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The looking-down mode of space airship bistatic radars faces complex sea–land clutter, and the mode of wide-range surveillance and the over-sight detection of the satellite platform generates a low SNR and range–Doppler ambiguity. The method traditionally used involves the transmission of multiple Pulse Repetition Frequencies (PRFs) and correlating them to solve the ambiguity. However, with a low SNR, the traditional disambiguation fails due to the large number of false alarms and target omissions. In order to solve this problem, a new algorithm for multi-target joint detection and range–Doppler disambiguation based on an ambiguity matrix is presented. Firstly, all possible state values corresponding to the ambiguous sequence are filled into the ambiguity matrix one by one. Secondly, the state values in the matrix cell are divided into several groups of subsequences according to the PRF. By disambiguating multiple sets of subsequences, performing subsequence fusion, and then undertaking point aggregation, the targets can be effectively detected in scenarios with a strong clutter rate, the false alarms can be suppressed, and the disambiguation of the range and Doppler is completed. The simulation shows that the proposed algorithm has the strong ability to detect targets and perform ambiguity resolution in the scenario of a multi-target and multi-false alarm. [ABSTRACT FROM AUTHOR]

The real-time pedestrian detection algorithm requires the model to be lightweight and robust. At the same time, the pedestrian object detection problem has the characteristics of aerial view Angle shooting, object overlap and weak light, etc. In order to design a more robust real-time detection model in weak light and crowded scene, this paper based on YOLO, raised a more efficient convolutional network. The experimental results show that, compared with YOLOX Network, the improved YOLO Network has a better detection effect in the lack of light scene and dense crowd scene, has a 5.0% advantage over YOLOX-s for pedestrians AP index, and has a 44.2% advantage over YOLOX-s for fps index.

As a natural carrier protein, zein was intensively studied for the construction of a flavonoid delivery system. Chrysin has presented superior tumor‐resistant, anti‐inflammatory, and anti‐oxidation potentials among the flavonoid candidates in clinical practice. However, due to inadequate research, the binding mechanism and structural affinity of zein to chrysin are still indeterminate. Therefore, multispectral methods were employed to explore the molecular interaction of zein and chrysin in this work. These techniques showed that chrysin reduced the intrinsic fluorescence of zein via a static process and that the interaction between zein and chrysin was mainly driven spontaneously by hydrophobic forces. Additionally, the experimental results revealed the changed microenvironment in the vicinity of tyrosine and affected secondary structure in the presence of chrysin, indicating zein's conformation were altered by chrysin. This work provided comprehensive insight into the combination of plant‐derived protein (zein) and flavonoids (chrysin) and helped rationalize the protection, transportation, and release of chrysin through a zein‐based delivery system. [ABSTRACT FROM AUTHOR]