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.

Root turnover is a key process of terrestrial ecosystem carbon cycle, which is of great significance to the study of soil carbon pool changes and global climate change. However, because there are many measurement and calculation methods of root turnover, the results obtained by different methods are quite different, and the current research on root turnover of forest ecosystem on the global regional scale is not sufficient, so the change law of root turnover of global forest ecosystem is still unclear. By collecting literature data and unifying the calculation method of turnover rate, this study integrates the spatial pattern of fine root turnover of five forest types in the world, and obtains the factors affecting fine root turnover of forest ecosystem in combination with soil physical and chemical properties and climate data. The results showed that there were significant differences in fine root turnover rate among different forest types, and it gradually decreased with the increase of latitude; the turnover rate of fine roots in forest ecosystem is positively correlated with annual average temperature and annual average precipitation; fine root turnover rate of forest ecosystem is positively correlated with soil organic carbon content, but negatively correlated with soil pH value. This study provides a scientific basis for revealing the law and mechanism of fine root turnover in forest ecosystem.

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.

With the increasing call for sustainable development, cities’ demand for green innovation has also been growing. However, relatively little research summarizes the influencing factors of urban green innovation. In this study, we conducted a visual analysis of 1193 research articles on green innovation in cities from the Web of Science core database using bibliometrics and visualization analysis. By analyzing co-occurrence, co-citation, and high-frequency keywords in the literature, we explored the current research status and development trends of influencing factors of urban green innovation and summarized the research in this field. The study found that collaboration among authors and institutions in this field needs to be strengthened to a certain extent. In addition, the study identified the research hotspots and frontiers in the field of urban green innovation, including “management”, “diffusion”, “smart city”, “indicator”, “sustainable city”, “governance”, and “environmental regulation”. Among them, “management”, “governance”, “indicator”, and “internet” are the research frontiers in this field, which are expected to have profound impacts on the future development of urban green innovation. The co-citation analysis results found that China has the highest research output in this field, followed by the United States, England, Australia, and Italy. In conclusion, this study uses CiteSpace software to identify important influencing factors and development trends of urban green innovation. Urban green innovation has gradually become a norm for social and collective behavior in the process of concretization, interdisciplinary development, and technological innovation. These findings have important reference value for promoting research and practice of urban green innovation.