The need to expand the range of banking services in Ukraine is stipulated with technological progress, the European integration processes and the legal regime of martial law introduced in the country. Under the conditions of war, the need to strengthen the security of banking activities and protect the banking system from the influence of any internal and external factors gains meaning. The topical direction of economic and legal research of scientists today is the possibility to introduce digital technologies with elements of artificial intelligence (AI) into the banking activity in Ukraine to improve its protection. The AI law as an independent branch of the Ukrainian law has not been developed so far. The sources of AI law, its functions, tasks, scope, risks and limits of legal responsibility for prohibited practices of artificial intelligence have not been defined. The purpose of the article is to analyze the theoretical and legal provisions that underpin the regulation of AI application in Ukrainian banking. The comparative legal method made it possible, considering the provisions of the draft law on AI of the European Union, to determine the trends in the development of the legal regulation of AI in Ukraine. Following the study, proposals to the legislation of Ukraine were formulated, which will contribute to the legal regulation of banking activities using digital technologies with elements of AI.

The paper at hand analyses the principal-agent relationship, where comparative perspective between principals’ (municipalities) and agents’ (public utility providers) in the field of water and wastewater management is scrutinized. The goal of the paper is twofold: firstly, to present empirical results validating principal-agent relationships that emerged due to the reorganization process of public enterprises; secondly, to highlight the similarities and differences between the perspectives of principals and agents regarding motives, advantages and disadvantages, and price-setting in relation to the reorganization process. The empirical research is based on the primary data collected through two self-prepared and structured online questionnaires—one for municipalities, and the other for public utility providers. The results reveal similarities between public enterprises and municipalities in motivating factors for full municipal ownership. However, differences are seen among the advantages of the reorganization process. Price-setting by public utilities is recognized as a motivating mechanism for agents.

Even in the late stages of the COVID-19, the physical and psychological trauma caused by the epidemic continues to affect people, particularly university students, whose physical and psychological health is vulnerable to environmental influences. The purpose of this article is to investigate the relationship between learning adaptability and “state” anxiety among university students enrolled during the COVID-19(2020-2022), as well as the role of self-management in mediating this process. The findings reveal a negative association between college students' academic adjustment and their state anxiety, a process that also includes a mediation role for self-management, with subjects in this research being college students enrolled during COVID-19. This study offers a theoretical foundation for investigating the factors influencing anxiety from an operationalized viewpoint, as well as for further effective regulation of university students' mental health and anxiety reduction.

The public health emergency has changed the environment and conditions of art teaching. Based on the abnormal teaching background, we can use this as an opportunity to explore new teaching forms. Relying on the unique functions of the network platform, the Art Cloud Classroom explores a new style of home-based art learning that is vivid, autonomous and interactive, develops students' art skills, develops positive interests and emotions, and makes every life a better place in the nourishment of art.

The development of artificial intelligence (AI) and 5G network technology has changed the production and lifestyle of people. AI also has promoted the transformation of talent training mode under the integration of college industry and education. In the context of the current transformation of education, AI and 5G networks are increasingly used in the education industry. This paper optimizes and upgrades the training mode of skilled talents in higher vocational colleges by using its advanced methods and technologies of information display. This means is helpful to analyze and solve a series of objective problems such as the single training form of the current talent training mode. This paper utilizes the principles and laws of industry university research (IUR) collaboration for reference to construct and optimize the talent training mode based on the analysis of the requirements of talent training and the role of each subject in talent training. Then, the ecological talent training environment can be realized. In the analysis of talent training mode under the cooperation of production and education, the correlation coefficients of network construction, environment construction, scientific research funds, scientific research level, and policy support were 0.618, 0.576, 0.493, 0.785, and 0.451, respectively. This showed that the scientific research level had the greatest impact on talent training in the talent training mode of IUR collaboration, while policy support had less impact on talent training compared with other factors. The combination of AI and 5G network technology with the talent training mode of IUR cooperation can effectively analyze the influencing factors and problems of the talent training mode. The hybrid method is of great significance to the talent training strategy and fitting degree.

The role of technology in stimulating economic growth needs to be reexamined considering current heightened economic conditions of Asian developing Economies. This study conducts a comparative analysis of technology proxied by R&D expenditures alongside macroeconomic variables crucial for economic growth. Monthly time-series data from 1990 to 2019 were analyzed using a vector error correction model (VECM), revealing a significant impact of technology on the economic growth of India, Pakistan, and the Philippines. However, in the cases of Indonesia, Malaysia, Thailand, and Bangladesh, macroeconomic indicators were found more crucial to their economic growth. Results of Granger causality underlined the relationship of R&D expenditures and macroeconomic variables with GDP growth rates. Sensitivity analyses endorsed robustness of the results which highlighted the significance and originality of this study in economic growth aligned with sustainable development goals (SDGs) for developing countries.