Emotional education plays an important role in the field of education and is of great significance to students' mental health and all-round development. As a discipline focusing on emotional expression and creativity cultivation, art education provides a unique opportunity to penetrate emotional education. By analyzing the penetration of emotion education in junior middle school art teaching, this paper discusses the role and implementation strategies of emotional education in art teaching, aiming to provide valuable reference for educators.

The objective of this paper is to assess the influence of various types of crises, including the Subprime, COVID-19, and political crises, on corporate governance attributes, regulations, and the association with bank risk. The consecutive occurrences of crises have significantly impacted the global economy, causing substantial disruptions across various facets of the international banking system. Our hypothesis posits that these crises not only influence governance characteristics and regulations but also impact their correlation with the risk and financial distress experienced by banks. Our study is conducted within the Tunisian context spanning from 2000 to 2021, utilizing a GMM regression on a dataset comprising 221 bank-year observations. Our findings indicate that crises have a discernible effect on the relationship between corporate governance and bank risk, as well as between regulation and bank risk. Our results are strong in a range of sensitivity checks, including the use of alternative proxies to measure the bank risks and corporate governance metrics.

In the current digital era, digital communication has a profound impact on the construction of product brands and affects the organizational performance of enterprises; thus, digital communication has become a power that cannot be ignored to improve the organizational performance of enterprises. This study demonstrated three hypotheses based on previous research and used a questionnaire survey to collect first-hand data from distributors of a China’s leading domestic down coat brand (named BRAND A in this study), and then studied and analyzed the relationships among digital integrated and interactive brand communication (DIIBC), brand value, and organizational performance through SEM analysis methods. The results showed that DIIBC had an indirect negative significant positive effect on organizational performance through brand value, while it had a highly significant direct positive effect on the organizational performance of this brand in China’s domestic down coat industry, and DIIBC’s final function on organizational performance was highly significant positive.

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.

This research aims to investigate how technological innovation influences social sustainability via the mediating role of organizational innovation and digital entrepreneurship. This investigation employed a quantitative research approach and used data from survey questionnaires based on a set of suppositions evaluated using structural equation modeling. A total of 320 respondent companies from digital provider companies in Thailand. The findings of the research expose that technological innovation has a positive effect on organizational innovation and digital entrepreneurship. Both serve as mediators in the correlation between technology innovation and social sustainability. Moreover, this research will be beneficial for businesses that are implementing new technologies and innovation, considering their role in attaining both environmental and social sustainability.

The aim of our study is to provide information on how and to what extent professionals of art institutions in Hungary and Slovakia (contemporary galleries and museums) use artificial intelligence in their work processes. Our research focuses on the extent to which these institutions use artificial intelligence in the development of the institution’s operational strategy, or how they can embed the assumed usefulness of artificial intelligence in the operation of the institution, be it the creation of an exhibition, the textual processing of the professional life of an artist, or a about a tool that shapes the gallery’s marketing strategy. We conducted ten in-depth interviews in the two countries, the interviewees were selected using the snowball method. The interview took place among professionals and professionally credible artists who are actively active in contemporary fine art life. The results revealed that the use of artificial intelligence as a tool in the creative work processes is not a requirement in the field of culture, neither in Hungary nor in Slovakia. All the interviewees already had professional experience with AI, 90% of those interviewed would like to deepen their knowledge of the creative use methods of AI, e.g., by creating working groups in the workplace on an experimental basis. Based on our conclusions, we can say that artificial intelligence currently has no conscious strategic use in contemporary art institutions. It can be said that creative professionals are aware of the possibilities of using artificial intelligence in their own field of image, video, and text creation, but there is uncertainty on the part of creators and curators when it comes to copyright. The in-depth interviews provided source material for the compilation of a standardized set of questions for a larger survey of 300-500 people, proportional to the sample, so our presented results are partial results of a larger research.