This paper examines transformation of the mining industry in the Global South due to the rising demand for electric vehicles (EVs), which is a part of disruptive green technologies. South Africa & Democratic Republic of the Congo (DRC) are two important suppliers of critical minerals like cobalt, nickel, lithium, copper. This research tries to explore economic dynamics of mineral extraction and green transport. Using quantitative regression analysis, this paper tries to find the relationship between demand for EVs and its economic impact on mining industry's overall sales. The analysis has shown impact of critical minerals & mining sale and how disruptive technology like Evs are affecting mineral-rich countries sustainable mining. This paper is trying to shows some light on economic importance of critical minerals in transition of mining industry due to green vehicles or Evs. The association between the emerging green technology and the mining sector. The study focuses on nations in the Global South that have substantial control over the supply chain of essential minerals used in electric car batteries. The main objective of this study is to conduct an academic investigation of the many implications of green transport on the mining sector in the Global South.

Global stock markets are incredibly unpredictable. Resource prices have a significant market impact on varying securities. With the use of cutting-edge technology like artificial intelligence, analysts and researchers are employing various machine learning techniques and econometrics methodologies to anticipate stock price trends in order to better comprehend stock market volatility. Volatility is the degree of variation in a time sequence of market rates. Stock market equity returns depend on the business output where the investor has trust in high and low equity. This research explores the interaction between industrialized and developing economies' market volatility relationships between 2000 and 2020 as well as the aforementioned impacts taking place on developing financial prudence worldwide. The aim of the study is to integrate an appropriate GARCH framework to estimate the uncertainty dependent on market conditions in the European Union, the Pacific, South America, Latin America, East Asia, West Asia and South Asia stock return indices. The Generalized Auto-Regressive Conditional Heteroscedasticity method is used for analyzing the effect of updates from the USA that influences the returns of S&P 500 globally as well as European Union, Pacific, South American, Latin American, East Asian, West Asian and South Asian indices returns. For capital markets of the world, there is a significant gap in equity return uncertainty. Such results have major effects on investors looking to diversify their portfolios. For international and domestic institutional shareholders, this paper is significant. The impact of international institutional investors' investments and effects of the growth of the equity market return may be omitted as the analysis is restricted exclusively to the European Union, the Pacific, South America, Latin America, East Asia, West Asia, and South Asia.

This article tries to explore consumer attitudes regarding a balanced diet and daily calorie intake monitoring during the COVID-19 pandemic in India. It has become vital to boost people’s immunity because of reoccurring diseases such as COVID-19, Ebola, and other chronic diseases such as diabetes, thyroid disease, etc. Healthy diets are important for supporting immune systems and keeping track of daily calorie consumption is an accompaniment to this. The research on attitudes toward a balanced diet is reviewed in this empirical study. Researchers employed a tri-component attitude model to assess consumer attitudes about a balanced diet and to track daily calorie consumption. A sample of 400 respondents was surveyed and data were collected with a structured questionnaire. The data were analysed using the structural equation modelling technique. The majority of respondents were found to lack declarative knowledge of both a balanced diet and daily calorie consumption. The effects of the COVID-19 pandemic on consumer attitudes about a healthy diet and daily calorie intake were effectively evaluated using beliefs, affection, and intentions. The repercussions for the government and business community were discussed. This study also evaluates the usefulness of the tri-component attitude model in the Indian context.

Cryptocurrency is the blockchain financial technology used for transactions in financial institutions and exchanges. Bitcoin has attracted much coverage from investors and commentators as it represents the maximum market capitalization on a crypto-currency exchange. The study aims to determine the correlation between the daily log–returns and to understand the tendencies in the cryptocurrency market instability of Bitcoin, Litecoin, XRP, Nxt, Dogecoin, Vertcoin, DigiByte, DASH, Counterparty, and MonaCoin. The correlation among the selected cryptocurrencies exists in the study. The analysis is focused primarily upon reference information from the preserved servers of cryptocurrency websites and finance.yahoo.com. This research assesses regular details on the Logarithmic return of Bitcoin, Litecoin, XRP, Nxt, Dogecoin, Vertcoin, DigiByte, DASH, Counterparty, and MonaCoin for a timeframe spanning from October 01st, 2014, to April 30th, 2020. From 131 cryptocurrencies, we considered only 10 Cryptocurrencies due to the availability of data after October 2014. Where there was insufficient information, there were average results determined from preceding and succeeding data. Findings demonstrate that there is GARCH modelling of cryptocurrencies against Bitcoin. Litecoin, XRP, Nxt, Dogecoin, Vertcoin, DigiByte, DASH, Counterparty, and MonaCoin; variability values throughout the duration had a significant effect on the updates from Bitcoin returns. We believe that it helps create information and resources that are valuable to practitioners and scholars who research and form cryptocurrency markets in the future.