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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Overview of INLs gamma irradiation and molecular characterization capabilities for presentation at the 2020 CAES Winter Collaboration Meeting
The present disclosure provides collaborative radiofrequency identification (RFID) readers that employ code division multiple access (CDMA) encoding to simultaneously broadcast to and read responses from tags in an overlapping reading zone with improved data synchronization and read yield rates. In some embodiments, a harmonic backscattering scheme is used to enable the system to have a much higher signal-to-noise ratio (SNR) and sensitivity, while the reader CDMA protocol can be integrated with an initial TDMA polling process or alternative tag CDMA scheme.
Advanced modeling and simulation tools have a crucial role to play in accelerating fusion energy deployment as a sustainable power source. Multiphysics, high-fidelity computational tools can help understand, model, and quantify the complex interactions between materials performance, plasma and neutron exposure, and engineering processes. As a result, they accelerate the design, safety analysis, and performance evaluation of fusion systems. This webinar introduces the Fusion ENergy Integrated multiphys-X (FENIX) framework, an open-source multiphysics tool for plasma facing component modeling. FENIX leverages the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, which has been developed by the United States Department of Energy Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. FENIX couples various MOOSE capabilities such as heat transfer, thermomechanics, thermal hydraulics, electromagnetics, and plasma kinetics with the MOOSE-based applications Cardinal (neutronics) and TMAP8 (tritium transport). During the webinar, we will present FENIX and discuss how its modularity, openness, software quality assurance processes, and licensing approach supports effective collaborations, including public-private partnerships.
Presentation slides shared at a project meeting with our utility collaborator.
In this talk, we introduce NOODLES, describe it's design, use cases, and how to get started with the protocol.
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The nexus of food, energy, and water (FEW) systems is key to ensuring global sustainability in the face of climate change, population growth, and urbanization. To address FEW resources inequity among different regions and countries, transdisciplinary research networking becomes increasingly important for tackling this intractable, complex grand challenge. In contrast to interdisciplinary or multidisciplinary research, transdisciplinary research emphasizes the interactions of scientific, cognitive, and social factors from a top-down view. Intellectual and strategic integrations entail weaving scientific, socioeconomic, and political perspectives together into a new convergence model and fostering a shared vision and comparable assessment, though these goals might not be realistically achievable in the short term. This article summarizes major barriers to transdisciplinary research on FEW nexus grand challenges and possible solutions to be implemented at multiple levels of distinct social systems. Implementation of the solutions relies on not only top-down incentives of governments but also bottom-up initiatives of academic communities and individual researchers. The relevance of shared interests and visions between the research communities and the public is emphasized.
Raffaella Buonsanti and Wilson Smith are leaders of their fields considering the careful design of materials and engineering, respectively. In this backstory, they share their view of the field of electrochemical synthesis both as it is now, and in the future.
The authors are founding team members of a new effort to develop an Open Energy Outlook for the United States. The effort aims to apply best practices of policy-focused energy system modeling, ensure transparency, build a networked community, and work toward a common purpose: examining possible US energy system futures to inform energy and climate policy efforts. Individual author biographies can be found on the project website: https://openenergyoutlook.org/.
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Specialized or secondary metabolites are small molecules of biological origin, often showing potent biological activities with applications in agriculture, engineering and medicine. Usually, the biosynthesis of these natural products is governed by sets of co-regulated and physically clustered genes known as biosynthetic gene clusters (BGCs). To share information about BGCs in a standardized and machine-readable way, the Minimum Information about a Biosynthetic Gene cluster (MIBiG) data standard and repository was initiated in 2015. Since its conception, MIBiG has been regularly updated to expand data coverage and remain up to date with innovations in natural product research. Here, we describe MIBiG version 4.0, an extensive update to the data repository and the underlying data standard. In a massive community annotation effort, 267 contributors performed 8304 edits, creating 557 new entries and modifying 590 existing entries, resulting in a new total of 3059 curated entries in MIBiG. Particular attention was paid to ensuring high data quality, with automated data validation using a newly developed custom submission portal prototype, paired with a novel peer-reviewing model. MIBiG 4.0 also takes steps towards a rolling release model and a broader involvement of the scientific community. MIBiG 4.0 is accessible online at https://mibig.secondarymetabolites.org/.
Extreme weather and aging infrastructure are creating unprecedented challenges in the United States and around the globe. Many communities have suffered damages from a variety of weather-related events, such as severe weather such as hurricanes, droughts, increasing temperatures, wildfires, and storm surges. Numerous efforts exist to improve resilience to protect national security, energy and water security, economic well-being, and quality of life. As severe weather events increase in frequency and severity, many cities, states, tribes, and federal agencies are addressing the impacts through resilience planning and measures. In an effort to support communities with resilience planning, the White House Council on Environmental Quality (CEQ) initiated preparedness pilot projects designed to showcase community resilience planning in the City of Houston and the State of Colorado. This publication is the full, technical document, for the Colorado pilot project. The process is also summarized in a user-friendly web-version on NREL's website (visit www.nrel.gov/resilience-planning-roadmap) for easier access and replicability. NASA's pilot project with the City of Houston is summarized separately (visit https://toolkit.climate.gov/case-studies/climate-resilience to learn more). water security, economic well-being, and quality of life. As severe weather events increase in frequency and severity, many cities, states, tribes, and federal agencies are addressing the impacts through resilience planning and measures. In an effort to support communities with resilience planning, the White House Council on Environmental Quality (CEQ) initiated preparedness pilot projects designed to showcase community resilience planning in the City of Houston and the State of Colorado. This publication is the full, technical document, for the Colorado pilot project. The process is also summarized in a user-friendly web-version on NREL's website (visit www.nrel.gov/resilience-planning-roadmap) for easier access and replicability. NASA's pilot project with the City of Houston is summarized separately (visit https://toolkit.climate.gov/case-studies/climate-resilience to learn more).
