With the progress of information technology, especially the widespread use of artificial intelligence technology, it has shown an important role in promoting economic and social development. Art and design in universities is a new discipline that combines modern technology with humanities and art. Only by emphasizing the development of science and technology, adapting to the requirements of the times, and closely integrating humanities and art with science and technology, can we gradually expand the educational channels for cultivating composite and innovative talents. Effectively organizing different types of scientific research activities, building a sound and comprehensive education system, plays an important role in adjusting teaching relationships, innovating teaching models, enhancing students' professional and comprehensive qualities, and improving their academic performance and employment competitiveness.

This study examines the viability and user acceptance of a Cultural Healing Virtual Museum as a novel method for enhancing employee well-being and psychological health in organizational environments. The research shows how combining art and design can create engaging cultural experiences, looking at how visual appeal, space layout, and interactive technology can help reduce stress, build emotional strength, and teach employees about culture. The study focuses on middle-aged working individuals, especially those facing stress and sub-health issues, utilizing a mixed-methods approach with 381 participants. Notably, 87.14% of participants reported awareness of the concept of cultural healing, and over 78% indicated a willingness to engage with immersive cultural wellness tools. Research indicates a pronounced inclination toward culturally relevant virtual settings that integrate traditional healing practices—such as Traditional Chinese Medicine (TCM), calligraphy, and meditation themes—with modern digital aesthetics. The findings demonstrate that art-based immersive components markedly improve emotional well-being, cultivate trust in organizational health programs, and elevate the propensity to participate in preventative self-care activities. Principal elements influencing engagement comprised visual coherence, symbolic significance, and emotional impact. Even though most feedback was positive, some participants expressed concerns about how comfortable they were with technology and using virtual reality, pointing out the need for easy training and designs that include everyone. These findings suggest that immersive wellness strategies rooted in art and heritage can contribute directly to human capital development by boosting proactive health behavior and reducing psychological strain. This research highlights the possibility of incorporating art, cultural heritage, and immersive technology into workplace wellness initiatives to bolster employee well-being, improve psychological health, and facilitate human capital development.

This study applies machine learning methods such as Decision Tree (CART) and Random Forest to classify drought intensity based on meteorological data. The goal of the study was to evaluate the effectiveness of these methods for drought classification and their use in water resource management and agriculture. The methodology involved using two machine learning models that analyzed temperature and humidity indicators, as well as wind speed indicators. The models were trained and tested on real meteorological data to assess their accuracy and identify key factors affecting predictions. Results showed that the Random Forest model achieved the highest accuracy of 94.4% when analyzing temperature and humidity indicators, while the Decision Tree (CART) achieved an accuracy of 93.2%. When analyzing wind speed indicators, the models’ accuracies were 91.3% and 93.0%, respectively. Feature importance revealed that atmospheric pressure, temperature at 2 m, and wind speed are key factors influencing drought intensity. One of the study’s limitations was the insufficient amount of data for high drought levels (classes 4 and 5), indicating the need for further data collection. The innovation of this study lies in the integration of various meteorological parameters to build drought classification models, achieving high prediction accuracy. Unlike previous studies, our approach demonstrates that using a wide range of meteorological data can significantly improve drought classification accuracy. Significant findings include the necessity to expand the dataset and integrate additional climatic parameters to improve models and enhance their reliability.

The issue of urban land management in the world in general and in Africa in particular has been exacerbated by the liberalization of land practices and the commodification of land, which has led to an increase in corrupt practices within land institutions in all cities. A mixed methodology was employed, combining a comparative case study of secondary towns with a quantitative survey of 559 landowners in the towns of Bohicon and Sokodé. In-depth interviews were conducted with 31 informants, who were surveyed on the land acquisition process, the individual determinants influencing corrupt practices, and the institutions most involved in these practices. The findings revealed that the acquisition of a formal title conferring property rights in both cities necessitates the completion of several steps. Corrupt practices are present at almost every stage of the transaction. The application of logistic regression models to the independent variables indicates that age and profession are highly significant in the sociodemographic characteristics of those most susceptible to engaging in these practices. Formal land administration institutions are the most involved in these types of everyday corruption. These practices are ultimately linked to people’s life paths and cannot therefore be combated without psychosociological education and the promotion of ethical behavior among all stakeholders, particularly among those who demand services.

The development of the personal innovative competences in workers is of capital importance for the competitiveness of organizations, where the ability of the employees must respond in an innovative way to diverse situations that arise in specific contexts. Considering this, the question arises: How do innovative employees' competences affect the sustainable development of Micro, Small and Medium Enterprises (MSMEs)? Therefore, the objective of this work is to present a multi-criteria method based on the Analytic Network Process (ANP), to relate innovative personal competences and the sustainable development of MSMEs. An instrument was applied to groups of experts from 31 Ecuadorian fruit-exporting MSMEs, to develop a multi-criteria decisional network that allowed identifying the innovative personal abilities that have the greatest impact on the sustainable development of these organizations. The results demonstrate the relevance of the elements of innovative personal competencies, with a cumulative participation of 39.15%, Sustainable Export Development with 32.18% and Improvements with 28.66%. It also presents three types of analysis: i) Global to establish the weight of each variable; ii) Influences, to establish solid cause-effect relationships between the variables and iii) Integrated. The most relevant innovative personal competences for sustainable development and improvements for exporting SMEs are teamwork, critical thinking, and creativity within the international context.