPHORE (Fr), SAFRAN (Fr), EURO4M-APGD (CH); the increased computing capacity and model developments; the emerging trend signals in extreme precipitation at daily and mainly sub-daily time scale in the Mediterranean and Alpine regions and the priority of convective extreme events under the WCRP Grand Challenge on climate extremes, because they carry both society-relevant and scientific challenges. The main objective of this effort are to investigate convective-scale events, their processes and their changes in a few key regions of Europe and the Mediterranean using convection-permitting RCMs, statistical models and available observations. To provide a collective assessment of the modeling capacity at convection-permitting scale and to shape a coherent and collective assessment of the consequences of climate change on convective event impacts at local to regional scales. The scientific aims of this research are to investigate how the convective events and the damaging phenomena associated with them will respond to changing climate conditions in several European regions with different climates. To understand if an improved representation of convective phenomena at convective permitting scales will lead to upscaled added value and finally to assess the possibility to replace these costly convection-permitting experiments with statistical approaches like "convection emulators". The common initial domain will be an extended Alpine domain and all the groups will simulate a minimum of 10 years period with ERA-interim boundary conditions, with the possibility of other two sub-domains one in the Northwest continental Europe and another in the Southeast Mediterranean. The scenario simulations will be completed for three different 10 years time slices one in the historical period, one in the near future and the last one in the far future for the RCP8.5 scenario. The first target of this scientific community is to have an ensemble of 1-2 years ERA-interim simulations ready by next summer.

Data-Oriented Astrophysics at NOAO: The Science Archive & The Data Lab

NASA Astrophysics Data System (ADS)

Juneau, Stephanie; NOAO Data Lab, NOAO Science Archive

2018-06-01

As we keep progressing into an era of increasingly large astronomy datasets, NOAO’s data-oriented mission is growing in prominence. The NOAO Science Archive, which captures and processes the pixel data from mountaintops in Chile and Arizona, now contains holdings at Petabyte scales. Working at the intersection of astronomy and data science, the main goal of the NOAO Data Lab is to provide users with a suite of tools to work close to this data, the catalogs derived from them, as well as externally provided datasets, and thus optimize the scientific productivity of the astronomy community. These tools and services include databases, query tools, virtual storage space, workflows through our Jupyter Notebook server, and scripted analysis. We currently host datasets from NOAO facilities such as the Dark Energy Survey (DES), the DESI imaging Legacy Surveys (LS), the Dark Energy Camera Plane Survey (DECaPS), and the nearly all-sky NOAO Source Catalog (NSC). We are further preparing for large spectroscopy datasets such as DESI. After a brief overview of the Science Archive, the Data Lab and datasets, I will briefly showcase scientific applications showing use of our data holdings. Lastly, I will describe our vision for future developments as we tackle the next technical and scientific challenges.

Validation of SplitVectors Encoding for Quantitative Visualization of Large-Magnitude-Range Vector Fields

PubMed Central

Zhao, Henan; Bryant, Garnett W.; Griffin, Wesley; Terrill, Judith E.; Chen, Jian

2017-01-01

We designed and evaluated SplitVectors, a new vector field display approach to help scientists perform new discrimination tasks on large-magnitude-range scientific data shown in three-dimensional (3D) visualization environments. SplitVectors uses scientific notation to display vector magnitude, thus improving legibility. We present an empirical study comparing the SplitVectors approach with three other approaches - direct linear representation, logarithmic, and text display commonly used in scientific visualizations. Twenty participants performed three domain analysis tasks: reading numerical values (a discrimination task), finding the ratio between values (a discrimination task), and finding the larger of two vectors (a pattern detection task). Participants used both mono and stereo conditions. Our results suggest the following: (1) SplitVectors improve accuracy by about 10 times compared to linear mapping and by four times to logarithmic in discrimination tasks; (2) SplitVectors have no significant differences from the textual display approach, but reduce cluttering in the scene; (3) SplitVectors and textual display are less sensitive to data scale than linear and logarithmic approaches; (4) using logarithmic can be problematic as participants' confidence was as high as directly reading from the textual display, but their accuracy was poor; and (5) Stereoscopy improved performance, especially in more challenging discrimination tasks. PMID:28113469

Validation of SplitVectors Encoding for Quantitative Visualization of Large-Magnitude-Range Vector Fields.

PubMed

Henan Zhao; Bryant, Garnett W; Griffin, Wesley; Terrill, Judith E; Jian Chen

2017-06-01

We designed and evaluated SplitVectors, a new vector field display approach to help scientists perform new discrimination tasks on large-magnitude-range scientific data shown in three-dimensional (3D) visualization environments. SplitVectors uses scientific notation to display vector magnitude, thus improving legibility. We present an empirical study comparing the SplitVectors approach with three other approaches - direct linear representation, logarithmic, and text display commonly used in scientific visualizations. Twenty participants performed three domain analysis tasks: reading numerical values (a discrimination task), finding the ratio between values (a discrimination task), and finding the larger of two vectors (a pattern detection task). Participants used both mono and stereo conditions. Our results suggest the following: (1) SplitVectors improve accuracy by about 10 times compared to linear mapping and by four times to logarithmic in discrimination tasks; (2) SplitVectors have no significant differences from the textual display approach, but reduce cluttering in the scene; (3) SplitVectors and textual display are less sensitive to data scale than linear and logarithmic approaches; (4) using logarithmic can be problematic as participants' confidence was as high as directly reading from the textual display, but their accuracy was poor; and (5) Stereoscopy improved performance, especially in more challenging discrimination tasks.

Phage-bacteria infection networks: From nestedness to modularity

NASA Astrophysics Data System (ADS)

Flores, Cesar O.; Valverde, Sergi; Weitz, Joshua S.

2013-03-01

Bacteriophages (viruses that infect bacteria) are the most abundant biological life-forms on Earth. However, very little is known regarding the structure of phage-bacteria infections. In a recent study we re-evaluated 38 prior studies and demonstrated that phage-bacteria infection networks tend to be statistically nested in small scale communities (Flores et al 2011). Nestedness is consistent with a hierarchy of infection and resistance within phages and bacteria, respectively. However, we predicted that at large scales, phage-bacteria infection networks should be typified by a modular structure. We evaluate and confirm this hypothesis using the most extensive study of phage-bacteria infections (Moebus and Nattkemper 1981). In this study, cross-infections were evaluated between 215 marine phages and 286 marine bacteria. We develop a novel multi-scale network analysis and find that the Moebus and Nattkemper (1981) study, is highly modular (at the whole network scale), yet also exhibits nestedness and modularity at the within-module scale. We examine the role of geography in driving these modular patterns and find evidence that phage-bacteria interactions can exhibit strong similarity despite large distances between sites. CFG acknowledges the support of CONACyT Foundation. JSW holds a Career Award at the Scientific Interface from the Burroughs Wellcome Fund and acknowledges the support of the James S. McDonnell Foundation

Wyoming Landscape Conservation Initiative—A case study in partnership development

USGS Publications Warehouse

D'Erchia, Frank

2016-10-21

The Wyoming Landscape Conservation Initiative (WLCI) is a successful example of collaboration between science and natural resource management at the landscape scale. In southwestern Wyoming, expanding energy and mineral development, urban growth, and other changes in land use over recent decades, combined with landscape-scale drivers such as climate change and invasive species, have presented compelling challenges to resource managers and a diverse group of Federal, State, industry, and non-governmental organizations, as well as citizen stakeholders. To address these challenges, the WLCI was established as a collaborative forum and interagency partnership to develop and implement science-based conservation actions. About a decade after being established, this report documents the establishment and history of the WLCI, focusing on the path to success of the initiative and providing insights and details that may be useful in developing similar partnerships in other locations. Not merely retrospective, the elements of the WLCI that are presented herein are still in play, still evolving, and still contributing to the resolution of compelling conservation challenges in the Western United States.The U.S. Geological Survey has developed many successful longstanding partnerships, of which the WLCI is one example.“As the Nation’s largest water, earth, and biological science and civilian mapping agency, the U.S. Geological Survey collects, monitors, analyzes, and provides scientific understanding about natural resource conditions, issues, and problems. The diversity of our scientific expertise enables us to carry out large-scale, multi-disciplinary investigations and provide impartial scientific information to resource managers, planners, and other customers” (U.S. Geological Survey, 2016).

A Computationally Efficient Parallel Levenberg-Marquardt Algorithm for Large-Scale Big-Data Inversion

NASA Astrophysics Data System (ADS)

Lin, Y.; O'Malley, D.; Vesselinov, V. V.

2015-12-01

Inverse modeling seeks model parameters given a set of observed state variables. However, for many practical problems due to the facts that the observed data sets are often large and model parameters are often numerous, conventional methods for solving the inverse modeling can be computationally expensive. We have developed a new, computationally-efficient Levenberg-Marquardt method for solving large-scale inverse modeling. Levenberg-Marquardt methods require the solution of a dense linear system of equations which can be prohibitively expensive to compute for large-scale inverse problems. Our novel method projects the original large-scale linear problem down to a Krylov subspace, such that the dimensionality of the measurements can be significantly reduced. Furthermore, instead of solving the linear system for every Levenberg-Marquardt damping parameter, we store the Krylov subspace computed when solving the first damping parameter and recycle it for all the following damping parameters. The efficiency of our new inverse modeling algorithm is significantly improved by using these computational techniques. We apply this new inverse modeling method to invert for a random transitivity field. Our algorithm is fast enough to solve for the distributed model parameters (transitivity) at each computational node in the model domain. The inversion is also aided by the use regularization techniques. The algorithm is coded in Julia and implemented in the MADS computational framework (http://mads.lanl.gov). Julia is an advanced high-level scientific programing language that allows for efficient memory management and utilization of high-performance computational resources. By comparing with a Levenberg-Marquardt method using standard linear inversion techniques, our Levenberg-Marquardt method yields speed-up ratio of 15 in a multi-core computational environment and a speed-up ratio of 45 in a single-core computational environment. Therefore, our new inverse modeling method is a powerful tool for large-scale applications.

Large Spatial Scale Ground Displacement Mapping through the P-SBAS Processing of Sentinel-1 Data on a Cloud Computing Environment

NASA Astrophysics Data System (ADS)

Casu, F.; Bonano, M.; de Luca, C.; Lanari, R.; Manunta, M.; Manzo, M.; Zinno, I.

2017-12-01

Since its launch in 2014, the Sentinel-1 (S1) constellation has played a key role on SAR data availability and dissemination all over the World. Indeed, the free and open access data policy adopted by the European Copernicus program together with the global coverage acquisition strategy, make the Sentinel constellation as a game changer in the Earth Observation scenario. Being the SAR data become ubiquitous, the technological and scientific challenge is focused on maximizing the exploitation of such huge data flow. In this direction, the use of innovative processing algorithms and distributed computing infrastructures, such as the Cloud Computing platforms, can play a crucial role. In this work we present a Cloud Computing solution for the advanced interferometric (DInSAR) processing chain based on the Parallel SBAS (P-SBAS) approach, aimed at processing S1 Interferometric Wide Swath (IWS) data for the generation of large spatial scale deformation time series in efficient, automatic and systematic way. Such a DInSAR chain ingests Sentinel 1 SLC images and carries out several processing steps, to finally compute deformation time series and mean deformation velocity maps. Different parallel strategies have been designed ad hoc for each processing step of the P-SBAS S1 chain, encompassing both multi-core and multi-node programming techniques, in order to maximize the computational efficiency achieved within a Cloud Computing environment and cut down the relevant processing times. The presented P-SBAS S1 processing chain has been implemented on the Amazon Web Services platform and a thorough analysis of the attained parallel performances has been performed to identify and overcome the major bottlenecks to the scalability. The presented approach is used to perform national-scale DInSAR analyses over Italy, involving the processing of more than 3000 S1 IWS images acquired from both ascending and descending orbits. Such an experiment confirms the big advantage of exploiting large computational and storage resources of Cloud Computing platforms for large scale DInSAR analysis. The presented Cloud Computing P-SBAS processing chain can be a precious tool in the perspective of developing operational services disposable for the EO scientific community related to hazard monitoring and risk prevention and mitigation.

Basin scale permeability and thermal evolution of a magmatic hydrothermal system

NASA Astrophysics Data System (ADS)

Taron, J.; Hickman, S. H.; Ingebritsen, S.; Williams, C.

2013-12-01

Large-scale hydrothermal systems are potentially valuable energy resources and are of general scientific interest due to extreme conditions of stress, temperature, and reactive chemistry that can act to modify crustal rheology and composition. With many proposed sites for Enhanced Geothermal Systems (EGS) located on the margins of large-scale hydrothermal systems, understanding the temporal evolution of these systems contributes to site selection, characterization and design of EGS. This understanding is also needed to address the long-term sustainability of EGS once they are created. Many important insights into heat and mass transfer within natural hydrothermal systems can be obtained through hydrothermal modeling assuming that stress and permeability structure do not evolve over time. However, this is not fully representative of natural systems, where the effects of thermo-elastic stress changes, chemical fluid-rock interactions, and rock failure on fluid flow and thermal evolution can be significant. The quantitative importance of an evolving permeability field within the overall behavior of a large-scale hydrothermal system is somewhat untested, and providing such a parametric understanding is one of the goals of this study. We explore the thermal evolution of a sedimentary basin hydrothermal system following the emplacement of a magma body. The Salton Sea geothermal field and its associated magmatic system in southern California is utilized as a general backdrop to define the initial state. Working within the general framework of the open-source scientific computing initiative OpenGeoSys (www.opengeosys.org), we introduce full treatment of thermodynamic properties at the extreme conditions following magma emplacement. This treatment utilizes a combination of standard Galerkin and control-volume finite elements to balance fluid mass, mechanical deformation, and thermal energy with consideration of local thermal non-equilibrium (LTNE) between fluids and solids. Permeability is allowed to evolve under several constitutive models tailored to both porous media and fractures, considering the influence of both mechanical stress and diagenesis. In this first analysis, a relatively simple mechanical model is used; complexity will be added incrementally to represent specific characteristics of the Salton Sea hydrothermal field.

The NCI High Performance Computing (HPC) and High Performance Data (HPD) Platform to Support the Analysis of Petascale Environmental Data Collections

NASA Astrophysics Data System (ADS)

Evans, B. J. K.; Pugh, T.; Wyborn, L. A.; Porter, D.; Allen, C.; Smillie, J.; Antony, J.; Trenham, C.; Evans, B. J.; Beckett, D.; Erwin, T.; King, E.; Hodge, J.; Woodcock, R.; Fraser, R.; Lescinsky, D. T.

2014-12-01

The National Computational Infrastructure (NCI) has co-located a priority set of national data assets within a HPC research platform. This powerful in-situ computational platform has been created to help serve and analyse the massive amounts of data across the spectrum of environmental collections - in particular the climate, observational data and geoscientific domains. This paper examines the infrastructure, innovation and opportunity for this significant research platform. NCI currently manages nationally significant data collections (10+ PB) categorised as 1) earth system sciences, climate and weather model data assets and products, 2) earth and marine observations and products, 3) geosciences, 4) terrestrial ecosystem, 5) water management and hydrology, and 6) astronomy, social science and biosciences. The data is largely sourced from the NCI partners (who include the custodians of many of the national scientific records), major research communities, and collaborating overseas organisations. By co-locating these large valuable data assets, new opportunities have arisen by harmonising the data collections, making a powerful transdisciplinary research platformThe data is accessible within an integrated HPC-HPD environment - a 1.2 PFlop supercomputer (Raijin), a HPC class 3000 core OpenStack cloud system and several highly connected large scale and high-bandwidth Lustre filesystems. New scientific software, cloud-scale techniques, server-side visualisation and data services have been harnessed and integrated into the platform, so that analysis is performed seamlessly across the traditional boundaries of the underlying data domains. Characterisation of the techniques along with performance profiling ensures scalability of each software component, all of which can either be enhanced or replaced through future improvements. A Development-to-Operations (DevOps) framework has also been implemented to manage the scale of the software complexity alone. This ensures that software is both upgradable and maintainable, and can be readily reused with complexly integrated systems and become part of the growing global trusted community tools for cross-disciplinary research.

Participatory Evaluation of Monitoring and Modeling of Sustainable Land Management Technologies in Areas Prone to Land Degradation

NASA Astrophysics Data System (ADS)

Stringer, L. C.; Fleskens, L.; Reed, M. S.; de Vente, J.; Zengin, M.

2014-11-01

Examples of sustainable land management (SLM) exist throughout the world. In many cases, SLM has largely evolved through local traditional practices and incremental experimentation rather than being adopted on the basis of scientific evidence. This means that SLM technologies are often only adopted across small areas. The DESIRE (DESertIfication mitigation and REmediation of degraded land) project combined local traditional knowledge on SLM with empirical evaluation of SLM technologies. The purpose of this was to evaluate and select options for dissemination in 16 sites across 12 countries. It involved (i) an initial workshop to evaluate stakeholder priorities (reported elsewhere), (ii) field trials/empirical modeling, and then, (iii) further stakeholder evaluation workshops. This paper focuses on workshops in which stakeholders evaluated the performance of SLM technologies based on the scientific monitoring and modeling results from 15 study sites. It analyses workshop outcomes to evaluate how scientific results affected stakeholders' perceptions of local SLM technologies. It also assessed the potential of this participatory approach in facilitating wider acceptance and implementation of SLM. In several sites, stakeholder preferences for SLM technologies changed as a consequence of empirical measurements and modeling assessments of each technology. Two workshop examples are presented in depth to: (a) explore the scientific results that triggered stakeholders to change their views; and (b) discuss stakeholders' suggestions on how the adoption of SLM technologies could be up-scaled. The overall multi-stakeholder participatory approach taken is then evaluated. It is concluded that to facilitate broad-scale adoption of SLM technologies, de-contextualized, scientific generalisations must be given local context; scientific findings must be viewed alongside traditional beliefs and both scrutinized with equal rigor; and the knowledge of all kinds of experts must be recognised and considered in decision-making about SLM, whether it has been formally codified or not. The approach presented in this paper provided this opportunity and received positive feedback from stakeholders.

Facilitating Progress towards the Sustainable Development Goals through Open Scientific Data and Indicators

NASA Astrophysics Data System (ADS)

Chen, R. S.; Levy, M. A.; de Sherbinin, A. M.; Fischer, A.

2015-12-01

The Sustainable Development Goals (SDGs) represent an unprecedented international commitment to a shared future encompassing sustainable management of the planet and significant improvement in the human condition around the world. The scientific community has both an ethical responsibility and substantial self-interest—as residents of this planet—to help the world community to better understand the complex, interlinked behavior of human and environmental systems and to elucidate pathways to achieve long-term sustainability. Critical to making progress towards the SDGs is the open availability of timely, reliable, usable, and well integrated data and indicators relevant to all SDGs and associated targets. Such data and indicators will not only be valuable in monitoring and evaluation of progress, but also in developing policies and making decisions on environmental and societal issues affecting sustainability from local to global scales. The open availability of such data and indicators can help motivate performance, promote accountability, and facilitate cooperation. A range of scientific, technical, organizational, political, and resource challenges need to be addressed in developing a coherent SDG monitoring and indicator framework. For example, assembling and integrating diverse data on consistent spatial and temporal scales across the relevant natural, social, health, and engineering sciences pose both scientific and technical difficulties, and may require new ways to interlink and organize existing cyberinfrastructure, reconcile different data policy regimes, and fund integration efforts. New information technologies promise more timely and efficient ways of collecting many types of data, but may also raise privacy, control, and equity issues. Scientific review processes to ensure data quality need to be coordinated with the types of quality control and review employed by national statistical agencies for trusted economic and social statistics. Although large investments are already being made in some observing systems such as satellite-based remote sensing, additional resources are needed to fill key gaps, make data useful for decision making, and build capacity in developing countries. Broad engagement by the scientific community is urgently needed.

Physical Modeling of Flow Over Gale Crater, Mars: Laboratory Measurements of Basin Secondary Circulations

NASA Astrophysics Data System (ADS)

Bristow, N.; Blois, G.; Kim, T.; Anderson, W.; Day, M. D.; Kocurek, G.; Christensen, K. T.

2017-12-01

Impact craters, common large-scale topographic features on the surface of Mars, are circular depressions delimited by a sharp ridge. A variety of crater fill morphologies exist, suggesting that complex intracrater circulations affect their evolution. Some large craters (diameter > 10 km), particularly at mid latitudes on Mars, exhibit a central mound surrounded by circular moat. Foremost among these examples is Gale crater, landing site of NASA's Curiosity rover, since large-scale climatic processes early in in the history of Mars are preserved in the stratigraphic record of the inner mound. Investigating the intracrater flow produced by large scale winds aloft Mars craters is key to a number of important scientific issues including ongoing research on Mars paleo-environmental reconstruction and the planning of future missions (these results must be viewed in conjunction with the affects of radial katabatibc flows, the importance of which is already established in preceding studies). In this work we consider a number of crater shapes inspired by Gale morphology, including idealized craters. Access to the flow field within such geometrically complex topography is achieved herein using a refractive index matched approach. Instantaneous velocity maps, using both planar and volumetric PIV techniques, are presented to elucidate complex three-dimensional flow within the crater. In addition, first- and second-order statistics will be discussed in the context of wind-driven (aeolian) excavation of crater fill.

James Webb Space Telescope Core 2 Test - Cryogenic Thermal Balance Test of the Observatorys Core Area Thermal Control Hardware

NASA Technical Reports Server (NTRS)

Cleveland, Paul; Parrish, Keith; Thomson, Shaun; Marsh, James; Comber, Brian

2016-01-01

The James Webb Space Telescope (JWST), successor to the Hubble Space Telescope, will be the largest astronomical telescope ever sent into space. To observe the very first light of the early universe, JWST requires a large deployed 6.5-meter primary mirror cryogenically cooled to less than 50 Kelvin. Three scientific instruments are further cooled via a large radiator system to less than 40 Kelvin. A fourth scientific instrument is cooled to less than 7 Kelvin using a combination pulse-tube Joule-Thomson mechanical cooler. Passive cryogenic cooling enables the large scale of the telescope which must be highly folded for launch on an Ariane 5 launch vehicle and deployed once on orbit during its journey to the second Earth-Sun Lagrange point. Passive cooling of the observatory is enabled by the deployment of a large tennis court sized five layer Sunshield combined with the use of a network of high efficiency radiators. A high purity aluminum heat strap system connects the three instrument's detector systems to the radiator systems to dissipate less than a single watt of parasitic and instrument dissipated heat. JWST's large scale features, while enabling passive cooling, also prevent the typical flight configuration fully-deployed thermal balance test that is the keystone of most space missions' thermal verification plans. This paper describes the JWST Core 2 Test, which is a cryogenic thermal balance test of a full size, high fidelity engineering model of the Observatory's 'Core' area thermal control hardware. The 'Core' area is the key mechanical and cryogenic interface area between all Observatory elements. The 'Core' area thermal control hardware allows for temperature transition of 300K to approximately 50 K by attenuating heat from the room temperature IEC (instrument electronics) and the Spacecraft Bus. Since the flight hardware is not available for test, the Core 2 test uses high fidelity and flight-like reproductions.

Solar X-ray Astronomy Sounding Rocket Program

NASA Technical Reports Server (NTRS)

Moses, J. Daniel

1989-01-01

Several broad objectives were pursued by the development and flight of the High Resolution Soft X-Ray Imaging Sounding Rocket Payload, followed by the analysis of the resulting data and by comparison with both ground based and space based observations from other investigators. The scientific objectives were: to study the thermal equilibrium of active region loop systems by analyzing the X-ray observations to determine electron temperatures, densities, and pressures; by recording the changes in the large scale coronal structures from the maximum and descending phases of Cycle 21 to the ascending phase of Cycle 22; and to extend the study of small scale coronal structures through the minimum of Cycle 21 with new emphasis on correlative observations.

Salton Sea Scientific Drilling Program

USGS Publications Warehouse

Sass, J.H.

1988-01-01

The Salton Sea Scientific Drilling Program (SSSDP) was the first large-scale drilling project undertaken by the U.S Continental Scientific Drilling Program. The objectives of the SSSDP were (1) to drill a deep well into the Salton Sea Geothermal Field in the Imperial Valley of California, (2) to retrieve a high percentage of core and cuttings along the entire depth of the well, (3) to obtain a comprehensive suite of geophysical logs, (4) to conduct flow tests at two depths  (and to take fluid samples therefrom), and (5) to carry out several downhole experiments. These activites enabled the U.S Geological Survey and cooperating agencies to study the physical and chemical processes involved in an active hydrothermal system driven by a molten-rock heat source. This program, orginally conceived by Wilfred A. Elders, professor of geology at the University of California at Riverside, was coordinated under an inter-agency accord among the Geological Survey, the U.S Department of Energy, and the National Science Foundation. 

