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Primarily generated at the interface between the wheel and the rail, railroad vibrations then propagate through the supporting soil. If these vibrations reach nearby bridges and buildings, they amplify the vibration nuisance and cause ground noise, which has detrimental effects on nearby residents, sensitive equipment, and historic structures. By analyzing measured data from metro vibration field vibration experiments, this article attempts to contribute to the body of knowledge on environmental vibration propagation patterns by offering insightful conclusions. Before analyzing the deformation response of the metro jet system (MJS) vibration isolation piles to the structure and the ground, we investigated the effect of MJS vibration isolation piles in the ground of the existing subway tunnel structure on the control of vibration of the proximate structure and conducted dynamic tests on the vibration of bridges without vibration isolation measures caused by operating subway trains. The tests determined that the acceleration of the bridge's lateral vibration exceeded the code limit; one of the contributing factors was that the bridge's structure had already sustained damage. The utilization of MJS isolation piles was also discovered to safeguard the extant bridge pile foundations. The paper presents an innovation in the form of economically viable vibration mitigation strategies that were implemented subsequent to the identification that the lateral vibration acceleration of the preexisting bridge surpassed the prescribed code standards. Considerable insight is gained regarding the design and implementation of vibration control systems for structures situated near caverns, encompassing deep foundation works. [ABSTRACT FROM AUTHOR]

Characterized by soil moisture content and plant growth, agricultural drought occurs when the soil moisture content is lower than the water requirement of plants. Microwave remote sensing observation has the advantages of all-weather application and sensitivity to soil moisture change. However, microwave remote sensing can only invert 0~5 cm of soil surface moisture, so it cannot effectively reflect the drought situation of farmland. Therefore, this study took Henan Province as the study area, used soil moisture active and passive (SMAP) satellite soil moisture data, employed NDVI, LST, and ET as the independent variables, and took the drought grade on the sample as the dependent variable. Using the 2017–2019 data as the training set and the 2020 data as the testing set, a random forest drought monitoring model with comprehensive influence of multiple factors was constructed based on the training set data. In the process of model training, the cross-validation method was employed to establish and verify the model. This involved allocating 80% of the sample data for model construction and reserving 20% for model verification. The results demonstrated an 85% accuracy on the training set and an 87% accuracy on the testing set. Additionally, two drought events occurring during the winter wheat growing period in Henan Province were monitored, and the validity of these droughts was confirmed using on-site soil moisture and the vegetation supply water index (VSWI). The findings indicated a high incidence of agricultural drought in the southwestern part of Henan Province, while the central and northern regions experienced a lower incidence during the jointing to heading and filling stages. Subsequently, leveraging the results from the random forest drought monitoring, this study conducted a time series analysis using the Mann–Kendall test and a spatial analysis employing Moran's I index to examine the temporal and spatial distribution of agricultural drought in Henan Province. This analysis aimed to unveil trends in soil moisture changes affecting agricultural drought, as observed via the SMAP satellite (NASA). The results suggested a possible significant spatial auto-correlation in the occurrence of agricultural drought. [ABSTRACT FROM AUTHOR]