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All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Sao Paulo Lightning Mapping Array (SP-LMA): Network Assessment and Analyses for Intercomparison Studies and GOES-R Proxy Activities

A 12 station Lightning Mapping Array (LMA) network was deployed during October 2011 in the vicinity of Sao Paulo, Brazil (SP-LMA) to contribute total lightning measurements to an international field campaign [CHUVA - Cloud processes of tHe main precipitation systems in Brazil: A contribUtion to cloud resolVing modeling and to the GPM (GlobAl Precipitation Measurement)]. The SP-LMA was operational from November 2011 through March 2012 during the Vale do Paraiba campaign. Sensor spacing was on the order of 15-30 km, with a network diameter on the order of 40-50km. The SP-LMA provides good 3-D lightning mapping out to 150 km from the network center, with 2-D coverage considerably farther. In addition to supporting CHUVA science/mission objectives, the SP-LMA is supporting the generation of unique proxy data for the Geostationary Lightning Mapper (GLM) and Advanced Baseline Imager (ABI), on NOAA's Geostationary Operational Environmental Satellite-R (GOES-R: scheduled for a 2015 launch). These proxy data will be used to develop and validate operational algorithms so that they will be ready to use on "day1" following the GOES-R launch. As the CHUVA Vale do Paraiba campaign opportunity was formulated, a broad community-based interest developed for a comprehensive Lightning Location System (LLS) intercomparison and assessment study, leading to the participation and/or deployment of eight other ground-based networks and the space-based Lightning Imaging Sensor (LIS). The SP-LMA data is being intercompared with lightning observations from other deployed lightning networks to advance our understanding of the capabilities/contributions of each of these networks toward GLM proxy and validation activities. This paper addresses the network assessment including noise reduction criteria, detection efficiency estimates, and statistical and climatological (both temporal and spatially) analyses for intercomparison studies and GOES-R proxy activities.

Bailey, J. C.↗
DOE OSTI2022

Sinclair Community College and OARnet Requirements Analysis Report

EPOC uses the Deep Dive process to discuss and analyze current and planned science, research, or education activities and the anticipated data output of a particular use case, site, or project to help inform the strategic planning of a campus or regional networking environment. This includes understanding future needs related to network operations, network capacity upgrades, and other technological service investments. A Deep Dive comprehensively surveys major research stakeholders’ plans and processes in order to investigate data management requirements over the next 5–10 years. Between October 2021 and March 2022 staff members from the Engagement and Performance Operations Center (EPOC) met with researchers and staff from Sinclair Community College (SCC) and OARnet with the purpose of performing a Deep Dive into scientific and research drivers. The goal of this activity was to help characterize the requirements for a number of campus use cases, and to enable cyberinfrastructure support staff to better understand the needs of the researchers within the community.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2026

Survey of Deep Learning and Physics-Based Approaches in Computational Wave Imaging

Computational wave imaging (CWI) extracts hidden structure and physical properties of a volume of material by analyzing wave signals that traverse that volume. Applications include seismic exploration of the Earth’s subsurface, acoustic imaging and nondestructive testing (NDT) in material science, and ultrasound computed tomography (USCT) in medicine. Current approaches for solving CWI problems can be divided into two categories: those rooted in traditional physics and those based on deep learning. Physics-based methods stand out for their ability to provide high-resolution and quantitatively accurate estimates of acoustic properties within the medium. However, they can be computationally intensive and are susceptible to ill-posedness and nonconvexity typical of CWI problems. Machine learning (ML)-based computational methods have recently emerged, offering a different perspective to address these challenges. Diverse scientific communities have independently pursued the integration of deep learning in CWI. This review discusses how contemporary scientific ML techniques, and deep neural networks in particular, have been developed to enhance and integrate with traditional physics-based methods for solving CWI problems. We present a structured framework that consolidates existing research spanning multiple domains, including computational imaging, wave physics, and data science. This study concludes with important lessons learned from existing ML-based methods and identifies technical hurdles and emerging trends through a systematic analysis of the extensive literature on this topic.