LAWS (Laser Atmospheric Wind Sounder) earth observing system

NASA Technical Reports Server (NTRS)

1988-01-01

Wind profiles can be measured from space using current technology. These wind profiles are essential for answering many of the interdisciplinary scientific questions to be addressed by EOS, the Earth Observing System. This report provides guidance for the development of a spaceborne wind sounder, the Laser Atmospheric Wind Sounder (LAWS), discussing the current state of the technology and reviewing the scientific rationale for the instrument. Whether obtained globally from the EOS polar platform or in the tropics and subtropics from the Space Station, wind profiles from space will provide essential information for advancing the skill of numerical weather prediction, furthering knowledge of large-scale atmospheric circulation and climate dynamics, and improving understanding of the global biogeochemical and hydrologic cycles. The LAWS Instrument Panel recommends that it be given high priority for new instrument development because of the pressing scientific need and the availability of the necessary technology. LAWS is to measure wind profiles with an accuracy of a few meters per second and to sample at intervals of 100 km horizontally for layers km thick.

History, Philosophy and Sociology of Science in Science Education: Results from the Third International Mathematics and Science Study

NASA Astrophysics Data System (ADS)

Wang, Hsingchi A.; Sshmidt, William H.

Throughout the history of enhancing the public scientific literacy, researchers have postulated that since every citizen is expected to have informal opinions on the relationships among government, education, and issues of scientific research and development, it is imperative that appreciation of the past complexities of science and society and the nature of scientific knowledge be a part of the education of both scientists and non-scientists. HPSS inclusion has been found to be an effective way to reach the goal of enhancing science literacy for all citizens. Although reports stated that HPSS inclusion is not a new educational practice in other part of the world, nevertheless, no large scale study has ever been attempted to report the HPSS educational conditions around the world. This study utilizes the rich data collected by TIMSS to unveil the current conditions of HPSS in the science education of about forty TIMSS countries. Based on the analysis results, recommendations to science educators of the world are provided.

Multidimensional model to assess the readiness of Saudi Arabia to implement evidence based child maltreatment prevention programs at a large scale.

PubMed

Almuneef, Maha A; Qayad, Mohamed; Noor, Ismail K; Al-Eissa, Majid A; Albuhairan, Fadia S; Inam, Sarah; Mikton, Christopher

2014-03-01

There has been increased awareness of child maltreatment in Saudi Arabia recently. This study assessed the readiness for implementing large-scale evidence-based child maltreatment prevention programs in Saudi Arabia. Key informants, who were key decision makers and senior managers in the field of child maltreatment, were invited to participate in the study. A multidimensional tool, developed by WHO and collaborators from several middle and low income countries, was used to assess 10 dimensions of readiness. A group of experts also gave an objective assessment of the 10 dimensions and key informants' and experts' scores were compared. On a scale of 100, the key informants gave a readiness score of 43% for Saudi Arabia to implement large-scale, evidence-based CM prevention programs, and experts gave an overall readiness score of 40%. Both the key informants and experts agreed that 4 of the dimensions (attitudes toward child maltreatment prevention, institutional links and resources, material resources, and human and technical resources) had low readiness scores (<5) each and three dimensions (knowledge of child maltreatment prevention, scientific data on child maltreatment prevention, and will to address child maltreatment problem) had high readiness scores (≥5) each. There was significant disagreement between key informants and experts on the remaining 3 dimensions. Overall, Saudi Arabia has a moderate/fair readiness to implement large-scale child maltreatment prevention programs. Capacity building; strengthening of material resources; and improving institutional links, collaborations, and attitudes toward the child maltreatment problem are required to improve the country's readiness to implement such programs. Copyright © 2013 Elsevier Ltd. All rights reserved.

Evaluating alternative systems of peer review: a large-scale agent-based modelling approach to scientific publication.

PubMed

Kovanis, Michail; Trinquart, Ludovic; Ravaud, Philippe; Porcher, Raphaël

2017-01-01

The debate on whether the peer-review system is in crisis has been heated recently. A variety of alternative systems have been proposed to improve the system and make it sustainable. However, we lack sufficient evidence and data related to these issues. Here we used a previously developed agent-based model of the scientific publication and peer-review system calibrated with empirical data to compare the efficiency of five alternative peer-review systems with the conventional system. We modelled two systems of immediate publication, with and without online reviews (crowdsourcing), a system with only one round of reviews and revisions allowed (re-review opt-out) and two review-sharing systems in which rejected manuscripts are resubmitted along with their past reviews to any other journal (portable) or to only those of the same publisher but of lower impact factor (cascade). The review-sharing systems outperformed or matched the performance of the conventional one in all peer-review efficiency, reviewer effort and scientific dissemination metrics we used. The systems especially showed a large decrease in total time of the peer-review process and total time devoted by reviewers to complete all reports in a year. The two systems with immediate publication released more scientific information than the conventional one but provided almost no other benefit. Re-review opt-out decreased the time reviewers devoted to peer review but had lower performance on screening papers that should not be published and relative increase in intrinsic quality of papers due to peer review than the conventional system. Sensitivity analyses showed consistent findings to those from our main simulations. We recommend prioritizing a system of review-sharing to create a sustainable scientific publication and peer-review system.

Einstein Inflationary Probe (EIP)

NASA Technical Reports Server (NTRS)

Hinshaw, Gary

2004-01-01

I will discuss plans to develop a concept for the Einstein Inflation Probe: a mission to detect gravity waves from inflation via the unique signature they impart to the cosmic microwave background (CMB) polarization. A sensitive CMB polarization satellite may be the only way to probe physics at the grand-unified theory (GUT) scale, exceeding by 12 orders of magnitude the energies studied at the Large Hadron Collider. A detection of gravity waves would represent a remarkable confirmation of the inflationary paradigm and set the energy scale at which inflation occurred when the universe was a fraction of a second old. Even a strong upper limit to the gravity wave amplitude would be significant, ruling out many common models of inflation, and pointing to inflation occurring at much lower energy, if at all. Measuring gravity waves via the CMB polarization will be challenging. We will undertake a comprehensive study to identify the critical scientific requirements for the mission and their derived instrumental performance requirements. At the core of the study will be an assessment of what is scientifically and experimentally optimal within the scope and purpose of the Einstein Inflation Probe.

Spatial and temporal patterns of stranded intertidal marine debris: is there a picture of global change?

PubMed

Browne, Mark Anthony; Chapman, M Gee; Thompson, Richard C; Amaral Zettler, Linda A; Jambeck, Jenna; Mallos, Nicholas J

2015-06-16

Floating and stranded marine debris is widespread. Increasing sea levels and altered rainfall, solar radiation, wind speed, waves, and oceanic currents associated with climatic change are likely to transfer more debris from coastal cities into marine and coastal habitats. Marine debris causes economic and ecological impacts, but understanding the scope of these requires quantitative information on spatial patterns and trends in the amounts and types of debris at a global scale. There are very few large-scale programs to measure debris, but many peer-reviewed and published scientific studies of marine debris describe local patterns. Unfortunately, methods of defining debris, sampling, and interpreting patterns in space or time vary considerably among studies, yet if data could be synthesized across studies, a global picture of the problem may be avaliable. We analyzed 104 published scientific papers on marine debris in order to determine how to evaluate this. Although many studies were well designed to answer specific questions, definitions of what constitutes marine debris, the methods used to measure, and the scale of the scope of the studies means that no general picture can emerge from this wealth of data. These problems are detailed to guide future studies and guidelines provided to enable the collection of more comparable data to better manage this growing problem.

Quantifying patterns of research interest evolution

NASA Astrophysics Data System (ADS)

Jia, Tao; Wang, Dashun; Szymanski, Boleslaw

Changing and shifting research interest is an integral part of a scientific career. Despite extensive investigations of various factors that influence a scientist's choice of research topics, quantitative assessments of mechanisms that give rise to macroscopic patterns characterizing research interest evolution of individual scientists remain limited. Here we perform a large-scale analysis of extensive publication records, finding that research interest change follows a reproducible pattern characterized by an exponential distribution. We identify three fundamental features responsible for the observed exponential distribution, which arise from a subtle interplay between exploitation and exploration in research interest evolution. We develop a random walk based model, which adequately reproduces our empirical observations. Our study presents one of the first quantitative analyses of macroscopic patterns governing research interest change, documenting a high degree of regularity underlying scientific research and individual careers.

Bioregulatory systems medicine: an innovative approach to integrating the science of molecular networks, inflammation, and systems biology with the patient's autoregulatory capacity?

PubMed Central

Goldman, Alyssa W.; Burmeister, Yvonne; Cesnulevicius, Konstantin; Herbert, Martha; Kane, Mary; Lescheid, David; McCaffrey, Timothy; Schultz, Myron; Seilheimer, Bernd; Smit, Alta; St. Laurent, Georges; Berman, Brian

2015-01-01

Bioregulatory systems medicine (BrSM) is a paradigm that aims to advance current medical practices. The basic scientific and clinical tenets of this approach embrace an interconnected picture of human health, supported largely by recent advances in systems biology and genomics, and focus on the implications of multi-scale interconnectivity for improving therapeutic approaches to disease. This article introduces the formal incorporation of these scientific and clinical elements into a cohesive theoretical model of the BrSM approach. The authors review this integrated body of knowledge and discuss how the emergent conceptual model offers the medical field a new avenue for extending the armamentarium of current treatment and healthcare, with the ultimate goal of improving population health. PMID:26347656

Not Just About the Science: Cold War Politics and the International Indian Ocean Expedition

NASA Astrophysics Data System (ADS)

Harper, K.

2016-12-01

The International Indian Ocean Expedition broke ground for a series of multi-national oceanographic expeditions starting in the late 1950s. In and of itself, it would have been historically significant—like the International Geophysical Year (1957-58)—for pulling together the international scientific community during the Cold War. However, US support for this and follow-on Indian Ocean expeditions were not just about the science; they were also about diplomacy, specifically efforts to bring non-aligned India into the US political orbit and out of the clutches of its Cold War enemy, the Soviet Union. This paper examines the behind-the-scenes efforts at the highest reaches of the US government to extract international political gain out of a large-scale scientific effort.

Improving the energy efficiency of sparse linear system solvers on multicore and manycore systems.

PubMed

Anzt, H; Quintana-Ortí, E S

2014-06-28

While most recent breakthroughs in scientific research rely on complex simulations carried out in large-scale supercomputers, the power draft and energy spent for this purpose is increasingly becoming a limiting factor to this trend. In this paper, we provide an overview of the current status in energy-efficient scientific computing by reviewing different technologies used to monitor power draft as well as power- and energy-saving mechanisms available in commodity hardware. For the particular domain of sparse linear algebra, we analyse the energy efficiency of a broad collection of hardware architectures and investigate how algorithmic and implementation modifications can improve the energy performance of sparse linear system solvers, without negatively impacting their performance. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Clickstream data yields high-resolution maps of science.

PubMed

Bollen, Johan; Van de Sompel, Herbert; Hagberg, Aric; Bettencourt, Luis; Chute, Ryan; Rodriguez, Marko A; Balakireva, Lyudmila

2009-01-01

Intricate maps of science have been created from citation data to visualize the structure of scientific activity. However, most scientific publications are now accessed online. Scholarly web portals record detailed log data at a scale that exceeds the number of all existing citations combined. Such log data is recorded immediately upon publication and keeps track of the sequences of user requests (clickstreams) that are issued by a variety of users across many different domains. Given these advantages of log datasets over citation data, we investigate whether they can produce high-resolution, more current maps of science. Over the course of 2007 and 2008, we collected nearly 1 billion user interactions recorded by the scholarly web portals of some of the most significant publishers, aggregators and institutional consortia. The resulting reference data set covers a significant part of world-wide use of scholarly web portals in 2006, and provides a balanced coverage of the humanities, social sciences, and natural sciences. A journal clickstream model, i.e. a first-order Markov chain, was extracted from the sequences of user interactions in the logs. The clickstream model was validated by comparing it to the Getty Research Institute's Architecture and Art Thesaurus. The resulting model was visualized as a journal network that outlines the relationships between various scientific domains and clarifies the connection of the social sciences and humanities to the natural sciences. Maps of science resulting from large-scale clickstream data provide a detailed, contemporary view of scientific activity and correct the underrepresentation of the social sciences and humanities that is commonly found in citation data.

Clickstream Data Yields High-Resolution Maps of Science

PubMed Central

Bollen, Johan; Van de Sompel, Herbert; Rodriguez, Marko A.; Balakireva, Lyudmila

2009-01-01

Background Intricate maps of science have been created from citation data to visualize the structure of scientific activity. However, most scientific publications are now accessed online. Scholarly web portals record detailed log data at a scale that exceeds the number of all existing citations combined. Such log data is recorded immediately upon publication and keeps track of the sequences of user requests (clickstreams) that are issued by a variety of users across many different domains. Given these advantages of log datasets over citation data, we investigate whether they can produce high-resolution, more current maps of science. Methodology Over the course of 2007 and 2008, we collected nearly 1 billion user interactions recorded by the scholarly web portals of some of the most significant publishers, aggregators and institutional consortia. The resulting reference data set covers a significant part of world-wide use of scholarly web portals in 2006, and provides a balanced coverage of the humanities, social sciences, and natural sciences. A journal clickstream model, i.e. a first-order Markov chain, was extracted from the sequences of user interactions in the logs. The clickstream model was validated by comparing it to the Getty Research Institute's Architecture and Art Thesaurus. The resulting model was visualized as a journal network that outlines the relationships between various scientific domains and clarifies the connection of the social sciences and humanities to the natural sciences. Conclusions Maps of science resulting from large-scale clickstream data provide a detailed, contemporary view of scientific activity and correct the underrepresentation of the social sciences and humanities that is commonly found in citation data. PMID:19277205

Blueprint for a microwave trapped ion quantum computer.

PubMed

Lekitsch, Bjoern; Weidt, Sebastian; Fowler, Austin G; Mølmer, Klaus; Devitt, Simon J; Wunderlich, Christof; Hensinger, Winfried K

2017-02-01

The availability of a universal quantum computer may have a fundamental impact on a vast number of research fields and on society as a whole. An increasingly large scientific and industrial community is working toward the realization of such a device. An arbitrarily large quantum computer may best be constructed using a modular approach. We present a blueprint for a trapped ion-based scalable quantum computer module, making it possible to create a scalable quantum computer architecture based on long-wavelength radiation quantum gates. The modules control all operations as stand-alone units, are constructed using silicon microfabrication techniques, and are within reach of current technology. To perform the required quantum computations, the modules make use of long-wavelength radiation-based quantum gate technology. To scale this microwave quantum computer architecture to a large size, we present a fully scalable design that makes use of ion transport between different modules, thereby allowing arbitrarily many modules to be connected to construct a large-scale device. A high error-threshold surface error correction code can be implemented in the proposed architecture to execute fault-tolerant operations. With appropriate adjustments, the proposed modules are also suitable for alternative trapped ion quantum computer architectures, such as schemes using photonic interconnects.

Convective phenomena at high resolution over Europe and the Mediterranean. The join EURO-CORDEX and Med-CORDEX flagship pilot study

NASA Astrophysics Data System (ADS)

Coppola, E.; Sobolowski, S.

2017-12-01

The join EURO-CORDEX and Med-CORDEX Flagship Pilot Study dedicated to the frontier research of using convective permitting (CP) models to address the impact of human induced climate change on convection, has been recently approved and the scientific community behind the project is made of 30 different scientific European institutes. The motivations for such a challenge is the availability of large field campaigns dedicated to the study of heavy precipitation events; the increased computing capacity and model developments; the emerging trend signals in extreme precipitation at daily and mainly sub-daily time scale in the Mediterranean and Alpine regions and the priority of convective extreme events under the WCRP Grand Challenge on climate extremes. The main objective of this effort are to investigate convective-scale events, their processes and changes in a few key regions of Europe and the Mediterranean using CP RCMs, statistical models and available observations. To provide a collective assessment of the modeling capacity at CP scale and to shape a coherent and collective assessment of the consequences of climate change on convective event impacts at local to regional scales. The scientific aims of this research are to investigate how the convective events and the damaging phenomena associated with them will respond to changing climate conditions in different European climates zone. To understand if an improved representation of convective phenomena at convective permitting scales will lead to upscaled added value and finally to assess the possibility to replace these costly convection-permitting experiments with statistical approaches like "convection emulators". The common initial domain will be an extended Alpine domain and all the groups will simulate a minimum of 10 years period with ERA-interim boundary conditions, with the possibility of other two sub-domains one in the Northwest continental Europe and another in the Southeast Mediterranean. The scenario simulations will be completed for three different 10 years time slices one in the historical period, one in the near future and the last one in the far future for the RCP8.5 scenario. The first target of this scientific community is to have an ensemble of 1-2 years ERA-interim simulations ready by late 2017 and a set of test cases to use as a pilot study.

Next Generation Analytic Tools for Large Scale Genetic Epidemiology Studies of Complex Diseases

PubMed Central

Mechanic, Leah E.; Chen, Huann-Sheng; Amos, Christopher I.; Chatterjee, Nilanjan; Cox, Nancy J.; Divi, Rao L.; Fan, Ruzong; Harris, Emily L.; Jacobs, Kevin; Kraft, Peter; Leal, Suzanne M.; McAllister, Kimberly; Moore, Jason H.; Paltoo, Dina N.; Province, Michael A.; Ramos, Erin M.; Ritchie, Marylyn D.; Roeder, Kathryn; Schaid, Daniel J.; Stephens, Matthew; Thomas, Duncan C.; Weinberg, Clarice R.; Witte, John S.; Zhang, Shunpu; Zöllner, Sebastian; Feuer, Eric J.; Gillanders, Elizabeth M.

2012-01-01

Over the past several years, genome-wide association studies (GWAS) have succeeded in identifying hundreds of genetic markers associated with common diseases. However, most of these markers confer relatively small increments of risk and explain only a small proportion of familial clustering. To identify obstacles to future progress in genetic epidemiology research and provide recommendations to NIH for overcoming these barriers, the National Cancer Institute sponsored a workshop entitled “Next Generation Analytic Tools for Large-Scale Genetic Epidemiology Studies of Complex Diseases” on September 15–16, 2010. The goal of the workshop was to facilitate discussions on (1) statistical strategies and methods to efficiently identify genetic and environmental factors contributing to the risk of complex disease; and (2) how to develop, apply, and evaluate these strategies for the design, analysis, and interpretation of large-scale complex disease association studies in order to guide NIH in setting the future agenda in this area of research. The workshop was organized as a series of short presentations covering scientific (gene-gene and gene-environment interaction, complex phenotypes, and rare variants and next generation sequencing) and methodological (simulation modeling and computational resources and data management) topic areas. Specific needs to advance the field were identified during each session and are summarized. PMID:22147673

A novel combined SLAM based on RBPF-SLAM and EIF-SLAM for mobile system sensing in a large scale environment.

PubMed

He, Bo; Zhang, Shujing; Yan, Tianhong; Zhang, Tao; Liang, Yan; Zhang, Hongjin

2011-01-01

Mobile autonomous systems are very important for marine scientific investigation and military applications. Many algorithms have been studied to deal with the computational efficiency problem required for large scale simultaneous localization and mapping (SLAM) and its related accuracy and consistency. Among these methods, submap-based SLAM is a more effective one. By combining the strength of two popular mapping algorithms, the Rao-Blackwellised particle filter (RBPF) and extended information filter (EIF), this paper presents a combined SLAM-an efficient submap-based solution to the SLAM problem in a large scale environment. RBPF-SLAM is used to produce local maps, which are periodically fused into an EIF-SLAM algorithm. RBPF-SLAM can avoid linearization of the robot model during operating and provide a robust data association, while EIF-SLAM can improve the whole computational speed, and avoid the tendency of RBPF-SLAM to be over-confident. In order to further improve the computational speed in a real time environment, a binary-tree-based decision-making strategy is introduced. Simulation experiments show that the proposed combined SLAM algorithm significantly outperforms currently existing algorithms in terms of accuracy and consistency, as well as the computing efficiency. Finally, the combined SLAM algorithm is experimentally validated in a real environment by using the Victoria Park dataset.

Large space telescope, phase A. Volume 4: Scientific instrument package

NASA Technical Reports Server (NTRS)

1972-01-01

The design and characteristics of the scientific instrument package for the Large Space Telescope are discussed. The subjects include: (1) general scientific objectives, (2) package system analysis, (3) scientific instrumentation, (4) imaging photoelectric sensors, (5) environmental considerations, and (6) reliability and maintainability.

Scientific Accomplishments for ARL Brain Structure-Function Couplings Research on Large-Scale Brain Networks from FY11-FY13 (DSI Final Report)

DTIC Science & Technology

2014-03-01

streamlines) from two types of diffusion weighted imaging scans, diffusion tensor imaging ( DTI ) and diffusion spectrum imaging (DSI). We examined...individuals. Importantly, the results also showed that this effect was greater for the DTI method than the DSI method. This suggested that DTI can better...compared to level surface walking. This project combines experimental EEG data and electromyography (EMG) data recorded from seven muscles of the leg

Selling the Space Telescope - The interpenetration of science, technology, and politics

NASA Technical Reports Server (NTRS)

Smith, Robert W.

1991-01-01

Attention is given to the politics of initiating the Space Telescope program and to the manner in which the coalition, or working consensus, for the Telescope was assembled, in particular, the role played by astronomers. It is contended that what ensued was a case study in the influence of government patronage on a large-scale scientific and technological program. It is concluded that while a politically feasible Space Telescope did result, in the selling process the Telescope had been both oversold and underfunded.

Mira: Argonne's 10-petaflops supercomputer

ScienceCinema

Papka, Michael; Coghlan, Susan; Isaacs, Eric; Peters, Mark; Messina, Paul

2018-02-13

Mira, Argonne's petascale IBM Blue Gene/Q system, ushers in a new era of scientific supercomputing at the Argonne Leadership Computing Facility. An engineering marvel, the 10-petaflops supercomputer is capable of carrying out 10 quadrillion calculations per second. As a machine for open science, any researcher with a question that requires large-scale computing resources can submit a proposal for time on Mira, typically in allocations of millions of core-hours, to run programs for their experiments. This adds up to billions of hours of computing time per year.

Technological disasters, crisis management and leadership stress.

PubMed

Weisaeth, Lars; Knudsen, Øistein; Tønnessen, Arnfinn

2002-07-01

This paper discusses how psychological stress disturbs decision making during technological crisis and disaster, and how to prevent this from happening. This is exemplified by scientific studies of a Norwegian large scale accident involving hazardous material, and of handling the far-off effects of the nuclear disaster at Chernobyl. The former constitutes an operative level of crisis management, whereas the latter involves crisis management at the strategic and political level. We conclude that stress had a negative effect on decision making in both cases.

Mira: Argonne's 10-petaflops supercomputer

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

Papka, Michael; Coghlan, Susan; Isaacs, Eric

2013-07-03

Mira, Argonne's petascale IBM Blue Gene/Q system, ushers in a new era of scientific supercomputing at the Argonne Leadership Computing Facility. An engineering marvel, the 10-petaflops supercomputer is capable of carrying out 10 quadrillion calculations per second. As a machine for open science, any researcher with a question that requires large-scale computing resources can submit a proposal for time on Mira, typically in allocations of millions of core-hours, to run programs for their experiments. This adds up to billions of hours of computing time per year.

Towards the Teraflop CFD

NASA Technical Reports Server (NTRS)

Schreiber, Robert; Simon, Horst D.

1992-01-01

We are surveying current projects in the area of parallel supercomputers. The machines considered here will become commercially available in the 1990 - 1992 time frame. All are suitable for exploring the critical issues in applying parallel processors to large scale scientific computations, in particular CFD calculations. This chapter presents an overview of the surveyed machines, and a detailed analysis of the various architectural and technology approaches taken. Particular emphasis is placed on the feasibility of a Teraflops capability following the paths proposed by various developers.

An integrated circuit floating point accumulator

NASA Technical Reports Server (NTRS)

Goldsmith, T. C.

1977-01-01

Goddard Space Flight Center has developed a large scale integrated circuit (type 623) which can perform pulse counting, storage, floating point compression, and serial transmission, using a single monolithic device. Counts of 27 or 19 bits can be converted to transmitted values of 12 or 8 bits respectively. Use of the 623 has resulted in substantial savaings in weight, volume, and dollar resources on at least 11 scientific instruments to be flown on 4 NASA spacecraft. The design, construction, and application of the 623 are described.

