Exploring the role of PRDX4 in the development of uterine corpus endometrial carcinoma.

Peroxicedoxin 4 (PRDX4), a member of the peroxicedoxins (PRDXs), has been reported in many cancer-related studies, but its role in uterine corpus endometrial carcinoma (UCEC) is not fully understood. In the present study, we found that PRDX4 was highly expressed in UCEC tissues and cell lines through the combination of bioinformatics analysis and experiments, and elevated PRDX4 levels were associated with poor prognosis. Knockdown of PRDX4 significantly blocked the proliferation and migration of the UCEC cell line Ishikawa and reduced degree of cell confluence.

Restoration of Spatially Variant Blurred Images with Wide-Field Telescope Based on Deep Learning.

The wide-field telescope is a research hotspot in the field of aerospace. Increasing the field of view of the telescope can expand the observation range and enhance the observation ability. However, a wide field will cause some spatially variant optical aberrations, which makes it difficult to obtain stellar information accurately from astronomical images.

Optimization of the Winding Layer Structure of High-Pressure Composite Overwrapped Pressure Vessels.

The large thickness COPV is designed by netting theory and the finite element simulation method, but the actual performance is low and the cylinder performance still cannot be improved after increasing the thickness of the composite winding layer. This paper analyzes the reasons for this and puts forward a feasible solution: without changing the thickness of the winding layer, the performance of COPV can be effectively increased by increasing the proportion of annular winding fiber. This method has been verified by tests and is supported by theory.

Nonuniform Correction of Ground-Based Optical Telescope Image Based on Conditional Generative Adversarial Network.

Ground-based telescopes are often affected by vignetting, stray light and detector nonuniformity when acquiring space images. This paper presents a space image nonuniform correction method using the conditional generative adversarial network (). Firstly, we create a dataset for training by introducing the physical vignetting model and by designing the simulation polynomial to realize the nonuniform background.

Multi-Scale Deep Neural Network Based on Dilated Convolution for Spacecraft Image Segmentation.

In recent years, image segmentation techniques based on deep learning have achieved many applications in remote sensing, medical, and autonomous driving fields. In space exploration, the segmentation of spacecraft objects by monocular images can support space station on-orbit assembly tasks and space target position and attitude estimation tasks, which has essential research value and broad application prospects. However, there is no segmentation network designed for spacecraft targets.