42 ENGINEERING↗
DOE OSTI2022

Stardust Network Measurement Components (esnet-stardust-components) v1

This software contains a set of components that allow us to measure and analyze the use and performance of computer networks using existing off the shelf Open Source components organized into a scalable and extensible system. The components were developed for and used within ESnet's Stardust Measurement Environment. The components are used to collect, process and display network measurement data in an architecture that employs a combination of Elasticsearch, Logstash and Grafana. The advantage of this approach is we can tailor system behavior to our analytical needs and expand its capability with new types of network measurement without waiting for a commercial vendor to support our fairly niche use cases. Additionally we have existing collaborations within our community that came about from prior research efforts that will benefit from the release of this software so that others can also contribute features.

Balas, Edward↗
NASA NTRS1979

Central atlantic regional ecological test site: A prototype regional environmental information system, volume 1

The Central Atlantic Regional Ecological Test Site (CARETS) project was a demonstration project for introducing data from Landsat and high-altitude aircraft sensors into regional land planning and management. This report summarizes the CARETS project results and describes its output of maps, reports, computer tapes, and other products. CARETS used a geographic information system model under which land use maps were prepared from sensor data, then digitized, processed, and linked to other environmental and social data sets, and to environmental consequences such as air pollution, stream runoff, local climatic factors, and coastal erosion. Landsat data showed the test region in 1972 to be nine percent urban and built-up land, 38 percent agriculture, 50 percent forest, three percent nonforested wetlands, and less than one percent barren land, exclusive of water-covered areas. User surveys, conferences, and workshops involving 65 agencies facilitated widespread distribution of data products and produced evaluations concerning their usefulness. We found a heterogeneous user community with diverse information needs largely preferring aerial photographs rather than satellite multispectral scanner data. Among project recommendations are establishment of a network of regional land resource information centers, working toward improved compatibility of Federal, State and local information programs supportive of land use decisions.

Land use↗
NASA NTRS1992

The EXOSAT database and archive

The EXOSAT database provides on-line access to the results and data products (spectra, images, and lightcurves) from the EXOSAT mission as well as access to data and logs from a number of other missions (such as EINSTEIN, COS-B, ROSAT, and IRAS). In addition, a number of familiar optical, infrared, and x ray catalogs, including the Hubble Space Telescope (HST) guide star catalog are available. The complete database is located at the EXOSAT observatory at ESTEC in the Netherlands and is accessible remotely via a captive account. The database management system was specifically developed to efficiently access the database and to allow the user to perform statistical studies on large samples of astronomical objects as well as to retrieve scientific and bibliographic information on single sources. The system was designed to be mission independent and includes timing, image processing, and spectral analysis packages as well as software to allow the easy transfer of analysis results and products to the user's own institute. The archive at ESTEC comprises a subset of the EXOSAT observations, stored on magnetic tape. Observations of particular interest were copied in compressed format to an optical jukebox, allowing users to retrieve and analyze selected raw data entirely from their terminals. Such analysis may be necessary if the user's needs are not accommodated by the products contained in the database (in terms of time resolution, spectral range, and the finesse of the background subtraction, for instance). Long-term archiving of the full final observation data is taking place at ESRIN in Italy as part of the ESIS program, again using optical media, and ESRIN have now assumed responsibility for distributing the data to the community. Tests showed that raw observational data (typically several tens of megabytes for a single target) can be transferred via the existing networks in reasonable time.

