In order to ensure the safe navigation of USVs (unmanned surface vessels) and real-time collision avoidance, this study conducts global and local path planning for USVs in a variable dynamic environment, while local path planning is proposed under the consideration of USV motion characteristics and COLREGs (International Convention on Regulations for Collision Avoidance at Sea) requirements. First, the basis of collision avoidance decisions based on the dynamic window method is introduced. Second, the knowledge of local collision avoidance theory is used to study the local path planning of USV, and finally, simulation experiments are carried out in different situations and environments containing unknown obstacles. The local path planning experiments with unknown obstacles can prove that the local path planning algorithm proposed in this study has good results and can ensure that the USV makes collision avoidance decisions based on COLREGs when it meets with a ship.

Abnormalities of navigation buoys include tilting, rusting, breaking, etc. Realizing automatic extraction and evaluation of rust on buoys is of great significance for maritime supervision. Severe rust may cause damage to the buoy itself. Therefore, a lightweight method based on machine vision is proposed for extracting and evaluating the rust of the buoy. The method integrates image segmentation and processing. Firstly, image segmentation technology is used to extract the metal part of the buoy based on an improved U-Net. Secondly, the RGB image is converted into an HSV image by preprocessing, and the transformation law of HSV channel color value is analyzed to obtain the best segmentation threshold and then the pixels of the rusted and the metal parts can be extracted. Finally, the rust ratio of the buoy is calculated to evaluate the rust level of the buoy. Results show that both the segmentation precision and recall are above 0.95, and the accuracy is nearly 1.00. Compared with the rust evaluation algorithm directly using the image processing method, the accuracy and processing speed of rust grade evaluation are greatly improved.

Through harmonic vibration test and harmonic simulation analysis, the first natural frequency of controller bracket did not meet the experimental test requirements that proposed by the manufacturer (greater than 2000Hz). Through modal analysis of controller bracket, we could optimize controller bracket from design structure, processing technology, handling and other aspects. Cast aluminum material ZALSi12 was adopted. After modal analysis, the frequency of optimized structure was 2374Hz, which meets the experimental requirements proposed by the manufacturer.

CAR-T cell therapy shows revolutionary promises in the therapeutic treatment of cancer, offering the possibility of long-lasting remissions and potential cures for certain cancers. The principle of this immunotherapy is to improve patient's own T cells. It shows clinically significant efficacy in difficult-to-treat cancers. However, when overcoming solid tumors, this therapy encounters limitations of tumor infiltration, the multiple limitations of the tumor microenvironment, and the toxicity produced by CAR-T cells themselves. All these factors make the efficacy of CAR-T cell immunotherapy significantly reduced. The investigation of the causes leading to these issues is a central focus of research. The focus of this paper is on the accomplishments made in CAR-T cell therapy and the drugs that are currently available on the market. It will also cover current shortcomings of this immunotherapy and difficulties that need to be overcome. The paper will also cover a vision and prediction of future CAR-T cell therapy technology.