Forecasting oil, coal, and natural gas prices in the pre-and post-COVID scenarios: Contextual evidence from India using time series forecasting tools.

Stock market price prediction is considered a critically important issue for designing future investments and consumption plans. Besides, given the fact that the COVID-19 pandemic has adversely impacted stock markets worldwide, especially over the past two years, investment decisions have become more challenging for risky. Hence, we propose a two-phase framework for forecasting prices of oil, coal, and natural gas in India, both for pre-and post-COVID-19 scenarios.

Impact of foreign direct investment on income inequality: Evidence from selected Asian economies.

The United Nations lists 17 Sustainable Development Goals for Agenda 2030, one of which is SDG-10, which focuses on eradicating inequality and addressing critical regional and global challenges. The fight against income inequality is heavily dependent on foreign direct investment all over the world. In this connection, the present study aimed to investigate the individual and interactive impact of foreign direct investment, human capital, and economic growth on income inequality by employing the interactive model.

An Improved Forest Fire Detection Method Based on the Detectron2 Model and a Deep Learning Approach.

With an increase in both global warming and the human population, forest fires have become a major global concern. This can lead to climatic shifts and the greenhouse effect, among other adverse outcomes. Surprisingly, human activities have caused a disproportionate number of forest fires.

Improved Face Detection Method via Learning Small Faces on Hard Images Based on a Deep Learning Approach.

Most facial recognition and face analysis systems start with facial detection. Early techniques, such as Haar cascades and histograms of directed gradients, mainly rely on features that had been manually developed from particular images. However, these techniques are unable to correctly synthesize images taken in untamed situations.

Can financial globalization and good governance help turning emerging economies carbon neutral? Evidence from members of the BRICS-T.

Since turning carbon neutral is regarded as a major macroeconomic agenda worldwide, this study examines whether financial globalization and good governance can help Brazil, Russia, India, China, South Africa, and Turkey in achieving carbon neutrality. Considering the period of analysis from 2000 to 2020 and utilizing robust econometric methods, it is observed that the environmental consequences vary across different components of financial globalization. In particular, the results validate the pollution haven hypothesis by confirming the carbon emission-boosting effect of de facto financial globalization indicators.

Environmental factors and its influence on human health in BRICS: implications for human development.

BRICS economies are facing severe environmental issues that exert a detrimental impact on human health. The analysis intends to examine the impact of CO emissions, environmental policy stringency, and environmental innovations on health outcomes for the BRICS economies. The long-run results of the ARDL-PMG infer that CO has a significant negative in the life expectancy model while it has a significant positive in the death rate model.

Synthesis of efficient cobalt-metal organic framework as reusable nanocatalyst in the synthesis of new 1,4-dihydropyridine derivatives with antioxidant activity.

Efficient cobalt-metal organic framework (Co-MOF) was prepared via a controllable microwave-assisted reverse micelle synthesis route. The products were characterized by SEM image, N adsorption/desorption isotherm, FTIR spectrum, and TG analysis. Results showed that the products have small particle size distribution, homogenous morphology, significant surface area, and high thermal stability.

Exploring the links between fossil fuel energy consumption, industrial value-added, and carbon emissions in G20 countries.

The primary objective of this study is to explore the links between fossil fuel energy consumption, industrial value-added, and carbon emissions in G20 countries over the period 1990-2020. Panel unit root test, co-integration test, and CS-ARDL estimator were used to determine the relationship among variables. The empirical results suggest that the driving force of carbon emissions in G20 countries varies significantly in advanced versus emerging economies.

Asymmetric macroeconomic determinants of renewable energy consumption: do financial institutions and ICT trade matter?

This study aims to examine the asymmetric impact of financial institutions and information and communication technologies (ICT) trade on renewable energy demand in BRICS economies by using the cross-sectionally augmented nonlinear autoregressive distributed lag model. The asymmetric estimates of the financial institutions index confirm that a positive shock increases renewable energy consumption, and a negative shock reduces renewable energy consumption in BRICS economies. Similarly, the long-run asymmetric estimates attached to ICT trade are positively significant, confirming that a positive shock increases renewable energy consumption and a negative shock hurts renewable energy consumption.

Optimization of dyes and toxic metals removal from environmental water samples by clinoptilolite zeolite using response surface methodology approach.

The present study aimed to remove crystal violet (CV), malachite green (MG), Cd(II), and Pb(II) from an aqueous solution using clinoptilolite zeolite (CZ) as an adsorbent. Response surface methodology (RSM) based on central composite design (CCD) was used to analyze and optimize the process parameters, such as pH, analyte concentration, adsorbent amount, and sonication time. Quadratic models with the coefficient of determination (R) of 0.

Asymmetric impact of pandemics-related uncertainty on CO emissions: evidence from top-10 polluted countries.

The recent COVD-19 pandemic has been a major shock, affecting various macroeconomic indicators, including the environmental quality. The question of how the pandemics-related uncertainty will affect the environment is of paramount importance. The study analyzes the asymmetric impact of pandemic uncertainty on CO emissions in top-10 polluted economies (China, USA, India, Russia, Germany, Japan, Iran, South Korea, Indonesia, and Saudi Arabia).

Optimization of doubly-fed induction generator (DFIG)based wind turbine to achieve maximum power generation with imperialist competitive algorithm (ICA).

