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.

The major goal of decisions made by a business organization is to enhance business performance. These days, owners, managers and other stakeholders are seeking for opportunities of modelling and automating decisions by analysing the most recent data with the help of artificial intelligence (AI). This study outlines a simple theoretical model framework using internal and external information on current and potential clients and performing calculations followed by immediate updating of contracting probabilities after each sales attempt. This can help increase sales efficiency, revenues, and profits in an easily programmable way and serve as a basis for focusing on the most promising deals customising personal offers of best-selling products for each potential client. The search for new customers is supported by the continuous and systematic collection and analysis of external and internal statistical data, organising them into a unified database, and using a decision support model based on it. As an illustration, the paper presents a fictitious model setup and simulations for an insurance company considering different regions, age groups and genders of clients when analysing probabilities of contracting, average sales and profits per contract. The elements of the model, however, can be generalised or adjusted to any sector. Results show that dynamic targeting strategies based on model calculations and most current information outperform static or non-targeted actions. The process from data to decision-making to improve business performance and the decision itself can be easily algorithmised. The feedback of the results into the model carries the potential for automated self-learning and self-correction. The proposed framework can serve as a basis for a self-sustaining artificial business intelligence system.

The study documents the model of the knowledge transfer process between the University, the Vocational Training Center and the industrial actors. The research seeks to answer to the following questions. Where is new knowledge generated? Where does knowledge originate from? Is there a central actor? If so, which organization? Hypotheses tested by the research: H1: Knowledge starts from the higher education institution. H2: Most “new knowledge” is generated in universities and large multinational companies. H3: The university is a central actor in the knowledge flow, transmitting both hard and soft skills, as well as subject (‘know-what’), organizational (‘know-why’), use (‘know-how’), relational (‘know-who’), and creative (‘care-why’) knowledge. The aim of the research is to model the way of knowledge flow between the collaborating institutions. The novelty of this research is that it extends the analysis of the knowledge flow process not only to the actors of previous researches (higher education institutions, business organizations, and government) but also to secondary vocational education and training institutions. The methodology used in the research is the analysis of the documents of the actors investigated and the questionnaire survey among the participants. Knowledge transfer is the responsibility of the university and its partner training and business organizations. In vocational education and training, knowledge flows based on the knowledge economy, innovation and technological development are planned, managed and operational. The research has shown that knowledge is a specific good that it is indivisible in its production and consumption, that it is easy and cheap to transfer and learn.

In this paper, a study developed at the University of Seniors in Aragón is presented. The Sono-libro, used as an innovative resource, is assessed in the proposal with an educational and pedagogical purpose. The aim is to understand the motivational and learning perception variation after the incorporation of the Sono-libro in the sample. In this quantitative longitudinal design study, the listening habits of the participants are comparatively analyzed at two moments: The first data collection took place before the implementation of the proposal, and the second collection occurred after the proposal. The sample consists of 116 subjects, with 64.16% being women and an average age of 66 years of age. Data was obtained through a validated ad hoc questionnaire judged by experts. The results of the data collections showed an increase in both motivation and perception of the learning obtained, indicating the benefits of incorporating digital resources into contexts of adult students.