This study evaluated the performance of several machine learning classifiers—Decision Tree, Random Forest, Logistic Regression, Gradient Boosting, SVM, KNN, and Naive Bayes—for adaptability classification in online and onsite learning environments. Decision Tree and Random Forest models achieved the highest accuracy of 0.833, with balanced precision, recall, and F1-scores, indicating strong, overall performance. In contrast, Naive Bayes, while having the lowest accuracy (0.625), exhibited high recall, making it potentially useful for identifying adaptable students despite lower precision. SHAP (SHapley Additive exPlanations) analysis further identified the most influential features on adaptability classification. IT Resources at the University emerged as the primary factor affecting adaptability, followed by Digital Tools Exposure and Class Scheduling Flexibility. Additionally, Psychological Readiness for Change and Technical Support Availability were impactful, underscoring their importance in engaging students in online learning. These findings illustrate the significance of IT infrastructure and flexible scheduling in fostering adaptability, with implications for enhancing online learning experiences.

This research presents a bibliometric review of scientific production on the social and economic factors that influence mortality from tuberculosis between the years 2000 and 2024. The analysis covered 1742 documents from 848 sources, revealing an annual growth of 6% in scientific production with a notable increase starting in 2010, reaching a peak in 2021. This increase reflects growing concern about socioeconomic inequalities affecting tuberculosis mortality, exacerbated in part by the COVID-19 pandemic. The main authors identified in the study include Naghavi, Basu and Hay, whose works have had a significant impact on the field. The most prominent journals in the dissemination of this research are Plos One, International Journal of Tuberculosis and Lung Disease and The Lancet. The countries with the greatest scientific production include the United States, the United Kingdom, India and South Africa, highlighting a strong international contribution and a global approach to the problem. The semantic development of the research shows a concentration on terms such as “mortality rate”, “risk factors” and “public health”, with a thematic map highlighting driving themes such as “socioeconomic factors” and “developing countries”. The theoretical evolution reflects a growing interest in economic and social aspects to gender contexts and associated diseases. This study provides a comprehensive view of current scientific knowledge, identifying key trends and emerging areas for future research.

Since 2022, global geopolitical conflicts have intensified, and there has been a notable increase in the international community’s demand for currency diversification. This has created a new opportunity for the internationalization of the Renminbi (RMB). This paper examines the factors influencing the internationalization of the RMB, with a particular focus on its role as a unit of account, medium of exchange and store of value. These functions are considered in conjunction with the digital technological innovation represented by e-CNY. The methodology employed is based on the vector autoregression (VAR) model, Granger causality test and variance decomposition analysis. The Granger causality test indicates that digital technology innovation is not the primary driver of RMB internationalization at this juncture. The impulse response analysis and variance decomposition analysis revealed that the impact and direction of influence exerted by the various factors on RMB internationalization exhibit considerable discrepancies.

This paper aims to explore the impact of V-Girls APP on the improvement of female college students' Health literacy and its mechanism. Using a questionnaire survey method, the survey subjects were female students from a certain university. The results showed that using the V-Girls app can significantly improve the health knowledge level, health behavior habits, and mental health status of female college students. Further analysis reveals that the impact mechanisms of V-Girls APP mainly include cognitive mechanisms, social support mechanisms, and behavioral guidance mechanisms. The results of this study provide new ways and ideas for improving female college students' Health literacy.

The objective of this article is to present the analysis we conducted regarding interdisciplinarity in the training of legal professionals in the Law program at UNAD, focusing on emerging anthropocentric and biocentric perspectives that offer a different view in the training process from territorial and environmental approaches. The program, which has been in existence for three years and being the first virtual modality program authorized in Colombia, is a pioneer in its field. In consequence, we ask ourselves: What are the relevant aspects in the training of legal professionals in the face of the environmental challenges of the 21st century? For this purpose, we used a qualitative methodology with semi-structured interviews, surveys and literature review, highlighting the holistic and hermeneutic methods. We found five key aspects: a) interdisciplinary perspective in legal training; b) development of skills and competencies; c) paradigmatic changes from anthropocentrism to biocentrism from a pedagogical perspective in law; d) training of legal professionals with an environmental humanistic sense; and e) the territorial and environmental approach of the UNAD Law program. Furthermore, in the discussion, we analyzed the aspects identified above, based on complex thinking, professional skills and competences, environmental humanism and ethics in the exercise of the legal profession from a formative approach. We conclude by highlighting the importance of interdisciplinarity, critical thinking and the territorial approach as positive aspects with an opportunity for strengthening, particularly related with emerging paradigms and environmental humanism in law.

Thailand and the EU started negotiating a free trade agreement (FTA) in 2005, but negotiations were subsequently suspended in 2014 after the country’s military coup. The significance of these negotiations are important because of the mutual benefit of achieving higher levels of trade and investment between the world’s largest single market and the second largest ASEAN economy. The Specific Factors (SF) model of production and trade is applied to identify potential winner and loser industries and factors of production in Thailand. The model identifies short-run loses for some labor inputs, return to capital, and output in agriculture and services. In the manufacturing and energy sectors, higher output will benefit some labor inputs and capital owners. Understanding the short-run impact of an FTA could allow policymakers in Thailand to reinforce the institutional infrastructure such as implementing trade adjustment assistance programs (TAA), to help re-train workers who may become unemployed due to free trade.