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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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Confidence Estimation for Mass Spectrometry Proteomics. Crema is an open-source Python tool that estimates the false discovery rate (FDR) of a set of peptide-spectrum matches that result from proteomics data analysis. Crema implements standard FDR estimation methods that are widely used within the field. This package is meant to be simple, easy to use, stand-along, and easy to maintain.
This is a method of performing trilinear analysis on large data sets using a modification of the PARAFAC-ALS algorithm. It iteratively decomposes the data matrix into a core matrix and three loading matrices based on the Tucker1 model. The algorithm is particularly useful for data sets that are too large to upload into a computer?s main memory. While the performance advantage in utilizing our algorithm is dependent on the number of data elements and dimensions of the data array, we have seen a significant performance improvement over operating PARAFAC-ALS on the full data set. SAND2020-12649 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.
Background Nationally, Hispanics experience health disparities manifested as a higher prevalence of chronic diseases in comparison to non-Hispanic Whites. Factors that influence health disparities in this population include inadequate dissemination of culturally and linguistically appropriate health information. Method Our qualitative analysis is based on data obtained from three focus groups with Spanish-speaking Hispanic adults conducted at a clinic in Nebraska. Participants were asked about their perceptions of health information in the form of videos, brochures, and websites. We followed the consolidated criteria for reporting qualitative research and used the theoretical framework of content analysis. Results For videos, attributes associated with higher levels of trust included a friendly health professional, the logo or name of a health care institute, and a reference specifying “se habla Español.” For brochures, attributes associated with trust included use of visual aids, use of numerous colors and big font sizes, the year of printing, and a health care agency logo. For websites, characteristics associated with trust were inclusion of plain language, use of pictures and videos, and date of last update. In all focus groups, participants perceived the use of mixed English/Spanish language in health information from pamphlets and websites as unprofessional. The use of unknown governmental logos in health promotional videos and websites was perceived as untrustworthy information. Conclusions Spanish-speaking Hispanics prefer health information supported by a health care agency or delivered by a health care professional. Health communication strategies should avoid the use of mixed English/Spanish language in sensitive information especially when combined with governmental logos.
Currently, five legal authorities require U.S. federal agencies to purchase energy-efficient products. However, compliance with these requirements has consistently been low (~55%). Recent surveys indicate that energy efficiency requirements are not communicated properly within federal agencies and energy-efficiency is not a top priority. In the constantly evolving energy industry, with many solutions for a clean energy future, effective communication methods are vital for widespread adoption of energy efficiency. We have been conducting experiments within the U.S. federal sector that test the effectiveness of messaging strategies developed by using behavioral science principles like loss aversion, framing, and herd behavior. This will identify effective communications methods that encourage energy efficiency adoption. In this study, we measure the effectiveness of different communication strategies by monitoring the web traffic of hyperlinks placed within our digital communications and outreach materials. To determine effective strategies that influence federal buyer behavior, the web traffic from subjects that received the behavioral science-based messaging (treatment group) is compared to that from subjects that received regular messaging (control group) for each of the strategies. This paper provides an overview of the behavioral science principles that we applied, data collection methods, and results of our analysis. Since the lack of effective communication of energy-efficiency policies is also a common problem in the private sector, the messaging strategies developed in this study can be applicable to other large private sector institutions
This project leverages advances in machine learning based data analysis techniques and untargeted omic analytical methods to progress nuclear nonproliferation technologies beyond current capabilities. The developed approaches can be used to identify and detect complex chemical fingerprints of facilities of interest. These techniques have been developed for fields such as metabolomics and genomics but have not been applied to nuclear nonproliferation applications. Adaptation of these techniques for volatile organic compound analysis has far reaching application within the scientific community including environmental chemistry, atmospheric physics, and climate sciences.
Establish the level of reproducibility of NIF iron opacity shots, quantify to-date improvements in data quality through, e.g. background reduction, improved signal, and improved analysis methods, and formalize the approach that will be taken in the future to compare NIF data, Z data, and theory.
The NNSS has been at the forefront of custom high-fidelity x-ray/gamma radiographic imaging solutions that serve our national security for over five decades. Our radiography team utilizes expertise in physics modeling and analysis, along with optical, mechanical, and electrical design, in close collaboration with our customers, to develop imaging methods and capabilities that go beyond their needs. Conceptual designs are developed through R&D efforts to provide solutions for the specific problem at hand. Field systems are designed and built in-house, then qualified utilizing a range of facilities across the National Security Enterprise. Radiographic imaging systems are deployed by our team in the most challenging environments. The NNSS has a strong math and programming team that provides novel on-site image analysis methods that extract crucial information from data returned in field tests.
