Guangdong Testing Institute for Product Quality Supervision

ABSTRACT Acoustic emission (AE) technology is commonly employed to identify damage modes in carbon fiber–reinforced composites under deformation, yet remains challenging due to signal aliasing in AE data. This study investigates AE‐based damage characterization in two‐dimensional triaxially braided composites and proposes a comprehensive signal processing framework to address overlap in both the time and frequency domains. A novel AE signal segmentation method is developed by integrating root mean square (RMS) analysis with the Akaike Information Criterion (AIC) to improve the resolution of temporally overlapping AE events. For spectral decomposition, variational mode decomposition (VMD) is employed, with parameters adaptively optimized via the neural population dynamic optimization algorithm (NPDOA). A new similarity metric continuous wavelet transform‐based image subtraction (CWTIS) is introduced and combined with permutation entropy to construct a dual‐objective fitness function for VMD parameter tuning. Noise‐dominated components are filtered based on CWTIS scores, and physically relevant intrinsic mode functions (IMFs) are reconstructed into interpretable sub‐signals. Experimental validation through uniaxial tensile tests demonstrates that the proposed framework increases the number of detected AE events by 136% and significantly improves cluster separability across damage modes. Notably, the detection of matrix cracking signals improves by over 1100%, revealing previously masked low‐amplitude damage. Overall, the proposed method enhances the fidelity, granularity, and interpretability of AE signals and provides a robust tool for damage diagnosis and structural health monitoring in advanced composite materials.

ABSTRACT Traditional shielding materials face limitations such as high weight and poor flexibility, driving interest in polymer‐based composites. This study investigates lightweight and flexible LDPE/EPDM thermoplastic vulcanizates (TPVs) with conductive carbon black (CB) for electromagnetic interference (EMI) shielding. We explored the effects of the processing sequence of adding CB before and after dynamic vulcanization and CB content on the mechanical, thermal, and electrical properties of TPVs. By controlling the processing sequence, CB was selectively dispersed within the continuous LDPE phase, forming more complete conductive networks. With 45 wt% CB, the TPV exhibited excellent electrical conductivity and EMI shielding performance. Mechanical and thermal analyses showed that with the increase in CB content, modulus and thermal stability were enhanced while maintaining flexibility and processability. This work presents a scalable approach for developing lightweight, high‐performance EMI shielding materials for emerging applications.

This study aimed to identify the lactonase gene in Limosilactobacillus fermentum FUA033 that facilitates the conversion of ellagic acid into urolithin A. Lactonase gene candidates were identified genome analysis. A series of overexpression, knockout, and complementation strains of these candidate genes were subsequently generated. The urolithin A yield of the lac1563 knockout strain was significantly reduced compared to the wild-type strain, whereas the overexpression strain exhibited a markedly higher yield. The complementation strain showed no significant difference in urolithin A yield relative to the wild-type strain. In contrast, alterations in the lac329 gene did not significantly impact urolithin A production compared to the wild-type strain. Additionally, the candidate lactonase genes were cloned and heterologously expressed in Escherichia coli. The recombinant lactonase derived from the lac1563 gene, unlike that from the lac329 gene, demonstrated activity toward ellagic acid. Optimal activity of the lac1563 lactonase occurred at 37 °C and pH 7.0. Enzyme activity was notably enhanced by Mn2+ and Co2+, while inhibited by Zn2+ and Cu2+. These findings contribute valuable insights into the metabolic pathway of ellagic acid conversion to urolithin A and establish the lac1563 gene as a promising candidate for biotechnological applications aimed at urolithin A production.

Afacile and highly specific optical sensing strategy is established for glyphosate (GLYP) detection using structure-switching signaling aptamers (F-SSSAs) with fluorescence signal reporting functionality. The strategy involves two domains: the FITC-labeled signal transduction domain for fluorescence signal reporting, while the functional domain (specific structure-switching aptamers) controls the target recognition. Graphene oxide (GO) works as a robust F-SSSAs quencher in the absence of GLYP. However, the F-SSSAs structure is switched in the presence of GLYP, prominently affecting the interaction with GO. The fluorescence of the structure-switching signaling aptamer-based sensing system is subsequently restored. The present strategy exhibits two dynamic linear relationships for GLYP detection in the ranges 0.2 to 80 ng·mL-1 and 100 to 800 ng·mL-1, with a low detection limit (LOD) of 0.07 ng·mL-1. Significantly, the proposed sensing system has been successfully utilized to detect GLYP in water, soil, and rice, demonstrating its potential applications in GLYP monitoring.