Secrecy and Physics

NASA Astrophysics Data System (ADS)

Galison, Peter

2010-02-01

Secrecy in matters of national defense goes back far past antiquity. But our modern form of national secrecy owes a huge amount to a the large scale, systematic, and technical system of scientific secrecy that began in the Radar and Manhattan Projects of World War II and came to its current form in the Cold War. Here I would like to capture some of this trajectory and to present some of the paradoxes and deep conundrums that our secrecy system offers us in the Post-Cold War world. )

Workshop on Advances in Scientific Computation and Differential Equations 󈨡 (SCADE)

DTIC Science & Technology

1994-07-18

STATEMENT ~~’"j’’ Approved for public release; distribution unlimited. I ABSTRACT (MAMMU 200WOMW 94 808 1 64 4.L SUBIECT TERMS Ii11URE Of PAGES 12 16...called differential algebraic ODEs (DAES). (Some important early research on this topic was by L. Petzold.) Both theoretically and in terms of...completely specify the solution. In many physical systems, especially those in biology, or other large scale slowly responding systems, the inclusion of some

Experience in using commercial clouds in CMS

NASA Astrophysics Data System (ADS)

Bauerdick, L.; Bockelman, B.; Dykstra, D.; Fuess, S.; Garzoglio, G.; Girone, M.; Gutsche, O.; Holzman, B.; Hufnagel, D.; Kim, H.; Kennedy, R.; Mason, D.; Spentzouris, P.; Timm, S.; Tiradani, A.; Vaandering, E.; CMS Collaboration

2017-10-01

Historically high energy physics computing has been performed on large purpose-built computing systems. In the beginning there were single site computing facilities, which evolved into the Worldwide LHC Computing Grid (WLCG) used today. The vast majority of the WLCG resources are used for LHC computing and the resources are scheduled to be continuously used throughout the year. In the last several years there has been an explosion in capacity and capability of commercial and academic computing clouds. Cloud resources are highly virtualized and intended to be able to be flexibly deployed for a variety of computing tasks. There is a growing interest amongst the cloud providers to demonstrate the capability to perform large scale scientific computing. In this presentation we will discuss results from the CMS experiment using the Fermilab HEPCloud Facility, which utilized both local Fermilab resources and Amazon Web Services (AWS). The goal was to work with AWS through a matching grant to demonstrate a sustained scale approximately equal to half of the worldwide processing resources available to CMS. We will discuss the planning and technical challenges involved in organizing the most IO intensive CMS workflows on a large-scale set of virtualized resource provisioned by the Fermilab HEPCloud. We will describe the data handling and data management challenges. Also, we will discuss the economic issues and cost and operational efficiency comparison to our dedicated resources. At the end we will consider the changes in the working model of HEP computing in a domain with the availability of large scale resources scheduled at peak times.

Experience in using commercial clouds in CMS

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

Bauerdick, L.; Bockelman, B.; Dykstra, D.

Historically high energy physics computing has been performed on large purposebuilt computing systems. In the beginning there were single site computing facilities, which evolved into the Worldwide LHC Computing Grid (WLCG) used today. The vast majority of the WLCG resources are used for LHC computing and the resources are scheduled to be continuously used throughout the year. In the last several years there has been an explosion in capacity and capability of commercial and academic computing clouds. Cloud resources are highly virtualized and intended to be able to be flexibly deployed for a variety of computing tasks. There is amore » growing interest amongst the cloud providers to demonstrate the capability to perform large scale scientific computing. In this presentation we will discuss results from the CMS experiment using the Fermilab HEPCloud Facility, which utilized both local Fermilab resources and Amazon Web Services (AWS). The goal was to work with AWS through a matching grant to demonstrate a sustained scale approximately equal to half of the worldwide processing resources available to CMS. We will discuss the planning and technical challenges involved in organizing the most IO intensive CMS workflows on a large-scale set of virtualized resource provisioned by the Fermilab HEPCloud. We will describe the data handling and data management challenges. Also, we will discuss the economic issues and cost and operational efficiency comparison to our dedicated resources. At the end we will consider the changes in the working model of HEP computing in a domain with the availability of large scale resources scheduled at peak times.« less

ArrayBridge: Interweaving declarative array processing with high-performance computing

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

Xing, Haoyuan; Floratos, Sofoklis; Blanas, Spyros

Scientists are increasingly turning to datacenter-scale computers to produce and analyze massive arrays. Despite decades of database research that extols the virtues of declarative query processing, scientists still write, debug and parallelize imperative HPC kernels even for the most mundane queries. This impedance mismatch has been partly attributed to the cumbersome data loading process; in response, the database community has proposed in situ mechanisms to access data in scientific file formats. Scientists, however, desire more than a passive access method that reads arrays from files. This paper describes ArrayBridge, a bi-directional array view mechanism for scientific file formats, that aimsmore » to make declarative array manipulations interoperable with imperative file-centric analyses. Our prototype implementation of ArrayBridge uses HDF5 as the underlying array storage library and seamlessly integrates into the SciDB open-source array database system. In addition to fast querying over external array objects, ArrayBridge produces arrays in the HDF5 file format just as easily as it can read from it. ArrayBridge also supports time travel queries from imperative kernels through the unmodified HDF5 API, and automatically deduplicates between array versions for space efficiency. Our extensive performance evaluation in NERSC, a large-scale scientific computing facility, shows that ArrayBridge exhibits statistically indistinguishable performance and I/O scalability to the native SciDB storage engine.« less

Lightweight and Statistical Techniques for Petascale Debugging: Correctness on Petascale Systems (CoPS) Preliminry Report

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

de Supinski, B R; Miller, B P; Liblit, B

2011-09-13

Petascale platforms with O(10{sup 5}) and O(10{sup 6}) processing cores are driving advancements in a wide range of scientific disciplines. These large systems create unprecedented application development challenges. Scalable correctness tools are critical to shorten the time-to-solution on these systems. Currently, many DOE application developers use primitive manual debugging based on printf or traditional debuggers such as TotalView or DDT. This paradigm breaks down beyond a few thousand cores, yet bugs often arise above that scale. Programmers must reproduce problems in smaller runs to analyze them with traditional tools, or else perform repeated runs at scale using only primitive techniques.more » Even when traditional tools run at scale, the approach wastes substantial effort and computation cycles. Continued scientific progress demands new paradigms for debugging large-scale applications. The Correctness on Petascale Systems (CoPS) project is developing a revolutionary debugging scheme that will reduce the debugging problem to a scale that human developers can comprehend. The scheme can provide precise diagnoses of the root causes of failure, including suggestions of the location and the type of errors down to the level of code regions or even a single execution point. Our fundamentally new strategy combines and expands three relatively new complementary debugging approaches. The Stack Trace Analysis Tool (STAT), a 2011 R&D 100 Award Winner, identifies behavior equivalence classes in MPI jobs and highlights behavior when elements of the class demonstrate divergent behavior, often the first indicator of an error. The Cooperative Bug Isolation (CBI) project has developed statistical techniques for isolating programming errors in widely deployed code that we will adapt to large-scale parallel applications. Finally, we are developing a new approach to parallelizing expensive correctness analyses, such as analysis of memory usage in the Memgrind tool. In the first two years of the project, we have successfully extended STAT to determine the relative progress of different MPI processes. We have shown that the STAT, which is now included in the debugging tools distributed by Cray with their large-scale systems, substantially reduces the scale at which traditional debugging techniques are applied. We have extended CBI to large-scale systems and developed new compiler based analyses that reduce its instrumentation overhead. Our results demonstrate that CBI can identify the source of errors in large-scale applications. Finally, we have developed MPIecho, a new technique that will reduce the time required to perform key correctness analyses, such as the detection of writes to unallocated memory. Overall, our research results are the foundations for new debugging paradigms that will improve application scientist productivity by reducing the time to determine which package or module contains the root cause of a problem that arises at all scales of our high end systems. While we have made substantial progress in the first two years of CoPS research, significant work remains. While STAT provides scalable debugging assistance for incorrect application runs, we could apply its techniques to assertions in order to observe deviations from expected behavior. Further, we must continue to refine STAT's techniques to represent behavioral equivalence classes efficiently as we expect systems with millions of threads in the next year. We are exploring new CBI techniques that can assess the likelihood that execution deviations from past behavior are the source of erroneous execution. Finally, we must develop usable correctness analyses that apply the MPIecho parallelization strategy in order to locate coding errors. We expect to make substantial progress on these directions in the next year but anticipate that significant work will remain to provide usable, scalable debugging paradigms.« less

PREFACE: 7th European Conference on Applied Superconductivity (EUCAS '05)

NASA Astrophysics Data System (ADS)

Weber, Harald W.; Sauerzopf, Franz M.

2006-07-01

This issue of Journal of Physics: Conference Series contains those contributed papers that were submitted to the Conference Proceedings of the 7th European Conference on Applied Superconductivity (EUCAS '05) on 11 - 15 September 2005. The plenary and invited papers were published in the journal Superconductor Science and Technology 19 2006 (March issue). The scientific aims of EUCAS '05 followed the tradition established at the preceding conferences in Göttingen, Edinburgh, Eindhoven, Sitges (Barcelona), Lyngby (Copenhagen) and finally Sorrento (Napoli). The focus was placed on the interplay between the most recent developments in superconductor research and the positioning of applications of superconductivity in the marketplace. Although initially founded as an exchange forum mainly for European scientists, it has gradually developed into a truly international meeting with significant attendance from the Far East and the United States. The Vienna conference attracted 813 participants in the scientific programme and 90 guests: of the particpants 59% were from Europe, 31% from the Far East, 6% from the United States and Canada and 4% from other nations worldwide. There were 32 plenary and invited lectures highlighting the state-of-the-art in the areas of materials, large-scale and small-scale applications, and 625 papers were contributed (556 of these were posters) demonstrating the broad range of exciting activities in all research areas of our field. A total of 27 companies presented their most recent developments in the field. This volume contains 349 papers, among them 173 on materials (49.6%), 90 on large scale applications (25.8%) and 86 on small scale applications (24.6%). EUCAS '05 generated a feeling of optimism and enthusiasm for this fascinating field of research and for its well established technological potential, especially among the numerous young researchers attending this Conference. We are grateful to all those who participated in the meeting and contributed to its success. Harald W Weber (Conference Chairman) Franz M Sauerzopf (Conference Secretary)

Visualization: A pathway to enhanced scientific productivity in the expanding missions of Space and Earth Sciences

NASA Technical Reports Server (NTRS)

Szuszczewicz, E. P.

1995-01-01

The movement toward the solution of problems involving large-scale system science, the ever-increasing capabilities of three-dimensional, time-dependent numerical models, and the enhanced capabilities of 'in situ' and remote sensing instruments bring a new era of scientific endeavor that requires an important change in our approach to mission planning and the task of data reduction and analysis. Visualization is at the heart of the requirements for a much-needed enhancement in scientific productivity as we face these new challenges. This article draws a perspective on the problem as it crosses discipline boundaries from solar physics to atmospheric and ocean sciences. It also attempts to introduce visualization as a new approach to scientific discovery and a tool which expedites and improves our insight into physically complex problems. A set of simple illustrations demonstrates a number of visualization techniques and the discussion emphasizes the trial-and-error and search-and-discover modes that are necessary for the techniques to reach their full potential. Further discussions also point to the importance of integrating data access, management, mathematical operations, and visualization into a single system. Some of the more recent developments in this area are reviewed.

A DBMS architecture for global change research

NASA Astrophysics Data System (ADS)

Hachem, Nabil I.; Gennert, Michael A.; Ward, Matthew O.

1993-08-01

The goal of this research is the design and development of an integrated system for the management of very large scientific databases, cartographic/geographic information processing, and exploratory scientific data analysis for global change research. The system will represent both spatial and temporal knowledge about natural and man-made entities on the eath's surface, following an object-oriented paradigm. A user will be able to derive, modify, and apply, procedures to perform operations on the data, including comparison, derivation, prediction, validation, and visualization. This work represents an effort to extend the database technology with an intrinsic class of operators, which is extensible and responds to the growing needs of scientific research. Of significance is the integration of many diverse forms of data into the database, including cartography, geography, hydrography, hypsography, images, and urban planning data. Equally important is the maintenance of metadata, that is, data about the data, such as coordinate transformation parameters, map scales, and audit trails of previous processing operations. This project will impact the fields of geographical information systems and global change research as well as the database community. It will provide an integrated database management testbed for scientific research, and a testbed for the development of analysis tools to understand and predict global change.

From path models to commands during additive printing of large-scale architectural designs

NASA Astrophysics Data System (ADS)

Chepchurov, M. S.; Zhukov, E. M.; Yakovlev, E. A.; Matveykin, V. G.

2018-05-01

The article considers the problem of automation of the formation of large complex parts, products and structures, especially for unique or small-batch objects produced by a method of additive technology [1]. Results of scientific research in search for the optimal design of a robotic complex, its modes of operation (work), structure of its control helped to impose the technical requirements on the technological process for manufacturing and design installation of the robotic complex. Research on virtual models of the robotic complexes allowed defining the main directions of design improvements and the main goal (purpose) of testing of the the manufactured prototype: checking the positioning accuracy of the working part.

SEAPAK user's guide, version 2.0. Volume 2: Descriptions of programs

NASA Technical Reports Server (NTRS)

Mcclain, Charles R.; Darzi, Michael; Firestone, James K.; Fu, Gary; Yeh, Eueng-Nan; Endres, Daniel L.

1991-01-01

The SEAPAK is a user-interactive satellite data analysis package that was developed for the processing and interpretation of Nimbus-7/Coastal Zone Color Scanner (CZCS) and the NOAA Advanced Very High Resolution Radiometer (AVHRR) data. Significant revisions were made since version 1.0, and the ancillary environmental data analysis module was greatly expanded. The package continues to be user friendly and user interactive. Also, because the scientific goals of the ocean color research being conducted have shifted to large space and time scales, batch processing capabilities for both satellite and ancillary environmental data analyses were enhanced, thus allowing for large quantities of data to be ingested and analyzed.

Access control and privacy in large distributed systems

NASA Technical Reports Server (NTRS)

Leiner, B. M.; Bishop, M.

1986-01-01

Large scale distributed systems consists of workstations, mainframe computers, supercomputers and other types of servers, all connected by a computer network. These systems are being used in a variety of applications including the support of collaborative scientific research. In such an environment, issues of access control and privacy arise. Access control is required for several reasons, including the protection of sensitive resources and cost control. Privacy is also required for similar reasons, including the protection of a researcher's proprietary results. A possible architecture for integrating available computer and communications security technologies into a system that meet these requirements is described. This architecture is meant as a starting point for discussion, rather that the final answer.

SEAPAK user's guide, version 2.0. Volume 1: System description

NASA Technical Reports Server (NTRS)

Mcclain, Charles R.; Darzi, Michael; Firestone, James K.; Fu, Gary; Yeh, Eueng-Nan; Endres, Daniel L.

1991-01-01

The SEAPAK is a user interactive satellite data analysis package that was developed for the processing and interpretation of Nimbus-7/Coastal Zone Color Scanner (CZCS) and the NOAA Advanced Very High Resolution Radiometer (AVHRR) data. Significant revisions were made to version 1.0 of the guide, and the ancillary environmental data analysis module was expanded. The package continues to emphasize user friendliness and user interactive data analyses. Additionally, because the scientific goals of the ocean color research being conducted have shifted to large space and time scales, batch processing capabilities for both satellite and ancillary environmental data analyses were enhanced, thus allowing large quantities of data to be ingested and analyzed in background.

Exploration of Korean Students' Scientific Imagination Using the Scientific Imagination Inventory

ERIC Educational Resources Information Center

Mun, Jiyeong; Mun, Kongju; Kim, Sung-Won

2015-01-01

This article reports on the study of the components of scientific imagination and describes the scales used to measure scientific imagination in Korean elementary and secondary students. In this study, we developed an inventory, which we call the Scientific Imagination Inventory (SII), in order to examine aspects of scientific imagination. We…

Global-scale Observations of the Limb and Disk (GOLD) Mission: Science from Geostationary Orbit on-board a Commercial Communications Satellite

NASA Astrophysics Data System (ADS)

Eastes, R.; Deaver, T.; Krywonos, A.; Lankton, M. R.; McClintock, W. E.; Pang, R.

2011-12-01

Geostationary orbits are ideal for many science investigations of the Earth system on global scales. These orbits allow continuous observations of the same geographic region, enabling spatial and temporal changes to be distinguished and eliminating the ambiguity inherent to observations from low Earth orbit (LEO). Just as observations from geostationary orbit have revolutionized our understanding of changes in the troposphere, they will dramatically improve our understanding of the space environment at higher altitudes. However, geostationary orbits are infrequently used for science missions because of high costs. Geostationary satellites are large, typically weighing tons. Consequently, devoting an entire satellite to a science mission requires a large financial commitment, both for the spacecraft itself and for sufficient science instrumentation to justify a dedicated spacecraft. Furthermore, the small number of geostationary satellites produced for scientific missions increases the costs of each satellite. For these reasons, it is attractive to consider flying scientific instruments on satellites operated by commercial companies, some of whom have fleets of ~40 satellites. However, scientists' lack of understanding of the capabilities of commercial spacecraft as well as commercial companies' concerns about risks to their primary mission have impeded the cooperation necessary for the shared use of a spacecraft. Working with a commercial partner, the GOLD mission has successfully overcome these issues. Our experience indicates that there are numerous benefits to flying on commercial communications satellites (e.g., it is possible to downlink large amounts of data) and the costs are low if the experimental requirements adequately match the capabilities and available resources of the host spacecraft. Consequently, affordable access to geostationary orbit aboard a communications satellite now appears possible for science payloads.

MememxGATE: Unearthing Latent Content Features for Improved Search and Relevancy Ranking Across Scientific Literature

NASA Astrophysics Data System (ADS)

Wilson, B. D.; McGibbney, L. J.; Mattmann, C. A.; Ramirez, P.; Joyce, M.; Whitehall, K. D.

2015-12-01

Quantifying scientific relevancy is of increasing importance to NASA and the research community. Scientific relevancy may be defined by mapping the impacts of a particular NASA mission, instrument, and/or retrieved variables to disciplines such as climate predictions, natural hazards detection and mitigation processes, education, and scientific discoveries. Related to relevancy, is the ability to expose data with similar attributes. This in turn depends upon the ability for us to extract latent, implicit document features from scientific data and resources and make them explicit, accessible and useable for search activities amongst others. This paper presents MemexGATE; a server side application, command line interface and computing environment for running large scale metadata extraction, general architecture text engineering, document classification and indexing tasks over document resources such as social media streams, scientific literature archives, legal documentation, etc. This work builds on existing experiences using MemexGATE (funded, developed and validated through the DARPA Memex Progrjam PI Mattmann) for extracting and leveraging latent content features from document resources within the Materials Research domain. We extend the software functionality capability to the domain of scientific literature with emphasis on the expansion of gazetteer lists, named entity rules, natural language construct labeling (e.g. synonym, antonym, hyponym, etc.) efforts to enable extraction of latent content features from data hosted by wide variety of scientific literature vendors (AGU Meeting Abstract Database, Springer, Wiley Online, Elsevier, etc.) hosting earth science literature. Such literature makes both implicit and explicit references to NASA datasets and relationships between such concepts stored across EOSDIS DAAC's hence we envisage that a significant part of this effort will also include development and understanding of relevancy signals which can ultimately be utilized for improved search and relevancy ranking across scientific literature.

Performance analysis of a dual-tree algorithm for computing spatial distance histograms

PubMed Central

Chen, Shaoping; Tu, Yi-Cheng; Xia, Yuni

2011-01-01

Many scientific and engineering fields produce large volume of spatiotemporal data. The storage, retrieval, and analysis of such data impose great challenges to database systems design. Analysis of scientific spatiotemporal data often involves computing functions of all point-to-point interactions. One such analytics, the Spatial Distance Histogram (SDH), is of vital importance to scientific discovery. Recently, algorithms for efficient SDH processing in large-scale scientific databases have been proposed. These algorithms adopt a recursive tree-traversing strategy to process point-to-point distances in the visited tree nodes in batches, thus require less time when compared to the brute-force approach where all pairwise distances have to be computed. Despite the promising experimental results, the complexity of such algorithms has not been thoroughly studied. In this paper, we present an analysis of such algorithms based on a geometric modeling approach. The main technique is to transform the analysis of point counts into a problem of quantifying the area of regions where pairwise distances can be processed in batches by the algorithm. From the analysis, we conclude that the number of pairwise distances that are left to be processed decreases exponentially with more levels of the tree visited. This leads to the proof of a time complexity lower than the quadratic time needed for a brute-force algorithm and builds the foundation for a constant-time approximate algorithm. Our model is also general in that it works for a wide range of point spatial distributions, histogram types, and space-partitioning options in building the tree. PMID:21804753

Studies of Coronae and Large Volcanoes on Venus: Constraining the Diverse Outcomes of Small-Scale Mantle Upwellings on Venus

NASA Technical Reports Server (NTRS)

Stofan, Ellen R.

2005-01-01

Proxemy Research had a grant from NASA to perform science research on upwelling and volcanism on Venus. This was a 3 year Planetary Geology and Geophysics grant to E. Stofan, entitled Coronae and Large volcanoes on Venus. This grant closes on 12/31/05. Here we summarize the scientific progress and accomplishments of this grant. Scientific publications and abstracts of presentations are indicated in the final section. This was a very productive grant and the progress that was made is summarized. Attention is drawn to the publications and abstracts published in each year. The proposal consisted of two tasks, one examining coronae and one studying large volcanoes. The corona task (Task 1) consisted of three parts: 1) a statistical study of the updated corona population, with Sue Smrekar, Lori Glaze, Paula Martin and Steve Baloga; 2) geologic analysis of several specific groups of coronae, with Sue Smrekar and others; and 3) determining the histories and significance of a number of coronae with extreme amounts of volcanism, with Sue Smrekar. Task 2, studies of large volcanoes, consisted of two subtasks. In the first, we studied the geologic history of several volcanoes, with John Guest, Peter Grindrod, Antony Brian and Steve Anderson. In the second subtask, I analyzed a number of Venusian volcanoes with evidence of summit diking along with Peter Grindrod and Francis Nimmo.

A CCD experimental platform for large telescope in Antarctica based on FPGA

NASA Astrophysics Data System (ADS)

Zhu, Yuhua; Qi, Yongjun

2014-07-01

The CCD , as a detector , is one of the important components of astronomical telescopes. For a large telescope in Antarctica, a set of CCD detector system with large size, high sensitivity and low noise is indispensable. Because of the extremely low temperatures and unattended, system maintenance and software and hardware upgrade become hard problems. This paper introduces a general CCD controller experiment platform, using Field programmable gate array FPGA, which is, in fact, a large-scale field reconfigurable array. Taking the advantage of convenience to modify the system, construction of driving circuit, digital signal processing module, network communication interface, control algorithm validation, and remote reconfigurable module may realize. With the concept of integrated hardware and software, the paper discusses the key technology of building scientific CCD system suitable for the special work environment in Antarctica, focusing on the method of remote reconfiguration for controller via network and then offering a feasible hardware and software solution.

Linking Automated Data Analysis and Visualization with Applications in Developmental Biology and High-Energy Physics

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

Ruebel, Oliver

2009-11-20

Knowledge discovery from large and complex collections of today's scientific datasets is a challenging task. With the ability to measure and simulate more processes at increasingly finer spatial and temporal scales, the increasing number of data dimensions and data objects is presenting tremendous challenges for data analysis and effective data exploration methods and tools. Researchers are overwhelmed with data and standard tools are often insufficient to enable effective data analysis and knowledge discovery. The main objective of this thesis is to provide important new capabilities to accelerate scientific knowledge discovery form large, complex, and multivariate scientific data. The research coveredmore » in this thesis addresses these scientific challenges using a combination of scientific visualization, information visualization, automated data analysis, and other enabling technologies, such as efficient data management. The effectiveness of the proposed analysis methods is demonstrated via applications in two distinct scientific research fields, namely developmental biology and high-energy physics.Advances in microscopy, image analysis, and embryo registration enable for the first time measurement of gene expression at cellular resolution for entire organisms. Analysis of high-dimensional spatial gene expression datasets is a challenging task. By integrating data clustering and visualization, analysis of complex, time-varying, spatial gene expression patterns and their formation becomes possible. The analysis framework MATLAB and the visualization have been integrated, making advanced analysis tools accessible to biologist and enabling bioinformatic researchers to directly integrate their analysis with the visualization. Laser wakefield particle accelerators (LWFAs) promise to be a new compact source of high-energy particles and radiation, with wide applications ranging from medicine to physics. To gain insight into the complex physical processes of particle acceleration, physicists model LWFAs computationally. The datasets produced by LWFA simulations are (i) extremely large, (ii) of varying spatial and temporal resolution, (iii) heterogeneous, and (iv) high-dimensional, making analysis and knowledge discovery from complex LWFA simulation data a challenging task. To address these challenges this thesis describes the integration of the visualization system VisIt and the state-of-the-art index/query system FastBit, enabling interactive visual exploration of extremely large three-dimensional particle datasets. Researchers are especially interested in beams of high-energy particles formed during the course of a simulation. This thesis describes novel methods for automatic detection and analysis of particle beams enabling a more accurate and efficient data analysis process. By integrating these automated analysis methods with visualization, this research enables more accurate, efficient, and effective analysis of LWFA simulation data than previously possible.« less

Large-scale modeling on the fate and transport of polycyclic aromatic hydrocarbons (PAHs) in multimedia over China

NASA Astrophysics Data System (ADS)

Huang, Y.; Liu, M.; Wada, Y.; He, X.; Sun, X.