MCNP is a general-purpose, continuous-energy, generalized-geometry, time-dependent, Monte Carlo radiation-transport code designed to track many particle types over broad ranges of energies. MCNP has the capability to track particles on unstructured polyhedral meshes that are embedded into the legacy constructive solid geometry (CSG).
Scientific research communities can be represented as heterogeneous or multidimensional networks encompassing multiple types of entities and relationships. These networks might include researchers, institutions, meetings, and publications, connected by relationships like authorship, employment, and attendance. We describe a method for efficiently and flexibly capturing, storing, and extracting information from multidimensional scientific networks using a graph database. The database structure is based on an ontology that captures allowable types of entities and relationships. This allows us to construct a variety of projections of the underlying multidimensional graph through database queries to answer specific research questions. We demonstrate this process through a study of the U.S. Biological Threat Reduction Program (BTRP), which seeks to develop Threat Reduction Networks to build and strengthen a sustainable international community of biosecurity, biosafety, and biosurveillance experts to address shared biological threat reduction challenges. Networks like these create connectional intelligence among researchers and institutions around the world, and are central to the concept of cooperative threat reduction. Our analysis focuses on a series of seven BTRP genome sequencing training workshops, showing how they created a growing network of participants and countries over time, which is also reflected in coauthorship relationships among attendees. By capturing concept and relationship hierarchies, our ontology-based approach allows us to pose general or specific questions about networks within the same framework. This approach can be applied to other research communities or multidimensional social networks to capture, analyze, and visualize different types of interactions and how they change over time.
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Fact sheet on Tribal Sovereignty.
Abstract We aimed to determine the survival benefits of chemotherapy (CT) added to radiotherapy (RT) in different risk groups of patients with early‐stage extranodal nasal‐type NK/T‐cell lymphoma (ENKTCL), and to investigate the risk of postponing RT based on induction CT responses. A total of 1360 patients who received RT with or without new‐regimen CT from 20 institutions were retrospectively reviewed. The patients had received RT alone, RT followed by CT (RT + CT), or CT followed by RT (CT + RT). The patients were stratified into different risk groups using the nomogram‐revised risk index (NRI). A comparative study was performed using propensity score‐matched (PSM) analysis. Adding new‐regimen CT to RT (vs RT alone) significantly improved overall survival (OS, 73.2% vs 60.9%, P < .001) and progression‐free survival (PFS, 63.5% vs 54.2%, P < .001) for intermediate‐risk/high‐risk patients, but not for low‐risk patients. For intermediate‐risk/high‐risk patients, RT + CT and CT + RT resulted in non‐significantly different OS (77.7% vs 72.4%; P = .290) and PFS (67.1% vs 63.1%; P = .592). For patients with complete response (CR) after induction CT, initiation of RT within or beyond three cycles of CT resulted in similar OS (78.2% vs 81.7%, P = .915) and PFS (68.2% vs 69.9%, P = .519). For patients without CR, early RT resulted in better PFS (63.4% vs 47.6%, P = .019) than late RT. Risk‐based, response‐adapted therapy involving early RT combined with CT is a viable, effective strategy for intermediate‐risk/high‐risk early‐stage patients with ENKTCL in the modern treatment era.
Abstract The IEA PVPS Task 13 group, experts who focus on photovoltaic performance, operation, and reliability from several leading R&D centers, universities, and industrial companies, is developing a framework for the calculation of performance loss rates of a large number of commercial and research photovoltaic (PV) power plants and their related weather data coming across various climatic zones. The general steps to calculate the performance loss rate are (i) input data cleaning and grading; (ii) data filtering; (iii) performance metric selection, corrections, and aggregation; and finally, (iv) application of a statistical modeling method to determine the performance loss rate value. In this study, several high‐quality power and irradiance datasets have been shared, and the participants of the study were asked to calculate the performance loss rate of each individual system using their preferred methodologies. The data are used for benchmarking activities and to define capabilities and uncertainties of all the various methods. The combination of data filtering, metrics (performance ratio or power based), and statistical modeling methods are benchmarked in terms of (i) their deviation from the average value and (ii) their uncertainty, standard error, and confidence intervals. It was observed that careful data filtering is an essential foundation for reliable performance loss rate calculations. Furthermore, the selection of the calculation steps filter/metric/statistical method is highly dependent on one another, and the steps should not be assessed individually.