The instability of perilous rock is mostly manifested as sudden collapse and failure without obvious displacement characteristics. Therefore, it is difficult to achieve the purpose of monitoring and early warning by conventional displacement monitoring. But the existing stability monitoring indicators are mostly deformation, stress, and strain. There is a problem that the stability evaluation parameters are inconsistent with the monitoring parameters. Taking sliding-type perilous rock as the research object, the structural plane is assumed to be homogeneous and isotropic, and linear elastic deformation in the amplitude range. Based on the dynamic theory and limit equilibrium model, the quantitative relationship model can be established involving safety factors, natural vibration frequency, structural surface bonding area, elastic modulus, and mass. The remote laser vibrometer is used to monitor the natural vibration frequency of the sliding-type perilous rock on the slope of the Huangzangsi Hydrojunction, and the stability evaluation of the perilous rock is achieved based on the quantitative relationship model between the safety factor and the natural vibration frequency. In this way, the frequency of slipping perilous rock stability evaluation and safety factor can be monitored. The results are basically the same with the safety factor calculated by the limit equilibrium method, indicating that the method is correct and feasible. The research has high theoretical significance and practical value for the safety monitoring and advanced warning of sliding perilous rock.

Against the backdrop of the ongoing advancement of China’s dual-carbon goals and the coordinated strategy for ecological protection and high-quality development in the Yellow River Basin (YRB), it is important to clarify the spatiotemporal dynamics of air pollution in the densely populated urban agglomerations of the mid–lower YRB. Using station-based daily observations from 2015 to 2024, this study examines six major air pollutants (PM_2.5, PM₁₀, CO, NO₂, O₃ and SO₂) across the Shandong Peninsula, Central Plains, and Guanzhong Plain urban agglomerations. Sen’s slope estimator and the Mann–Kendall test are applied to quantify long-term trends, while partial correlation analysis and the GeoDetector model are used to diagnose pollutant co-variations and the drivers of spatial heterogeneity. Results indicate that while PM_2.5, PM₁₀, NO₂, SO₂, and CO concentrations significantly decreased, O₃ exhibited a statistically significant upward trend (Z = 2.32, p = 0.02), particularly with pronounced summer maxima. PM_2.5 shows clear seasonal variation, with elevated levels during winter and reduced levels during summer. Marked spatial contrasts are also observed: elevated particulate matter and CO are concentrated in the northern part of the Central Plains, while higher O₃ levels are more evident in coastal areas, particularly within the Shandong Peninsula urban agglomeration. In terms of inter-pollutant relationships, particulate matter and CO are positively associated with SO₂, whereas O₃ is negatively correlated with NO₂. GeoDetector results further suggest that air temperature, wind speed, and topography are the key factors associated with the spatial differentiation of pollutant levels; notably, the interaction between wind speed and temperature provides the greatest explanatory power, with effects that vary seasonally. These findings provide a scientific basis for region-specific air-pollution control and for advancing the co-benefits of carbon reduction and pollution mitigation in the YRB.

In this work, we propose a novel dual optical frequency comb (DOFC) generation scheme based on dual cascaded difference frequency generation (DCDFG). Feasible designs are introduced that enable the two sets of cascaded optical waves, initially generated by DCDFG in an aperiodically periodically poled lithium niobate (APPLN) crystal with a pump wave and two signal waves, then transferred to high-order Stokes waves by oscillations of cascaded Stokes waves and the optimization of phase mismatching of each-order DCDFG; finally, a DOFC was constructed. We demonstrate a high-performance DOFC with characteristics of high repetition frequency difference, tunable repetition frequency difference, high flatness, and a tunable spectral distribution range by providing a theoretical framework. We argue that the scheme proposed in this work is promising for achieving a high-quality DOFC.

A thorough understanding of the resistivity response characteristics of ethanol-contaminated soil is of great significance for the development of non-destructive geophysical detection techniques and for supporting contaminated site investigation and assessment. This experimental study aims to systematically investigate the resistivity behavior of ethanol-contaminated sandy soils, with a focus on the coupled mechanisms of multiple factors, including water content, ethanol concentration, particle size distribution, and contamination time. It is hypothesized that water content serves as the dominant factor controlling resistivity, whereas ethanol concentration and contamination time regulate resistivity by altering the physicochemical properties of the pore fluid. Under laboratory conditions, silt, fine sand, and medium sand were selected as the test materials. Resistivity was systematically measured using a Miller Soil Box with increasing water content, Wenner array configuration across varying water contents (3–24%), ethanol concentrations (40–98%), and contamination durations (0–144 h). The experimental results indicate the following: (1) Regardless of the presence of ethanol contamination, the resistivity of sandy soil decreases with increasing water content following a power-law relationship. The decrease is most pronounced at low water contents (3–9%), and gradually stabilizes at higher water contents. The results show that, at a constant water content, resistivity systematically and consistently follows the order: silt > medium sand > fine sand. (2) The influence of ethanol concentration on resistivity is constrained by water content levels, and the overall increase in resistivity is primarily attributed to ion dilution and the obstruction of conductive pathways. (3) Over time, resistivity exhibits a two-stage increasing trend, associated with ethanol volatilization and water loss. Resistivity changes in fine sand samples contaminated with ethanol at concentrations ranging from 75% to 95% follow a two-stage pattern. The initial phase of growth is characterized by a gradual increase over a period of 0–48 h, followed by a more rapid increase during the subsequent phase, which extends from 48 to 144 h. The results show that higher initial ethanol concentrations enhance the sensitivity of resistivity to temporal changes. Comprehensive analysis indicates that the resistivity variation mechanism under multi-factor coupling conditions can be summarized as follows: the water content is the dominant factor in the regulation of the conductive pathways; the particle size distribution determines pore structure and the characteristics of the particle interface; ethanol concentration and contamination time dynamically alter pore fluid properties, collectively regulating the resistivity response. Although the experiments were conducted under controlled laboratory conditions and the results have certain limitations, they provide a preliminary reference for interpreting resistivity responses in relatively homogeneous sandy contaminated sites and offer theoretical support for the application of resistivity methods in contamination identification and dynamic monitoring.