Global CO₂ emissions pose a serious threat of climate change for high-growth countries, requiring increased efforts to preserve the environment and meet growing economic needs through the use of renewable energies. This research significantly enhances the current literature by filling a void and differentiating between short-term and long-term impacts across economic growth, renewable energy consumption, energy intensity, and CO₂ emissions in BRIC countries from 2002 to 2019. In contrast to approaches that analyze global effects, this study’s focus on short and long-term effects offers a more dependable insight into energy and environmental research. The empirical results confirmed that the effect of economic growth on CO₂ emissions is positive both in the short and long term. Moreover, the effect of energy consumption is negative in the short term and positive in the long term. The effect of energy intensity is positive in the short term and negative in the long term. Accordingly, policy recommendations must be adopted to ensure that these economies respond to the notion of sustainable development and the relationship with the environment. BRIC countries must strengthen their industries in the long term in favor of the use of renewable energies by introducing innovation and technology. These economies face the challenge of a transition to renewable energy sources by creating a new energy and industrial sector environment that is more environmentally friendly atmosphere.

The incorporation of artificial intelligence (AI) into language education has created new opportunities for improving the instruction and acquisition of Chinese characters. Nevertheless, the cognitive difficulties linked to the acquisition of Chinese characters, such as their intricate visual features and lack of clear meaning, necessitate thoughtful deliberation when developing AI-supported learning interventions. The objective of this project is to explore the capacity of a collaborative method between humans and machines in teaching Chinese characters, utilising the advantages of both human expertise and AI technology. We specifically investigate the utilisation of ChatGPT, a substantial language model, for the creation of instructional materials and evaluation methods aimed at teaching Chinese characters to individuals who are not native speakers. The study utilises a mixed-methods approach, which involves both qualitative examination of lesson plans created by ChatGPT and quantitative evaluation of student learning outcomes. The results indicate that the suggested framework for human-machine collaboration can successfully tackle the cognitive difficulties associated with learning Chinese characters, resulting in enhanced learner involvement and performance. Nevertheless, the research also emphasises the constraints of AI-generated material and the significance of human involvement in guaranteeing the accuracy and dependability of educational interventions. This research adds to the expanding collection of literature on AI-assisted language learning and offers practical insights for educators and instructional designers who aim to use AI tools into Chinese language curriculum. The results emphasise the necessity of employing a multi-disciplinary strategy in AI-supported language learning, incorporating knowledge from cognitive psychology, educational technology, and second language acquisition.

Studies show that Fourth Industrial Revolution (4IR) technologies can enhance compliance with COVID-19 guidelines within the parties in the construction industry in the future and mitigate job loss. It implies that mitigating job loss improves the achievement of Sustainable Development Goal 1 (SDG 1) (eliminate poverty). There is a paucity of literature concerning 4IR technologies application and COVID-19 impact on South Africa’s construction industry. Thus, this paper investigates the impacts of the pandemic on the sector and the roles of digital technologies in mitigating job loss in future pandemics. Data were collected via virtual semi-structured interviews. The participants proffered unexplored insights into the impact of the pandemic on the sector and the possible roles that 4IR technology can play in mitigating the spread of the virus within the sector. Findings show that the sector was hit, especially the low-income earners, threatens to achieve Goal 1, despite government institutions’ intervention, such as economic support programmes, health and safety guidelines awareness, and medical facilities. Findings group the emerged impacts into health and safety, environmental, economic, productivity, social, and legal and insurance issues in South Africa. The study shows that technology can be advantageous to improving achieving Goal 1 in a pandemic era due to limited job loss.

As the complexity and scale of software applications increase, the challenges associated with testing these systems grow correspondingly, necessitating innovative and sustainable testing strategies. This paper explores a multifaceted approach aimed at addressing the intricate challenges inherent in testing large-scale software applications. Through a comprehensive examination of current industry practices and emerging trends, this study introduces a novel framework that integrates advanced testing techniques with state-of-the-art tools. This framework not only mitigates the challenges posed by the complexity and size of modern applications but also enhances the efficiency and effectiveness of the testing process. Key aspects of this research include a detailed exploration of test methodologies suited for large-scale applications, an evaluation of advanced tools designed for complex test scenarios, and an analysis of the impact of the test environment on sustainability. The findings offer valuable insights and actionable strategies for software development and testing professionals aiming to optimize testing processes and improve the quality and sustainability of their software in a rapidly evolving technological landscape.

Background: Traditional education in neurosurgery primarily relies on observation, giving residents and interns limited opportunities for clinical practice. However, the development of 3D printing has the potential to improve this situation. Based on bibliometrics, we analyze the application of 3D printing technology in neurosurgery medical education and surgical training. Methods: We searched the publications in this field in Web of Science core collection database from September 2000 to September 2023. VOS viewer, Citespace and Microsoft Office Excel were used to visually analyze and draw knowledge graphs. Results: A total of 231 articles and reviews were included. The United States is the country with the largest volume of articles and Mayo Clinic is the leading organization in this field. Partnership between countries, authors and institutions is also presented. World Neurosurgery is the journal with the highest number of publications. The top three key words by occurrence rate are “3D printing”, “surgery” and “simulation”. Conclusions: In recent years, more and more attention has been paid to the research in this field. According to bibliometric analysis, “accuracy” and “surgery simulation” are the research focuses in this field, while “augment reality” is the potential research target.