2017-12-01

In recent decades, with rapid economic growth, industrial development and urbanization, expanding pollution of polycyclic aromatic hydrocarbons (PAHs) has become a diversified and complicated phenomenon in China. However, the availability of sufficient monitoring activities for PAHs in multi-compartment and the corresponding multi-interface migration processes are still limited, especially at a large geographic area. In this study, we couple the Multimedia Fate Model (MFM) to the Community Multi-Scale Air Quality (CMAQ) model in order to consider the fugacity and the transient contamination processes. This coupled dynamic contaminant model can evaluate the detailed local variations and mass fluxes of PAHs in different environmental media (e.g., air, surface film, soil, sediment, water and vegetation) across different spatial (a county to country) and temporal (days to years) scales. This model has been applied to a large geographical domain of China at a 36 km by 36 km grid resolution. The model considers response characteristics of typical environmental medium to complex underlying surface. Results suggest that direct emission is the main input pathway of PAHs entering the atmosphere, while advection is the main outward flow of pollutants from the environment. In addition, both soil and sediment act as the main sink of PAHs and have the longest retention time. Importantly, the highest PAHs loadings are found in urbanized and densely populated regions of China, such as Yangtze River Delta and Pearl River Delta. This model can provide a good scientific basis towards a better understanding of the large-scale dynamics of environmental pollutants for land conservation and sustainable development. In a next step, the dynamic contaminant model will be integrated with the continental-scale hydrological and water resources model (i.e., Community Water Model, CWatM) to quantify a more accurate representation and feedbacks between the hydrological cycle and water quality at even larger geographical domains. Keywords: PAHs; Community multi-scale air quality model; Multimedia fate model; Land use

Assessing the harms of cannabis cultivation in Belgium.

PubMed

Paoli, Letizia; Decorte, Tom; Kersten, Loes

2015-03-01

Since the 1990s, a shift from the importation of foreign cannabis to domestic cultivation has taken place in Belgium, as it has in many other countries. This shift has prompted Belgian policy-making bodies to prioritize the repression of cannabis cultivation. Against this background, the article aims to systematically map and assess for the first time ever the harms associated with cannabis cultivation, covering the whole spectrum of growers. This study is based on a web survey primarily targeting small-scale growers (N=1293) and on three interconnected sets of qualitative data on large-scale growers and traffickers (34 closed criminal proceedings, interviews with 32 criminal justice experts, and with 17 large-scale cannabis growers and three traffickers). The study relied on Greenfield and Paoli's (2013) harm assessment framework to identify the harms associated with cannabis cultivation and to assess the incidence, severity and causes of such harms. Cannabis cultivation has become endemic in Belgium. Despite that, it generates, for Belgium, limited harms of medium-low or medium priority. Large-scale growers tend to produce more harms than the small-scale ones. Virtually all the harms associated with cannabis cultivation are the result of the current criminalizing policies. Given the spread of cannabis cultivation and Belgium's position in Europe, reducing the supply of cannabis does not appear to be a realistic policy objective. Given the limited harms generated, there is scarce scientific justification to prioritize cannabis cultivation in Belgian law enforcement strategies. As most harms are generated by large-scale growers, it is this category of cultivator, if any, which should be the focus of law enforcement repression. Given the policy origin of most harms, policy-makers should seek to develop policies likely to reduce such harms. At the same time, further research is needed to comparatively assess the harms associated with cannabis cultivation (and trafficking) with those arising from use. Copyright © 2014 Elsevier B.V. All rights reserved.

Handling the Diversity in the Coming Flood of InSAR Data with the InSAR Scientific Computing Environment

NASA Astrophysics Data System (ADS)

Rosen, P. A.; Gurrola, E. M.; Sacco, G. F.; Agram, P. S.; Lavalle, M.; Zebker, H. A.

2014-12-01

The NASA ESTO-developed InSAR Scientific Computing Environment (ISCE) provides acomputing framework for geodetic image processing for InSAR sensors that ismodular, flexible, and extensible, enabling scientists to reduce measurementsdirectly from a diverse array of radar satellites and aircraft to newgeophysical products. ISCE can serve as the core of a centralized processingcenter to bring Level-0 raw radar data up to Level-3 data products, but isadaptable to alternative processing approaches for science users interested innew and different ways to exploit mission data. This is accomplished throughrigorous componentization of processing codes, abstraction and generalization ofdata models, and a xml-based input interface with multi-level prioritizedcontrol of the component configurations depending on the science processingcontext. The proposed NASA-ISRO SAR (NISAR) Mission would deliver data ofunprecedented quantity and quality, making possible global-scale studies inclimate research, natural hazards, and Earth's ecosystems. ISCE is planned tobecome a key element in processing projected NISAR data into higher level dataproducts, enabling a new class of analyses that take greater advantage of thelong time and large spatial scales of these new data than current approaches.NISAR would be but one mission in a constellation of radar satellites in thefuture delivering such data. ISCE has been incorporated into two prototypecloud-based systems that have demonstrated its elasticity to addressing largerdata processing problems in a "production" context and its ability to becontrolled by individual science users on the cloud for large data problems.

An analysis of scientific self-efficacy as a benefit of summer research participation for underrepresented minorities in science, technology, engineering, and mathematics (STEM) fields

NASA Astrophysics Data System (ADS)

Carter, Frances D.

2011-12-01

Low participation and performance in science, technology, engineering, and mathematics (STEM) fields by U.S. citizens are widely recognized as major problems with substantial economic, political, and social ramifications. Studies of collegiate interventions designed to broaden participation in STEM fields suggest that participation in undergraduate research is a key program component that enhances such student outcomes as undergraduate GPA, graduation, persistence in a STEM major, and graduate school enrollment. However, little is known about the mechanisms that are responsible for these positive effects. The current study hypothesizes that undergraduate research participation increases scientific self-efficacy and scientific research proficiency. This hypothesis was tested using data obtained from a survey of minority students from several STEM intervention programs that offer undergraduate research opportunities. Students were surveyed both prior to and following the summer of 2010. Factor analysis was used to examine the factor structure of participants' responses on scientific self-efficacy and scientific research proficiency scales. Difference-in-difference analysis was then applied to the resulting factor score differences to estimate the relationship of summer research participation with scientific self-efficacy and scientific research proficiency. Factor analytic results replicate and further validate previous findings of a general scientific self-efficacy construct (Schultz, 2008). While the factor analytic results for the exploratory scientific research proficiency scale suggest that it was also a measureable construct, the factor structure was not generalizable over time. Potential reasons for the lack of generalizability validity for the scientific research proficiency scale are explored and recommendations for emerging scales are provided. Recent restructuring attempts within federal science agencies threaten the future of STEM intervention programs. Causal estimates of the effect of undergraduate research participation on specific and measurable benefits can play an important role in ensuring the sustainability of STEM intervention programs. Obtaining such estimates requires additional studies that, inter alia, incorporate adequate sample sizes, valid measurement scales, and the ability to account for unobserved variables. Political strategies, such as compromise, can also play an important role in ensuring the sustainability of STEM intervention programs.

Dynamic fracture of tantalum under extreme tensile stress.

PubMed

Albertazzi, Bruno; Ozaki, Norimasa; Zhakhovsky, Vasily; Faenov, Anatoly; Habara, Hideaki; Harmand, Marion; Hartley, Nicholas; Ilnitsky, Denis; Inogamov, Nail; Inubushi, Yuichi; Ishikawa, Tetsuya; Katayama, Tetsuo; Koyama, Takahisa; Koenig, Michel; Krygier, Andrew; Matsuoka, Takeshi; Matsuyama, Satoshi; McBride, Emma; Migdal, Kirill Petrovich; Morard, Guillaume; Ohashi, Haruhiko; Okuchi, Takuo; Pikuz, Tatiana; Purevjav, Narangoo; Sakata, Osami; Sano, Yasuhisa; Sato, Tomoko; Sekine, Toshimori; Seto, Yusuke; Takahashi, Kenjiro; Tanaka, Kazuo; Tange, Yoshinori; Togashi, Tadashi; Tono, Kensuke; Umeda, Yuhei; Vinci, Tommaso; Yabashi, Makina; Yabuuchi, Toshinori; Yamauchi, Kazuto; Yumoto, Hirokatsu; Kodama, Ryosuke

2017-06-01

The understanding of fracture phenomena of a material at extremely high strain rates is a key issue for a wide variety of scientific research ranging from applied science and technological developments to fundamental science such as laser-matter interaction and geology. Despite its interest, its study relies on a fine multiscale description, in between the atomic scale and macroscopic processes, so far only achievable by large-scale atomic simulations. Direct ultrafast real-time monitoring of dynamic fracture (spallation) at the atomic lattice scale with picosecond time resolution was beyond the reach of experimental techniques. We show that the coupling between a high-power optical laser pump pulse and a femtosecond x-ray probe pulse generated by an x-ray free electron laser allows detection of the lattice dynamics in a tantalum foil at an ultrahigh strain rate of [Formula: see text] ~2 × 10 8 to 3.5 × 10 8 s -1 . A maximal density drop of 8 to 10%, associated with the onset of spallation at a spall strength of ~17 GPa, was directly measured using x-ray diffraction. The experimental results of density evolution agree well with large-scale atomistic simulations of shock wave propagation and fracture of the sample. Our experimental technique opens a new pathway to the investigation of ultrahigh strain-rate phenomena in materials at the atomic scale, including high-speed crack dynamics and stress-induced solid-solid phase transitions.

Dynamic fracture of tantalum under extreme tensile stress

PubMed Central

Albertazzi, Bruno; Ozaki, Norimasa; Zhakhovsky, Vasily; Faenov, Anatoly; Habara, Hideaki; Harmand, Marion; Hartley, Nicholas; Ilnitsky, Denis; Inogamov, Nail; Inubushi, Yuichi; Ishikawa, Tetsuya; Katayama, Tetsuo; Koyama, Takahisa; Koenig, Michel; Krygier, Andrew; Matsuoka, Takeshi; Matsuyama, Satoshi; McBride, Emma; Migdal, Kirill Petrovich; Morard, Guillaume; Ohashi, Haruhiko; Okuchi, Takuo; Pikuz, Tatiana; Purevjav, Narangoo; Sakata, Osami; Sano, Yasuhisa; Sato, Tomoko; Sekine, Toshimori; Seto, Yusuke; Takahashi, Kenjiro; Tanaka, Kazuo; Tange, Yoshinori; Togashi, Tadashi; Tono, Kensuke; Umeda, Yuhei; Vinci, Tommaso; Yabashi, Makina; Yabuuchi, Toshinori; Yamauchi, Kazuto; Yumoto, Hirokatsu; Kodama, Ryosuke

2017-01-01

The understanding of fracture phenomena of a material at extremely high strain rates is a key issue for a wide variety of scientific research ranging from applied science and technological developments to fundamental science such as laser-matter interaction and geology. Despite its interest, its study relies on a fine multiscale description, in between the atomic scale and macroscopic processes, so far only achievable by large-scale atomic simulations. Direct ultrafast real-time monitoring of dynamic fracture (spallation) at the atomic lattice scale with picosecond time resolution was beyond the reach of experimental techniques. We show that the coupling between a high-power optical laser pump pulse and a femtosecond x-ray probe pulse generated by an x-ray free electron laser allows detection of the lattice dynamics in a tantalum foil at an ultrahigh strain rate of ε. ~2 × 108 to 3.5 × 108 s−1. A maximal density drop of 8 to 10%, associated with the onset of spallation at a spall strength of ~17 GPa, was directly measured using x-ray diffraction. The experimental results of density evolution agree well with large-scale atomistic simulations of shock wave propagation and fracture of the sample. Our experimental technique opens a new pathway to the investigation of ultrahigh strain-rate phenomena in materials at the atomic scale, including high-speed crack dynamics and stress-induced solid-solid phase transitions. PMID:28630909

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

Albertazzi, Bruno; Ozaki, Norimasa; Zhakhovsky, Vasily

The understanding of fracture phenomena of a material at extremely high strain rates is a key issue for a wide variety of scientific research ranging from applied science and technological developments to fundamental science such as laser-matter interaction and geology. Despite its interest, its study relies on a fine multiscale description, in between the atomic scale and macroscopic processes, so far only achievable by large-scale atomic simulations. Direct ultrafast real-time monitoring of dynamic fracture (spallation) at the atomic lattice scale with picosecond time resolution was beyond the reach of experimental techniques. We show that the coupling between a high-power opticalmore » laser pump pulse and a femtosecond x-ray probe pulse generated by an x-ray free electron laser allows detection of the lattice dynamics in a tantalum foil at an ultrahigh strain rate of Embedded Image ~2 × 10 8 to 3.5 × 10 8 s -1. A maximal density drop of 8 to 10%, associated with the onset of spallation at a spall strength of ~17 GPa, was directly measured using x-ray diffraction. The experimental results of density evolution agree well with large-scale atomistic simulations of shock wave propagation and fracture of the sample. Our experimental technique opens a new pathway to the investigation of ultrahigh strain-rate phenomena in materials at the atomic scale, including high-speed crack dynamics and stress-induced solid-solid phase transitions.« less

‘Sciencenet’—towards a global search and share engine for all scientific knowledge

PubMed Central

Lütjohann, Dominic S.; Shah, Asmi H.; Christen, Michael P.; Richter, Florian; Knese, Karsten; Liebel, Urban

2011-01-01

Summary: Modern biological experiments create vast amounts of data which are geographically distributed. These datasets consist of petabytes of raw data and billions of documents. Yet to the best of our knowledge, a search engine technology that searches and cross-links all different data types in life sciences does not exist. We have developed a prototype distributed scientific search engine technology, ‘Sciencenet’, which facilitates rapid searching over this large data space. By ‘bringing the search engine to the data’, we do not require server farms. This platform also allows users to contribute to the search index and publish their large-scale data to support e-Science. Furthermore, a community-driven method guarantees that only scientific content is crawled and presented. Our peer-to-peer approach is sufficiently scalable for the science web without performance or capacity tradeoff. Availability and Implementation: The free to use search portal web page and the downloadable client are accessible at: http://sciencenet.kit.edu. The web portal for index administration is implemented in ASP.NET, the ‘AskMe’ experiment publisher is written in Python 2.7, and the backend ‘YaCy’ search engine is based on Java 1.6. Contact: urban.liebel@kit.edu Supplementary Material: Detailed instructions and descriptions can be found on the project homepage: http://sciencenet.kit.edu. PMID:21493657

magHD: a new approach to multi-dimensional data storage, analysis, display and exploitation

NASA Astrophysics Data System (ADS)

Angleraud, Christophe

2014-06-01

The ever increasing amount of data and processing capabilities - following the well- known Moore's law - is challenging the way scientists and engineers are currently exploiting large datasets. The scientific visualization tools, although quite powerful, are often too generic and provide abstract views of phenomena, thus preventing cross disciplines fertilization. On the other end, Geographic information Systems allow nice and visually appealing maps to be built but they often get very confused as more layers are added. Moreover, the introduction of time as a fourth analysis dimension to allow analysis of time dependent phenomena such as meteorological or climate models, is encouraging real-time data exploration techniques that allow spatial-temporal points of interests to be detected by integration of moving images by the human brain. Magellium is involved in high performance image processing chains for satellite image processing as well as scientific signal analysis and geographic information management since its creation (2003). We believe that recent work on big data, GPU and peer-to-peer collaborative processing can open a new breakthrough in data analysis and display that will serve many new applications in collaborative scientific computing, environment mapping and understanding. The magHD (for Magellium Hyper-Dimension) project aims at developing software solutions that will bring highly interactive tools for complex datasets analysis and exploration commodity hardware, targeting small to medium scale clusters with expansion capabilities to large cloud based clusters.

An analysis of the relationship between information and communication technology (ICT) and scientific literacy in Canada and Australia

NASA Astrophysics Data System (ADS)

Luu, King

Despite the lack of substantial evidence for improvement in the quality of teaching and learning with information and communication technology (ICT), governmental organizations, including those of Canada and Australia, have made large investments into ICT. This investment has been largely predicated on the hypothesized relationship between ICT and science achievement, and the need for ICT as a means of providing broad-scale training to meet the demand for a skilled workforce. To better understand this possible relationship, this study used data from the 2006 administration of the Programme for International Student Assessment (PISA 2006) to determine the extent to which scientific literacy is predicted by student- and school-level variables related to ICT, after adjusting for student demographic characteristics and school characteristics. The findings suggest that, once student demographic characteristics and school characteristics have been accounted for, students with prior experience with ICT, who browse the Internet more frequently, and who are confident with basic ICT tasks earned higher scientific literacy scores. Gender differences existed with respect to types of productivity and entertainment software used; this difference may be attributed to personal choice and initiative to learn ICT. Finally, differences in ICT use between Canada and Australia, particularly with school use, may be due to initiatives in Australia (e.g., National Goals of Schooling for the Twenty-first Century) that promote the increased use of ICT in classrooms.

Hydrometeorological variability on a large french catchment and its relation to large-scale circulation across temporal scales

NASA Astrophysics Data System (ADS)

Massei, Nicolas; Dieppois, Bastien; Fritier, Nicolas; Laignel, Benoit; Debret, Maxime; Lavers, David; Hannah, David

2015-04-01

In the present context of global changes, considerable efforts have been deployed by the hydrological scientific community to improve our understanding of the impacts of climate fluctuations on water resources. Both observational and modeling studies have been extensively employed to characterize hydrological changes and trends, assess the impact of climate variability or provide future scenarios of water resources. In the aim of a better understanding of hydrological changes, it is of crucial importance to determine how and to what extent trends and long-term oscillations detectable in hydrological variables are linked to global climate oscillations. In this work, we develop an approach associating large-scale/local-scale correlation, enmpirical statistical downscaling and wavelet multiresolution decomposition of monthly precipitation and streamflow over the Seine river watershed, and the North Atlantic sea level pressure (SLP) in order to gain additional insights on the atmospheric patterns associated with the regional hydrology. We hypothesized that: i) atmospheric patterns may change according to the different temporal wavelengths defining the variability of the signals; and ii) definition of those hydrological/circulation relationships for each temporal wavelength may improve the determination of large-scale predictors of local variations. The results showed that the large-scale/local-scale links were not necessarily constant according to time-scale (i.e. for the different frequencies characterizing the signals), resulting in changing spatial patterns across scales. This was then taken into account by developing an empirical statistical downscaling (ESD) modeling approach which integrated discrete wavelet multiresolution analysis for reconstructing local hydrometeorological processes (predictand : precipitation and streamflow on the Seine river catchment) based on a large-scale predictor (SLP over the Euro-Atlantic sector) on a monthly time-step. This approach basically consisted in 1- decomposing both signals (SLP field and precipitation or streamflow) using discrete wavelet multiresolution analysis and synthesis, 2- generating one statistical downscaling model per time-scale, 3- summing up all scale-dependent models in order to obtain a final reconstruction of the predictand. The results obtained revealed a significant improvement of the reconstructions for both precipitation and streamflow when using the multiresolution ESD model instead of basic ESD ; in addition, the scale-dependent spatial patterns associated to the model matched quite well those obtained from scale-dependent composite analysis. In particular, the multiresolution ESD model handled very well the significant changes in variance through time observed in either prepciptation or streamflow. For instance, the post-1980 period, which had been characterized by particularly high amplitudes in interannual-to-interdecadal variability associated with flood and extremely low-flow/drought periods (e.g., winter 2001, summer 2003), could not be reconstructed without integrating wavelet multiresolution analysis into the model. Further investigations would be required to address the issue of the stationarity of the large-scale/local-scale relationships and to test the capability of the multiresolution ESD model for interannual-to-interdecadal forecasting. In terms of methodological approach, further investigations may concern a fully comprehensive sensitivity analysis of the modeling to the parameter of the multiresolution approach (different families of scaling and wavelet functions used, number of coefficients/degree of smoothness, etc.).

Transitioning Rationally Designed Catalytic Materials to Real 'Working' Catalysts Produced at Commercial Scale: Nanoparticle Materials

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

Schaidle, Joshua A.; Habas, Susan E.; Baddour, Frederick G.

Catalyst design, from idea to commercialization, requires multi-disciplinary scientific and engineering research and development over 10-20 year time periods. Historically, the identification of new or improved catalyst materials has largely been an empirical trial-and-error process. However, advances in computational capabilities (new tools and increased processing power) coupled with new synthetic techniques have started to yield rationally-designed catalysts with controlled nano-structures and tailored properties. This technological advancement represents an opportunity to accelerate the catalyst development timeline and to deliver new materials that outperform existing industrial catalysts or enable new applications, once a number of unique challenges associated with the scale-up ofmore » nano-structured materials are overcome.« less

LIDAR and acoustics applications to ocean productivity

NASA Technical Reports Server (NTRS)

Collins, D. J.

1982-01-01

The requirements for the submersible, the instrumentation necessary to perform these measurements, and the optical and acoustical technology required to develop the ocean color scanner instrumentation are described. The development of a second generation ocean color scanner produced the need for coincident in situ scientific measurements which examine the primary productivity of the upper ocean on time and space scales which are large compared to the environmental scales. The vertical and horizontal variability of the biota, including the relationship between chlorophyll and primary productivity, the productivity of zooplankton, and the dynamic interaction between phytoplankton and zooplankton, and between these populations and the physical environment are investigated. A towed submersible will be constructed which accommodates both an underwater LIDAR instrument and a multifrequency sonar.

Seafloor identification in sonar imagery via simulations of Helmholtz equations and discrete optimization

NASA Astrophysics Data System (ADS)

Engquist, Björn; Frederick, Christina; Huynh, Quyen; Zhou, Haomin

2017-06-01

We present a multiscale approach for identifying features in ocean beds by solving inverse problems in high frequency seafloor acoustics. The setting is based on Sound Navigation And Ranging (SONAR) imaging used in scientific, commercial, and military applications. The forward model incorporates multiscale simulations, by coupling Helmholtz equations and geometrical optics for a wide range of spatial scales in the seafloor geometry. This allows for detailed recovery of seafloor parameters including material type. Simulated backscattered data is generated using numerical microlocal analysis techniques. In order to lower the computational cost of the large-scale simulations in the inversion process, we take advantage of a pre-computed library of representative acoustic responses from various seafloor parameterizations.

Addressing Criticisms of Large-Scale Marine Protected Areas.

PubMed

O'Leary, Bethan C; Ban, Natalie C; Fernandez, Miriam; Friedlander, Alan M; García-Borboroglu, Pablo; Golbuu, Yimnang; Guidetti, Paolo; Harris, Jean M; Hawkins, Julie P; Langlois, Tim; McCauley, Douglas J; Pikitch, Ellen K; Richmond, Robert H; Roberts, Callum M

2018-05-01

Designated large-scale marine protected areas (LSMPAs, 100,000 or more square kilometers) constitute over two-thirds of the approximately 6.6% of the ocean and approximately 14.5% of the exclusive economic zones within marine protected areas. Although LSMPAs have received support among scientists and conservation bodies for wilderness protection, regional ecological connectivity, and improving resilience to climate change, there are also concerns. We identified 10 common criticisms of LSMPAs along three themes: (1) placement, governance, and management; (2) political expediency; and (3) social-ecological value and cost. Through critical evaluation of scientific evidence, we discuss the value, achievements, challenges, and potential of LSMPAs in these arenas. We conclude that although some criticisms are valid and need addressing, none pertain exclusively to LSMPAs, and many involve challenges ubiquitous in management. We argue that LSMPAs are an important component of a diversified management portfolio that tempers potential losses, hedges against uncertainty, and enhances the probability of achieving sustainably managed oceans.

Testing the robustness of Citizen Science projects: Evaluating the results of pilot project COMBER

PubMed Central

Faulwetter, Sarah; Dailianis, Thanos; Smith, Vincent Stuart; Koulouri, Panagiota; Dounas, Costas; Arvanitidis, Christos

2016-01-01

Abstract Background Citizen Science (CS) as a term implies a great deal of approaches and scopes involving many different fields of science. The number of the relevant projects globally has been increased significantly in the recent years. Large scale ecological questions can be answered only through extended observation networks and CS projects can support this effort. Although the need of such projects is apparent, an important part of scientific community cast doubt on the reliability of CS data sets. New information The pilot CS project COMBER has been created in order to provide evidence to answer the aforementioned question in the coastal marine biodiversity monitoring. The results of the current analysis show that a carefully designed CS project with clear hypotheses, wide participation and data sets validation, can be a valuable tool for the large scale and long term changes in marine biodiversity pattern change and therefore for relevant management and conservation issues. PMID:28174507

Addressing Criticisms of Large-Scale Marine Protected Areas

PubMed Central

Ban, Natalie C; Fernandez, Miriam; Friedlander, Alan M; García-Borboroglu, Pablo; Golbuu, Yimnang; Guidetti, Paolo; Harris, Jean M; Hawkins, Julie P; Langlois, Tim; McCauley, Douglas J; Pikitch, Ellen K; Richmond, Robert H; Roberts, Callum M

2018-01-01

Abstract Designated large-scale marine protected areas (LSMPAs, 100,000 or more square kilometers) constitute over two-thirds of the approximately 6.6% of the ocean and approximately 14.5% of the exclusive economic zones within marine protected areas. Although LSMPAs have received support among scientists and conservation bodies for wilderness protection, regional ecological connectivity, and improving resilience to climate change, there are also concerns. We identified 10 common criticisms of LSMPAs along three themes: (1) placement, governance, and management; (2) political expediency; and (3) social–ecological value and cost. Through critical evaluation of scientific evidence, we discuss the value, achievements, challenges, and potential of LSMPAs in these arenas. We conclude that although some criticisms are valid and need addressing, none pertain exclusively to LSMPAs, and many involve challenges ubiquitous in management. We argue that LSMPAs are an important component of a diversified management portfolio that tempers potential losses, hedges against uncertainty, and enhances the probability of achieving sustainably managed oceans. PMID:29731514

Vertical land motion controls regional sea level rise patterns on the United States east coast since 1900

NASA Astrophysics Data System (ADS)

Piecuch, C. G.; Huybers, P. J.; Hay, C.; Mitrovica, J. X.; Little, C. M.; Ponte, R. M.; Tingley, M.