Classification of transient and variable light curves is an essential step in using astronomical observations to develop an understanding of the underlying physical processes from which they arise. However, upcoming deep photometric surveys, including the Large Synoptic Survey Telescope (LSST), will produce a deluge of low signal-to-noise data for which traditional type estimation procedures are inappropriate. Probabilistic classification is more appropriate for such data but is incompatible with the traditional metrics used on deterministic classifications. Furthermore, large survey collaborations like LSST intend to use the resulting classification probabilities for diverse science objectives, indicating a need for a metric that balances a variety of goals. We describe the process used to develop an optimal performance metric for an open classification challenge that seeks to identify probabilistic classifiers that can serve many scientific interests. The Photometric LSST Astronomical Time-series Classification Challenge (PLASTICC) aims to identify promising techniques for obtaining classification probabilities of transient and variable objects by engaging a broader community beyond astronomy. Using mock classification probability submissions emulating realistically complex archetypes of those anticipated of PLASTICC, we compare the sensitivity of two metrics of classification probabilities under various weighting schemes, finding that both yield results that are qualitatively consistent with intuitive notions of classification performance. We thus choose as a metric for PLASTICC a weighted modification of the cross-entropy because it can be meaningfully interpreted in terms of information content. Finally, we propose extensions of our methodology to ever more complex challenge goals and suggest some guiding principles for approaching the choice of a metric of probabilistic data products.
Graphical method for plotting contours of Rice distribution function as rocket-borne radar reflection data, determining leakage factor
The use of interactive graphics is presented as an attractive method for performing multi-parameter data analysis of proton recoil distributions to determine neutron spectra. Interactive graphics allows the user to view results on-line as the program is running and to maintain maximum control over the path along which the calculation will proceed. Other advantages include less time to obtain results and freedom from handling paper tapes and IBM cards.
A method is described which owes its practicality to the capability of Schmidt telescopes to record a number of galaxy images on a single plate and to the existence of high speed computer controlled area-scanning precision microdensitometers such as the Photometric Data Systems model 1010. The method of analysis results in quantitative color-index information which is displayed in a manner that allows any user to effectively study the morphological properties of the distribution of color-index in galaxies.
Analytical methods have been developed for consolidation of fatigue, fatigue-crack propagation, and fracture data for use in design of metallic aerospace structural components. To evaluate these methods, a comprehensive file of data on 2024 and 7075 aluminums, Ti-6A1-4V, and 300M and D6Ac steels was established. Data were obtained from both published literature and unpublished reports furnished by aerospace companies. Fatigue and fatigue-crack-propagation analyses were restricted to information obtained from constant-amplitude load or strain cycling of specimens in air at room temperature. Fracture toughness data were from tests of center-cracked tension panels, part-through crack specimens, and compact-tension specimens.
Wind tunnel tests were conducted to determine the aerodynamic heating created by gaps in the reusable surface insulation (RSI) thermal protection system (TPS) for the space shuttle. The effects of various parameters of the RSI on convective heating characteristics are described. The wind tunnel tests provided a data base for accurate assessment of gap heating. Analysis and correlation of the data provide methods for predicting heating in the RSI gaps on the space shuttle.
The results of a survey of U. S., British and French subcritical aircraft flight flutter testing methods are presented and evaluation of the applicability of these methods to the testing of the space shuttle are discussed. Ten U. S. aircraft programs covering the large civil transport aircraft and a variety of military aircraft are reviewed. In addition, three major French and British programs are covered by the survey. The significant differences between the U. S., French and British practices in the areas of methods of excitation, data acquisition, transmission and analysis are reviewed. The effect of integrating the digital computer into the flight flutter test program is discussed. Significant saving in analysis and flight test time are shown to result from the use of special digital computer routines and digital filters.
Results are presented of extensive testing recently completed on boron-aluminum composites to determine mechanical property data for structural design and analysis. Average property data and associated test methods are given for unidirectional and cross plied laminates at room temperature and 600 F. Results from crippling tests of hat-shaped stringers and mechanical fastener joint tests of laminates containing titanium interleaves are also presented. Compared to aluminum which has approximately same density, tests show that boron-aluminum loaded in compression is 4 1/2 times stronger and 3 1/2 times stiffer. When loaded in tension it is 2 times stronger and 3 times stiffer.
Methods are described for relating the densities in a roll of duplicate imagery to the exposure on the original by generating the system response curve. A four-quadrant tone-reproduction cycle is also described.
The results of a fan noise data analysis and prediction effort using experimental data obtained from tests on the QF-1B research fan are described. Surface pressure measurements were made with flush mounted sensors installed on selected rotor blades and stator vanes and noise measurements were made by microphones located at the far field. Power spectral density analysis, time history studies, and calculation of coherence functions were made. The emphasis of these studies was on the characteristics of tones in the spectra. The amplitude behavior of spectral tones was found to have a large, often predominant, random component, suggesting that turbulent processes play an important role in the generation of tonal as well as broadband noise. Inputs from the data analysis were used in a prediction method which assumes that acoustic dipoles, produced by unsteady blade and van forces, are the important source of fan noise.
A comprehensive method has been developed to predict the static aerodynamic characteristics of missiles with one or two sets of cruciform fins. The method, utilizing a data base augmented by analysis, is applicable over the Mach number range 0.8 to 3.0 and for angles of attack from 0 to 45 deg. Arbitrary bank angles and control deflections are allowed. Loads are calculated on each component of the missile and include effects of body and fin vortices. Comparison with data shows good agreement over a wide range of flight conditions.