An Underwater Target Detection Algorithm Based on Attention Mechanism and Improved YOLOv7

For underwater robots in the process of performing target detection tasks,the color distortion and the uneven quality of underwater images lead to great difficulties in the feature extraction process of the model,which is prone to issues like error detection,omission detection,and poor accuracy.Therefore,this paper proposed the CER-YOLOv7(CBAM-EIOU-RepVGG-YOLOv7)underwater target detection algorithm.To improve the algorithm’s capability to retain valid features from both spatial and channel perspectives during the feature extraction phase,we have added a Convolutional Block Attention Module(CBAM)to the backbone network.The Reparameterization Visual Geometry Group(RepVGG)module is inserted into the backbone to improve the training and inference capabilities.The Efficient Intersection over Union(EIoU)loss is also used as the localization loss function,which reduces the error detection rate and missed detection rate of the algorithm.The experimental results of the CER-YOLOv7 algorithm on the UPRC(Underwater Robot Prototype Competition)dataset show that the mAP(mean Average Precision)score of the algorithm is 86.1%,which is a 2.2%improvement compared to the YOLOv7.The feasibility and validity of the CER-YOLOv7 are proved through ablation and comparison experiments,and it is more suitable for underwater target detection.

Contrasting Drought Tolerance in Two Apple Cultivars Associated with Difference in Leaf Morphology and Anatomy

Apple is one of the most important fruit trees in temperate zones, and is cultivated widely throughout the world. Drought stress affects the normal growth of apple tree, and further affects fruit yield and quality. The present study examined the effects of drought on photosynthesis and water use efficiency (WUE) of two apple cultivars (Honeycrisp and Yanfu 3) that differ in drought tolerance. The results showed that the photosynthetic rate decreased in response to drought stress for both cultivars, with significant differences in intensity. Values for net photosynthetic rate (Pn) in stressed Yanfu 3 remained significantly lower than in the controls, while, for Honeycrisp, only a slight drop in photosynthesis. Similarly, stomatal conductance (Gs), intercellular CO2 concentration (Ci), transpiration rate (Tr) were markedly reduced in Yanfu 3 under drought stress. However, Honeycrisp showed only minor changes. Under drought stress, the contents of Chl a, Chl b and Chl t in Yanfu 3 were all decreased significantly compared with the control. However, little difference in Honeycrisp was noted between stressed plants and controls. Values for WUE in stressed Yanfu 3 remained higher than in the controls from day 3 until the end of the experiment, while no significant difference was observed in Honeycrisp. Furthermore, Honeycrisp also exhibited superior physiological traits, as indicated by its anatomical and morphological characteristics. Therefore, we conclude that the superior drought tolerance of Honeycrisp was due to its anatomical and morphological characteristics, which possibly contributed to the maintenance of higher photosynthetic capacity than Yanfu 3.

Study on the Temperature of the Bridge Wire in the Initiator Used in Nuclear Explosion Valve

This paper established the mathematical model of bridge wire temperature rise under direct current condition and gave the solution. It computed bridge wire temperature by using the thermal-electric coupling method provided by ANSYS-Workbench finite element analysis software. In the end, the temperature bridge wire applied to different electric current was measured by the infrared thermal imaging temperature measurement method. The result shows that the ANSYS simulation results are in agreement with the theoretical calculation and the experimental results. It is feasible to compute bridge wire temperature of initiator by using ANSYS-Workbench software, and it is an important method to analyze complex structure of pyrotechnics.