2017-12-01

Understanding observed spatial variations in centennial relative sea level trends on the United States east coast has important scientific and societal applications. Past studies based on models and proxies variously suggest roles for crustal displacement, ocean dynamics, and melting of the Greenland ice sheet. Here we perform joint Bayesian inference on regional relative sea level, vertical land motion, and absolute sea level fields based on tide gauge records and GPS data. Posterior solutions show that regional vertical land motion explains most (80% median estimate) of the spatial variance in the large-scale relative sea level trend field on the east coast over 1900-2016. The posterior estimate for coastal absolute sea level rise is remarkably spatially uniform compared to previous studies, with a spatial average of 1.4-2.3 mm/yr (95% credible interval). Results corroborate glacial isostatic adjustment models and reveal that meaningful long-period, large-scale vertical velocity signals can be extracted from short GPS records.

Large-scale single-chirality separation of single-wall carbon nanotubes by simple gel chromatography

PubMed Central

Liu, Huaping; Nishide, Daisuke; Tanaka, Takeshi; Kataura, Hiromichi

2011-01-01

Monostructured single-wall carbon nanotubes (SWCNTs) are important in both scientific research and electronic and biomedical applications; however, the bulk separation of SWCNTs into populations of single-chirality nanotubes remains challenging. Here we report a simple and effective method for the large-scale chirality separation of SWCNTs using a single-surfactant multicolumn gel chromatography method utilizing one surfactant and a series of vertically connected gel columns. This method is based on the structure-dependent interaction strength of SWCNTs with an allyl dextran-based gel. Overloading an SWCNT dispersion on the top column results in the adsorption sites of the column becoming fully occupied by the nanotubes that exhibit the strongest interaction with the gel. The unbound nanotubes flow through to the next column, and the nanotubes with the second strongest interaction with the gel are adsorbed in this stage. In this manner, 13 different (n, m) species were separated. Metallic SWCNTs were finally collected as unbound nanotubes because they exhibited the lowest interaction with the gel. PMID:21556063

LSSGalPy: Interactive Visualization of the Large-scale Environment Around Galaxies

NASA Astrophysics Data System (ADS)

Argudo-Fernández, M.; Duarte Puertas, S.; Ruiz, J. E.; Sabater, J.; Verley, S.; Bergond, G.

2017-05-01

New tools are needed to handle the growth of data in astrophysics delivered by recent and upcoming surveys. We aim to build open-source, light, flexible, and interactive software designed to visualize extensive three-dimensional (3D) tabular data. Entirely written in the Python language, we have developed interactive tools to browse and visualize the positions of galaxies in the universe and their positions with respect to its large-scale structures (LSS). Motivated by a previous study, we created two codes using Mollweide projection and wedge diagram visualizations, where survey galaxies can be overplotted on the LSS of the universe. These are interactive representations where the visualizations can be controlled by widgets. We have released these open-source codes that have been designed to be easily re-used and customized by the scientific community to fulfill their needs. The codes are adaptable to other kinds of 3D tabular data and are robust enough to handle several millions of objects. .

A ZigBee wireless networking for remote sensing applications in hydrological monitoring system

NASA Astrophysics Data System (ADS)

Weng, Songgan; Zhai, Duo; Yang, Xing; Hu, Xiaodong

2017-01-01

Hydrological monitoring is recognized as one of the most important factors in hydrology. Particularly, investigation of the tempo-spatial variation patterns of water-level and their effect on hydrological research has attracted more and more attention in recent. Because of the limitations in both human costs and existing water-level monitoring devices, however, it is very hard for researchers to collect real-time water-level data from large-scale geographical areas. This paper designs and implements a real-time water-level data monitoring system (MCH) based on ZigBee networking, which explicitly serves as an effective and efficient scientific instrument for domain experts to facilitate the measurement of large-scale and real-time water-level data monitoring. We implement a proof-of-concept prototype of the MCH, which can monitor water-level automatically, real-timely and accurately with low cost and low power consumption. The preliminary laboratory results and analyses demonstrate the feasibility and the efficacy of the MCH.

Arctic Tundra Greening and Browning at Circumpolar and Regional Scales

NASA Astrophysics Data System (ADS)

Epstein, H. E.; Bhatt, U. S.; Walker, D. A.; Raynolds, M. K.; Yang, X.

2017-12-01

Remote sensing data have historically been used to assess the dynamics of arctic tundra vegetation. Until recently the scientific literature has largely described the "greening" of the Arctic; from a remote sensing perspective, an increase in the Normalized Difference Vegetation Index (NDVI), or a similar satellite-based vegetation index. Vegetation increases have been heterogeneous throughout the Arctic, and were reported to be up to 25% in certain areas over a 30-year timespan. However, more recently, arctic tundra vegetation dynamics have gotten more complex, with observations of more widespread tundra "browning" being reported. We used a combination of remote sensing data, including the Global Inventory Monitoring and Modeling System (GIMMS), as well as higher spatial resolution Landsat data, to evaluate the spatio-temporal patterns of arctic tundra vegetation dynamics (greening and browning) at circumpolar and regional scales over the past 3-4 decades. At the circumpolar scale, we focus on the spatial heterogeneity (by tundra subzone and continent) of tundra browning over the past 5-15 years, followed by a more recent recovery (greening since 2015). Landsat time series allow us to evaluate the landscape-scale heterogeneity of tundra greening and browning for northern Alaska and the Yamal Peninsula in northwestern Siberia, Russia. Multi-dataset analyses reveal that tundra greening and browning (i.e. increases or decreases in the NDVI respectively) are generated by different sets of processes. Tundra greening is largely a result of either climate warming, lengthening of the growing season, or responses to disturbances, such as fires, landslides, and freeze-thaw processes. Browning on the other hand tends to be more event-driven, such as the shorter-term decline in vegetation due to fire, insect defoliation, consumption by larger herbivores, or extreme weather events (e.g. winter warming or early summer frost damage). Browning can also be caused by local or regional cooling, or changes in the snow regime (e.g. depth, timing of melt). The spatio-temporal dynamics of tundra vegetation are only now beginning to get serious attention from the scientific community and the continual use of remote sensing data across spatial scales allows us to monitor these dynamics and elucidate their controls.

(abstract) TOPEX/Poseidon: Four Years of Synoptic Oceanography

NASA Technical Reports Server (NTRS)

Fu, Lee-Lueng

1996-01-01

Exceeding all expectations of measurement precision and accuracy, the US/France TOPEX/Poseidon satellite mission is now in its 5th year. Returning more than 98 percent of the altimetric data, the measured global geocentric height of the sea surface has provided unprecedented opportunities to address a host of scientific problems ranging from the dynamics of ocean circulation to the distribution of internal tidal energy. Scientific highlights of this longest-running altimetric satellite mission include improvements in our understanding of the dynamics and thermodynamics of the large-scale ocean variability, such as, the properties of planetary waves; the energetics of basin-wide gyres; the heat budget of the ocean; and the ocean's response to wind forcing. For the first time, oceanographers have quantitative descriptions of a dynamic variable of the physical state of the global oceans available in near-real-time.

Networking for High Energy and Nuclear Physics

NASA Astrophysics Data System (ADS)

Newman, Harvey B.

2007-07-01

This report gives an overview of the status and outlook for the world's research networks and major international links used by the high energy physics and other scientific communities, network technology advances on which our community depends and in which we have an increasingly important role, and the problem of the Digital Divide, which is a primary focus of ICFA's Standing Committee on Inter-regional Connectivity (SCIC). Wide area networks of sufficient, and rapidly increasing end-to-end capability are vital for every phase of high energy physicists' work. Our bandwidth usage, and the typical capacity of the major national backbones and intercontinental links used by our field have progressed by a factor of more than 1000 over the past decade, and the outlook is for a similar increase over the next decade. This striking exponential growth trend, outstripping the growth rates in other areas of information technology, has continued in the past year, with many of the major national, continental and transoceanic networks supporting research and education progressing from a 10 Gigabits/sec (Gbps) backbone to multiple 10 Gbps links in their core. This is complemented by the use of point-to-point "light paths" to support the most demanding applications, including high energy physics, in a growing list of cases. As we approach the era of LHC physics, the growing need to access and transport Terabyte-scale and later 10 to 100 Terabyte datasets among more than 100 "Tier1" and "Tier2" centers at universities and laboratories spread throughout the world has brought the key role of networks, and the ongoing need for their development, sharply into focus. Bandwidth itself on an increasing scale is not enough. Realizing the scientific wealth of the LHC and our other major scientific programs depends crucially on our ability to use the bandwidth efficiently and reliably, with reliable high rates of data throughput, and effectively, where many parallel large-scale data transfers serving the community complete with high probability, often while coexisting with many other streams of network traffic. Responding to these needs, and to the scientific mission, physicists working with network engineers and computer scientists have made substantial progress in the development of protocols and systems that promise to meet these needs, placing our community among the world leaders in the development as well as use of large-scale networks. A great deal of work remains, and is continuing. As we advance in these areas, often (as in the past year) with great rapidity, there is a growing danger that we will leave behind our collaborators in regions with less-developed networks, or with regulatory frameworks or business models that put the required networks financially out of reach. This threatens to further open the Digital Divide that already exists among the regions of the world. In 2002, the SCIC recognized the threat that this Divide represents to our global scientific collaborations, and since that time has worked assiduously to reduce or eliminate it; both within our community, and more broadly in the world research community of which HEP is a part.

Scientific Training in the Era of Big Data: A New Pedagogy for Graduate Education.

PubMed

Aikat, Jay; Carsey, Thomas M; Fecho, Karamarie; Jeffay, Kevin; Krishnamurthy, Ashok; Mucha, Peter J; Rajasekar, Arcot; Ahalt, Stanley C

2017-03-01

The era of "big data" has radically altered the way scientific research is conducted and new knowledge is discovered. Indeed, the scientific method is rapidly being complemented and even replaced in some fields by data-driven approaches to knowledge discovery. This paradigm shift is sometimes referred to as the "fourth paradigm" of data-intensive and data-enabled scientific discovery. Interdisciplinary research with a hard emphasis on translational outcomes is becoming the norm in all large-scale scientific endeavors. Yet, graduate education remains largely focused on individual achievement within a single scientific domain, with little training in team-based, interdisciplinary data-oriented approaches designed to translate scientific data into new solutions to today's critical challenges. In this article, we propose a new pedagogy for graduate education: data-centered learning for the domain-data scientist. Our approach is based on four tenets: (1) Graduate training must incorporate interdisciplinary training that couples the domain sciences with data science. (2) Graduate training must prepare students for work in data-enabled research teams. (3) Graduate training must include education in teaming and leadership skills for the data scientist. (4) Graduate training must provide experiential training through academic/industry practicums and internships. We emphasize that this approach is distinct from today's graduate training, which offers training in either data science or a domain science (e.g., biology, sociology, political science, economics, and medicine), but does not integrate the two within a single curriculum designed to prepare the next generation of domain-data scientists. We are in the process of implementing the proposed pedagogy through the development of a new graduate curriculum based on the above four tenets, and we describe herein our strategy, progress, and lessons learned. While our pedagogy was developed in the context of graduate education, the general approach of data-centered learning can and should be applied to students and professionals at any stage of their education, including at the K-12, undergraduate, graduate, and professional levels. We believe that the time is right to embed data-centered learning within our educational system and, thus, generate the talent required to fully harness the potential of big data.

On Establishing Big Data Wave Breakwaters with Analytics (Invited)

NASA Astrophysics Data System (ADS)

Riedel, M.

2013-12-01

The Research Data Alliance Big Data Analytics (RDA-BDA) Interest Group seeks to develop community based recommendations on feasible data analytics approaches to address scientific community needs of utilizing large quantities of data. RDA-BDA seeks to analyze different scientific domain applications and their potential use of various big data analytics techniques. A systematic classification of feasible combinations of analysis algorithms, analytical tools, data and resource characteristics and scientific queries will be covered in these recommendations. These combinations are complex since a wide variety of different data analysis algorithms exist (e.g. specific algorithms using GPUs of analyzing brain images) that need to work together with multiple analytical tools reaching from simple (iterative) map-reduce methods (e.g. with Apache Hadoop or Twister) to sophisticated higher level frameworks that leverage machine learning algorithms (e.g. Apache Mahout). These computational analysis techniques are often augmented with visual analytics techniques (e.g. computational steering on large-scale high performance computing platforms) to put the human judgement into the analysis loop or new approaches with databases that are designed to support new forms of unstructured or semi-structured data as opposed to the rather tradtional structural databases (e.g. relational databases). More recently, data analysis and underpinned analytics frameworks also have to consider energy footprints of underlying resources. To sum up, the aim of this talk is to provide pieces of information to understand big data analytics in the context of science and engineering using the aforementioned classification as the lighthouse and as the frame of reference for a systematic approach. This talk will provide insights about big data analytics methods in context of science within varios communities and offers different views of how approaches of correlation and causality offer complementary methods to advance in science and engineering today. The RDA Big Data Analytics Group seeks to understand what approaches are not only technically feasible, but also scientifically feasible. The lighthouse Goal of the RDA Big Data Analytics Group is a classification of clever combinations of various Technologies and scientific applications in order to provide clear recommendations to the scientific community what approaches are technicalla and scientifically feasible.

Study of Potential Cost Reductions Resulting from Super-Large-Scale Manufacturing of PV Modules: Final Subcontract Report, 7 August 2003--30 September 2004

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

Keshner, M. S.; Arya, R.

2004-10-01

Hewlett Packard has created a design for a ''Solar City'' factory that will process 30 million sq. meters of glass panels per year and produce 2.1-3.6 GW of solar panels per year-100x the volume of a typical, thin-film, solar panel manufacturer in 2004. We have shown that with a reasonable selection of materials, and conservative assumptions, this ''Solar City'' can produce solar panels and hit the price target of $1.00 per peak watt (6.5x-8.5x lower than prices in 2004) as the total price for a complete and installed rooftop (or ground mounted) solar energy system. This breakthrough in the pricemore » of solar energy comes without the need for any significant new invention. It comes entirely from the manufacturing scale of a large plant and the cost savings inherent in operating at such a large manufacturing scale. We expect that further optimizations from these simple designs will lead to further improvements in cost. The manufacturing process and cost depend on the choice for the active layer that converts sunlight into electricity. The efficiency by which sunlight is converted into electricity can range from 7% to 15%. This parameter has a large effect on the overall price per watt. There are other impacts, as well, and we have attempted to capture them without creating undue distractions. Our primary purpose is to demonstrate the impact of large-scale manufacturing. This impact is largely independent of the choice of active layer. It is not our purpose to compare the pro's and con's for various types of active layers. Significant improvements in cost per watt can also come from scientific advances in active layers that lead to higher efficiency. But, again, our focus is on manufacturing gains and not on the potential advances in the basic technology.« less

Hints on the nature of dark matter from the properties of Milky Way satellites

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

Anderhalden, Donnino; Diemand, Juerg; Schneider, Aurel

2013-03-01

The nature of dark matter is still unknown and one of the most fundamental scientific mysteries. Although successfully describing large scales, the standard cold dark matter model (CDM) exhibits possible shortcomings on galactic and sub-galactic scales. It is exactly at these highly non-linear scales where strong astrophysical constraints can be set on the nature of the dark matter particle. While observations of the Lyman-α forest probe the matter power spectrum in the mildly non-linear regime, satellite galaxies of the Milky Way provide an excellent laboratory as a test of the underlying cosmology on much smaller scales. Here we present resultsmore » from a set of high resolution simulations of a Milky Way sized dark matter halo in eight distinct cosmologies: CDM, warm dark matter (WDM) with a particle mass of 2 keV and six different cold plus warm dark matter (C+WDM) models, varying the fraction, f{sub wdm}, and the mass, m{sub wdm}, of the warm component. We used three different observational tests based on Milky Way satellite observations: the total satellite abundance, their radial distribution and their mass profile. We show that the requirement of simultaneously satisfying all three constraints sets very strong limits on the nature of dark matter. This shows the power of a multi-dimensional small scale approach in ruling out models which would be still allowed by large scale observations.« less

Hydrodynamic Simulations and Tomographic Reconstructions of the Intergalactic Medium

NASA Astrophysics Data System (ADS)

Stark, Casey William

The Intergalactic Medium (IGM) is the dominant reservoir of matter in the Universe from which the cosmic web and galaxies form. The structure and physical state of the IGM provides insight into the cosmological model of the Universe, the origin and timeline of the reionization of the Universe, as well as being an essential ingredient in our understanding of galaxy formation and evolution. Our primary handle on this information is a signal known as the Lyman-alpha forest (or Ly-alpha forest) -- the collection of absorption features in high-redshift sources due to intervening neutral hydrogen, which scatters HI Ly-alpha photons out of the line of sight. The Ly-alpha forest flux traces density fluctuations at high redshift and at moderate overdensities, making it an excellent tool for mapping large-scale structure and constraining cosmological parameters. Although the computational methodology for simulating the Ly-alpha forest has existed for over a decade, we are just now approaching the scale of computing power required to simultaneously capture large cosmological scales and the scales of the smallest absorption systems. My thesis focuses on using simulations at the edge of modern computing to produce precise predictions of the statistics of the Ly-alpha forest and to better understand the structure of the IGM. In the first part of my thesis, I review the state of hydrodynamic simulations of the IGM, including pitfalls of the existing under-resolved simulations. Our group developed a new cosmological hydrodynamics code to tackle the computational challenge, and I developed a distributed analysis framework to compute flux statistics from our simulations. I present flux statistics derived from a suite of our large hydrodynamic simulations and demonstrate convergence to the per cent level. I also compare flux statistics derived from simulations using different discretizations and hydrodynamic schemes (Eulerian finite volume vs. smoothed particle hydrodynamics) and discuss differences in their convergence behavior, their overall agreement, and the implications for cosmological constraints. In the second part of my thesis, I present a tomographic reconstruction method that allows us to make 3D maps of the IGM with Mpc resolution. In order to make reconstructions of large surveys computationally feasible, I developed a new Wiener Filter application with an algorithm specialized to our problem, which significantly reduces the space and time complexity compared to previous implementations. I explore two scientific applications of the maps: finding protoclusters by searching the maps for large, contiguous regions of low flux and finding cosmic voids by searching the maps for regions of high flux. Using a large N-body simulation, I identify and characterize both protoclusters and voids at z = 2.5, in the middle of the redshift range being mapped by ongoing surveys. I provide simple methods for identifying protocluster and void candidates in the tomographic flux maps, and then test them on mock surveys and reconstructions. I present forecasts for sample purity and completeness and other scientific applications of these large, high-redshift objects.

Preface to the volume Large Rivers

NASA Astrophysics Data System (ADS)

Latrubesse, Edgardo M.; Abad, Jorge D.

2018-02-01

The study and knowledge of the geomorphology of large rivers increased significantly during the last years and the factors that triggered these advances are multiple. On one hand, modern technologies became more accessible and their disseminated usage allowed the collection of data from large rivers as never seen before. The generalized use of high tech data collection with geophysics equipment such as acoustic Doppler current profilers-ADCPs, multibeam echosounders, plus the availability of geospatial and computational tools for morphodynamics, hydrological and hydrosedimentological modeling, have accelerated the scientific production on the geomorphology of large rivers at a global scale. Despite the advances, there is yet a lot of work ahead. Good parts of the large rivers are in the tropics and many are still unexplored. The tropics also hold crucial fluvial basins that concentrate good part of the gross domestic product of large countries like the Parana River in Argentina and Brazil, the Ganges-Brahmaputra in India, the Indus River in Pakistan, and the Mekong River in several countries of South East Asia. The environmental importance of tropical rivers is also outstanding. They hold the highest biodiversity of fluvial fauna and alluvial vegetation and many of them, particularly those in Southeast Asia, are among the most hazardous systems for floods in the entire world. Tropical rivers draining mountain chains such as the Himalaya, the Andes and insular Southeast Asia are also among the most heavily sediment loaded rivers and play a key role in both the storage of sediment at continental scale and the transference of sediments from the continent to the Ocean at planetary scale (Andermann et al., 2012; Latrubesse and Restrepo, 2014; Milliman and Syvitski, 1992; Milliman and Farsnworth, 2011; Sinha and Friend, 1994).

Measuring science or religion? A measurement analysis of the National Science Foundation sponsored science literacy scale 2006-2010.

PubMed

Roos, J Micah

2014-10-01

High scientific literacy is widely considered a public good. Methods of assessing public scientific knowledge or literacy are equally important. In an effort to measure lay scientific literacy in the United States, the National Science Foundation (NSF) science literacy scale has been a part of the last three waves of the General Social Survey. However, there has been debate over the validity of some survey items as indicators of science knowledge. While many researchers treat the NSF science scale as measuring a single dimension, previous work (Bann and Schwerin, 2004; Miller, 1998, 2004) suggests a bidimensional structure. This paper hypothesizes and tests a new measurement model for the NSF science knowledge scale and finds that two items about evolution and the big bang are more measures of a religious belief dimension termed "Young Earth Worldview" than they are measures of scientific knowledge. Results are replicated in seven samples. © The Author(s) 2013.

xSDK Foundations: Toward an Extreme-scale Scientific Software Development Kit

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

Heroux, Michael A.; Bartlett, Roscoe; Demeshko, Irina

Here, extreme-scale computational science increasingly demands multiscale and multiphysics formulations. Combining software developed by independent groups is imperative: no single team has resources for all predictive science and decision support capabilities. Scientific libraries provide high-quality, reusable software components for constructing applications with improved robustness and portability. However, without coordination, many libraries cannot be easily composed. Namespace collisions, inconsistent arguments, lack of third-party software versioning, and additional difficulties make composition costly. The Extreme-scale Scientific Software Development Kit (xSDK) defines community policies to improve code quality and compatibility across independently developed packages (hypre, PETSc, SuperLU, Trilinos, and Alquimia) and provides a foundationmore » for addressing broader issues in software interoperability, performance portability, and sustainability. The xSDK provides turnkey installation of member software and seamless combination of aggregate capabilities, and it marks first steps toward extreme-scale scientific software ecosystems from which future applications can be composed rapidly with assured quality and scalability.« less

xSDK Foundations: Toward an Extreme-scale Scientific Software Development Kit

DOE PAGES

Heroux, Michael A.; Bartlett, Roscoe; Demeshko, Irina; ...

2017-03-01

Here, extreme-scale computational science increasingly demands multiscale and multiphysics formulations. Combining software developed by independent groups is imperative: no single team has resources for all predictive science and decision support capabilities. Scientific libraries provide high-quality, reusable software components for constructing applications with improved robustness and portability. However, without coordination, many libraries cannot be easily composed. Namespace collisions, inconsistent arguments, lack of third-party software versioning, and additional difficulties make composition costly. The Extreme-scale Scientific Software Development Kit (xSDK) defines community policies to improve code quality and compatibility across independently developed packages (hypre, PETSc, SuperLU, Trilinos, and Alquimia) and provides a foundationmore » for addressing broader issues in software interoperability, performance portability, and sustainability. The xSDK provides turnkey installation of member software and seamless combination of aggregate capabilities, and it marks first steps toward extreme-scale scientific software ecosystems from which future applications can be composed rapidly with assured quality and scalability.« less

Cancer Diagnosis Epigenomics Scientific Workflow Scheduling in the Cloud Computing Environment Using an Improved PSO Algorithm

PubMed

N, Sadhasivam; R, Balamurugan; M, Pandi

2018-01-27

Objective: Epigenetic modifications involving DNA methylation and histone statud are responsible for the stable maintenance of cellular phenotypes. Abnormalities may be causally involved in cancer development and therefore could have diagnostic potential. The field of epigenomics refers to all epigenetic modifications implicated in control of gene expression, with a focus on better understanding of human biology in both normal and pathological states. Epigenomics scientific workflow is essentially a data processing pipeline to automate the execution of various genome sequencing operations or tasks. Cloud platform is a popular computing platform for deploying large scale epigenomics scientific workflow. Its dynamic environment provides various resources to scientific users on a pay-per-use billing model. Scheduling epigenomics scientific workflow tasks is a complicated problem in cloud platform. We here focused on application of an improved particle swam optimization (IPSO) algorithm for this purpose. Methods: The IPSO algorithm was applied to find suitable resources and allocate epigenomics tasks so that the total cost was minimized for detection of epigenetic abnormalities of potential application for cancer diagnosis. Result: The results showed that IPSO based task to resource mapping reduced total cost by 6.83 percent as compared to the traditional PSO algorithm. Conclusion: The results for various cancer diagnosis tasks showed that IPSO based task to resource mapping can achieve better costs when compared to PSO based mapping for epigenomics scientific application workflow. Creative Commons Attribution License

Large Pilot-Scale Carbon Dioxide (CO2) Capture Project Using Aminosilicone Solvent.Final Scientific/Technical Report

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

Hancu, Dan

GE Global Research has developed, over the last 8 years, a platform of cost effective CO2 capture technologies based on a non-aqueous aminosilicone solvent (GAP-1m). As demonstrated in previous funded DOE projects (DE-FE0007502 and DEFE0013755), the GAP-1m solvent has increased CO2 working capacity, lower volatility and corrosivity than the benchmark aqueous amine technology. Performance of the GAP-1m solvent was recently demonstrated in a 0.5 MWe pilot at National Carbon Capture Center, AL with real flue gas for over 500 hours of operation using a Steam Stripper Column (SSC). The pilot-scale PSTU engineering data were used to (i) update the techno-economicmore » analysis, and EH&S assessment, (ii) perform technology gap analysis, and (iii) conduct the solvent manufacturability and scale-up study.« less

Emergency department triage scales and their components: a systematic review of the scientific evidence.

