Based on the research on 31 provincial-level administrative regions at the end of 2022, we used the geographic concentration index, geographic imbalance index, SPSS and ARCGIS spatial analysis techniques to study the spatial distribution, distribution factor correlation, and accessibility of national 5A-level scenic spots. The research results show that the overall distribution of my country's 5A-level scenic spots is unbalanced, with a low degree of concentration, showing a pattern of denseness in the east and sparseness in the west, with large inter-provincial differences. The density of traffic highways is positively correlated with the distribution density of 5A-level scenic spots. The traffic lines in the central and eastern regions are dense, and there are a large number of 5A-level scenic spots, especially the Beijing-Tianjin-Hebei region, the Yangtze River Delta region, and the middle and lower reaches of the Yangtze River and Yellow River. Therefore, the spatial distribution of China's 5A-level tourist attractions is mainly affected by the interaction of economic, transportation and social factors, among which GDP, transportation network and attraction of scenic spots are the most critical factors. These research results can provide a reference for optimizing the spatial layout of China's scenic resources and promoting regional socio-economic development.

Infrared thermal imaging technology is another new branch for medical imaging after traditional medical imaging technologies such as X-ray, ultrasound and magnetic resonance (MRI). It has the advantages of noninvasive, nondestructive, simple and fast. Its application can radiate multiple clinical departments. This paper mainly expounds the principle, influencing factors of medical infrared thermography and its application in radiation protection and other medical fields.

High-quality development in China requires higher vocational education, scientific and technological innovation, and sustainable economic development. The spatial distribution patterns of these factors show higher levels in the east and coastal areas compared to the west and inland regions, emphasizing the need for coupling coordination with the social economy. This study examines the impact of sustainable economic development on the coupling coordination degree using the spatial Durbin model. The results show a positive promotion and spillover effect, with regional variations. The main factors affecting the difference in coupling coordination are the amount of technology market contracts, fiscal expenditure on science and technology, patent application authorizations, tertiary industry output value, and the number of R&D institutions. According to the grey prediction model, the coupling coordination degree is expected to increase from 2022 to 2025, but achieving primary coordination may still be challenging in some areas. Therefore, strategies that utilize regional characteristics for coordinated development should be developed to improve the level of coupling coordination and create a mutually beneficial environment.

With the continuous development and rapid progress of Internet technology, the technology of “Internet +” has been widely used in almost all walks of life, including education. The new learning mode of “Internet + education” is changing learners’ learning habits, and this learning mode has become a hot issue that scholars pay attention to. Although there is much research on blended learning, the research on the influencing factors of blended learning in Chinese private colleges and universities is limited. In this paper, the questionnaire was designed based on the theory of planning behavior and the technical acceptance model theory, and distribute these questionnaires to undergraduates at Harbin Cambridge University, a private university in China, and 162 valid questionnaires were collected. Analysis was performed by multiple linear regression and structural equation model method. It is found that college students’ blended learning effect is positively correlated with perceived usefulness, interactive behavior, and learning acceptance, while perceived ease of use and learning atmosphere have no significant influence on the learning effect. This study further found that perceived usefulness and interactive behavior can influence the effect of blended learning through the mediating effect of learning acceptance. The results of this study provide a new idea for the study of blended learning; that is, students will know how to improve the effectiveness of blended learning, and also provide a valuable reference for teachers to solve the problem of how to improve the quality and effectiveness of blended classroom teaching.

The issue of quality of higher vocational education in China has become a common concern in all aspects of society, and promoting the improvement of the quality of education within higher vocational colleges is an important way to realize the high-quality development of higher vocational education. Based on the self-constructed five-dimensional model of factors influencing the improvement of the quality of education within higher vocational colleges, an empirical study was conducted using questionnaires and SPSS27.0 software on the teacher and student groups within 13 higher vocational colleges in Hainan Province, and the results showed that the teacher groups of different genders, titles, ages, academic qualifications and disciplines as well as the student groups of different genders and admission modes have different opinions on factors such as the level of governance, education and teaching, the integration of industry and education, student development and policy guarantees; and that there are different degrees of perception differences between teachers’ and students’ groups on the effect of internal education quality improvement. In order to promote the internal quality improvement of higher vocational colleges, it is necessary to improve the construction of modern university system to enhance the governance level, deepen the integration of production and teaching to innovate the education and training mode of talents, promote the development of the whole chain of education to improve the comprehensive quality of students, strengthen the construction of teaching staff to deepen the reform of education and teaching, and innovate the internal education policy and system to regulate the management order.

Based on the population change data of 2005–2009, 2010–2014, 2015–2019 and 2005–2019, the shrinking cities in Northeast China are determined to analyze their spatial distribution pattern. And the influencing factors and effects of shrinking cities in Northeast China are explored by using multiple linear regression method and random forest regression method. The results show that: 1) In space, the shrinking cities in Northeast China are mainly distributed in the “land edge” areas represented by Changbai Mountain, Sanjiang Plain, Xiaoxing’an Mountain and Daxing’an Mountain. In terms of time, the contraction center shows an obvious trend of moving northward, while the opposite expansion center shows a trend of moving southward, and the shrinking cities gather further; 2) in the study of influencing factors, the results of multiple linear regression and random forest regression show that socio-economic factors play a major role in the formation of shrinking cities; 3) the precision of random forest regression is higher than that of multiple linear regression. The results show that per capita GDP has the greatest impact on the contraction intensity, followed by the unemployment rate, science and education expenses and the average wage of on-the-job workers. Among the four influencing factors, only the unemployment rate promotes the contraction, and the other three influencing factors inhibit the formation of shrinking cities to various degrees.