Rapid Mold Detection in Chinese Herbal Medicine Using Enhanced Deep Learning Technology.

Mold contamination poses a significant challenge in the processing and storage of Chinese herbal medicines (CHM), leading to quality degradation and reduced efficacy. To address this issue, we propose a rapid and accurate detection method for molds in CHM, with a specific focus on , using electronic nose (e-nose) technology. The proposed method introduces an eccentric temporal convolutional network (ETCN) model, which effectively captures temporal and spatial information from the e-nose data, enabling efficient and precise mold detection in CHM.

Comparison of arterial stiffness and ultrasound indices in patients with and without chronic obstructive pulmonary disease.

Objective: The purpose of this study was to compare arterial stiffness and ultrasound indices in patients with and without chronic obstructive pulmonary disease.

Methods: In our retrospective study, 83 chronic obstructive pulmonary disease patients were assigned to the chronic obstructive pulmonary disease group and 80 healthy controls were enrolled. Pearson's correlation analysis software was used to analyze the correlation between arterial stiffness (including brachial ankle pulse wave velocity and ankle-brachial blood pressure index) and ultrasound index (including resistance index, pulsatility index, and intima-media thickness) at the carotid artery in chronic obstructive pulmonary disease patients.