With the development of the new situation, the "00s" have become the mainstream college students in universities, and the "05s" are about to enter universities. The group of college students born in the 2000s has shown ideological characteristics such as high openness, strong self-esteem, strong individualism, active thinking, and weak psychological resilience, which have brought new challenges to ideological and mental health education in universities. At present, it has become a common trend for graduate students in universities to serve as part-time counselors, and the structure of university counselors is generally "a combination of full-time and part-time, with full-time as the main focus, and full-time leading and part-time". As a full-time counselor in a university, I have worked as a part-time counselor during my graduate studies. Based on my personal and practical experience as a part-time counselor, I will consider and study the impact of part-time counselors on the construction of the university counselor team. In order to make the construction of the university counselor team more professional, professional, and diversified, I will propose constructive suggestions.

Hospitals belong to public places, and implementing refined management in hospitals is a need for patients. Under party building management, hospitals must manage hospitals in accordance with the party's governing philosophy. In the new era, China's party building management is facing enormous challenges. In order to implement party and government management in the new era, hospitals must strengthen their understanding of party building and further implement refined management at a deeper level.

The quality of preschool education is related to the stability of the early childhood teaching force. With the help of qualitative research methods, the study analyzed the data of eight teachers who left the profession and explored the process of teachers leaving the profession, and found that the encounter between "settling down" and "professional feelings", the struggle for transformation between "professional feelings" and "the situation", and the struggle for transformation between "settling down" and "the situation" are all related to the stability of the early childhood education workforce. It was found that the encounter and tug-of-war between "settling down" and "professional feelings", the struggle for transformation between "professional feelings" and "the situation", and the rational weighing between "settling down" and "the situation" are the important factors affecting the departure from the profession. The essence is the tension between "teachers as human beings" and "human beings as teachers". Therefore, it is necessary to pay attention to the unity of "person" and "teacher", and to alleviate the problem of teachers leaving the organization by creating a fair, democratic and professional working atmosphere and strengthening the awareness of professional education.

To gain a deep understanding of maintenance and repair planning, investigate the weak points of the distribution network, and discover unusual events, it is necessary to trace the shutdowns that occurred in the network. Many incidents happened due to the failure of thermal equipment in schools. On the other hand, the most important task of electricity distribution companies is to provide reliable and stable electricity, which minimal blackouts and standard voltage should accompany. This research uses seasonal time series and artificial neural network approaches to provide models to predict the failure rate of one of the equipment used in two areas covered by the greater Tehran electricity distribution company. These data were extracted weekly from April 2019 to March 2021 from the ENOX incident registration software. For this purpose, after pre-processing the data, the appropriate final model was presented with the help of Minitab and MATLAB software. Also, average air temperature, rainfall, and wind speed were selected as input variables for the neural network. The mean square error has been used to evaluate the proposed models’ error rate. The results show that the time series models performed better than the multi-layer perceptron neural network in predicting the failure rate of the target equipment and can be used to predict future periods.

A topic of current interest in forestry science concerns the regeneration of degraded forests and areas. Within this topic, an important aspect refers to the time that different forests take to recover their original levels of diversity and other characteristics that are key to resume their functioning as ecosystems. The present work focuses on the premontane rainforests of the central Peruvian rainforest, in the Chanchamayo valley, Junín, between 1,000 and 1,500 masl. A total of 19 Gentry Transects of 2 × 500 m, including all woody plants ≥2.5 cm diameter at breast height were established in areas of mature forests, and forests of different ages after clear-cutting without burning. Five forest ages were considered, 5-10, 20, 30, 40 and ≥50 years. The alpha-diversity and composition of the tree flora under each of these conditions was compared and analyzed. It was observed that, from 40 years of age, Fisher’s alpha-diversity index becomes quite similar to that characterizing mature forests; from 30 years of age, the taxonomic composition by species reached a similarity of 69–73%, like those occurring in mature forests. The characteristic botanical families, genera and species at each of the ages were compared, specifying that as the age of the forest increases, there are fewer shared species with a high number of individuals. Early forests, up to 20 years of age, are characterized by the presence of Piperaceae; after 30 years of age, they are characterized by the Moraceae family.

Every year, hundreds of fires occur in the forests and rangelands across the world and damage thousands hectare of trees, shrubs, and plants which cause environmental and economic damages. This study aims to establish a real time forest fire alert system for better forest management and monitoring in Golestan Province. In this study, in order to prepare fire hazard maps, the required layers were produced based on fire data in Golestan forests and MODIS sensor data. At first, the natural fire data was divided into two categories of training and test samples randomly. Then, the vegetation moisture stresses and greenness were considered using six indexes of NDVI, MSI, WDVI, OSAVI, GVMI and NDWI in natural fire area of training category on the day before fire occurrence and a long period of 15 years, and the risk threshold of the parameters was considered in addition to selecting the best spectral index of vegetation. Finally, the model output was validated for fire occurrences of the test category. The results showed the possibility of prediction of fire site before occurrence of fire with more than 80 percent accuracy.