Design and development of bridge erecting machine with small curve radius and bottom feeding beam.

As a key equipment in highway and railway construction, bridge erecting machines directly affect the feasibility, progress, and quality of project implementation. In order to solve the problem that traditional bridge building machines are only suitable for application scenarios with large turning radii and large lifting sites, and have low lifting efficiency, which cannot meet the requirements of urban elevated bridge construction, a small radius bottom feeding beam bridge building machine suitable for urban highway and railway construction is proposed. The feasibility and reliability were verified through force analysis and finite element analysis; Design a secondary turning structure and bridge construction process for the front leg, adjusting the turning angle to around 7°, significantly reducing the turning radius of the bridge building machine; Propose a technology for feeding and lifting beams at the bottom of dual-use bridge decks for highways and railways.

On efficient expanding training datasets of breast tumor ultrasound segmentation model.

Automatic segmentation of breast tumor ultrasound images can provide doctors with objective and efficient references for lesions and regions of interest. Both dataset optimization and model structure optimization are crucial for achieving optimal image segmentation performance, and it can be challenging to satisfy the clinical needs solely through model structure enhancements in the context of insufficient breast tumor ultrasound datasets for model training. While significant research has focused on enhancing the architecture of deep learning models to improve tumor segmentation performance, there is a relative paucity of work dedicated to dataset augmentation.

Re-designing a yield-improving strategy of pear orchards in the Yangtze River Basin, China.

Background: Pear yield is a primary source of income for smallholder farmers in China, yet significant yield disparities exist among different smallholders. Systematic analyses of limiting factors and the feasibility of solutions at the smallholder level are limited. This study employs a novel DEED (Describe, Explain, Explore, and Design) research cycle centered on smallholders to formulate yield-improving strategies.