Imitating the structure of the venous valve and its characteristics of passive opening and closing with changes in heart pressure, a piezoelectric pump with flexible valves (PPFV) was designed. Firstly, the structure and the working principle of the PPFV were introduced. Then, the flexible valve, the main functional component of the pump, was analyzed theoretically. Finally, an experimental prototype was manufactured and its performance was tested. The research proves that the PPFV can achieve a smooth transition between valved and valveless by only changing the driving signal of the piezoelectric (PZT) vibrator. The results demonstrate that when the driving voltage is 100 V and the frequency is 25 Hz, the experimental flow rate of the PPFV is about 119.61 mL/min, and the output pressure is about 6.16 kPa. This kind of pump can realize the reciprocal conversion of a large flow rate, high output pressure, and a small flow rate, low output pressure under the electronic control signal. Therefore, it can be utilized for fluid transport and pressure transmission at both the macro-level and the micro-level, which belongs to the macro–micro combined component.

Hip replacement femoral implants are made of substantial materials that all have stiffness considerably higher than that of bone, which can cause significant bone resorption secondary to stress shielding and lead to severe complications. The topology optimization design method based on the uniform distribution of material micro-structure density can form a continuous mechanical transmission route, which can better solve the problem of reducing the stress shielding effect. A multi-scale parallel topology optimization method is proposed in this paper and a topological structure of type B femoral stem is derived. Using the traditional topology optimization method (Solid Isotropic Material with Penalization, SIMP), a topological structure of type A femoral stem is also derived. The sensitivity of the two kinds of femoral stems to the change of load direction is compared with the variation amplitude of the structural flexibility of the femoral stem. Furthermore, the finite element method is used to analyze the stress of type A and type B femoral stem under multiple conditions. Simulation and experimental results show that the average stress of type A and type B femoral stem on the femur are $14.80$ MPa, $23.55$ MPa, $16.94$ MPa and $10.89$ MPa, $20.92$ MPa, $16.50$ MPa, respectively. For type B femoral stem, the average error of strain is $-1682\mathsf{\mu }\mathsf{\epsilon }$ and the average relative error is $20.3\%$ at the test points on the medial side and the mean error of strain is $1281\mathsf{\mu }\mathsf{\epsilon }$ and the mean relative error is $19.5\%$ at the test points on the outside.

The problem of adaptive event-triggered control for uncertain nonlinear systems with full-state constraints was investigated. State constraints can significantly affect system performance, especially when time-varying external disturbances are present, potentially leading to instability. Thus, a fixed-time disturbance observer was designed. It estimated unknown uncertainties within a predetermined time. Meanwhile, an asymmetric barrier Lyapunov function was developed. It ensured the stability of the system state under constraints. Furthermore, to reduce the utilization rate of the system’s communication resources, an adaptive event-triggered control scheme was proposed, and an integrated control method was established to preset the convergence time of the system’s state error, greatly improving the convergence speed. Theoretical analysis and simulations demonstrated the effectiveness of the proposed approach. The results show that the system achieved stable control within a fixed time, even under full-state constraints and external disturbances, while using fewer communication resources.

This study explores the issue of fixed-time dynamic event-triggered consensus control for uncertain nonlinear multi-agent systems (MASs) within directed graph frameworks. In practical applications, the system encounters multiple constraints such as unknown time-varying parameters, unknown external disturbances, and input dead zones, which may increase the communication burden of the system. Therefore, achieving fixed-time consensus tracking control under the aforementioned conditions is challenging. To address these issues, an adaptive fixed-time consensus tracking control method based on boundary estimation and fuzzy logic systems (FLSs) is proposed to achieve online compensation for the input dead zone. Additionally, to optimize the utilization of communication resources, a periodic adaptive event-triggered control (PAETC) is designed. The mechanism dynamically adjusts the frequency at which the trigger is updated in real time, reducing communication resource usage by responding to changes in the control signal. Finally, the efficacy of the proposed approach is confirmed via theoretical evaluation and simulation.

Conventional fertigation systems suffer from limited cross-regional adaptability, mainly due to unstable fertilizer flow from fixed-aperture units, poor terrain adaptability, and an inadequate response to environmental heterogeneity. This study proposes an autonomous, cross-regional intelligent fertigation system based on an STM32F1 microcontroller and UART communication protocols. The system integrates a mechanically adjustable iris fertilizer delivery unit, a dual-axis fertigation module, a data interconnection unit, and comprehensive control software with dynamic calibration capabilities. Prototype evaluations conducted on both sloped terrain (up to 38°) and flat surfaces demonstrate a stable performance, achieving fertilizer flow control errors below 3%, irrigation deviation under 5%, and fertilization deviation within 2%. Real-time data acquisition, remote monitoring, and intelligent operation are supported by a YOLOv5s-based visual recognition system, which attains an mAP@0.5 of 92.5%. This integrated solution offers a robust approach to precision agriculture across diverse environmental conditions.

The traditional iron and steel industry has been optimized by advanced foreign technology, and its products have been improved. However, there are some urgent problems to be solved, such as the gap between product quality and foreign countries, overcapacity, and so on. By building an "online quality analysis platform based on big data," this design integrates the quality information of products scattered in different systems of each manufacturing unit into an integrated quality control system, so as to realize the connection of quality information between upstream and downstream processes such as steelmaking, continuous casting, rolling, heat treatment, inspection, and testing. The system is designed according to user's needs so that the product quality of steel enterprises has achieved a consistent system. It can improve quality control from empiricism to scientific and systematic platform data analysis, improve the stability of product quality production and user satisfaction, and promote the vigorous development of Intelligent Manufacturing in iron and steel enterprises.