Hunan City University

Abstract Achieving high-precision imaging of hidden cracks in tunnel linings is challenging due to strong interference from rebar clutter. To address this issue, we propose a collaborative imaging method that integrates Edge-Enhanced High-Resolution Reverse Time Migration (EEHR-RTM) with Adaptive Frequency-Wavenumber Migration (A-FKM). The EEHR-RTM method accurately reconstructs the geometric contours of both rebars and cracks, while the A-FKM framework effectively suppresses strong rebar interference signals and preserves the amplitude of defect reflections. Validation through FDTD simulations and laboratory model tests demonstrates that, compared to conventional RTM, the proposed method significantly improves key quantitative metrics: the Signal-to-Noise Ratio increases from 5.40 dB to 29.58 dB, the Gradient Energy increases from 2.417×10⁹ to 1.110×10¹⁸, and the Edge Density increases from 0.004 to 0.027. Furthermore, compared to traditional F-K migration, LRSD, and SVD, the proposed method achieves a maximum rebar clutter removal rate of up to 87.9%. This approach enables high-definition imaging of millimeter-scale cracks even under strong rebar interference, providing a reliable technical pathway for the nondestructive testing of hidden defects in tunnel linings.

Breast cancer is a common malignancy where the immune system plays a key role in disease progression and treatment response. SERPINA1 is an immune-related gene, but its function in breast cancer remains unclear. This study explored the expression, immune role, and prognostic value of SERPINA1 in breast cancer. We analyzed data from TCGA and other public databases to evaluate SERPINA1 expression and performed Western blot and qPCR experiments for validation. Various bioinformatics tools were used to assess immune-related functions, identify differentially expressed genes, conduct pathway enrichment analyses, and construct a prognostic risk model. External datasets were used for validation, and immune activity and drug sensitivity were compared between different risk groups. SERPINA1 was significantly overexpressed in breast cancer tissues compared to normal tissues, and high expression was associated with better overall survival. High SERPINA1 expression correlated with enhanced activation of immune-related pathways, such as T and B-cell signaling. Patients with high SERPINA1 levels showed higher immune and stromal scores, increased infiltration of CD8⁺ T cells, macrophages, and dendritic cells, and elevated expression of immune checkpoint molecules. A prognostic model based on SERPINA1-associated immune genes effectively stratified patient survival risk and was validated in multiple external datasets. Patients in the low-risk group had stronger immune activity and were more sensitive to various chemotherapy and targeted drugs, suggesting the model’s potential in guiding personalized treatment. SERPINA1 is closely linked to favorable prognosis and an active immune microenvironment in breast cancer. The SERPINA1-based prognostic model may be useful for survival prediction and personalized immunotherapy strategies.

ABSTRACT To elucidate the mechanism of strength development in asphalt mixtures during compaction, this study selected stone mastic asphalt (SMA) as the research object. The compaction process was disintegrated into five different compaction stages based on superpave gyratory compaction (SGC) and Marshall impact compaction (MIC) methods. The uniaxial compressive (UC) strength, indirect tensile (IDT) strength and uniaxial penetration (UP) strength under various compaction degrees were obtained. Through comparative analysis, the study identified the strength evolution patterns of SMA mixtures under two compaction methods, established a quantitative relationship between the compaction degree and strength, and subsequently proposed a strength evolution model tailored for SMA mixtures. The findings indicated that there was an obvious power function increasing relationship between the compaction degree and the strength of SMA mixtures. Compaction minimally affects strength initially but significantly in later stages. The UP strength increased the most, while the IDT strength increased the least during compaction. Repeated experiments demonstrated that the strength evolution model proposed in this study exhibits high accuracy under two compaction methods, two SMA gradations and all three loading modes. The results can provide the theoretical and scientific basis for revealing the strength formation characteristics of SMA mixture.