A novel parametric control method for the compressor blade, the full-blade surface parametric method, is proposed in this paper. Compared with the traditional parametric method, the method has good surface smoothness and construction convenience while maintaining low-dimensional characteristics, and compared with the semi-blade surface parametric method, the proposed method has a larger degree of geometric deformation freedom and can account for changes in both the suction surface and pressure surface. Compared with the semi-blade surface parametric method, the method only has four more control parameters for each blade, so it does not significantly increase the optimization time. The effectiveness of this novel parametric control method has been verified in the aerodynamic optimization field of compressors by an optimization case of Stage35 (a single-stage transonic axial compressor) under multi-operating conditions. The optimization case has brought the following results: the adiabatic efficiency of the optimized blade at design speed is 1.4% higher than that of the original one and the surge margin 2.9% higher, while at off-design speed, the adiabatic efficiency is improved by 0.6% and the surge margin by 1.3%.

The purpose of this study is to obtain the digital twin parameters of the thyroid gland and to build a constitutional model of the thyroid gland based on continuum mechanics, which will lay the foundation for the establishment of a surgical training system for the thyroid surgery robot and the development of the digital twin of the thyroid gland. First, thyroid parenchyma was obtained from fresh porcine thyroid tissue and subjected to quasi-static unconfined uniaxial compression tests using a biomechanical test platform with two strain rates (0.005 s⁻¹ and 0.05 s⁻¹) and two loading orientations (perpendicular to the thyroid surface and parallel to the thyroid surface). Based on this, a tensile thyroid model was established to simulate the stretching process by using the finite element method. The thyroid stretching test was carried out under the same parameters to verify the validity of the hyperelastic constitutive model. The quasi-static mechanical property parameters of the thyroid tissue were obtained by a quasi-static unconstrained uniaxial compression test, and a constitutional model that can describe the quasi-static mechanical properties of thyroid tissue was proposed based on the principle of continuum media mechanics, which is of great value for the establishment of a surgical training system for the head and neck surgery robot and for the development of the thyroid digital twin.

Solen strictus Gould are mainly cave dwellers, using their axe feet to dig caves. The Solen strictus Gould also exhibit escape-swimming behavior when food, environment, and so on changes. In this paper, Solen strictus Gould were captured on a high-speed camera as they escaped, and it was found that the Solen strictus Gould whipped while the water spout between the axe foot and the mantle sprayed water outwards. The combined propulsion of these two methods allows the Solen strictus Gould to advance rapidly in a short time. It is calculated that the swimming speed of razor clams is positively correlated with their size and that the adult Solen strictus Gould can travel up to 12 times their body length per second. This study enriches the data on the behavioral characteristics of Solen strictus Gould and is of interest regarding Solen strictus Gould in artificial farming, marine fishing, offshore ecological restoration, and underwater bionic robot development.

(1) Background: A severe decline in knee joint function significantly affects the mobility of the elderly, making it a key concern in the field of geriatric health. To alleviate the pressure on the knee joints of the elderly during daily movements such as sitting and standing, effective biomechanical solutions are required. (2) Methods: In this study, a biomechanical framework was established based on mechanical analysis to derive the transfer relationship between the ground reaction force and the knee joint moment. Experiments were designed to collect knee joint data on the elderly during the sit-to-stand process. Meanwhile, magnetic resonance imaging (MRI) images were processed through a medical imaging control system to construct a detailed digital 3D knee joint model. A finite element analysis was used to verify the model to ensure the accuracy of its structure and mechanical properties. An improved radial basis function was used to fit the pressure during the entire sit-to-stand conversion process to reduce the computational workload, with an error of less than 5%. In addition, a small-target human key point recognition network was developed to analyze the image sequences captured by the camera. The knee joint angle and the knee joint pressure distribution during the sit-to-stand conversion process were mapped to a three-dimensional interactive platform to form a digital twin system. (3) Results: The system can effectively capture the biomechanical behavior of the knee joint during movement and shows high accuracy in joint angle tracking and structure simulation. (4) Conclusions: This study provides an accurate and comprehensive method for analyzing the biomechanical characteristics of the knee joint during the movement of the elderly, laying a solid foundation for clinical rehabilitation research and the design of assistive devices in the field of rehabilitation medicine.

Soybean rust, caused by the fungus Phakopsora pachyrhizi, is recognized as the most devastating disease affecting soybean crops worldwide. In practical applications, performing accurate Phakopsora pachyrhizi segmentation (PPS) is essential for elucidating the morphodynamics of soybean rust, thereby facilitating effective prevention strategies and advancing research on related soybean diseases. Despite its importance, studies focusing on PPS-related datasets and the automatic segmentation of Phakopsora pachyrhizi remain limited. To address this gap, we propose an efficient semantic segmentation model named MS-UNet (Multi-Scale Confusion UNet Network). In the hierarchical Vision Transformer (ViT) module, the feature maps are down-sampled to reduce the lengths of the keys (K) and values (V), thereby minimizing the computational complexity. This design not only lowers the resource demands of the transformer but also enables the network to effectively capture multi-scale and high-resolution features. Additionally, depthwise separable convolutions are employed to compensate for positional information, which alleviates the difficulty the ViT faces in learning robust positional encodings, especially for small datasets. Furthermore, MS-UNet dynamically generates labels for both hard-to-segment and easy-to-segment regions, compelling the network to concentrate on more challenging locations and improving its overall segmentation capability. Compared to the existing state-of-the-art methods, our approach achieves a superior performance in PPS tasks.