The aim of our study is to provide information on how and to what extent professionals of art institutions in Hungary and Slovakia (contemporary galleries and museums) use artificial intelligence in their work processes. Our research focuses on the extent to which these institutions use artificial intelligence in the development of the institution’s operational strategy, or how they can embed the assumed usefulness of artificial intelligence in the operation of the institution, be it the creation of an exhibition, the textual processing of the professional life of an artist, or a about a tool that shapes the gallery’s marketing strategy. We conducted ten in-depth interviews in the two countries, the interviewees were selected using the snowball method. The interview took place among professionals and professionally credible artists who are actively active in contemporary fine art life. The results revealed that the use of artificial intelligence as a tool in the creative work processes is not a requirement in the field of culture, neither in Hungary nor in Slovakia. All the interviewees already had professional experience with AI, 90% of those interviewed would like to deepen their knowledge of the creative use methods of AI, e.g., by creating working groups in the workplace on an experimental basis. Based on our conclusions, we can say that artificial intelligence currently has no conscious strategic use in contemporary art institutions. It can be said that creative professionals are aware of the possibilities of using artificial intelligence in their own field of image, video, and text creation, but there is uncertainty on the part of creators and curators when it comes to copyright. The in-depth interviews provided source material for the compilation of a standardized set of questions for a larger survey of 300-500 people, proportional to the sample, so our presented results are partial results of a larger research.

The most important issue of economic development is the question of the real reasons for the growth of labor productivity based on innovative equipment and technologies or “closing technologies”, both directly and in the sphere of organization and management of economic systems. Organizational innovations can also be classified as “closing technologies”. For example, the creation of strategic institution, alliances and associations capable of changing the situation in the global economy, likely World Bank (WB), World Health Organization (WHO), International association Brazil, Russia, India, China, South Africa (BRICS) etc. This approach involves the formation of fundamental innovative solutions at all levels of the management hierarchy. The imperfection of the existing ideological and methodological paradigm, ignoring the mathematical constants of the Universe when designing economic supersystems or economic systems as integral distributed systems with complex dynamics similar to natural systems, the inefficiency of institutional intervention is the main reason for the impossibility of minimizing the structural and functional instability of the state economic system. The consequence of this is systemic violations and disproportions in the economy, risks associated with changes in the structure of the world economy and a colossal difference in the level of economic security of states and the phenomenon of crisis transfer.

This research aims to identify the development of research theme trends that were carried out from 1999 to 2024. Thus, the study’s results can provide recommendations regarding research themes that can be developed to meet theoretical and practical needs. Researchers use bibliometric analysis to obtain the appropriate analysis. This analysis method can be developed to support the dynamic development of public health science with settings and researchers from developing countries, both through quantitative and qualitative interpretation. The analysis results show that over 25 years, public health science, from the perspective of researchers and developing countries, has experienced dynamic development. This change was driven by the emergence of various issues in society itself. For example, the 1999–2009 shows that lifestyle changes have resulted in multiple diseases. In the following period, the concept of sustainability emerged, which encouraged awareness of sustainable development and resource scarcity that would affect public health quality. As for the 2020–2024 period, the emergence of Covid 19 changed the previous research paradigm.

The ongoing railway reforms in Ukraine are crucial for the country’s integration into the European Union’s transportation network. A major challenge lies in the difference in track gauge widths: Ukraine predominantly uses a 1520 mm gauge, while European countries utilize a 1435 mm gauge. This 85 mm difference presents significant logistical and operational barriers, hindering smooth cross-border trade and travel. The study examines the current state of Ukraine’s railway system, highlighting the urgent need for infrastructure modernization to meet European standards. Methods include a comparative analysis of Ukraine’s railway network with those of EU member states, focusing on integration challenges and potential solutions. Results indicate that aligning Ukraine’s railway with European standards could substantially enhance connectivity, reduce transit times, and foster economic growth. However, “Ukrzaliznytsia’s” slow adaptation to these necessary changes is a major roadblock. The study concludes that the construction of a standard-gauge railway linking Ukraine to the EU is vital not only for improving trade routes but also for supporting Ukraine’s broader political and economic aspirations towards EU membership. Circular economy principles, such as resource optimisation, extending the life cycle of existing infrastructure and reusing materials from dismantled railway facilities, can offer a cost-effective and sustainable approach. This infrastructural change will serve as a catalyst for deeper integration, strengthening Ukraine’s position within the European transportation network.

The study aims to explore the extent to which Jordanian e-news sites rely on artificial intelligence applications in their news content. The researchers will use a media survey methodology, and the sample will consist of 45 editors-in-chief and editors from 10 Jordanian news sites, namely: Ammon, Khabrny, Joe24, Saraya, Amman Net, Jafra, Crown News, Petra, Kingdom, and Roya. The researcher will use an electronic questionnaire, which led to several findings, the most significant of which are: Many news and media sites have introduced artificial intelligence systems to enhance the services they provide to the public. A significant number of journalistic and electronic media websites have shown interest in data analysis tools for their media services. Electronic news sites are clearly striving to improve their capabilities in using artificial intelligence technologies to enhance the services they provide to the Jordanian audience. Additionally, most electronic media websites have expressed a willingness to develop a plan to improve cybersecurity systems to protect against hacking and intrusion attempts, safeguarding their data and the AI systems that operate continuously.AI systems in media organizations also aim to enhance the news experience for users by enriching media services with modern, communicative content.

This study conducts a systematic review to explore the applications of Artificial Intelligence (AI) in mobile learning to support indigenous communities in Malaysia. It also examines the AI techniques used more broadly in education. The main objectives of this research are to investigate the role of Artificial Intelligence (AI) in support the mobile learning and education and provide a taxonomy that shows the stages of process that used in this research and presents the main AI applications that used in mobile learning and education. To identify relevant studies, four reputable databases—ScienceDirect, Web of Science, IEEE Xplore, and Scopus—were systematically searched using predetermined inclusion/exclusion criteria. This screening process resulted in 50 studies which were further classified into groups: AI Technologies (19 studies), Machine Learning (11), Deep Learning (8), Chatbots/ChatGPT/WeChat (4), and Other (8). The results were analyzed taxonomically to provide a structured framework for understanding the diverse applications of AI in mobile learning and education. This review summarizes current research and organizes it into a taxonomy that reveals trends and techniques in using AI to support mobile learning, particularly for indigenous groups in Malaysia.