Reynolds, A. P.↗
NASA NTRS2012

Tropical Rainfall Measuring Mission (TRMM) Precipitation Data and Services for Research and Applications

Precipitation is a critical component of the Earth's hydrological cycle. Launched on 27 November 1997, TRMM is a joint U.S.-Japan satellite mission to provide the first detailed and comprehensive data set of the four-dimensional distribution of rainfall and latent heating over vastly under-sampled tropical and subtropical oceans and continents (40 S - 40 N). Over the past 14 years, TRMM has been a major data source for meteorological, hydrological and other research and application activities around the world. The purpose of this short article is to inform that the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) provides TRMM archive and near-real-time precipitation data sets and services for research and applications. TRMM data consist of orbital data from TRMM instruments at the sensor s resolution, gridded data at a range of spatial and temporal resolutions, subsets, ground-based instrument data, and ancillary data. Data analysis, display, and delivery are facilitated by the following services: (1) Mirador (data search and access); (2) TOVAS (TRMM Online Visualization and Analysis System); (3) OPeNDAP (Open-source Project for a Network Data Access Protocol); (4) GrADS Data Server (GDS); and (5) Open Geospatial Consortium (OGC) Web Map Service (WMS) for the GIS community. Precipitation data application services are available to support a wide variety of applications around the world. Future plans include enhanced and new services to address data related issues from the user community. Meanwhile, the GES DISC is preparing for the Global Precipitation Measurement (GPM) mission which is scheduled for launch in 2014.

Liu, Zhong↗
NASA NTRS2021

NASA Leveraging Commercial Communication Ground Stations for Small Satellites

The Space Communications and Navigation (SCaN) program at NASA has reorganized its operations portfolio into two networks: the Deep Space Network and the new Near Space Network (NSN). With this reorganization, NASA can begin transforming to 100% direct-to-Earth commercial communications services for missions in the near-Earth region. NASA’s leveraging of commercial direct-to-Earth ground stations offers several benefits for the small satellite community, including lower cost, greater coverage, and increased technology infusion. In the fall of 2020, SCaN announced their intention to rely primarily on industry-provided communications services for missions close to Earth by 2030. Commercial services are one way to infuse new technology into the ground station network without requiring an investment from NASA. Digital Video Broadcast, Satellite Second Generation (DVB-S2) is one example of a current technology. When combined with variable coding and modulation (VCM), the system automatically optimizes the data rate based on signal performance, significantly increasing total downlink data volume without an increase in the spacecraft effective isotropic radiated power (EIRP). There are several commercial service providers, including Amazon Web Service (AWS) Ground Station (AGS) and the KSATLITE ground stations that support SmallSat missions using DVB-S2 waveforms for downlinks. This paper identifies some commercial off-the-shelf (COTS) CubeSat/SmallSat DVB-S2 X-band and Ka-band radios. Overall, NASA’s increased dependence on commercial direct-to-Earth ground stations is a significant benefit for the small satellite community.

Space Communications↗
NASA NTRSDate not supplied

SERVIR - Connecting Space to Village in Africa, Asia and the Americas

SERVIR is a joint NASA and USAID program that partners with countries and organizations to support locally led efforts to strengthen climate resilience, food and water security, forest and carbon management, and air quality. This unique program integrates NASA’s world class scientists and data with USAID’s development expertise and network of partners and relationships around the world. SERVIR harnesses the power of satellite data and science collaboration to support healthy, sustainable communities, livelihoods and environments. SERVIR’s name is derived from Latin, meaning "to serve.” We serve and partner with leading local, national, and regional institutions in Africa, Asia, and Latin America and in partnership with scientists and subject matter experts to co-develop and implement activities called “services.” Each of SERVIR’s services provide a comprehensive suite of geospatial data, software, and training materials, all of which are tailored to the unique needs of SERVIR’s end users. Each service is collaboratively designed and implemented with the help of partners and users, such as local governments and NGOs, to better support decision-making. When SERVIR plans new services, it prioritizes long-term dialogue and engagement with communities to ensure that services are sustainable, socially inclusive, and suited to local needs. SERVIR strives to make the power of Earth science more accessible and inclusive. All web tools are made publicly available to help promote greater uptake and long-term use of SERVIR’s services.