PubMed

Farrohknia, Nasim; Castrén, Maaret; Ehrenberg, Anna; Lind, Lars; Oredsson, Sven; Jonsson, Håkan; Asplund, Kjell; Göransson, Katarina E

2011-06-30

Emergency department (ED) triage is used to identify patients' level of urgency and treat them based on their triage level. The global advancement of triage scales in the past two decades has generated considerable research on the validity and reliability of these scales. This systematic review aims to investigate the scientific evidence for published ED triage scales. The following questions are addressed: 1. Does assessment of individual vital signs or chief complaints affect mortality during the hospital stay or within 30 days after arrival at the ED?2. What is the level of agreement between clinicians' triage decisions compared to each other or to a gold standard for each scale (reliability)? 3. How valid is each triage scale in predicting hospitalization and hospital mortality? A systematic search of the international literature published from 1966 through March 31, 2009 explored the British Nursing Index, Business Source Premier, CINAHL, Cochrane Library, EMBASE, and PubMed. Inclusion was limited to controlled studies of adult patients (≥ 15 years) visiting EDs for somatic reasons. Outcome variables were death in ED or hospital and need for hospitalization (validity). Methodological quality and clinical relevance of each study were rated as high, medium, or low. The results from the studies that met the inclusion criteria and quality standards were synthesized applying the internationally developed GRADE system. Each conclusion was then assessed as having strong, moderately strong, limited, or insufficient scientific evidence. If studies were not available, this was also noted.We found ED triage scales to be supported, at best, by limited and often insufficient evidence.The ability of the individual vital signs included in the different scales to predict outcome is seldom, if at all, studied in the ED setting. The scientific evidence to assess interrater agreement (reliability) was limited for one triage scale and insufficient or lacking for all other scales. Two of the scales yielded limited scientific evidence, and one scale yielded insufficient evidence, on which to assess the risk of early death or hospitalization in patients assigned to the two lowest triage levels on a 5-level scale (validity).

Emergency Department Triage Scales and Their Components: A Systematic Review of the Scientific Evidence

PubMed Central

2011-01-01

Emergency department (ED) triage is used to identify patients' level of urgency and treat them based on their triage level. The global advancement of triage scales in the past two decades has generated considerable research on the validity and reliability of these scales. This systematic review aims to investigate the scientific evidence for published ED triage scales. The following questions are addressed: 1. Does assessment of individual vital signs or chief complaints affect mortality during the hospital stay or within 30 days after arrival at the ED? 2. What is the level of agreement between clinicians' triage decisions compared to each other or to a gold standard for each scale (reliability)? 3. How valid is each triage scale in predicting hospitalization and hospital mortality? A systematic search of the international literature published from 1966 through March 31, 2009 explored the British Nursing Index, Business Source Premier, CINAHL, Cochrane Library, EMBASE, and PubMed. Inclusion was limited to controlled studies of adult patients (≥15 years) visiting EDs for somatic reasons. Outcome variables were death in ED or hospital and need for hospitalization (validity). Methodological quality and clinical relevance of each study were rated as high, medium, or low. The results from the studies that met the inclusion criteria and quality standards were synthesized applying the internationally developed GRADE system. Each conclusion was then assessed as having strong, moderately strong, limited, or insufficient scientific evidence. If studies were not available, this was also noted. We found ED triage scales to be supported, at best, by limited and often insufficient evidence. The ability of the individual vital signs included in the different scales to predict outcome is seldom, if at all, studied in the ED setting. The scientific evidence to assess interrater agreement (reliability) was limited for one triage scale and insufficient or lacking for all other scales. Two of the scales yielded limited scientific evidence, and one scale yielded insufficient evidence, on which to assess the risk of early death or hospitalization in patients assigned to the two lowest triage levels on a 5-level scale (validity). PMID:21718476

Scaled-model guidelines for formation-flying solar coronagraph missions.

PubMed

Landini, Federico; Romoli, Marco; Baccani, Cristian; Focardi, Mauro; Pancrazzi, Maurizio; Galano, Damien; Kirschner, Volker

2016-02-15

Stray light suppression is the main concern in designing a solar coronagraph. The main contribution to the stray light for an externally occulted space-borne solar coronagraph is the light diffracted by the occulter and scattered by the optics. It is mandatory to carefully evaluate the diffraction generated by an external occulter and the impact that it has on the stray light signal on the focal plane. The scientific need for observations to cover a large portion of the heliosphere with an inner field of view as close as possible to the photospheric limb supports the ambition of launching formation-flying giant solar coronagraphs. Their dimension prevents the possibility of replicating the flight geometry in a clean laboratory environment, and the strong need for a scaled model is thus envisaged. The problem of scaling a coronagraph has already been faced for exoplanets, for a single point source on axis at infinity. We face the problem here by adopting an original approach and by introducing the scaling of the solar disk as an extended source.

BioPig: a Hadoop-based analytic toolkit for large-scale sequence data.

PubMed

Nordberg, Henrik; Bhatia, Karan; Wang, Kai; Wang, Zhong

2013-12-01

The recent revolution in sequencing technologies has led to an exponential growth of sequence data. As a result, most of the current bioinformatics tools become obsolete as they fail to scale with data. To tackle this 'data deluge', here we introduce the BioPig sequence analysis toolkit as one of the solutions that scale to data and computation. We built BioPig on the Apache's Hadoop MapReduce system and the Pig data flow language. Compared with traditional serial and MPI-based algorithms, BioPig has three major advantages: first, BioPig's programmability greatly reduces development time for parallel bioinformatics applications; second, testing BioPig with up to 500 Gb sequences demonstrates that it scales automatically with size of data; and finally, BioPig can be ported without modification on many Hadoop infrastructures, as tested with Magellan system at National Energy Research Scientific Computing Center and the Amazon Elastic Compute Cloud. In summary, BioPig represents a novel program framework with the potential to greatly accelerate data-intensive bioinformatics analysis.

SciSpark's SRDD : A Scientific Resilient Distributed Dataset for Multidimensional Data

NASA Astrophysics Data System (ADS)

Palamuttam, R. S.; Wilson, B. D.; Mogrovejo, R. M.; Whitehall, K. D.; Mattmann, C. A.; McGibbney, L. J.; Ramirez, P.

2015-12-01

Remote sensing data and climate model output are multi-dimensional arrays of massive sizes locked away in heterogeneous file formats (HDF5/4, NetCDF 3/4) and metadata models (HDF-EOS, CF) making it difficult to perform multi-stage, iterative science processing since each stage requires writing and reading data to and from disk. We have developed SciSpark, a robust Big Data framework, that extends ApacheTM Spark for scaling scientific computations. Apache Spark improves the map-reduce implementation in ApacheTM Hadoop for parallel computing on a cluster, by emphasizing in-memory computation, "spilling" to disk only as needed, and relying on lazy evaluation. Central to Spark is the Resilient Distributed Dataset (RDD), an in-memory distributed data structure that extends the functional paradigm provided by the Scala programming language. However, RDDs are ideal for tabular or unstructured data, and not for highly dimensional data. The SciSpark project introduces the Scientific Resilient Distributed Dataset (sRDD), a distributed-computing array structure which supports iterative scientific algorithms for multidimensional data. SciSpark processes data stored in NetCDF and HDF files by partitioning them across time or space and distributing the partitions among a cluster of compute nodes. We show usability and extensibility of SciSpark by implementing distributed algorithms for geospatial operations on large collections of multi-dimensional grids. In particular we address the problem of scaling an automated method for finding Mesoscale Convective Complexes. SciSpark provides a tensor interface to support the pluggability of different matrix libraries. We evaluate performance of the various matrix libraries in distributed pipelines, such as Nd4jTM and BreezeTM. We detail the architecture and design of SciSpark, our efforts to integrate climate science algorithms, parallel ingest and partitioning (sharding) of A-Train satellite observations from model grids. These solutions are encompassed in SciSpark, an open-source software framework for distributed computing on scientific data.

Supporting observation campaigns with high resolution modeling

NASA Astrophysics Data System (ADS)

Klocke, Daniel; Brueck, Matthias; Voigt, Aiko

2017-04-01

High resolution simulation in support of measurement campaigns offers a promising and emerging way to create large-scale context for small-scale observations of clouds and precipitation processes. As these simulation include the coupling of measured small-scale processes with the circulation, they also help to integrate the research communities from modeling and observations and allow for detailed model evaluations against dedicated observations. In connection with the measurement campaign NARVAL (August 2016 and December 2013) simulations with a grid-spacing of 2.5 km for the tropical Atlantic region (9000x3300 km), with local refinement to 1.2 km for the western part of the domain, were performed using the icosahedral non-hydrostatic (ICON) general circulation model. These simulations are again used to drive large eddy resolving simulations with the same model for selected days in the high definition clouds and precipitation for advancing climate prediction (HD(CP)2) project. The simulations are presented with the focus on selected results showing the benefit for the scientific communities doing atmospheric measurements and numerical modeling of climate and weather. Additionally, an outlook will be given on how similar simulations will support the NAWDEX measurement campaign in the North Atlantic and AC3 measurement campaign in the Arctic.

An engineering closure for heavily under-resolved coarse-grid CFD in large applications

NASA Astrophysics Data System (ADS)

Class, Andreas G.; Yu, Fujiang; Jordan, Thomas

2016-11-01

Even though high performance computation allows very detailed description of a wide range of scales in scientific computations, engineering simulations used for design studies commonly merely resolve the large scales thus speeding up simulation time. The coarse-grid CFD (CGCFD) methodology is developed for flows with repeated flow patterns as often observed in heat exchangers or porous structures. It is proposed to use inviscid Euler equations on a very coarse numerical mesh. This coarse mesh needs not to conform to the geometry in all details. To reinstall physics on all smaller scales cheap subgrid models are employed. Subgrid models are systematically constructed by analyzing well-resolved generic representative simulations. By varying the flow conditions in these simulations correlations are obtained. These comprehend for each individual coarse mesh cell a volume force vector and volume porosity. Moreover, for all vertices, surface porosities are derived. CGCFD is related to the immersed boundary method as both exploit volume forces and non-body conformal meshes. Yet, CGCFD differs with respect to the coarser mesh and the use of Euler equations. We will describe the methodology based on a simple test case and the application of the method to a 127 pin wire-wrap fuel bundle.

Large underground, liquid based detectors for astro-particle physics in Europe: scientific case and prospects

NASA Astrophysics Data System (ADS)

Autiero, D.; Äystö, J.; Badertscher, A.; Bezrukov, L.; Bouchez, J.; Bueno, A.; Busto, J.; Campagne, J.-E.; Cavata, Ch; Chaussard, L.; de Bellefon, A.; Déclais, Y.; Dumarchez, J.; Ebert, J.; Enqvist, T.; Ereditato, A.; von Feilitzsch, F.; Fileviez Perez, P.; Göger-Neff, M.; Gninenko, S.; Gruber, W.; Hagner, C.; Hess, M.; Hochmuth, K. A.; Kisiel, J.; Knecht, L.; Kreslo, I.; Kudryavtsev, V. A.; Kuusiniemi, P.; Lachenmaier, T.; Laffranchi, M.; Lefievre, B.; Lightfoot, P. K.; Lindner, M.; Maalampi, J.; Maltoni, M.; Marchionni, A.; Marrodán Undagoitia, T.; Marteau, J.; Meregaglia, A.; Messina, M.; Mezzetto, M.; Mirizzi, A.; Mosca, L.; Moser, U.; Müller, A.; Natterer, G.; Oberauer, L.; Otiougova, P.; Patzak, T.; Peltoniemi, J.; Potzel, W.; Pistillo, C.; Raffelt, G. G.; Rondio, E.; Roos, M.; Rossi, B.; Rubbia, A.; Savvinov, N.; Schwetz, T.; Sobczyk, J.; Spooner, N. J. C.; Stefan, D.; Tonazzo, A.; Trzaska, W.; Ulbricht, J.; Volpe, C.; Winter, J.; Wurm, M.; Zalewska, A.; Zimmermann, R.

2007-11-01

This document reports on a series of experimental and theoretical studies conducted to assess the astro-particle physics potential of three future large scale particle detectors proposed in Europe as next generation underground observatories. The proposed apparatuses employ three different and, to some extent, complementary detection techniques: GLACIER (liquid argon TPC), LENA (liquid scintillator) and MEMPHYS (water Cherenkov), based on the use of large mass of liquids as active detection media. The results of these studies are presented along with a critical discussion of the performance attainable by the three proposed approaches coupled to existing or planned underground laboratories, in relation to open and outstanding physics issues such as the search for matter instability, the detection of astrophysical neutrinos and geo-neutrinos and to the possible use of these detectors in future high intensity neutrino beams.

Large-scale modeling of the primary visual cortex: influence of cortical architecture upon neuronal response.

PubMed

McLaughlin, David; Shapley, Robert; Shelley, Michael

2003-01-01

A large-scale computational model of a local patch of input layer 4 [Formula: see text] of the primary visual cortex (V1) of the macaque monkey, together with a coarse-grained reduction of the model, are used to understand potential effects of cortical architecture upon neuronal performance. Both the large-scale point neuron model and its asymptotic reduction are described. The work focuses upon orientation preference and selectivity, and upon the spatial distribution of neuronal responses across the cortical layer. Emphasis is given to the role of cortical architecture (the geometry of synaptic connectivity, of the ordered and disordered structure of input feature maps, and of their interplay) as mechanisms underlying cortical responses within the model. Specifically: (i) Distinct characteristics of model neuronal responses (firing rates and orientation selectivity) as they depend upon the neuron's location within the cortical layer relative to the pinwheel centers of the map of orientation preference; (ii) A time independent (DC) elevation in cortico-cortical conductances within the model, in contrast to a "push-pull" antagonism between excitation and inhibition; (iii) The use of asymptotic analysis to unveil mechanisms which underly these performances of the model; (iv) A discussion of emerging experimental data. The work illustrates that large-scale scientific computation--coupled together with analytical reduction, mathematical analysis, and experimental data, can provide significant understanding and intuition about the possible mechanisms of cortical response. It also illustrates that the idealization which is a necessary part of theoretical modeling can outline in sharp relief the consequences of differing alternative interpretations and mechanisms--with final arbiter being a body of experimental evidence whose measurements address the consequences of these analyses.

Scalable Performance Measurement and Analysis

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

Gamblin, Todd

2009-01-01

Concurrency levels in large-scale, distributed-memory supercomputers are rising exponentially. Modern machines may contain 100,000 or more microprocessor cores, and the largest of these, IBM's Blue Gene/L, contains over 200,000 cores. Future systems are expected to support millions of concurrent tasks. In this dissertation, we focus on efficient techniques for measuring and analyzing the performance of applications running on very large parallel machines. Tuning the performance of large-scale applications can be a subtle and time-consuming task because application developers must measure and interpret data from many independent processes. While the volume of the raw data scales linearly with the number ofmore » tasks in the running system, the number of tasks is growing exponentially, and data for even small systems quickly becomes unmanageable. Transporting performance data from so many processes over a network can perturb application performance and make measurements inaccurate, and storing such data would require a prohibitive amount of space. Moreover, even if it were stored, analyzing the data would be extremely time-consuming. In this dissertation, we present novel methods for reducing performance data volume. The first draws on multi-scale wavelet techniques from signal processing to compress systemwide, time-varying load-balance data. The second uses statistical sampling to select a small subset of running processes to generate low-volume traces. A third approach combines sampling and wavelet compression to stratify performance data adaptively at run-time and to reduce further the cost of sampled tracing. We have integrated these approaches into Libra, a toolset for scalable load-balance analysis. We present Libra and show how it can be used to analyze data from large scientific applications scalably.« less

Linking the Scales of Scientific inquiry and Watershed Management: A Focus on Green Infrastructure

NASA Astrophysics Data System (ADS)

Golden, H. E.; Hoghooghi, N.

2017-12-01

Urbanization modifies the hydrologic cycle, resulting in potentially deleterious downstream water quality and quantity effects. However, the cumulative interacting effects of water storage, transport, and biogeochemical processes occurring within other land cover and use types of the same watershed can render management explicitly targeted to limit the negative outcomes from urbanization ineffective. For example, evidence indicates that green infrastructure, or low impact development (LID), practices can attenuate the adverse water quality and quantity effects of urbanizing systems. However, the research providing this evidence has been conducted at local scales (e.g., plots, small homogeneous urban catchments) that isolate the measurable effects of such approaches. Hence, a distinct disconnect exists between the scale of scientific inquiry and the scale of management and decision-making practices. Here we explore the oft-discussed yet rarely directly addressed scientific and management conundrum: How do we scale our well-documented scientific knowledge of the water quantity and quality responses to LID practices measured and modeled at local scales to that of "actual" management scales? We begin by focusing on LID practices in mixed land cover watersheds. We present key concepts that have emerged from LID research at the local scale, considerations for scaling this research to watersheds, recent advances and findings in scaling the effects of LID practices on water quality and quantity at watershed scales, and the use of combined novel measurements and models for these scaling efforts. We underscore these concepts with a case study that evaluates the effects of three LID practices using simulation modeling across a mixed land cover watershed. This synthesis and case study highlight that scientists are making progress toward successfully tailoring fundamental research questions with decision-making goals in mind, yet we still have a long road ahead.

A Novel Coarsening Method for Scalable and Efficient Mesh Generation

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

Yoo, A; Hysom, D; Gunney, B

2010-12-02

In this paper, we propose a novel mesh coarsening method called brick coarsening method. The proposed method can be used in conjunction with any graph partitioners and scales to very large meshes. This method reduces problem space by decomposing the original mesh into fixed-size blocks of nodes called bricks, layered in a similar way to conventional brick laying, and then assigning each node of the original mesh to appropriate brick. Our experiments indicate that the proposed method scales to very large meshes while allowing simple RCB partitioner to produce higher-quality partitions with significantly less edge cuts. Our results further indicatemore » that the proposed brick-coarsening method allows more complicated partitioners like PT-Scotch to scale to very large problem size while still maintaining good partitioning performance with relatively good edge-cut metric. Graph partitioning is an important problem that has many scientific and engineering applications in such areas as VLSI design, scientific computing, and resource management. Given a graph G = (V,E), where V is the set of vertices and E is the set of edges, (k-way) graph partitioning problem is to partition the vertices of the graph (V) into k disjoint groups such that each group contains roughly equal number of vertices and the number of edges connecting vertices in different groups is minimized. Graph partitioning plays a key role in large scientific computing, especially in mesh-based computations, as it is used as a tool to minimize the volume of communication and to ensure well-balanced load across computing nodes. The impact of graph partitioning on the reduction of communication can be easily seen, for example, in different iterative methods to solve a sparse system of linear equation. Here, a graph partitioning technique is applied to the matrix, which is basically a graph in which each edge is a non-zero entry in the matrix, to allocate groups of vertices to processors in such a way that many of matrix-vector multiplication can be performed locally on each processor and hence to minimize communication. Furthermore, a good graph partitioning scheme ensures the equal amount of computation performed on each processor. Graph partitioning is a well known NP-complete problem, and thus the most commonly used graph partitioning algorithms employ some forms of heuristics. These algorithms vary in terms of their complexity, partition generation time, and the quality of partitions, and they tend to trade off these factors. A significant challenge we are currently facing at the Lawrence Livermore National Laboratory is how to partition very large meshes on massive-size distributed memory machines like IBM BlueGene/P, where scalability becomes a big issue. For example, we have found that the ParMetis, a very popular graph partitioning tool, can only scale to 16K processors. An ideal graph partitioning method on such an environment should be fast and scale to very large meshes, while producing high quality partitions. This is an extremely challenging task, as to scale to that level, the partitioning algorithm should be simple and be able to produce partitions that minimize inter-processor communications and balance the load imposed on the processors. Our goals in this work are two-fold: (1) To develop a new scalable graph partitioning method with good load balancing and communication reduction capability. (2) To study the performance of the proposed partitioning method on very large parallel machines using actual data sets and compare the performance to that of existing methods. The proposed method achieves the desired scalability by reducing the mesh size. For this, it coarsens an input mesh into a smaller size mesh by coalescing the vertices and edges of the original mesh into a set of mega-vertices and mega-edges. A new coarsening method called brick algorithm is developed in this research. In the brick algorithm, the zones in a given mesh are first grouped into fixed size blocks called bricks. These brick are then laid in a way similar to conventional brick laying technique, which reduces the number of neighboring blocks each block needs to communicate. Contributions of this research are as follows: (1) We have developed a novel method that scales to a really large problem size while producing high quality mesh partitions; (2) We measured the performance and scalability of the proposed method on a machine of massive size using a set of actual large complex data sets, where we have scaled to a mesh with 110 million zones using our method. To the best of our knowledge, this is the largest complex mesh that a partitioning method is successfully applied to; and (3) We have shown that proposed method can reduce the number of edge cuts by as much as 65%.« less

Generation of dense granular deposits for porosity analysis: assessment and application of large-scale non-smooth granular dynamics

NASA Astrophysics Data System (ADS)

Schruff, T.; Liang, R.; Rüde, U.; Schüttrumpf, H.; Frings, R. M.

2018-01-01

The knowledge of structural properties of granular materials such as porosity is highly important in many application-oriented and scientific fields. In this paper we present new results of computer-based packing simulations where we use the non-smooth granular dynamics (NSGD) method to simulate gravitational random dense packing of spherical particles with various particle size distributions and two types of depositional conditions. A bin packing scenario was used to compare simulation results to laboratory porosity measurements and to quantify the sensitivity of the NSGD regarding critical simulation parameters such as time step size. The results of the bin packing simulations agree well with laboratory measurements across all particle size distributions with all absolute errors below 1%. A large-scale packing scenario with periodic side walls was used to simulate the packing of up to 855,600 spherical particles with various particle size distributions (PSD). Simulation outcomes are used to quantify the effect of particle-domain-size ratio on the packing compaction. A simple correction model, based on the coordination number, is employed to compensate for this effect on the porosity and to determine the relationship between PSD and porosity. Promising accuracy and stability results paired with excellent computational performance recommend the application of NSGD for large-scale packing simulations, e.g. to further enhance the generation of representative granular deposits.

The MPO system for automatic workflow documentation

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

Abla, G.; Coviello, E. N.; Flanagan, S. M.

Data from large-scale experiments and extreme-scale computing is expensive to produce and may be used for critical applications. However, it is not the mere existence of data that is important, but our ability to make use of it. Experience has shown that when metadata is better organized and more complete, the underlying data becomes more useful. Traditionally, capturing the steps of scientific workflows and metadata was the role of the lab notebook, but the digital era has resulted instead in the fragmentation of data, processing, and annotation. Here, this article presents the Metadata, Provenance, and Ontology (MPO) System, the softwaremore » that can automate the documentation of scientific workflows and associated information. Based on recorded metadata, it provides explicit information about the relationships among the elements of workflows in notebook form augmented with directed acyclic graphs. A set of web-based graphical navigation tools and Application Programming Interface (API) have been created for searching and browsing, as well as programmatically accessing the workflows and data. We describe the MPO concepts and its software architecture. We also report the current status of the software as well as the initial deployment experience.« less

The MPO system for automatic workflow documentation

DOE PAGES

Abla, G.; Coviello, E. N.; Flanagan, S. M.; ...

2016-04-18

Data from large-scale experiments and extreme-scale computing is expensive to produce and may be used for critical applications. However, it is not the mere existence of data that is important, but our ability to make use of it. Experience has shown that when metadata is better organized and more complete, the underlying data becomes more useful. Traditionally, capturing the steps of scientific workflows and metadata was the role of the lab notebook, but the digital era has resulted instead in the fragmentation of data, processing, and annotation. Here, this article presents the Metadata, Provenance, and Ontology (MPO) System, the softwaremore » that can automate the documentation of scientific workflows and associated information. Based on recorded metadata, it provides explicit information about the relationships among the elements of workflows in notebook form augmented with directed acyclic graphs. A set of web-based graphical navigation tools and Application Programming Interface (API) have been created for searching and browsing, as well as programmatically accessing the workflows and data. We describe the MPO concepts and its software architecture. We also report the current status of the software as well as the initial deployment experience.« less

Parallel Tensor Compression for Large-Scale Scientific Data.

