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Soil erosion often leads to land degradation, agricultural production reduction, and environmental deterioration, which seriously restricts the sustainable development of regions. Clarifying the driving factors of soil erosion is the premise of preventing soil erosion. Given the lack of current research on the driving factors/force changes of soil erosion in different regions or under different erosion intensity grades, this paper pioneered to use machine learning methods to address this problem. Firstly, the widely used (Revised) Universal Soil Loss Equation ((R)USLE) framework was applied to simulate the spatial distribution of soil erosion. Then, the K-fold algorithm was used to evaluate the accuracy and stability of five machine learning algorithms for fitting soil erosion. The random forest (RF) method performed best, with average accuracy reaching 86.35%. Then, the Permutation Importance (PI) and the Partial Dependence Plot (PDP) methods based on RF were introduced to quantitatively analyze the main driving factors under different geological conditions and the driving force changes of each factor under different erosion intensity grades, respectively. Results showed that the main drivers of soil erosion in Chongqing and Guizhou were cover management factors (PI: 0.4672, 0.4788), while that in Sichuan was slope length and slope factor (PI: 0.6165). Under different erosion intensity grades, the driving force of each factor shows nonlinear and complex inhibitory or promoting effects with factor value changing. These findings can provide scientific guidance for the refined management of soil erosion, which is significant for halting or reversing land degradation and achieving sustainable use of land resources. [ABSTRACT FROM AUTHOR]

Prunus mira Koehne, a Prunus plant in the Rosaceae family, is named ཁམབུ། in Tibetan and "Guang he tao" in Chinese. It is mainly distributed in Tibet Autonomous Region, Yunnan Province, and Sichuan Province in China. It is also a rare "living fossil group" of peach genetic resources in the world. It is used in traditional Chinese medicine for the treatment of dysmenorrhea, injury, intestinal dryness, constipation, and other diseases, and is used in Tibetan medicine for the treatment of hair, eyebrows, and beard shedding. In this article, the botanical characteristics, medicinal history, modern applied research, and ethnobotanical investigation of P. mira were recorded and evaluated. P. mira was first recorded in Dumu Materia Medica. P. mira in Sichuan Province is mainly distributed in Ganzi Tibetan Autonomous Prefecture, and has certain economic and medicinal value. P. mira has high nutritional composition. It is made into high-quality edible oil, cosmetic base oil, fruit juice, fruit wine, fruit vinegar, "Liang guo", and other products. Oleic acid and linoleic acid are the main fat-soluble components of P. mira , which has an anti-inflammatory medicinal value and promotes hair growth. Its longevity and cold resistance can bring great genetic value and play an important role in maintaining peach genetic diversity. At present, there are few studies on the pharmacological effects of specific active components of P. mira and there are also few clinical studies. We can continue to study these aspects in the future. At the same time, products of P. mira have great market potential. All in all, P. mira is very worthy of further research and development. [ABSTRACT FROM AUTHOR]

• Evaluate the urban resilience from a multidimensional perspective. • Validate and analyze by using NPP-VIIRS nighttime light data. • The average urban resilience index increased from 0.027 to 0.058 from 2011 to 2021. • The coefficient of variation decreased from 0.823 in 2011 to 0.751 in 2021. • The moran's i of urban resilience increased from 0.2017 in 2011 to 0.4476 in 2021. Modern cities are facing increasingly complex challenges, and assessing urban resilience is crucial to improve their ability to withstand various types of shocks and disasters, especially in the China's North-South Seismic Belt with frequent tectonic activities and natural disasters. To address this issue, this study determined the weights of the assessment system based on the entropy weight method, and evaluated the urban resilience of four provinces in China's North-South Seismic Belt in multiple dimensions from the perspectives of society, economy, infrastructure, and ecology. Furthermore, we systematically explored the spatiotemporal trends of urban resilience and its spatial correlation from 2011 to 2021. Lastly, the assessment results were validated and analyzed by four historical earthquake cases using national polar-orbiting partnership - visible infrared imaging radiometer suite (NPP-VIIRS) nighttime light data. The findings reveal that the average urban resilience index increased from 0.027 to 0.058 from 2011 to 2021, signifying a remarkable surge of 115.42%. Sichuan emerged as a consistent frontrunner in terms of urban resilience. Overall, the study area shows a spatial distribution pattern of higher urban resilience in the east and lower resilience in the west, due to the larger population and more developed economy in the east. However, the south has a higher average annual growth rate, while the north has a lower average annual growth rate. A notable observation is the gradual reduction in the coefficient of variation of urban resilience from 0.823 in 2011 to 0.751 in 2021, indicating a decline in the disparity of resilience levels. Meanwhile, Moran's I gradually increased from 0.2017 in 2011 to 0.4476 in 2021, signifying a progressive intensification in the spatial correlation of urban resilience and an evident propensity toward aggregation. By selecting shifts in the total nighttime light index (TNLI) during representative earthquake incidents as an indirect gauge of urban resilience levels, this study finds congruence with the assessment outcomes, thereby further substantiating the precision of the urban resilience evaluations. Policymakers should prioritize the allocation of resources to less resilient cities to improve their ability to withstand and recover from disaster events. The urban resilience assessment system in this study, despite its multidimensionality, may still not be able to fully cover all the factors affecting urban resilience. This study provides a significant decision-making basis for policymakers in urban development and disaster response, as well as a useful reference for building a more robust and sustainable urban future. [ABSTRACT FROM AUTHOR]