SERVIR↗
NASA NTRS2016

Navigation Architecture for a Space Mobile Network

The Tracking and Data Relay Satellite System (TDRSS) Augmentation Service for Satellites (TASS) is a proposed beacon service to provide a global, space based GPS augmentation service based on the NASA Global Differential GPS (GDGPS) System. The TASS signal will be tied to the GPS time system and usable as an additional ranging and Doppler radiometric source. Additionally, it will provide data vital to autonomous navigation in the near Earth regime, including space weather information, TDRS ephemerides, Earth Orientation Parameters (EOP), and forward commanding capability. TASS benefits include enhancing situational awareness, enabling increased autonomy, and providing near real-time command access for user platforms. As NASA Headquarters' Space Communication and Navigation Office (SCaN) begins to move away from a centralized network architecture and towards a Space Mobile Network (SMN) that allows for user initiated services, autonomous navigation will be a key part of such a system. This paper explores how a TASS beacon service enables the Space Mobile Networking paradigm, what a typical user platform would require, and provides an in-depth analysis of several navigation scenarios and operations concepts. This paper provides an overview of the TASS beacon and its role within the SMN and user community. Supporting navigation analysis is presented for two user mission scenarios: an Earth observing spacecraft in low earth orbit (LEO), and a highly elliptical spacecraft in a lunar resonance orbit. These diverse flight scenarios indicate the breadth of applicability of the TASS beacon for upcoming users within the current network architecture and in the SMN.

Data Relay↗
DOE OSTI2022

Context matters: Natural tree mortality can lead to neighbor growth release or suppression

Where competition suppresses tree growth, mortality of adjacent trees can release the surviving individuals, leading to a growth increase. However, primary forests are complicated systems, where trees interact in both competitive and facilitative ways mediated by their size, species, and the broad ecological context in which they grow. Thus, the magnitude and even direction of growth responses to the mortality of nearby trees may vary, which has implications for our understanding of community- and ecosystem-level dynamics following mortality events. Unfortunately, although many studies focus on the impacts of light availability and general crowding on tree growth, we know relatively little about the effects of naturally occurring mortality events on the growth of neighboring trees. To address this issue, we used 40 years of data from 15 permanent forest-monitoring plots in Mt Rainier old-growth forests, comparing observed to expected radial growth of individual trees following the death of their nearest neighbor. Although we found evidence of a general growth-release response, this was not universal among all trees, with small trees in particular exhibiting growth suppression (rather than release) following neighboring tree mortality. In addition to small size, growth-suppression was more likely if the dead neighbor was the same species, consistent with facilitative effects as mediated through belowground networks. At the stand level, the average growth release after nearest neighbor mortality was greatest in low-density stands with large trees, with elevation and community composition also playing a role. Decades more monitoring could reveal how long growth release (or suppression) is sustained by individual trees following neighboring mortality events, as well as potential response lags and the role of species identity in determining whether interactions with neighbors are competitive or facilitative. Nonetheless, our results suggest that although mature trees have competitive effects on their larger neighbors, they also have an important role in supporting the ingrowth of small trees. More broadly, we demonstrate that the nature of interactions between individual neighboring trees is highly context dependent.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Acidification in the U.S. Southeast: Causes, Potential Consequences and the Role of the Southeast Ocean and Coastal Acidification Network

