Health data governance is essential for optimal processing of data collection, sharing, and reuse. Although the World Health Organization (WHO) has proposed practical guidelines for managing health data during the pandemic, the Organization for Economic Cooperation and Development (OECD) found that many countries still lack the use of health data for decision-making. Therefore, this research aimed to identify and assess the challenges faced by health organization in implementing health data governance from various countries based on research articles. The challenges were assessed based on key components of health data governance from practitioner and scientist perspectives. These components include stakeholder, policy, data management, organization, data governance maturity assessment, and goals. The method used followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for collecting and reporting. Data were collected from several databases online with large repositories of academic studies, including IEEE Xplore, ScienceDirect, National Library of Medicine, ProQuest, Taylor and Francis Group, Scopus, and Wiley Online libraries. Based on the 41 papers reviewed, the results showed that policy was found to be the biggest challenge for health data governance. This was followed by data management such as quality, ownership, and access, as well as stakeholders and data governance organization. However, there were no challenges regarding maturity assessment and data governance goals, as the majority of research focused on implementation. Policy and policymaker awareness were identified as major components for the implementation of health data governance. To address challenges in data management and governance organization, creating committees focused on these components proved to be an effective solution. These results provided valuable recommendations for regulators and leaders in a healthcare organization to optimally implement health data governance.

The digital era has ushered in significant advancements in Generative Artificial Intelligence (GAI), particularly through Generative Models and Large Language Models (LLMs) like ChatGPT, revolutionizing educational paradigms. This research, set against the backdrop of Society 5.0 and aimed at sustainable educational practices, utilizes qualitative analysis to explore the impact of Generative AI in various learning environments. It highlights the potential of LLMs to offer personalized learning experiences, democratize education, and enhance global educational outcomes. The study finds that Generative AI revitalizes learning methodologies and supports educational systems’ sustainability by catering to diverse learning needs and breaking down access barriers. In conclusion, the paper discusses the future educational strategies influenced by Generative AI, emphasizing the need for alignment with Society 5.0’s principles to foster adaptable and sustainable educational inclusion.

Colonialism has had a profoundly negative impact on national consciousness. Although the Republic of Kazakhstan has gained independence, it has not yet fully overcome the adverse effects of colonialism on its national consciousness. A portion of the Kazakh people has been Russified. Meanwhile, the younger generation, raised in their native language, either lacks a deep understanding of or is gradually forgetting the foundations of national identity that date back to ancient times. During the Soviet era, communist ideology prevented the population from truly knowing their history, traditions, and beliefs. In this context, literature plays a crucial role in reviving national memory. This article examines the concept of personality in literary works and the uniqueness of national identity based on the works of several contemporary authors. The introduction provides an overview of researchers’ conclusions related to the concept of personality. The ancient origins of national identity—sacred elements, rituals, shamanism, and the mystical connections between humans, nature, and animals—as depicted in literary works are analyzed within the dynamics of the present day, alongside the fates of the characters. The desecration of sacred elements is not merely ignorance but a sign of the erasure of national memory; rituals are not just words but embody sacred concepts accumulated from centuries of the people’s experience, which are reflected in the works. Accordingly, the research article analyzes and provides examples from several literary works. In compiling conclusions about the concept of personality, the study utilized descriptive, biographical, and socio-psychological methods to describe national identity in literary works and its ancient manifestations, as well as the depiction of sacred elements and rituals.

This study comprehensively evaluates the system performance by considering the thermodynamic and exergy analysis of hydrogen production by the water electrolysis method. Energy inputs, hydrogen and oxygen production capacities, exergy balance, and losses of the electrolyzer system were examined in detail. In the study, most of the energy losses are due to heat losses and electrochemical conversion processes. It has also been observed that increased electrical input increases the production of hydrogen and oxygen, but after a certain point, the rate of efficiency increase slows down. According to the exergy analysis, it was determined that the largest energy input of the system was electricity, hydrogen stood out as the main product, and oxygen and exergy losses were important factors affecting the system performance. The results, in line with other studies in the literature, show that the integration of advanced materials, low-resistance electrodes, heat recovery systems, and renewable energy is critical to increasing the efficiency of electrolyzer systems and minimizing energy losses. The modeling results reveal that machine learning programs have significant potential to achieve high accuracy in electrolysis performance estimation and process view. This study aims to contribute to the production of growth generation technologies and will shed light on global and technological regional decision-making for sustainable energy policies as it expands.