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Abstract Surface‐enhanced Raman scattering (SERS) imaging technology faces significant technical bottlenecks in ensuring balanced spatial resolution, preventing image bias induced by substrate heterogeneity, accurate quantitative analysis, and substrate preparation that enhances Raman signal strength on a global scale. To systematically solve these problems, artificial intelligence techniques are applied to analyze the signals of pesticides based on 3D and dynamic SERS imaging. Utilizing perovskite/silver nanoparticles composites (CaTiO3/Ag@BONPs) as enhanced substrates, enabling it not only to cleanse pesticide residues from the surface to pulp of fruits and vegetables, but also to investigate the penetration dynamics of an array of pesticides (chlorpyrifos, thiabendazole, thiram, and acetamiprid). The findings challenge existing paradigms, unveiling a previously unnoticed weakening process during pesticide invasion and revealing the surprising permeability of non‐systemic pesticides. Of particular note is easy to overlook that the combined application of pesticides can inadvertently intensify their invasive capacity due to pesticide interactions. The innovative study delves into the realm of pesticide penetration, propelling a paradigm shift in the understanding of food safety. Meanwhile, this strategy provides strong support for the cutting‐edge application of SERS imaging technology and also brings valuable reference and enlightenment for researchers in related fields.

The Bohai Sea is the sea area with the worst ice condition in China, and the ice loads significantly threaten the safety of structures in the sea. The intense vibrations of the pile-supported bridge under stochastic ice loads will increase the fatigue damage of a bridge structure and reduce the fatigue life of a bridge structure. In the present study, a comprehensive analysis model is presented to study fatigue damage for pile-supported bridges under ice loads in Bohai Sea. On the basis of measured statistical data of ice parameters and stochastic ice loads spectrum of Bohai Sea, the time histories of the stochastic ice loads of Bohai Sea are simulated. Fatigue damage analysis is carried out in time domain utilizing the finite element method considering soil and bridge structure interaction. The effect of soil conditions and water depth on the cumulative fatigue damage of the pile-supported bridges is studied. Numerical results indicate that in comparison with stiff soil conditions, pile-supported bridges in soft oil conditions can increase the cumulative fatigue damage substantially; pile-supported bridges in deep water also can increase the cumulative fatigue damage obviously. The study presented the first danger position of cumulative damage of the pile cross section under stochastic ice loads. The findings of this study can be used to fatigue damage evaluation and bridge construction in the ice-covered sea area.

Extreme value of vehicle load plays an important role in bridge design and risk assessment. Peaks over threshold (POT) is a method commonly used in extreme load estimation. The selection of thresholds for the POT method is extremely crucial, but the selected optimal threshold varies under different test criteria. Therefore, a method to select the suitable threshold is developed based on multiple criteria decision analysis (MCDA) in the paper. In MCDA, Chi-Square (χ2) test, Kolmogorov–Smirnov (K–S) test, and Root Mean Square Error (RMSE) in probability distribution functions (PDF) are employed as the test criteria and the weight of these criteria is calculated using the entropy method. Finally, vehicle loads obtained from simulation and field measurement are adopted to validate the effectiveness and feasibility of the proposed method. The results indicate that the proposed MCDA is a useful and complementary tool for threshold selection in the extreme value analysis.