Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the seventh-generation coronavirus family causing viral pandemic coronavirus disease (COVID-19) across globe affecting millions of people. The objectives of this study are to (1) identify the major research themes in COVID-19 literature, (2) determine the origin, symptoms and modes of transmission of COVID, (3) recommend the intervention and mitigation strategies adopted by the Governments globally against the spread of COVID-19 and the traumatization among the public? and (4) study the possible drugs/treatment plans against COVID-19. A systematic literature review and comprehensive analysis of 38 research articles on COVID-19 are conducted. An integrated Research focus parallel-ship network and keyword co-occurrence analysis are carried out to visualize the three research concepts in COVID-19 literature. Some of our observations include: (1) as SARS-CoV-2's RNA matches * 96% to SARS-CoV, it is assumed to be transmitted from the bats. (2) The common symptoms are high fever, dry cough, fatigue, sputum production, shortness of breath, diarrhoea etc. (3) A lockdown across 180 affected counties for more than a month with social-distancing and the precautions taken in SARS and MERS are recommended by the Governments. (4) Researchers' claim that nutrition and immunity enhancers and treatment plans such as arbidol, lopinavir/ritonavir, convalescent plasma and mesenchymal stem cells and drugs including remdesivir, hydroxychloroquine, azithromycin and favipiravir are effective against COVID-19. This complied report serves as guide to help the administrators, researchers and the medical officers to adopt recommended intervention strategies and the optimal treatment/drug against COVID-19.

COVID‐19 pandemic disease spread by the SARS‐COV‐2 single‐strand structure RNA virus, belongs to the 7 th generation of the coronavirus family. Following an unusual replication mechanism, it’s extreme ease of transmissivity has put many counties under lockdown. With 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 the COVID‐19 virus and identifies countries that have shown early signs of containment until 26 th March 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% to 92.9% to predict early signs of infection containment. Other policies and the decisions taken by countries to contain the infection are also discussed.

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In this study, Friction stir welding (FSW) is carried out on dissimilar aluminium alloys AA2219 and AA2014 using L16 orthogonal array based on Taguchi Mixed Factorial Design (TMFD) under four process variables: traverse speed, rotational speed, tilt angle and tool profile and the effects of FSW parameters on responses (Tensile Strength, Yield Strength and Elongation) are analyzed using single response optimization and multi-objective Taguchi coupled with Grey Relational Analysis. A parameter setting of A4B4C2D1 is found to be optimal demonstrating 86% of parent material strength. Further, mechanical and metallurgical studies were carried out using SEM, EDAX and XRD analyses. From micro-hardness testing, it was observed that failure occurs at the lower hardness side in the advancing side of AA2219. SEM fractography reveals dispersion of particle which improved weld strength by regulation of coarseness and dissolvability of precipitates in the weld region. EDS point, line and elemental mapping confirmed the presence of copper particle dispersion that acts as a binder and resist void formation, and this is further confirmed by XRD analysis.