Coastal acidification in southeastern U.S. estuaries and coastal waters is influenced by biological activity, run-off from the land, and increasing carbon dioxide in the atmosphere. Acidification can negatively impact coastal resources such as shellfish, finfish, and coral reefs, and the communities that rely on them. Organismal responses for species located in the U.S. Southeast document large negative impacts of acidification, especially in larval stages. For example, the toxicity of pesticides increases under acidified conditions and the combination of acidification and low oxygen has profoundly negative influences on genes regulating oxygen consumption. In corals, the rate of calcification decreases with acidification and processes such as wound recovery, reproduction, and recruitment are negatively impacted. Minimizing the changes in global ocean chemistry will ultimately depend on the reduction of carbon dioxide emissions, but adaptation to these changes and mitigation of the local stressors that exacerbate global acidification can be addressed locally. The evolution of our knowledge of acidification, from basic understanding of the problem to the emergence of applied research and monitoring, has been facilitated by the development of regional Coastal Acidification Networks (CANs) across the United States. This synthesis is a product of the Southeast Coastal and Ocean Acidification Network (SOCAN). SOCAN was established to better understand acidification in the coastal waters of the U.S. Southeast and to foster communication among scientists, resource managers, businesses, and governments in the region. Here we review acidification issues in the U.S. Southeast, including the regional mechanisms of acidification and their potential impacts on biological resources and coastal communities. We recommend research and monitoring priorities and discuss the role SOCAN has in advancing acidification research and mitigation of and adaptation to these changes.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1998

An Integrated Approach to Engineering Education in a Minority Community

Northeastern New Mexico epitomizes regions which are economically depressed, rural, and predominantly Hispanic. New Mexico Highlands University (NMHU), with a small student population of approximately 2800, offers a familiar environment attracting students who might otherwise not attend college. An outreach computer network of minority schools was created in northeastern New Mexico with NASA funding. Rural and urban minority schools gained electronic access to each other, to computer resources, to technical help at New Mexico Highlands University and gained access to the world via the Internet. This outreach program was initiated in the fall of 1992 in an effort to attract and to involve minority students in Engineering and the Mathematical Sciences. We installed 56 Kbs Internet connections to eight elementary schools, two middle schools, two high schools, a public library (servicing the home schooling community) and an International Baccalaureate school. For another fourteen rural schools, we provided computers and free dial-up service to servers on the New Mexico Highlands University campus.

Taylor, Bill↗
DOE OSTI2021

Ecosystems and Networks Integrated with Genes and Molecular Assemblies (ENIGMA): Component 5: Imaging Protein Conformations, Shapes & Assemblies in Solution & Administration project (Final Scientific/Technical Report, Subcontract No. 6974584)

We set ambitious goals to examine microorganism communities and measure both their chemical input and output as a read out of specific biochemical activity. These scientific goals are driving the development of sophisticated algorithms to analyze large amounts of experimental measurements made using high throughput technologies to explain and predict how the environment influences biological function at multiple scales and how the microbial systems in tum modify the environment. By examining how bacteria communities rely on symbiotic metabolic relationships for survival and reproductive success, and how these relationships consequently affect their biochemical capabilities. This was accomplished using state-of-the-art mass spectrometry-based methods, and metabolic fingerprinting approaches with a high degree of chemical specificity and sensitivity. During this period the original effort transitioned and was consolidated into what is now ENIGMA, the efforts on technology development expanded to include more untargeted metabolomics and its application to organisms on a systems level.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1994

Improved small satellite access of the space network

This report contains the results of a study performed under the sponsorship of the National Aeronautics and Space Administration (NASA) made as a grant to the Center for Space Telemetering and Telecommunication Systems at New Mexico State University. The purpose of this phase of the grant is to increase user access to the Space Network (SN) run by NASA for supplying space-to-ground communications for satellites and associated control centers. The identified need is to bring more users into the community of those accessing the SN, especially those in the small satellite class of users. The initial phase of the study concerned the potential for modifications to the standard transponder used in the SN. The results of that investigation are summarized in Section 4. As the hardware modifications were being investigated, a second option was developed, namely to consider changes to the operational mode for the small satellites. This operational concept was to use a single, fixed-pointing antenna in a spin-stabilized satellite and let the antenna pattern sweep past the Tracking and Data Relay Satellites (TDRS) in the SN. The question to be answered by this phase of the study was twofold: could enough contact time per day be made available using this simple operating mode and could the data rate be high enough to allow for sufficient data throughput to satisfy the user community using existing components. Section 2 outlines the methodology and simulation results to answer these questions. Section 3 contains a summary of an operational simulation of a simple satellite payload using these contact scenarios. The simulation is not all inclusive but shows how a payload simulation could be configured to utilize variable contact times. The answer to both of the questions desired to be answered is affirmative. By carefully choosing the correct system transmission power and antenna pattern, the system will allow support to the 50th percentile of expected systems. It is recommended that based on this initial study, further work be done to quantify the exact parameters for transmission through the space network and to optimize usage of the contact time to maximize throughput.

