Government College

About: Government College is a based out in . It is known for research contribution in the topics: Population & Ring (chemistry). The organization has 4481 authors who have published 5986 publications receiving 57398 citations.

Luminescence and EPR studies of ultraviolet light emitting La 2 Zr 2 O 7 :Gd 3+ phosphor powder

Abstract: The Gd3+ doped La2Zr2O7 phosphor has been prepared by solution combustion method and characterized using powder X-ray diffraction, scanning electron microscopy, electron paramagnetic resonance (EPR) and photoluminescence spectroscopy. The EPR spectrum of Gd3+ doped La2Zr2O7 exhibits resonance signals having effective g values at g ≈ 1.84, 1.93, 2.0, 3.00, 3.85 and 6.12. Upon UV light excitation (274 nm), the phosphor exhibits a strong and sharp UV emission at 312.5 nm, which is ascribed to 6P7/2 → 8S7/2 transition of Gd3+ ions. EPR and optical investigations of the sample confirm the presence of Gd3+ in the La2Zr2O7 matrix.

Exploring the growth of COVID-19 cases using exponential modelling across 42 countries and predicting signs of early containment using machine learning.

Abstract: The coronavirus disease 2019 (COVID-19) pandemic spread by the single-stranded RNA severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) belongs to the seventh generation of the coronavirus family. Following an unusual replication mechanism, its extreme ease of transmissivity has put many countries under lockdown. With the uncertainty of developing a cure/vaccine for the infection in the near future, the onus currently lies on healthcare infrastructure, policies, government activities, and behaviour of the people to contain the virus. This research uses exponential growth modelling studies to understand the spreading patterns of SARS-CoV-2 and identifies countries that showed early signs of containment until March 26, 2020. Predictive supervised machine learning models are built using infrastructure, environment, policies, and infection-related independent variables to predict early containment. COVID-19 infection data across 42 countries are used. Logistic regression results show a positive significant relationship between healthcare infrastructure and lockdown policies, and signs of early containment. Machine learning models based on logistic regression, decision tree, random forest, and support vector machines are developed and show accuracies between 76.2% and 92.9% to predict early signs of infection containment. Other policies and the decisions taken by countries to contain the infection are also discussed.