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

Kolda, Tamara G.; Ballard, Grey; Austin, Woody Nathan

As parallel computing trends towards the exascale, scientific data produced by high-fidelity simulations are growing increasingly massive. For instance, a simulation on a three-dimensional spatial grid with 512 points per dimension that tracks 64 variables per grid point for 128 time steps yields 8 TB of data. By viewing the data as a dense five way tensor, we can compute a Tucker decomposition to find inherent low-dimensional multilinear structure, achieving compression ratios of up to 10000 on real-world data sets with negligible loss in accuracy. So that we can operate on such massive data, we present the first-ever distributed memorymore » parallel implementation for the Tucker decomposition, whose key computations correspond to parallel linear algebra operations, albeit with nonstandard data layouts. Our approach specifies a data distribution for tensors that avoids any tensor data redistribution, either locally or in parallel. We provide accompanying analysis of the computation and communication costs of the algorithms. To demonstrate the compression and accuracy of the method, we apply our approach to real-world data sets from combustion science simulations. We also provide detailed performance results, including parallel performance in both weak and strong scaling experiments.« less

Mountain hydrology, snow color, and the fourth paradigm

NASA Astrophysics Data System (ADS)

Dozier, Jeff

2011-10-01

The world's mountain ranges accumulate substantial snow, whose melt produces the bulk of runoff and often combines with rain to cause floods. Worldwide, inadequate understanding and a reliance on sparsely distributed observations limit our ability to predict seasonal and paroxysmal runoff as climate changes, ecosystems adapt, populations grow, land use evolves, and societies make choices. To improve assessments of snow accumulation, melt, and runoff, scientists and community planners can take advantage of two emerging trends: (1) an ability to remotely sense snow properties from satellites at a spatial scale appropriate for mountain regions (10- to 100-meter resolution, coverage of the order of 100,000 square kilometers) and a daily temporal scale appropriate for the dynamic nature of snow and (2) The Fourth Paradigm [Hey et al., 2009], which posits a new scientific approach in which insight is discovered through the manipulation of large data sets as the evolutionary step in scientific thinking beyond the first three paradigms: empiricism, analyses, and simulation. The inspiration for the book's title comes from pioneering computer scientist Jim Gray, based on a lecture he gave at the National Academy of Sciences 3 weeks before he disappeared at sea.

Collective Influence of Multiple Spreaders Evaluated by Tracing Real Information Flow in Large-Scale Social Networks.

PubMed

Teng, Xian; Pei, Sen; Morone, Flaviano; Makse, Hernán A

2016-10-26

Identifying the most influential spreaders that maximize information flow is a central question in network theory. Recently, a scalable method called "Collective Influence (CI)" has been put forward through collective influence maximization. In contrast to heuristic methods evaluating nodes' significance separately, CI method inspects the collective influence of multiple spreaders. Despite that CI applies to the influence maximization problem in percolation model, it is still important to examine its efficacy in realistic information spreading. Here, we examine real-world information flow in various social and scientific platforms including American Physical Society, Facebook, Twitter and LiveJournal. Since empirical data cannot be directly mapped to ideal multi-source spreading, we leverage the behavioral patterns of users extracted from data to construct "virtual" information spreading processes. Our results demonstrate that the set of spreaders selected by CI can induce larger scale of information propagation. Moreover, local measures as the number of connections or citations are not necessarily the deterministic factors of nodes' importance in realistic information spreading. This result has significance for rankings scientists in scientific networks like the APS, where the commonly used number of citations can be a poor indicator of the collective influence of authors in the community.

Constraining Large-Scale Solar Magnetic Field Models with Optical Coronal Observations

NASA Astrophysics Data System (ADS)

Uritsky, V. M.; Davila, J. M.; Jones, S. I.

2015-12-01

Scientific success of the Solar Probe Plus (SPP) and Solar Orbiter (SO) missions will depend to a large extent on the accuracy of the available coronal magnetic field models describing the connectivity of plasma disturbances in the inner heliosphere with their source regions. We argue that ground based and satellite coronagraph images can provide robust geometric constraints for the next generation of improved coronal magnetic field extrapolation models. In contrast to the previously proposed loop segmentation codes designed for detecting compact closed-field structures above solar active regions, we focus on the large-scale geometry of the open-field coronal regions located at significant radial distances from the solar surface. Details on the new feature detection algorithms will be presented. By applying the developed image processing methodology to high-resolution Mauna Loa Solar Observatory images, we perform an optimized 3D B-line tracing for a full Carrington rotation using the magnetic field extrapolation code presented in a companion talk by S.Jones at al. Tracing results are shown to be in a good qualitative agreement with the large-scalie configuration of the optical corona. Subsequent phases of the project and the related data products for SSP and SO missions as wwll as the supporting global heliospheric simulations will be discussed.

Blueprint for a microwave trapped ion quantum computer

PubMed Central

Lekitsch, Bjoern; Weidt, Sebastian; Fowler, Austin G.; Mølmer, Klaus; Devitt, Simon J.; Wunderlich, Christof; Hensinger, Winfried K.

2017-01-01

The availability of a universal quantum computer may have a fundamental impact on a vast number of research fields and on society as a whole. An increasingly large scientific and industrial community is working toward the realization of such a device. An arbitrarily large quantum computer may best be constructed using a modular approach. We present a blueprint for a trapped ion–based scalable quantum computer module, making it possible to create a scalable quantum computer architecture based on long-wavelength radiation quantum gates. The modules control all operations as stand-alone units, are constructed using silicon microfabrication techniques, and are within reach of current technology. To perform the required quantum computations, the modules make use of long-wavelength radiation–based quantum gate technology. To scale this microwave quantum computer architecture to a large size, we present a fully scalable design that makes use of ion transport between different modules, thereby allowing arbitrarily many modules to be connected to construct a large-scale device. A high error–threshold surface error correction code can be implemented in the proposed architecture to execute fault-tolerant operations. With appropriate adjustments, the proposed modules are also suitable for alternative trapped ion quantum computer architectures, such as schemes using photonic interconnects. PMID:28164154

Integrating scientific knowledge into large-scale restoration programs: the CALFED Bay-Delta Program experience

USGS Publications Warehouse

Taylor, Kimberly A.; Short, A.

2009-01-01

Integrating science into resource management activities is a goal of the CALFED Bay-Delta Program, a multi-agency effort to address water supply reliability, ecological condition, drinking water quality, and levees in the Sacramento-San Joaquin Delta of northern California. Under CALFED, many different strategies were used to integrate science, including interaction between the research and management communities, public dialogues about scientific work, and peer review. This paper explores ways science was (and was not) integrated into CALFED's management actions and decision systems through three narratives describing different patterns of scientific integration and application in CALFED. Though a collaborative process and certain organizational conditions may be necessary for developing new understandings of the system of interest, we find that those factors are not sufficient for translating that knowledge into management actions and decision systems. We suggest that the application of knowledge may be facilitated or hindered by (1) differences in the objectives, approaches, and cultures of scientists operating in the research community and those operating in the management community and (2) other factors external to the collaborative process and organization.

Science to support the understanding of Ohio's water resources, 2014-15

USGS Publications Warehouse

Shaffer, Kimberly; Kula, Stephanie P.

2014-01-01

The U.S. Geological Survey (USGS) works in cooperation with local, State, and other Federal agencies, as well as universities, to furnish decision makers, policy makers, USGS scientists, and the general public with reliable scientific information and tools to assist them in management, stewardship, and use of Ohio’s natural resources. The diversity of scientific expertise among USGS personnel enables them to carry out large- and small-scale multidisciplinary studies. The USGS is unique among government organizations because it has neither regulatory nor developmental authority—its sole product is impartial, credible, relevant, and timely scientific information, equally accessible and available to everyone. The USGS Ohio Water Science Center provides reliable hydrologic and water-related ecological information to aid in the understanding of the use and management of the Nation’s water resources, in general, and Ohio’s water resources, in particular. This fact sheet provides an overview of current (2014) or recently completed USGS studies and data activities pertaining to water resources in Ohio. More information regarding projects of the USGS Ohio Water Science Center is available at http://oh.water.usgs.gov/.

Use of computational modeling combined with advanced visualization to develop strategies for the design of crop ideotypes to address food security

DOE PAGES

Christensen, A. J.; Srinivasan, V.; Hart, J. C.; ...

2018-03-17

Sustainable crop production is a contributing factor to current and future food security. Innovative technologies are needed to design strategies that will achieve higher crop yields on less land and with fewer resources. Computational modeling coupled with advanced scientific visualization enables researchers to explore and interact with complex agriculture, nutrition, and climate data to predict how crops will respond to untested environments. These virtual observations and predictions can direct the development of crop ideotypes designed to meet future yield and nutritional demands. This review surveys modeling strategies for the development of crop ideotypes and scientific visualization technologies that have ledmore » to discoveries in “big data” analysis. Combined modeling and visualization approaches have been used to realistically simulate crops and to guide selection that immediately enhances crop quantity and quality under challenging environmental conditions. Lastly, this survey of current and developing technologies indicates that integrative modeling and advanced scientific visualization may help overcome challenges in agriculture and nutrition data as large-scale and multidimensional data become available in these fields.« less

Public Reception of Climate Science: Coherence, Reliability, and Independence.

PubMed

Hahn, Ulrike; Harris, Adam J L; Corner, Adam

2016-01-01

Possible measures to mitigate climate change require global collective actions whose impacts will be felt by many, if not all. Implementing such actions requires successful communication of the reasons for them, and hence the underlying climate science, to a degree that far exceeds typical scientific issues which do not require large-scale societal response. Empirical studies have identified factors, such as the perceived level of consensus in scientific opinion and the perceived reliability of scientists, that can limit people's trust in science communicators and their subsequent acceptance of climate change claims. Little consideration has been given, however, to recent formal results within philosophy concerning the relationship between truth, the reliability of evidence sources, the coherence of multiple pieces of evidence/testimonies, and the impact of (non-)independence between sources of evidence. This study draws on these results to evaluate exactly what has (and, more important, has not yet) been established in the empirical literature about the factors that bias the public's reception of scientific communications about climate change. Copyright © 2015 Cognitive Science Society, Inc.

Use of computational modeling combined with advanced visualization to develop strategies for the design of crop ideotypes to address food security

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

Christensen, A. J.; Srinivasan, V.; Hart, J. C.

Sustainable crop production is a contributing factor to current and future food security. Innovative technologies are needed to design strategies that will achieve higher crop yields on less land and with fewer resources. Computational modeling coupled with advanced scientific visualization enables researchers to explore and interact with complex agriculture, nutrition, and climate data to predict how crops will respond to untested environments. These virtual observations and predictions can direct the development of crop ideotypes designed to meet future yield and nutritional demands. This review surveys modeling strategies for the development of crop ideotypes and scientific visualization technologies that have ledmore » to discoveries in “big data” analysis. Combined modeling and visualization approaches have been used to realistically simulate crops and to guide selection that immediately enhances crop quantity and quality under challenging environmental conditions. Lastly, this survey of current and developing technologies indicates that integrative modeling and advanced scientific visualization may help overcome challenges in agriculture and nutrition data as large-scale and multidimensional data become available in these fields.« less

Use of computational modeling combined with advanced visualization to develop strategies for the design of crop ideotypes to address food security.

PubMed

Christensen, A J; Srinivasan, Venkatraman; Hart, John C; Marshall-Colon, Amy

2018-05-01

Sustainable crop production is a contributing factor to current and future food security. Innovative technologies are needed to design strategies that will achieve higher crop yields on less land and with fewer resources. Computational modeling coupled with advanced scientific visualization enables researchers to explore and interact with complex agriculture, nutrition, and climate data to predict how crops will respond to untested environments. These virtual observations and predictions can direct the development of crop ideotypes designed to meet future yield and nutritional demands. This review surveys modeling strategies for the development of crop ideotypes and scientific visualization technologies that have led to discoveries in "big data" analysis. Combined modeling and visualization approaches have been used to realistically simulate crops and to guide selection that immediately enhances crop quantity and quality under challenging environmental conditions. This survey of current and developing technologies indicates that integrative modeling and advanced scientific visualization may help overcome challenges in agriculture and nutrition data as large-scale and multidimensional data become available in these fields.

AMRZone: A Runtime AMR Data Sharing Framework For Scientific Applications

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

Zhang, Wenzhao; Tang, Houjun; Harenberg, Steven

Frameworks that facilitate runtime data sharing across multiple applications are of great importance for scientific data analytics. Although existing frameworks work well over uniform mesh data, they can not effectively handle adaptive mesh refinement (AMR) data. Among the challenges to construct an AMR-capable framework include: (1) designing an architecture that facilitates online AMR data management; (2) achieving a load-balanced AMR data distribution for the data staging space at runtime; and (3) building an effective online index to support the unique spatial data retrieval requirements for AMR data. Towards addressing these challenges to support runtime AMR data sharing across scientific applications,more » we present the AMRZone framework. Experiments over real-world AMR datasets demonstrate AMRZone's effectiveness at achieving a balanced workload distribution, reading/writing large-scale datasets with thousands of parallel processes, and satisfying queries with spatial constraints. Moreover, AMRZone's performance and scalability are even comparable with existing state-of-the-art work when tested over uniform mesh data with up to 16384 cores; in the best case, our framework achieves a 46% performance improvement.« less

Use of computational modeling combined with advanced visualization to develop strategies for the design of crop ideotypes to address food security

PubMed Central

Christensen, A J; Srinivasan, Venkatraman; Hart, John C; Marshall-Colon, Amy

2018-01-01

Abstract Sustainable crop production is a contributing factor to current and future food security. Innovative technologies are needed to design strategies that will achieve higher crop yields on less land and with fewer resources. Computational modeling coupled with advanced scientific visualization enables researchers to explore and interact with complex agriculture, nutrition, and climate data to predict how crops will respond to untested environments. These virtual observations and predictions can direct the development of crop ideotypes designed to meet future yield and nutritional demands. This review surveys modeling strategies for the development of crop ideotypes and scientific visualization technologies that have led to discoveries in “big data” analysis. Combined modeling and visualization approaches have been used to realistically simulate crops and to guide selection that immediately enhances crop quantity and quality under challenging environmental conditions. This survey of current and developing technologies indicates that integrative modeling and advanced scientific visualization may help overcome challenges in agriculture and nutrition data as large-scale and multidimensional data become available in these fields. PMID:29562368

Beyond Music Sharing: An Evaluation of Peer-to-Peer Data Dissemination Techniques in Large Scientific Collaborations

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

Ripeanu, Matei; Al-Kiswany, Samer; Iamnitchi, Adriana

2009-03-01

The avalanche of data from scientific instruments and the ensuing interest from geographically distributed users to analyze and interpret it accentuates the need for efficient data dissemination. A suitable data distribution scheme will find the delicate balance between conflicting requirements of minimizing transfer times, minimizing the impact on the network, and uniformly distributing load among participants. We identify several data distribution techniques, some successfully employed by today's peer-to-peer networks: staging, data partitioning, orthogonal bandwidth exploitation, and combinations of the above. We use simulations to explore the performance of these techniques in contexts similar to those used by today's data-centric scientificmore » collaborations and derive several recommendations for efficient data dissemination. Our experimental results show that the peer-to-peer solutions that offer load balancing and good fault tolerance properties and have embedded participation incentives lead to unjustified costs in today's scientific data collaborations deployed on over-provisioned network cores. However, as user communities grow and these deployments scale, peer-to-peer data delivery mechanisms will likely outperform other techniques.« less

Large-Scale Operations Management Test of Use of the White Amur for Control of Problem Aquatic Plants. Selected Life History Information of Animal Species on Lake Conway, Florida.

DTIC Science & Technology

1982-08-01

Name Management Information 2 Loplsostus i. Inhabits warm, sluggish waters. (Continued) platyrhincus Can live in very stagnant waters 3 Amia calva a...water with abundant vegetation. Amia calva can survive very stagnant water due to its ability to surface and ’breathe’ the air. Active at twilight and...Name Scientific Name FishSpecies 1 Longnose gar Loplsosteus osseus 2 Florida gar Lepisosteus platjrhincus 3 Bowf in Aula calva 4 American eel Anguilla

The Psychology of Violent Conflict in Failing States: A Review of the Scientific Literature (Psychologie des Conflits Violents au sein d’etats en Deroute: Analyse de Publications Scientifiques)

DTIC Science & Technology

2010-12-01

however, was the possibility for students to choose the role of insurgents. Two weeks prior to the start of the simulation, the 78 undergraduate ...King, 2009), students in a political science class participated in a week-long simulation of large-scale regional insurgency. Before the simulation... Students could choose to be government officials, such as the president or the secretary of defence of a country. Alternatively students could role-play

The project De Caldas International Project: An example of a large-scale radwaste isolation natural analogue study

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

Shea, M.

1995-09-01

The proper isolation of radioactive waste is one of today`s most pressing environmental issues. Research is being carried out by many countries around the world in order to answer critical and perplexing questions regarding the safe disposal of radioactive waste. Natural analogue studies are an increasingly important facet of this international research effort. The Pocos de Caldas Project represents a major effort of the international technical and scientific community towards addressing one of modern civilization`s most critical environmental issues - radioactive waste isolation.

Compiling for Application Specific Computational Acceleration in Reconfigurable Architectures Final Report CRADA No. TSB-2033-01

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

De Supinski, B.; Caliga, D.

2017-09-28

The primary objective of this project was to develop memory optimization technology to efficiently deliver data to, and distribute data within, the SRC-6's Field Programmable Gate Array- ("FPGA") based Multi-Adaptive Processors (MAPs). The hardware/software approach was to explore efficient MAP configurations and generate the compiler technology to exploit those configurations. This memory accessing technology represents an important step towards making reconfigurable symmetric multi-processor (SMP) architectures that will be a costeffective solution for large-scale scientific computing.

Power and Thermal Technologies for Air and Space - Scientific Research Program. Delivery Order 0020: Advanced Conductors and Thermal Science

DTIC Science & Technology

2014-03-01

4.31. Thermal conductivity of CNT/Carbon foam substrate 4.4.3.3 Post-growth Nickel Coating Plating CNTs/carbon foam samples with nickel provides a...will be necessary to conduct large scale synthesis of textured Ca-Co-O on the amorphous- buffered n-type oxide substrate using sol-gel spin- coating and... Conductors and Thermal Science Evan L. Thomas, Qiuhong N. Zhang, Helen Shen, Serhiy N. Leontsev, John P. Murphy, Jack L. Burke, Lyle Brunke, and

Microscopic origins of the large piezoelectricity of leadfree (Ba,Ca)(Zr,Ti)O3

NASA Astrophysics Data System (ADS)

Nahas, Yousra; Akbarzadeh, Alireza; Prokhorenko, Sergei; Prosandeev, Sergey; Walter, Raymond; Kornev, Igor; Íñiguez, Jorge; Bellaiche, L.

2017-06-01

In light of directives around the world to eliminate toxic materials in various technologies, finding lead-free materials with high piezoelectric responses constitutes an important current scientific goal. As such, the recent discovery of a large electromechanical conversion near room temperature in (1-x)Ba(Zr0.2Ti0.8)O3-x(Ba0.7Ca0.3)TiO3 compounds has directed attention to understanding its origin. Here, we report the development of a large-scale atomistic scheme providing a microscopic insight into this technologically promising material. We find that its high piezoelectricity originates from the existence of large fluctuations of polarization in the orthorhombic state arising from the combination of a flat free-energy landscape, a fragmented local structure, and the narrow temperature window around room temperature at which this orthorhombic phase is the equilibrium state. In addition to deepening the current knowledge on piezoelectricity, these findings have the potential to guide the design of other lead-free materials with large electromechanical responses.

Cirrus cloud development in a mobile upper tropospheric trough: The November 26th FIRE cirrus case study

NASA Technical Reports Server (NTRS)

Mace, Gerald G.; Ackerman, Thomas P.

1993-01-01

The period from 18 UTC 26 Nov. 1991 to roughly 23 UTC 26 Nov. 1991 is one of the study periods of the FIRE (First International Satellite Cloud Climatology Regional Experiment) 2 field campaign. The middle and upper tropospheric cloud data that was collected during this time allowed FIRE scientists to learn a great deal about the detailed structure, microphysics, and radiative characteristics of the mid latitude cirrus that occurred during that time. Modeling studies that range from the microphysical to the mesoscale are now underway attempting to piece the detailed knowledge of this cloud system into a coherent picture of the atmospheric processes important to cirrus cloud development and maintenance. An important component of the modeling work, either as an input parameter in the case of cloud-scale models, or as output in the case of meso and larger scale models, is the large scale forcing of the cloud system. By forcing we mean the synoptic scale vertical motions and moisture budget that initially send air parcels ascending and supply the water vapor to allow condensation during ascent. Defining this forcing from the synoptic scale to the cloud scale is one of the stated scientific objectives of the FIRE program. From the standpoint of model validation, it is also necessary that the vertical motions and large scale moisture budget of the case studies be derived from observations. It is considered important that the models used to simulate the observed cloud fields begin with the correct dynamics and that the dynamics be in the right place for the right reasons.

Describing Ecosystem Complexity through Integrated Catchment Modeling

NASA Astrophysics Data System (ADS)

Shope, C. L.; Tenhunen, J. D.; Peiffer, S.

2011-12-01

Land use and climate change have been implicated in reduced ecosystem services (ie: high quality water yield, biodiversity, and agricultural yield. The prediction of ecosystem services expected under future land use decisions and changing climate conditions has become increasingly important. Complex policy and management decisions require the integration of physical, economic, and social data over several scales to assess effects on water resources and ecology. Field-based meteorology, hydrology, soil physics, plant production, solute and sediment transport, economic, and social behavior data were measured in a South Korean catchment. A variety of models are being used to simulate plot and field scale experiments within the catchment. Results from each of the local-scale models provide identification of sensitive, local-scale parameters which are then used as inputs into a large-scale watershed model. We used the spatially distributed SWAT model to synthesize the experimental field data throughout the catchment. The approach of our study was that the range in local-scale model parameter results can be used to define the sensitivity and uncertainty in the large-scale watershed model. Further, this example shows how research can be structured for scientific results describing complex ecosystems and landscapes where cross-disciplinary linkages benefit the end result. The field-based and modeling framework described is being used to develop scenarios to examine spatial and temporal changes in land use practices and climatic effects on water quantity, water quality, and sediment transport. Development of accurate modeling scenarios requires understanding the social relationship between individual and policy driven land management practices and the value of sustainable resources to all shareholders.

Science curiosity in learning environments: developing an attitudinal scale for research in schools, homes, museums, and the community

NASA Astrophysics Data System (ADS)

Weible, Jennifer L.; Toomey Zimmerman, Heather

2016-05-01

Although curiosity is considered an integral aspect of science learning, researchers have debated how to define, measure, and support its development in individuals. Prior measures of curiosity include questionnaire type scales (primarily for adults) and behavioral measures. To address the need to measure scientific curiosity, the Science Curiosity in Learning Environments (SCILE) scale was created and validated as a 12-item scale to measure scientific curiosity in youth. The scale was developed through (a) adapting the language of the Curiosity and Exploration Inventory-II [Kashdan, T. B., Gallagher, M. W., Silvia, P. J., Winterstein, B. P., Breen, W. E., Terhar, D., & Steger, M. F. (2009). The curiosity and exploration inventory-II: Development, factor structure, and psychometrics. Journal of Research in Personality, 43(6), 987-998] for youth and (b) crafting new items based on scientific practices drawn from U.S. science standards documents. We administered a preliminary set of 30 items to 663 youth ages 8-18 in the U.S.A. Exploratory and confirmatory factor analysis resulted in a three-factor model: stretching, embracing, and science practices. The findings indicate that the SCILE scale is a valid measure of youth's scientific curiosity for boys and girls as well as elementary, middle school, and high school learners.

XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem: Mid-year report FY17 Q2

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

Moreland, Kenneth D.; Pugmire, David; Rogers, David

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressingmore » four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.« less

XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem: Year-end report FY17.

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

Moreland, Kenneth D.; Pugmire, David; Rogers, David

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressingmore » four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.« less

XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem. Mid-year report FY16 Q2

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

Moreland, Kenneth D.; Sewell, Christopher; Childs, Hank

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressingmore » four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.« less

XVIS: Visualization for the Extreme-Scale Scientific-Computation Ecosystem Final Scientific/Technical Report

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

Geveci, Berk; Maynard, Robert

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. The XVis project brought together collaborators from predominant DOE projects for visualization on accelerators and combining their respectivemore » features into a new visualization toolkit called VTK-m.« less

XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem: Year-end report FY15 Q4.

