A comprehensive survey was conducted in 2012 and 2020 to assess the financial culture of Hungarian higher education students. The findings revealed that financial training effectiveness had not improved over time. To address this, a conative examination of financial personality was initiated by the Financial Compass Foundation, which gathered over 40,000 responses from three distinct age groups: Children, high school students, and adults. The study identified key behavioral patterns, such as excessive spending and financial fragility, which were prominent across all age groups. These results informed Hungary’s seven-year strategy to enhance financial literacy and integrate economic education into the National Core Curriculum. The research is now expanding internationally with the aim of building a comparative database. The study’s main findings highlight the widespread need for improved financial education, with more than 80% of adults demonstrating risky financial behaviors. The implications of these findings suggest the importance of early financial education and tailored interventions to foster long-term financial stability. The international expansion of this research will allow for the examination of country-specific financial behaviors and provide data-driven recommendations for policy development.

With the advent of the big data era, the amount of various types of data is growing exponentially. Technologies such as big data, cloud computing, and artificial intelligence have achieved unprecedented development speed, and countries, regions, and multiple fields have included big data technology in their key development strategies. Big data technology has been widely applied in various aspects of society and has achieved significant results. Using data to speak, analyze, manage, make decisions, and innovate has become the development direction of various fields in society. Taxation is the main form of China’s fiscal revenue, playing an important role in improving the national economic structure and regulating income distribution, and is the fundamental guarantee for promoting social development. Re examining the tax administration of tax authorities in the context of big data can achieve efficient and reasonable application of big data technology in tax administration, and better serve tax administration. Big data technology has the characteristics of scale, diversity, and speed. The effect of tax big data on tax collection and management is becoming increasingly prominent, gradually forming a new tax collection and management system driven by tax big data. The key research content of this article is how to organically combine big data technology with tax management, how to fully leverage the advantages of big data, and how to solve the problems of insufficient application of big data technology, lack of data security guarantee, and shortage of big data application talents in tax authorities when applying big data to tax management.

Researchers at Stanford University in the USA identified the world's Top 2% of Scientists based on data from the Scopus database. This study recognized leading scientists across various sub-fields, ranking them by the sm-subfield-1 (ns) indicator. A total of 174 distinguished scientists from 25 countries were highlighted, with a notable concentration from the USA. Harvard University was a leader, producing top scientists in 16 sub-fields. Among the 174 recognized, four are Nobel Prize Laureates, and two have received the Fields Medal. Ten scientists authored the most frequently cited papers across categories in the Web of Science, including the Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), and Arts & Humanities Citation Index (A&HCI). Professor Georg Kresse authored the most cited paper in three Web of Science categories: multidisciplinary materials science, applied physics, and condensed matter physics. The study further analyzed GDP and population metrics for each top scientist by sub-field. Seventy of the 174 scientists have consistently maintained their top rankings over the past five years.

Fiscal decentralization is one of the policy implementations of regional autonomy, which authorizes local governments to manage their local finances independently. However, with the evolution of the times and the dynamics that are taking place, the application of fiscal decentralization worldwide is changing at each time of year. Therefore, it is necessary to investigate fiscal decentralization research temporarily over the course of four decades. The study aims to explain the development of research on fiscal decentralization over a period of four decades. This research integrates Scopus database to offer a thorough conceptual and structural overview of the field by integrating bibliometric approaches and content analysis. The research procedure begins with the determination of the scope of the research, the inclusion and exclusion criteria for the selection process, the collection of data on Publish or Perish (PoP), and the execution of bibliometric analysis on VosViewer. The research shows that the type of journal with the highest productivity has sub-topics of economy, public service, development, and environmental. The development of fiscal decentralization research has a positive upward trend and most of the top-ranked journals indicate that fiscal decentralization has links and influences with other variables. It is apparent that the most often keywords emerged and studied in the research on fiscal decentralization are related to efficiency, measure, role, degree, growth, and fiscal federalism. Meanwhile, the least frequent keywords are related to poverty and inequality, health outcome, environmental pollution, Latin America, South Africa, fiscal autonomy, corruption, OECD country, determinant, and public sector. These keywords are the future lines of research that may be used for future research on the topic of fiscal decentralization.

On the basis of the enlightenment of international engineering education accreditation for the reform and development of higher education in China, combined with the important measures of the national “double first-class” construction, new challenges have been proposed for innovative talent cultivation among engineering majors in the context of promoting national development. These challenges also promote the reform of science-oriented courses among engineering majors. As a core mandatory course for engineering majors, biochemistry plays a crucial role in the entire educational process at universities, serving as a bridge between basic and specialized courses. To address challenges such as limited course resources, insufficient development of students’ advanced thinking and innovation skills, and overly standardized assessment methods, the bioengineering major from Guilin University of Technology restructured the biochemistry course content. A blended teaching model termed “three integrations, three stages, one sharing”, was implemented. This effort has yielded significant results, providing a research foundation for constructing an innovative talent cultivation system that is oriented toward industry needs within modern industrial colleges. It also offers valuable insights into and reference points for the cultivation of engineering talents and curriculum reform in local universities.

This study examines the effectiveness of Kazakhstan’s grant funding system in supporting research institutions and universities, focusing on the relationship between funding levels, expert evaluations, and research outputs. We analyzed 317 projects awarded grants in 2021, using parametric methods to assess publication outcomes in Scopus and Web of Science databases. Descriptive statistics for 1606 grants awarded between 2021 and 2023 provide additional insights into the broader funding landscape. The results highlight key correlations between funding, evaluation scores, and journal publication percentiles, with a notable negative correlation observed between international and national expert evaluations in specific scientific fields. A productivity analysis at the organizational level was conducted using non-parametric methods to evaluate institutional efficiency in converting funding into research output. Data were manually collected from the National Center of Science and Technology Evaluation and supplemented with publication data from Scopus and Web of Science, using unique grant numbers and principal investigators’ profiles. This comprehensive analysis contributes to the development of an analytical framework for improving research funding policies in Kazakhstan.