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Vessel-shaped fish cages are a new type of large aquaculture structure consisting of a floating body, steel frames, net system, and mooring system. The diffraction and radiation waves induced by the floating body can disturb the velocity field and induce additional changes to the hydrodynamic loads on the nets. In this paper, the velocity transfer functions around the nets induced by the diffraction and radiation waves are obtained and the effects of floating body on the forces of the nets are calculated by the Morison equation. By performing the iterations between the motion of floating body and loads on the nets, the fully coupled dynamic response of motion-disturbing velocity field-net loads is realized. Finally, the effects of diffraction and radiation waves on motion response, tension in the net twine, volume reduction, and connector loads are investigated. The results show that the influences of disturbing velocity field on cage motion response and volume reduction are not obvious, but they can lead to a significant increase in the tension in net twine and connector loads, which can provide helpful reference for the structural strength analysis and safety design of vessel-shaped fish cages.

Marine platform equipment， continuously exposed to the harsh marine environment， is persistently threatened by corrosion.Particularly， the irregular steel structuresof equipment are more susceptible to corrosion failure due to the synergistic effects of mechanical and electrochemical factors， significantly reducing equipment lifespan and Bringing great risks and hidden dangers to safety production.In this paper， the corrosion environment and corrosion laws of different zones of the marine ranch platform were briefly analyzed， especially the splash zone of the marine platform where the corrosion was the most serious.In order to strengthen the protection of this short board area， several widely used anti-corrosion technologies and their corresponding advantages and disadvantages were introduced.On this basis， a new type of coating anti-corrosion technology of multi-layered mineral grease coating was introduced， which could effectively prolong the service life of the marine ranch platform，providing a strong guarantee for the safe operation of the marine platform，and a certain reference for the long-term anticorrosion technology research of our country’s marine ranch platforms.

Aiming at improving the real-time performance and accuracy of UAV autonomous landing, a landing marker detection method based on deep learning is proposed. Firstly, the lightweight network MobileNetv2 is used as the backbone network for feature extraction. Secondly, drawing on the network structure of YOLOv4, depthwise separable convolution is introduced to reduce the number of parameters without affecting model performance. Then, a feature pyramid module based on skip connection structures is proposed. With this module, the feature maps output from the backbone can be stitched and the detail information and semantic information can be fused to obtain features with stronger characterization capability. Finally, the detection head is optimized by depthwise separable convolution to complete the target detection task. Experiments are conducted on the Pascal VOC dataset and the landing marker dataset. The results show that the improved detection algorithm effectively reduces the computational and parameter complexity of the model, improves the detection speed, and can meet the accuracy requirements of autonomous UAV landing.

This paper introduces a flexible statistical model for analyzing zero-inflated continuous data, which involves a novel zero-inflated Rayleigh (ZIR) distribution. The moment, entropy, order statistics and other structural properties of this distribution are derived. Some interesting conclusions are drawn while discussing the interrelationships between various extropies. Parameters of the ZIR distribution are estimated by both moments estimation and maximum likelihood estimation, and the properties of these estimators are investigated.

Aiming at the new coronavirus that appeared in 2019, which has caused a large number of infected patients worldwide due to its high contagiousness, in order to detect the source of infection in time and cut off the chain of transmission, we developed a new Chest X-ray (CXR) image classification algorithm with high accuracy, simple operation and fast processing for COVID-19. The algorithm is based on ConvNeXt pure convolutional neural network, we adjusted the network structure and loss function, added some new Data Augmentation methods and introduced attention mechanism. Compared with other classical convolutional neural network classification algorithms such as AlexNet, ResNet-34, ResNet-50, ResNet-101, ConvNeXt-tiny, ConvNeXt-small and ConvNeXt-base, the improved algorithm has better performance on COVID dataset. [ABSTRACT FROM AUTHOR]

The issue of toxicity and chemical stability are two concerns for organic–inorganic hybrid perovskites, impeding their further commercial applications. Double perovskite (CH3NH3)2SnI6 with a bandgap of 1.81 eV and stable chemical valence of Sn (+4) is considered as a promising alternative. By first-principles calculations, the electronic properties, defect physics, and interface engineering of the perovskite are investigated in this work. It is found that (i) MA2SnI6 has a direct bandgap with a large dispersion of a lower conduction band. Due to the direct I 5p–5p transition between band edges, the light absorption can be as high as 105 cm−1 in the visible range. (ii) An Sn rich and I poor condition is suggested when MA2SnI6 is used as an electron transporting material (ETM) because of its high n-type electronic conductivity. An Sn poor and I rich condition is proposed when MA2SnI6 is prepared for photovoltaic application, because it can suppress the formation of non-radiation centers. (iii) ICBA and Spiro are proposed to be suitable ETM and hole transporting material, respectively, in MA2SnI6 based solar cells. [ABSTRACT FROM AUTHOR]

Cu2ZnGeS4 is a promising semiconductor that has potentially wide applications. Intrinsic stability and electronic properties of the Cu2ZnGeS4 surface are investigated in this work. The surfaces are stabilized by defects that are found to show diverse physics from that of the bulk. Under Cu-rich conditions, the acceptor-like Cu-enriched and Zn-deficient defects dominate both in the bulk and on the surface. However, under Cu-poor conditions, acceptor-like Cu-deficient defects dominate in the bulk, whereas donor-like Cu-deficient and Zn-enriched defects dominate on the surface. Therefore, an n-p type inversion occurs at the area between the bulk and surface. Moreover, among the possible surface con figurations, only the 2ZnCu ( 112 ¯ ) surface does not generate surface states in the band gap. Hence, the Cu-poor condition is proposed if Cu2ZnGeS4 acts as a solar cell material. The results can also be generalized to other quaternary chalcogenides. [ABSTRACT FROM AUTHOR]