Radio spectral index from NVSS and TGSS

I extract the radio spectral index,α,from 541 195 common sources observed in the 150 MHz TIFR GMRT Sky Survey(TGSS) and the 1.4 GHz NRAO VLA Sky Survey(NVSS).This large common source catalog covers about 80% of the sky.The flux density limits in these surveys are such that the observed galaxies are presumably hosts of active galactic nuclei(AGNs).I confirm the steepening of αwith increasing flux density for this large sample and provide a parametric fit between α and flux density.Next,I divide the data into low flux(LF) and high flux(HF) density samples with roughly equal numbers of galaxies.The LF sample contains all galaxies below 100 m Jy TGSS and 20 m Jy NVSS flux density and the HF sample is all galaxies above 100 m Jy TGSS and 20 m Jy NVSS.I observe an increase in α with source size(TGSS measured),saturating for large sizes to 0.89 ± 0.22 and 0.76 ± 0.21 for the LF and HF sources,respectively.I discuss the observed results and possible physical mechanisms to explain observedα dependence with source size for LF and HF samples.

State of charge and health estimation of batteries for electric vehicles applications:key issues and challenges

Using electric vehicles(EVs)for transportation is considered as a necessary component for managing sustainable development and environmental issues.The present concerns regarding the environment,such as rapid fossil fuel depletion,increases in air pollution,accelerating energy demands,global warming,and climate change,have paved the way for the electrification of the transport sector.EVs can address all of the aforementioned issues.Portable power supplies have become the lifeline of the EV world,especially lithium-ion(Li-ion)batteries.Li-ion batteries have attracted considerable attention in the EV industry,owing to their high energy density,power density,lifespan,nominal voltage,and cost.One major issue with such batteries concerns providing a quick and accurate estimation of a battery’s state and health;therefore,accurate determinations of the battery’S performance and health,as well as an accurate prediction of its life,are necessary to ensure reliability and efficiency.This study conducts a review of the technological briefs of EVs and their types,as well as the corresponding battery characteristics.Various aspects of recent research and developments in Li-ion battery prognostics and health monitoring are summarized,along with the techniques,algorithms,and models used for current/voltage estimations,state-of-charge(SoC)estimations,capacity estimations,and remaining-useful-life predictions.