Insight into the compositional variation of volatile and polar compounds of Radix Bupleuri from different processing technologies by GC-MS and UHPLC-Q-TOF/MS metabolomics.

INTRODUCTION: Insight into comparing key active ingredients of Radix Bupleuri (RB) based on different processing technologies is a key step to reveal the material basis of drug efficacy and a challenging task for developing traditional Chinese medicine (TCM). OBJECTIVE: This work aims to establish a comprehensive comparative analysis method of TCM and its processed products, which can be used to analyze the changing trend of active components of RB before and after processing. METHODS: First, RB was processed with rice vinegar, rice wine, and honey. Then, ultra-high-performance liquid chromatography (UHPLC) and gas chromatography (GC) coupled with mass spectrometry (MS) technology as well as multiple statistical analyses were used to comprehensively evaluate the compositional variation of polar and volatile compounds in RB under different processing processes. Meanwhile, in UHPLC-MS, a sequential window acquisition of all theoretical fragment ion spectral and information-dependent acquisition mutual authentication (SIMA) was developed. RESULTS: A total of 30 polar components and 33 volatile components were identified as chemical markers (mainly type II saikosaponins, terpenes, and fatty acid esters). These may be the material basis for giving unique pharmacological activities to RB and its processed products. CONCLUSIONS: These findings provided a solid foundation for the differentiated clinical application of RB, and the SIMA method held great potential for achieving accurate analysis of TCM processing ingredients.

YFDM: YOLO for detecting Morse code.

With the increasing complexity of the shortwave communication environment, the efficiency and accuracy of the manual detection of Morse code no longer meet actual needs. Therefore, this paper proposes a Morse code detection algorithm called YFDM. For the time-frequency image of the received signal, a combination module of deformable convolution and C3 is used to enhance the backbone network's attention to the abstract semantics and location information of Morse code. GSConv and VOV-GSCSP modules are used to build a lightweight neck network. Finally, the confidence propagation cluster (CP-Cluster) algorithm is used to filter the detection frame. In an ablation experiment, the parameters and giga floating-point operations per second (GFLOPs) of YFDM were 5.961 M and 9.74 G, respectively, 15.11% and 38.9% less than those of YOLOv5. Moreover, when WIoUv1 was used as the loss function of the bounding box, the AP0.5:0.95 and frames per second (FPS) values of the algorithm reached the highest values, 0.68 and 72.4. The experimental results indicate that the algorithm can effectively reduce the weight of the model while ensuring the detection accuracy and inference speed.