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

Moreland, Kenneth D.; Sewell, Christopher; Childs, Hank

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressingmore » four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.« less

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

Shamis, Pavel; Graham, Richard L; Gorentla Venkata, Manjunath

The scalability and performance of collective communication operations limit the scalability and performance of many scientific applications. This paper presents two new blocking and nonblocking Broadcast algorithms for communicators with arbitrary communication topology, and studies their performance. These algorithms benefit from increased concurrency and a reduced memory footprint, making them suitable for use on large-scale systems. Measuring small, medium, and large data Broadcasts on a Cray-XT5, using 24,576 MPI processes, the Cheetah algorithms outperform the native MPI on that system by 51%, 69%, and 9%, respectively, at the same process count. These results demonstrate an algorithmic approach to the implementationmore » of the important class of collective communications, which is high performing, scalable, and also uses resources in a scalable manner.« less

Learning biology through connecting mathematics to scientific mechanisms: Student outcomes and teacher supports

NASA Astrophysics Data System (ADS)

Schuchardt, Anita

Integrating mathematics into science classrooms has been part of the conversation in science education for a long time. However, studies on student learning after incorporating mathematics in to the science classroom have shown mixed results. Understanding the mixed effects of including mathematics in science has been hindered by a historical focus on characteristics of integration tangential to student learning (e.g., shared elements, extent of integration). A new framework is presented emphasizing the epistemic role of mathematics in science. An epistemic role of mathematics missing from the current literature is identified: use of mathematics to represent scientific mechanisms, Mechanism Connected Mathematics (MCM). Building on prior theoretical work, it is proposed that having students develop mathematical equations that represent scientific mechanisms could elevate their conceptual understanding and quantitative problem solving. Following design and implementation of an MCM unit in inheritance, a large-scale quantitative analysis of pre and post implementation test results showed MCM students, compared to traditionally instructed students) had significantly greater gains in conceptual understanding of mathematically modeled scientific mechanisms, and their ability to solve complex quantitative problems. To gain insight into the mechanism behind the gain in quantitative problem solving, a small-scale qualitative study was conducted of two contrasting groups: 1) within-MCM instruction: competent versus struggling problem solvers, and 2) within-competent problem solvers: MCM instructed versus traditionally instructed. Competent MCM students tended to connect their mathematical inscriptions to the scientific phenomenon and to switch between mathematical and scientifically productive approaches during problem solving in potentially productive ways. The other two groups did not. To address concerns about teacher capacity presenting barriers to scalability of MCM approaches, the types and amount of teacher support needed to achieve these types of student learning gains were investigated. In the context of providing teachers with access to educative materials, students achieved learning gains in both areas in the absence of face-to-face teacher professional development. However, maximal student learning gains required the investment of face-to-face professional development. This finding can govern distribution of scarce resources, but does not preclude implementation of MCM instruction even where resource availability does not allow for face-to-face professional development.

Psychometric Properties of the Scientific Inquiry Scale

ERIC Educational Resources Information Center

Ossa-Cornejo, Carlos; Díaz-Mujica, Alejandro; Aedo-Saravia, Jaime; Merino-Escobar, Jose M.; Bustos-Navarrete, Claudio

2017-01-01

Introduction: There are a few methods to study inquiry's abilities in Chile, despite its importance in science education. This study analyzes the psychometric properties of a Scientific Inquiry Scale in pedagogy students of two Chilean universities. Method: The study uses an instrumental design with 325 students from 3 pedagogy majors. As a…

Significant enhancement of magnetoresistance with the reduction of particle size in nanometer scale

PubMed Central

Das, Kalipada; Dasgupta, P.; Poddar, A.; Das, I.

2016-01-01

The Physics of materials with large magnetoresistance (MR), defined as the percentage change of electrical resistance with the application of external magnetic field, has been an active field of research for quite some times. In addition to the fundamental interest, large MR has widespread application that includes the field of magnetic field sensor technology. New materials with large MR is interesting. However it is more appealing to vast scientific community if a method describe to achieve many fold enhancement of MR of already known materials. Our study on several manganite samples [La1−xCaxMnO3 (x = 0.52, 0.54, 0.55)] illustrates the method of significant enhancement of MR with the reduction of the particle size in nanometer scale. Our experimentally observed results are explained by considering model consisted of a charge ordered antiferromagnetic core and a shell having short range ferromagnetic correlation between the uncompensated surface spins in nanoscale regime. The ferromagnetic fractions obtained theoretically in the nanoparticles has been shown to be in the good agreement with the experimental results. The method of several orders of magnitude improvement of the magnetoresistive property will have enormous potential for magnetic field sensor technology. PMID:26837285

Inferring cortical function in the mouse visual system through large-scale systems neuroscience.

PubMed

Hawrylycz, Michael; Anastassiou, Costas; Arkhipov, Anton; Berg, Jim; Buice, Michael; Cain, Nicholas; Gouwens, Nathan W; Gratiy, Sergey; Iyer, Ramakrishnan; Lee, Jung Hoon; Mihalas, Stefan; Mitelut, Catalin; Olsen, Shawn; Reid, R Clay; Teeter, Corinne; de Vries, Saskia; Waters, Jack; Zeng, Hongkui; Koch, Christof

2016-07-05

The scientific mission of the Project MindScope is to understand neocortex, the part of the mammalian brain that gives rise to perception, memory, intelligence, and consciousness. We seek to quantitatively evaluate the hypothesis that neocortex is a relatively homogeneous tissue, with smaller functional modules that perform a common computational function replicated across regions. We here focus on the mouse as a mammalian model organism with genetics, physiology, and behavior that can be readily studied and manipulated in the laboratory. We seek to describe the operation of cortical circuitry at the computational level by comprehensively cataloging and characterizing its cellular building blocks along with their dynamics and their cell type-specific connectivities. The project is also building large-scale experimental platforms (i.e., brain observatories) to record the activity of large populations of cortical neurons in behaving mice subject to visual stimuli. A primary goal is to understand the series of operations from visual input in the retina to behavior by observing and modeling the physical transformations of signals in the corticothalamic system. We here focus on the contribution that computer modeling and theory make to this long-term effort.

Demonstration of Hadoop-GIS: A Spatial Data Warehousing System Over MapReduce.

PubMed

Aji, Ablimit; Sun, Xiling; Vo, Hoang; Liu, Qioaling; Lee, Rubao; Zhang, Xiaodong; Saltz, Joel; Wang, Fusheng

2013-11-01

The proliferation of GPS-enabled devices, and the rapid improvement of scientific instruments have resulted in massive amounts of spatial data in the last decade. Support of high performance spatial queries on large volumes data has become increasingly important in numerous fields, which requires a scalable and efficient spatial data warehousing solution as existing approaches exhibit scalability limitations and efficiency bottlenecks for large scale spatial applications. In this demonstration, we present Hadoop-GIS - a scalable and high performance spatial query system over MapReduce. Hadoop-GIS provides an efficient spatial query engine to process spatial queries, data and space based partitioning, and query pipelines that parallelize queries implicitly on MapReduce. Hadoop-GIS also provides an expressive, SQL-like spatial query language for workload specification. We will demonstrate how spatial queries are expressed in spatially extended SQL queries, and submitted through a command line/web interface for execution. Parallel to our system demonstration, we explain the system architecture and details on how queries are translated to MapReduce operators, optimized, and executed on Hadoop. In addition, we will showcase how the system can be used to support two representative real world use cases: large scale pathology analytical imaging, and geo-spatial data warehousing.

Large and local-scale influences on physical and chemical characteristics of coastal waters of Western Europe during winter

NASA Astrophysics Data System (ADS)

Tréguer, Paul; Goberville, Eric; Barrier, Nicolas; L'Helguen, Stéphane; Morin, Pascal; Bozec, Yann; Rimmelin-Maury, Peggy; Czamanski, Marie; Grossteffan, Emilie; Cariou, Thierry; Répécaud, Michel; Quéméner, Loic

2014-11-01

There is now a strong scientific consensus that coastal marine systems of Western Europe are highly sensitive to the combined effects of natural climate variability and anthropogenic climate change. However, it still remains challenging to assess the spatial and temporal scales at which climate influence operates. While large-scale hydro-climatic indices, such as the North Atlantic Oscillation (NAO) or the East Atlantic Pattern (EAP) and the weather regimes such as the Atlantic Ridge (AR), are known to be relevant predictors of physical processes, changes in coastal waters can also be related to local hydro-meteorological and geochemical forcing. Here, we study the temporal variability of physical and chemical characteristics of coastal waters located at about 48°N over the period 1998-2013 using (1) sea surface temperature, (2) sea surface salinity and (3) nutrient concentration observations for two coastal sites located at the outlet of the Bay of Brest and off Roscoff, (4) river discharges of the major tributaries close to these two sites and (5) regional and local precipitation data over the region of interest. Focusing on the winter months, we characterize the physical and chemical variability of these coastal waters and document changes in both precipitation and river runoffs. Our study reveals that variability in coastal waters is connected to the large-scale North Atlantic atmospheric circulation but is also partly explained by local river influences. Indeed, while the NAO is strongly related to changes in sea surface temperature at the Brest and Roscoff sites, the EAP and the AR have a major influence on precipitations, which in turn modulate river discharges that impact sea surface salinity at the scale of the two coastal stations.

Optimization study for the experimental configuration of CMB-S4

NASA Astrophysics Data System (ADS)

Barron, Darcy; Chinone, Yuji; Kusaka, Akito; Borril, Julian; Errard, Josquin; Feeney, Stephen; Ferraro, Simone; Keskitalo, Reijo; Lee, Adrian T.; Roe, Natalie A.; Sherwin, Blake D.; Suzuki, Aritoki

2018-02-01

The CMB Stage 4 (CMB-S4) experiment is a next-generation, ground-based experiment that will measure the cosmic microwave background (CMB) polarization to unprecedented accuracy, probing the signature of inflation, the nature of cosmic neutrinos, relativistic thermal relics in the early universe, and the evolution of the universe. CMB-S4 will consist of O(500,000) photon-noise-limited detectors that cover a wide range of angular scales in order to probe the cosmological signatures from both the early and late universe. It will measure a wide range of microwave frequencies to cleanly separate the CMB signals from galactic and extra-galactic foregrounds. To advance the progress towards designing the instrument for CMB-S4, we have established a framework to optimize the instrumental configuration to maximize its scientific output. The framework combines cost and instrumental models with a cosmology forecasting tool, and evaluates the scientific sensitivity as a function of various instrumental parameters. The cost model also allows us to perform the analysis under a fixed-cost constraint, optimizing for the scientific output of the experiment given finite resources. In this paper, we report our first results from this framework, using simplified instrumental and cost models. We have primarily studied two classes of instrumental configurations: arrays of large-aperture telescopes with diameters ranging from 2–10 m, and hybrid arrays that combine small-aperture telescopes (0.5-m diameter) with large-aperture telescopes. We explore performance as a function of telescope aperture size, distribution of the detectors into different microwave frequencies, survey strategy and survey area, low-frequency noise performance, and balance between small and large aperture telescopes for hybrid configurations. Both types of configurations must cover both large (~ degree) and small (~ arcmin) angular scales, and the performance depends on assumptions for performance vs. angular scale. The configurations with large-aperture telescopes have a shallow optimum around 4–6 m in aperture diameter, assuming that large telescopes can achieve good performance for low-frequency noise. We explore some of the uncertainties of the instrumental model and cost parameters, and we find that the optimum has a weak dependence on these parameters. The hybrid configuration shows an even broader optimum, spanning a range of 4–10 m in aperture for the large telescopes. We also present two strawperson configurations as an outcome of this optimization study, and we discuss some ideas for improving our simple cost and instrumental models used here. There are several areas of this analysis that deserve further improvement. In our forecasting framework, we adopt a simple two-component foreground model with spatially varying power-law spectral indices. We estimate de-lensing performance statistically and ignore non-idealities such as anisotropic mode coverage, boundary effect, and possible foreground residual. Instrumental systematics, which is not accounted for in our analyses, may also influence the conceptual design. Further study of the instrumental and cost models will be one of the main areas of study by the entire CMB-S4 community. We hope that our framework will be useful for estimating the influence of these improvements in the future, and we will incorporate them in order to further improve the optimization.

The SPHEREx All-Sky Spectral Survey

NASA Astrophysics Data System (ADS)

Bock, James; SPHEREx Science Team

2018-01-01

SPHEREx, a mission in NASA's Medium Explorer (MIDEX) program that was selected for Phase A in August 2017, is an all-sky survey satellite designed to address all three science goals in NASA's astrophysics division, with a single instrument, a wide-field spectral imager. SPHEREx will probe the physics of inflation by measuring non-Gaussianity by studying large-scale structure, surveying a large cosmological volume at low redshifts, complementing high-z surveys optimized to constrain dark energy. The origin of water and biogenic molecules will be investigated in all phases of planetary system formation - from molecular clouds to young stellar systems with protoplanetary disks - by measuring ice absorption spectra. We will chart the origin and history of galaxy formation through a deep survey mapping large-scale spatial power in two deep fields located near the ecliptic poles. Following in the tradition of all-sky missions such as IRAS, COBE and WISE, SPHEREx will be the first all-sky near-infrared spectral survey. SPHEREx will create spectra (0.75 – 4.2 um at R = 41; and 4.2 – 5 um at R = 135) with high sensitivity making background-limited observations using a passively-cooled telescope with a wide field-of-view for large mapping speed. During its two-year mission, SPHEREx will produce four complete all-sky maps that will serve as a rich archive for the astronomy community. With over a billion detected galaxies, hundreds of millions of high-quality stellar and galactic spectra, and over a million ice absorption spectra, the archive will enable diverse scientific investigations including studies of young stellar systems, brown dwarfs, high-redshift quasars, galaxy clusters, the interstellar medium, asteroids and comets. All aspects of the instrument and spacecraft have high heritage. SPHEREx requires no new technologies and carries large technical and resource margins on every aspect of the design. SPHEREx is a partnership between Caltech and JPL, following the successful management structure of the NuSTAR and GALEX missions. The spacecraft will be supplied by Ball Aerospace. The Korea Astronomy and Space Science Institute will contribute test hardware and scientific analysis.

Going wild: what a global small-animal tracking system could do for experimental biologists.

PubMed

Wikelski, Martin; Kays, Roland W; Kasdin, N Jeremy; Thorup, Kasper; Smith, James A; Swenson, George W

2007-01-01

Tracking animals over large temporal and spatial scales has revealed invaluable and spectacular biological information, particularly when the paths and fates of individuals can be monitored on a global scale. However, only large animals (greater than approximately 300 g) currently can be followed globally because of power and size constraints on the tracking devices. And yet the vast majority of animals is small. Tracking small animals is important because they are often part of evolutionary and ecological experiments, they provide important ecosystem services and they are of conservation concern or pose harm to human health. Here, we propose a small-animal satellite tracking system that would enable the global monitoring of animals down to the size of the smallest birds, mammals (bats), marine life and eventually large insects. To create the scientific framework necessary for such a global project, we formed the ICARUS initiative (www.IcarusInitiative.org), the International Cooperation for Animal Research Using Space. ICARUS also highlights how small-animal tracking could address some of the ;Grand Challenges in Environmental Sciences' identified by the US National Academy of Sciences, such as the spread of infectious diseases or the relationship between biological diversity and ecosystem functioning. Small-animal tracking would allow the quantitative assessment of dispersal and migration in natural populations and thus help solve enigmas regarding population dynamics, extinctions and invasions. Experimental biologists may find a global small-animal tracking system helpful in testing, validating and expanding laboratory-derived discoveries in wild, natural populations. We suggest that the relatively modest investment into a global small-animal tracking system will pay off by providing unprecedented insights into both basic and applied nature. Tracking small animals over large spatial and temporal scales could prove to be one of the most powerful techniques of the early 21st century, offering potential solutions to a wide range of biological and societal questions that date back two millennia to the Greek philosopher Aristotle's enigma about songbird migration. Several of the more recent Grand Challenges in Environmental Sciences, such as the regulation and functional consequences of biological diversity or the surveillance of the population ecology of zoonotic hosts, pathogens or vectors, could also be addressed by a global small-animal tracking system. Our discussion is intended to contribute to an emerging groundswell of scientific support to make such a new technological system happen.

Opal web services for biomedical applications.

PubMed

Ren, Jingyuan; Williams, Nadya; Clementi, Luca; Krishnan, Sriram; Li, Wilfred W

2010-07-01

Biomedical applications have become increasingly complex, and they often require large-scale high-performance computing resources with a large number of processors and memory. The complexity of application deployment and the advances in cluster, grid and cloud computing require new modes of support for biomedical research. Scientific Software as a Service (sSaaS) enables scalable and transparent access to biomedical applications through simple standards-based Web interfaces. Towards this end, we built a production web server (http://ws.nbcr.net) in August 2007 to support the bioinformatics application called MEME. The server has grown since to include docking analysis with AutoDock and AutoDock Vina, electrostatic calculations using PDB2PQR and APBS, and off-target analysis using SMAP. All the applications on the servers are powered by Opal, a toolkit that allows users to wrap scientific applications easily as web services without any modification to the scientific codes, by writing simple XML configuration files. Opal allows both web forms-based access and programmatic access of all our applications. The Opal toolkit currently supports SOAP-based Web service access to a number of popular applications from the National Biomedical Computation Resource (NBCR) and affiliated collaborative and service projects. In addition, Opal's programmatic access capability allows our applications to be accessed through many workflow tools, including Vision, Kepler, Nimrod/K and VisTrails. From mid-August 2007 to the end of 2009, we have successfully executed 239,814 jobs. The number of successfully executed jobs more than doubled from 205 to 411 per day between 2008 and 2009. The Opal-enabled service model is useful for a wide range of applications. It provides for interoperation with other applications with Web Service interfaces, and allows application developers to focus on the scientific tool and workflow development. Web server availability: http://ws.nbcr.net.

Learning Physics-based Models in Hydrology under the Framework of Generative Adversarial Networks

NASA Astrophysics Data System (ADS)

Karpatne, A.; Kumar, V.

2017-12-01

Generative adversarial networks (GANs), that have been highly successful in a number of applications involving large volumes of labeled and unlabeled data such as computer vision, offer huge potential for modeling the dynamics of physical processes that have been traditionally studied using simulations of physics-based models. While conventional physics-based models use labeled samples of input/output variables for model calibration (estimating the right parametric forms of relationships between variables) or data assimilation (identifying the most likely sequence of system states in dynamical systems), there is a greater opportunity to explore the full power of machine learning (ML) methods (e.g, GANs) for studying physical processes currently suffering from large knowledge gaps, e.g. ground-water flow. However, success in this endeavor requires a principled way of combining the strengths of ML methods with physics-based numerical models that are founded on a wealth of scientific knowledge. This is especially important in scientific domains like hydrology where the number of data samples is small (relative to Internet-scale applications such as image recognition where machine learning methods has found great success), and the physical relationships are complex (high-dimensional) and non-stationary. We will present a series of methods for guiding the learning of GANs using physics-based models, e.g., by using the outputs of physics-based models as input data to the generator-learner framework, and by using physics-based models as generators trained using validation data in the adversarial learning framework. These methods are being developed under the broad paradigm of theory-guided data science that we are developing to integrate scientific knowledge with data science methods for accelerating scientific discovery.

Data Transparency in Privately Funded Scientific Research

NASA Astrophysics Data System (ADS)

Brewer, P. G.

2016-12-01

Research investigations funded by the Gulf of Mexico Research Initiative (GoMRI) have resulted in a large pulse of scientific data produced by studies ranging across the research goals of the program. These studies have produced datasets from laboratory, field, and modeling activities describing phenomenon ranging from microscopic fluid dynamics to large-scale ocean currents, bacteria to marine mammals, and detailed field observations to synoptic mapping. One of GoMRI's central tenets is to ensure that all data are preserved and made publicly available. Thus, GoMRI formed the Gulf of Mexico Research Initiative Data and Information Cooperative (GRIIDC) with the mission to ensure a data and information legacy that promotes continual scientific discovery and public awareness of the Gulf of Mexico ecosystem. The GoMRI Research Board commitment to open data is exemplified in GoMRI's data program policies and management. The Research Board established a policy that research data must be publically available as soon as possible and no later than one year following collection or at the time of publication. GRIIDC's data specialists, and computer system experts along with a team of researchers funded by GOMRI and GoMRI Research Board members developed a data management system and process for storing and distributing all of the scientific data generated by the GoMRI researchers. Researcher compliance with the data policy is a requirement for annual funding increments, No Cost Extensions, and eligibility for future funding. Since data compliance is an important element of grant performance compliance with GOMRI data policies data are actively tracked and reported to the Board. This initiative comprises an essential component of GoMRI's research independence and legacy.

The NSF ITR Project: Framework for the National Virtual Observatory

NASA Astrophysics Data System (ADS)

Szalay, A. S.; Williams, R. D.; NVO Collaboration

2002-05-01

Technological advances in telescope and instrument design during the last ten years, coupled with the exponential increase in computer and communications capability, have caused a dramatic and irreversible change in the character of astronomical research. Large-scale surveys of the sky from space and ground are being initiated at wavelengths from radio to x-ray, thereby generating vast amounts of high quality irreplaceable data. The potential for scientific discovery afforded by these new surveys is enormous. Entirely new and unexpected scientific results of major significance will emerge from the combined use of the resulting datasets, science that would not be possible from such sets used singly. However, their large size and complexity require tools and structures to discover the complex phenomena encoded within them. We plan to build the NVO framework both through coordinating diverse efforts already in existence and providing a focus for the development of capabilities that do not yet exist. The NVO we envisage will act as an enabling and coordinating entity to foster the development of further tools, protocols, and collaborations necessary to realize the full scientific potential of large astronomical datasets in the coming decade. The NVO must be able to change and respond to the rapidly evolving world of IT technology. In spite of its underlying complex software, the NVO should be no harder to use for the average astronomer, than today's brick-and-mortar observatories and telescopes. Development of these capabilities will require close interaction and collaboration with the information technology community and other disciplines facing similar challenges. We need to ensure that the tools that we need exist or are built, but we do not duplicate efforts, and rely on relevant experience of others.

George Gamow: Scientific Amateur and Polymath

NASA Astrophysics Data System (ADS)

Harper, Eamon

George Gamow (1904-1968) was among the first of the many brilliant scientists who forsook Europe for the United States in the early 1930s. Although most were fleeing the fascist imperium of Hitler and Mussolini, Gamow was one of a few who managed to escape the burgeoning despotism of Stalin in the Soviet Union. His early application of quantum mechanics to the atomic nucleus and his subsequent insight into the role played by the physics of the atom and its nucleus in stars, galaxies, and the universe identifies him as a scientist of unusual genius. Gamow displayed a boisterous, infectious - almost Rutherfordian - interest in all aspects of pure science. His interests were broad and his industry prodigious. His scientific output covered areas as diverse as nuclear physics, astrophysics, cosmology, biological genetics, and the fascinating question of the relationship of the large-scale structure and development of the universe to the properties of elementary particles and fields. He also was an immensely imaginative and prolific author of popular expositions on scientific subjects. One who is as well-known for his authorship of the Mr. Tompkins series of science popularizations as for his contributions to the development of the physical consequences of the big-bang theory of the expanding universe and the prediction of the cosmic background radiation must be unique in the scientific pantheon.

MODIS algorithm development and data visualization using ACTS

NASA Technical Reports Server (NTRS)

Abbott, Mark R.

1992-01-01

The study of the Earth as a system will require the merger of scientific and data resources on a much larger scale than has been done in the past. New methods of scientific research, particularly in the development of geographically dispersed, interdisciplinary teams, are necessary if we are to understand the complexity of the Earth system. Even the planned satellite missions themselves, such as the Earth Observing System, will require much more interaction between researchers and engineers if they are to produce scientifically useful data products. A key component in these activities is the development of flexible, high bandwidth data networks that can be used to move large amounts of data as well as allow researchers to communicate in new ways, such as through video. The capabilities of the Advanced Communications Technology Satellite (ACTS) will allow the development of such networks. The Pathfinder global AVHRR data set and the upcoming SeaWiFS Earthprobe mission would serve as a testbed in which to develop the tools to share data and information among geographically distributed researchers. Our goal is to develop a 'Distributed Research Environment' that can be used as a model for scientific collaboration in the EOS era. The challenge is to unite the advances in telecommunications with the parallel advances in computing and networking.

DEXTER: Disease-Expression Relation Extraction from Text.

PubMed

Gupta, Samir; Dingerdissen, Hayley; Ross, Karen E; Hu, Yu; Wu, Cathy H; Mazumder, Raja; Vijay-Shanker, K

2018-01-01

Gene expression levels affect biological processes and play a key role in many diseases. Characterizing expression profiles is useful for clinical research, and diagnostics and prognostics of diseases. There are currently several high-quality databases that capture gene expression information, obtained mostly from large-scale studies, such as microarray and next-generation sequencing technologies, in the context of disease. The scientific literature is another rich source of information on gene expression-disease relationships that not only have been captured from large-scale studies but have also been observed in thousands of small-scale studies. Expression information obtained from literature through manual curation can extend expression databases. While many of the existing databases include information from literature, they are limited by the time-consuming nature of manual curation and have difficulty keeping up with the explosion of publications in the biomedical field. In this work, we describe an automated text-mining tool, Disease-Expression Relation Extraction from Text (DEXTER) to extract information from literature on gene and microRNA expression in the context of disease. One of the motivations in developing DEXTER was to extend the BioXpress database, a cancer-focused gene expression database that includes data derived from large-scale experiments and manual curation of publications. The literature-based portion of BioXpress lags behind significantly compared to expression information obtained from large-scale studies and can benefit from our text-mined results. We have conducted two different evaluations to measure the accuracy of our text-mining tool and achieved average F-scores of 88.51 and 81.81% for the two evaluations, respectively. Also, to demonstrate the ability to extract rich expression information in different disease-related scenarios, we used DEXTER to extract information on differential expression information for 2024 genes in lung cancer, 115 glycosyltransferases in 62 cancers and 826 microRNA in 171 cancers. All extractions using DEXTER are integrated in the literature-based portion of BioXpress.Database URL: http://biotm.cis.udel.edu/DEXTER.