Horan, Stephen↗
DOE OSTI2024

Distributed Multi-GPU Community Detection on Exascale Computing Platforms

Community detection is a fundamental operation in graph mining, and by uncovering hidden structures and patterns within complex systems it helps solve fundamental problems pertaining to social networks, such as information diffusion, epidemics, and recommender systems. Scaling graph algorithms for massive networks becomes challenging on modern distributed-memory multi-GPU (Graphics Processing Unit) systems due to limitations such as irregular memory access patterns, load imbalances, higher communication-computation ratios, and cross-platform support. We present a novel algorithm HiPDPL-GPU (distributed parallel Louvain) to address these challenges. We conduct experiments involving different partitioning techniques to achieve optimized performance of HiPDPL-GPU on the two largest supercomputers: Frontier and Summit. Remarkably, HiPDPL-GPU processes a graph with 4.2 billion edges in less than 3 minutes using 1024 GPUs. Qualitatively performance of HiPDPL-GPU is similar or better compared to other state-of-the-art CPU- and GPU-based implementations. While prior GPU implementations have predominantly employed CUDA, our first-of-its-kind implementation for community detection is cross-platform, accommodating both AMD and NVIDIA GPUs.

graph algorithms, high performance comptuing↗
DOE OSTI2024

Distributed Multi-GPU Community Detection on Exascale Computing Platforms

Community detection is a fundamental operation in graph mining, and by uncovering hidden structures and patterns within complex systems it helps solve fundamental problems pertaining to social networks, such as information diffusion, epidemics, and recommender systems. Scaling graph algorithms for massive networks becomes challenging on modern distributed-memory multi-GPU (Graphics Processing Unit) systems due to limitations such as irregular memory access patterns, load imbalances, higher communication-computation ratios, and cross-platform support. We present a novel algorithm HiPDPL-GPU (Distributed Parallel Louvain) to address these challenges. We conduct experiments involving different partitioning techniques to achieve an optimized performance of HiPDPL-GPU on the two largest supercomputers: Frontier and Summit. Remarkably, HiPDPL-GPU processes a graph with 4.2 billion edges in less than 3 minutes using 1024 GPUs. Qualitatively, the performance of HiPDPL-GPU is similar or better compared to other state-of-the-art CPU- and GPU-based implementations. While prior GPU implementations have predominantly employed CUDA, our first-of-its-kind implementation for community detection is cross-platform, accommodating both AMD and NVIDIA GPUs.

Sattar, Naw Safrin↗
DOE OSTI2025

The promising role of proteomes and metabolomes in defining the single-cell landscapes of plants

The plant community has a strong track-record of RNA sequencing technology deployment, which combined with the recent advent of spatial platforms (e.g., 10x genomics), has resulted in an explosion of outstanding single cell and nuclei datasets that can be put in an in situ context within tissues (e.g., a cell atlas)1. In the genomics era, application of proteomics technologies in the plant sciences has always trailed behind that of RNA sequencing technologies, largely due to accessibility, ease-of-use and access to expertise along with depth of analysis benefits. On the other hand, the use of early analytical tools for characterizing small molecules (metabolites) from plant systems predates nucleic acid sequencing and proteomics analysis2, as the search for plant-based natural products has played a significant role in improving human health throughout history. However, the employment of proteomics and metabolomics assays for characterizing plant cell processes now remains significantly behind transcriptional approaches, even though both provide a direct functional readout of cell states and phenotypes.

Anderton, Christopher R. [BATTELLE (PACIFIC NW LAB↗