The application of positive psychology in the work of mental health education in colleges and universities can help students better face setbacks, enable students to face learning and life with a positive attitude, and promote students' future development and promote students' healthy growth. Based on positive psychology, this paper analyzes and discusses its practice and exploration in college students' mental health education.

Climate change is occurring more quickly and has more complex effects than expected. The well-being of populations in general and financial resources have been impacted by climate change in recent years. Children, pregnant women and the elderly bear the brunt of the impacts caused by climate-related risks. This research aims to assess the perceptions of health personnel and clients on climate change as well as these impacts in the Greater Lomé health region in Togo. Furthermore, this research examines the differences between the perceptions of caregivers, patients and scientific observations in this area. Based on field observations, an interview guide and a questionnaire, the information collected shows that nearly 75.95% of those questioned perceived climate change, particularly in the form of an increase in precipitation concentrated on a cost duration causing floods and the scarcity of rain at the end of the year leading to droughts. More than 25.40% and 61.86% respectively perceive that droughts and floods impact their livelihoods, but do not fully understand the causes. The results are useful for planning useful actions to facilitate the management of climate-related risks in health establishments in the Greater Lomé health region. It is therefore important to carry out awareness campaigns, train stakeholders and take necessary measures to make health systems resilient.

In the process of teaching and learning at any stage, the important role of interest guidance cannot be ignored. Especially in college mathematics teaching, mathematical knowledge is very complex and abstract, and most students are unable to effectively understand and master it during the learning process. So it is even more important to fully stimulate students' interest in learning. This article analyzes the significance and current situation of stimulating students' learning interest in university mathematics teaching, and conducts effective strategy analysis. In order to effectively awaken students' desire for knowledge, guide students to change from passive learning to active learning, so that students can continue to grow and progress in this process.

Taking Xinjiang Agricultural University as an example, based on Rain Classroom and Dingding platform, the linear algebra course changes the current situation of "emphasizing theory and ignoring application" in traditional mathematics classrooms, adding applied teaching cases with the background of industry and agriculture, using online and offline The blended teaching mode, through inquiry-based and case-based teaching methods and students' autonomous learning and discussion methods, develops from a teaching mode focusing on "teaching" to focusing on "learning". The teaching mode has been comprehensively reformed, and satisfactory results have been achieved.

Hospital performance possesses strategic significance in achieving an essential completive advantage for the public hospitals. This study aimed to examine the relationship between patient safety culture (PSC) and the performance of traditional Chinese medicine (TCM) public hospitals in Sichuan, China. To address the research purpose, this study analyses the hospital performance and Patient safety culture in traditional Chinese medicine public hospital in China. We examine the propose model by analyzing cross-sectional survey data from 194 clinical directors at 194 public traditional Chinese medicine hospitals using the Partial least squares structural equation model in Smart PLS 4.0. This study provides predictive evidence that PSC in unit management and management support can lead to better patient safety outcomes. The results revealed patient safety outcomes significantly and positively effects of patient safety related to unit management and management support on overall hospital performance (p-value: 0.000–0.003).

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.