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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

Diffuse Auroral Intensities Produced By Whistler Mode and Electron Cyclotron Harmonic Waves

Whistler mode waves and ECH waves as observed by the THEMIS-D and THEMIS-E satellites have been analyzed. It is observed that ECH waves are very weak for pitch-angle diffusion whereas whistler mode waves are more efficient. Bounce-averaged pitch-angle diffusion rates at the edge of atmospheric loss-cone have been calculated for both waves. Further, these are used to obtain electron precipitation flux inside the loss-cone. The electron flux at the edge of the loss-cone is represented by the kappa distribution. Numerical calculation of precipitation flux is performed by varying the fitting parameters (which determine the shape of electron precipitation flux) appearing in the kappa distribution. Precipitation flux is used to obtain volume excitation rates and height-integrated volume excitation rates for the seven excitation states. Calculations have been performed using two standard atmosphere models corresponding to mean and high solar and geomagnetic activities. It has been observed from studies that the excitation rates produced by the ECH wave are several orders of magnitude smaller than the rates produced by whistler mode waves. We show that the scattering efficiency of whistler Mode is higher than that of ECH waves. The oblique whistler mode waves allow efficient scattering of electrons in diffuse aurora. Outcomes are discussed.

Arvind K. Tripathi↗
NASA NTRSDate not supplied

Harmonizing Multi-Disciplinary Data for Applied Research: A Comprehensive Analysis of GES DISC Datasets through NLP and TF-IDF Techniques

Data centers distribute data encompassing multiple disciplines, making it necessary to evaluate dataset applicability to applied research. Typically, these datasets are generated by specialized science teams and consist of single-discipline data, such as atmospheric temperature, pressure, and precipitation, leading to unique dataset formats and access services. However, in applied research, the utilization of datasets from multiple disciplines is commonly necessary. The increasing availability of research literature citing Earth Science datasets presents an opportunity to analyze the usage of datasets in multi-disciplinary research. This study proposes a novel approach wherein research publications citing datasets archived at the GES DISC (Goddard Earth Sciences Data and Information Services Center) are collected, and each publication is associated with specific research topics through the application of Natural Language Processing (NLP), using the Term Frequency Inverse Document Frequency (TF-IDF) technique on the publication titles and abstracts. Through this analysis, we gain insights into the distribution of dataset disciplines as they are being used in various applied research areas. This knowledge is essential for the development of dataset tools and services tailored to effectively support applied research studies, as it enhances a data center's comprehension of how datasets from multiple disciplines are integrated into research endeavors.

Infometrics↗