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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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At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Personal reflections on the highlights and changes in radiation and radioisotope measurement applications

Here, this paper describes the recent changes that the authors have perceived in the use of radiation and radioisotope measurement applications. The first change is that due to the increased use of Monte Carlo simulation which has occurred from a normal evolutionary process. This is due in large part to the increased accuracy that is being obtained by the use of detector response functions (DRFs) and the simultaneous increased computational efficiency that has become available with these DRFs, the availability of a greatly improved weight windows variance reduction method, and the availability of in-expensive computer clusters. This first change is a happy one. The other change that is occurring is in response to recent terrorist activities. That change is the replacement or major change in the use of long-lived radioisotopes in radioisotope measurement and other radioisotope source applications. In general this can be done by improving the security of these radioisotope sources or by replacing them altogether by using machine sources of radiation. In either case one would like to preclude altogether or at least minimize the possibility of terrorists being able to obtain radioisotopes and use them for clandestine purposes.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2014

Mixture effects at very low doses with combinations of anti-androgenic pesticides, antioxidants, industrial pollutant and chemicals used in personal care products

Many xenobiotics have been identified as in vitro androgen receptor (AR) antagonists, but information about their ability to produce combined effects at low concentrations is missing. Such data can reveal whether joint effects at the receptor are induced at low levels and may support the prioritisation of in vivo evaluations and provide orientations for the grouping of anti-androgens in cumulative risk assessment. Combinations of 30 AR antagonists from a wide range of sources and exposure routes (pesticides, antioxidants, parabens, UV-filters, synthetic musks, bisphenol-A, benzo(a)pyrene, perfluorooctane sulfonate and pentabromodiphenyl ether) were tested using a reporter gene assay (MDA-kb2). Chemicals were combined at three mixture ratios, equivalent to single components' effect concentrations that inhibit the action of dihydrotesterone by 1%, 10% or 20%. Concentration addition (CA) and independent action were used to calculate additivity expectations. We observed complete suppression of dihydrotestosterone effects when chemicals were combined at individual concentrations eliciting 1%, 10% or 20% AR antagonistic effect. Due to the large number of mixture components, the combined AR antagonistic effects occurred at very low concentrations of individual mixture components. CA slightly underestimated the combined effects at all mixture ratios. In conclusion, large numbers of AR antagonists from a wide variety of sources and exposure routes have the ability of acting together at the receptor to produce joint effects at very low concentrations. Significant mixture effects are observed when chemicals are combined at concentrations that individually do not induce observable AR antagonistic effects. Cumulative risk assessment for AR antagonists should apply grouping criteria based on effects where data are available, rather than on criteria of chemical similarity. - Highlights: • Mixtures of AR antagonists at low individual concentrations cause complete inhibition. • Concentration addition was an appropriate prediction model for observed effects. • Risk assessment for AR antagonists should use grouping criteria based on effects.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Health intelligence: how artificial intelligence transforms population and personalized health

Advances in computational and data sciences for data management, integration, mining, classification, filtering, visualization along with engineering innovations in medical devices have prompted demands for more comprehensive and coherent strategies to address the most fundamental questions in health care and medicine. Theory, methods, and models from artificial intelligence (AI) are changing the health care landscape in clinical and community settings and have already shown promising results in multiple applications in healthcare including, integrated health information systems, patient education, geocoding health data, social media analytics, epidemic and syndromic surveillance, predictive modeling and decision support, mobile health, and medical imaging (e.g. radiology and retinal image analyses). Health intelligence uses tools and methods from artificial intelligence and data science to provide better insights, reduce waste and wait time, and increase speed, service efficiencies, level of accuracy, and productivity in health care and medicine.

Shaban-Nejad, Arash↗