Today, due to the end of fossil fuels and efforts to reduce the use of renewable resources, wind energy is a suitable option for the production of electrical energy due to its high-power generation. To increase the output efficiency of wind turbines, maximum power point tracking techniques are required for wind turbine energy conversion systems. In this research, the maximum power point (MPPT) method for two-way fed wind turbine systems (DFIG) is presented.

Testing oil price volatility during Covid-19: Global economic impact.

This paper is occasioned by the current events in the crude oil markets throughout the Covid pandemic time. The study analyzes the evolving nature of crude oil cost unpredictability caused by the variations that influence the crude sector throughout the current contagion. Every day's dataset is within the first month of 2020 and December 30, 2021 were measured by applying VAR and GARCH models.

Mitigations pathways towards sustainable development: assessing the influence of higher education on environmental quality in BRICS economies.

Education plays a significant role in the development of economies. This study empirically contributes to the literature by examining the impacts of higher education on CO emissions of BRICS economies over the period 1998-2020. For empirical analysis, we used the ARDL bound testing approach.

Economic growth, technology, and CO emissions in BRICS: Investigating the non-linear impacts of economic complexity.

Upgrading economic structures and producing less pollution-intensive goods are indispensable for achieving Sustainable Development Goals (SDGs) in BRICS (Brazil, Russia, India, China, and South Africa) that produce 41% of global CO emissions. Economic complexity (ECC), which measures the sophistication of productivity and economic structure, has important environmental repercussions. Theoretically, the environmental impacts of economic complexity at higher levels and lower levels of complexity vary from each other.

Exploring the asymmetric determinants of consumption and production-based CO emissions in China.

Environmental pollution has intensified significantly in the last few decades. Policymakers have considered this issue due to its direct influence on human lives throughout the globe. This study explores the asymmetric determinants of consumption-based and production-based CO emissions for China, for time horizon 1990-2019.

A Roadmap toward Achieving Sustainable Environment: Evaluating the Impact of Technological Innovation and Globalization on Load Capacity Factor.

Technological innovations have been a matter of contention, and their environmental consequences remain unresolved. Moreover, studies have extensively evaluated environmental challenges using metrics such as nitrogen oxide emissions, sulfur dioxide, carbon emissions, and ecological footprint. The environment has the supply and demand aspect, which is not a component of any of these indicators.

Does information and communication technology impede environmental degradation? fresh insights from non-parametric approaches.

Although ICT has played a critical role in the socio-economic growth of human cultures, it has also brought with it significant environmental risks. Nevertheless, scholars remain divided on this topic; some believe that ICT has had a positive influence on the quality of the environment, while others believe that ICT has created major environmental issues. Hence, this research is another effort to assess the effects of ICT on CO emissions in the top 10 ICT nations (Denmark, Japan, Luxemburg, South Korea, Netherlands, Iceland, Norway, Sweden, Switzerland, and the United Kingdom) using a dataset from the period between 1986Q1 and 2019Q4.

The asymmetric nexus between air pollution and COVID-19: Evidence from a non-linear panel autoregressive distributed lag model.

The emergence of a new coronavirus (COVID-19) has become a major global concern that has damaged human health and disturbing environmental quality. Some researchers have identified a positive relationship between air pollution (fine particulate matter PM) and COVID-19. Nonetheless, no inclusive investigation has comprehensively examined this relationship for a tropical climate such as India.

Nexus between export variety and carbon emissions in Pakistan: The role of FDI and technological development.

Carbon emissions constitute a large portion of greenhouse gases that are responsible for global warming and climate change. This study examines the impact of export variety on carbon emissions along with foreign direct investment (FDI) and technological development as determinants of environmental degradation in Pakistan. Moreover, this study is conducted in the context of the environmental Kuznets curve hypothesis (EKC).

Roadmap for carbon neutrality: the mediating role of clean energy development-related investments.

Recently, the Japanese government has announced the national objective of turning the economy of Japan carbon-neutral by 2050. This declaration has therefore enhanced the imperativeness of replacing the use of unclean energy with cleaner alternatives so that the carbon-neutrality agenda can be attained in due course. Against this backdrop, this study aims to assess whether enhancing government investments in research and development for developing clean energy can help Japan curb its carbon dioxide emission figures.

Compressive sensing based secure data aggregation scheme for IoT based WSN applications.

Compressive Sensing (CS) based data collection schemes are found to be effective in enhancing the data collection performance and lifetime of IoT based WSNs. However, they face major challenges related to key distribution and adversary attacks in hostile and complex network deployments. As a result, such schemes cannot effectively ensure the security of data.

Deterministic clustering based compressive sensing scheme for fog-supported heterogeneous wireless sensor networks.

Data acquisition problem in large-scale distributed Wireless Sensor Networks (WSNs) is one of the main issues that hinder the evolution of Internet of Things (IoT) technology. Recently, combination of Compressive Sensing (CS) and routing protocols has attracted much attention. An open question in this approach is how to integrate these techniques effectively for specific tasks.

Comparative mapping and validation of multiple disease resistance QTL for simultaneously controlling common and dwarf bunt in bread wheat.

Resistance QTL on chromosomes 1AL and 7AL are effective against common and dwarf bunt, QTL on 1BS affects common bunt and QTL on 7DS affects dwarf bunt in bread wheat. Common bunt, caused by Tilletia caries and T. laevis, and dwarf bunt, caused by T.