With the development of micro/nano satellites and formation flying, more advanced spatial propulsion technology is required. In this paper, a review of microthrusters developments that based on micro electromechanical systems (MEMS) technology adopted in microthrusters is summarized. The microthrusters in previous research are classified and summarized according to the types of propellants and the working principles they utilized. The structure and the performance including the thrust, the impulse and the specific impulse of various microthrusters are compared. In addition, the advantages and the disadvantages of these microthrusters presented in the paper are discussed.

The design and analysis of continuum robots have consistently been a prominent research focus in the field of mechanics. However, portable continuum robots with minimal spatial occupancy, which have great potential for applications such as search and rescue, are scarcely available. This paper presents a novel helical-coiled multi-segment flexible continuum robot featuring helical deployment and compact design, with an integrated framework for structural design, kinematic modeling, and experimental validation. The design of the helical-coiled multi-segment flexible continuum robot for unstructured environment detection, including a flexible body, an actuation module, a feed module, and a sensing module, is presented systematically. Kinematic models of both single- and multi-segment continuum robots were established based on the constant curvature model to analyze the parameter mapping relationship from the end-effector position and orientation to the driving inputs. Furthermore, the feedforward motion of the robot was examined, and an uncoiling strategy based on S-curve compensation was employed to complete the kinematic analysis. Finally, the accuracy of the kinematic model considering the active uncoiling feed motion was validated through experimental analysis, demonstrating the motion characteristics of the continuum robot. Altogether, this study provides a framework for the design and analysis of helical-coiled continuum robots.

In the plant factories using stereoscopic cultivation systems, the cultivation plate transport equipment is an essential component of production. However, there are problems, such as high labor intensity, low levels of automation, and poor versatility of existing solutions, that can affect the efficiency of cultivation plate transport processes. To address these issues, this study designed a cultivation plate transport system that can automatically input and output cultivation plates, and can flexibly adjust its structure to accommodate different cultivation frame heights. We elucidated the working principles of the transport system and carried out structural design and parameter calculation for the lift cart, input actuator, and output actuator. In the input process, we used dynamic simulation technology to obtain an optimum propulsion speed of 0.3 m·s⁻¹. In the output process, we used finite element numerical simulation technology to verify that the deformation of the cultivation plate and the maximum stress suffered by it could meet the operational requirements. Finally, operation and performance experiments showed that, under the condition of satisfying the allowable amount of positioning error in the horizontal and vertical directions, the horizontal operation speed was 0.2 m·s⁻¹, the maximum positioning error was 2.87 mm, the vertical operation speed was 0.3 m·s⁻¹, and the maximum positioning error was 1.34 mm. Accordingly, the success rate of the transport system was 92.5–96.0%, and the operational efficiency was 176–317 plates/h. These results proved that the transport system could meet the operational requirements and provide feasible solutions for the automation of plant factory transport equipment.

It is essential to control concentration gradients at specific locations for many biochemical experiments. This paper proposes a tunable concentration gradient generator actuated by acoustically oscillating bubbles trapped in the bubble channels using a controllable position based on the gas permeability of polydimethylsiloxane (PDMS). The gradient generator consists of a glass substrate, a PDMS chip, and a piezoelectric transducer. When the trapped bubbles are activated by acoustic waves, the solution near the gas–liquid interface is mixed. The volume of the bubbles and the position of the gas–liquid interface are regulated through the permeability of the PDMS wall. The tunable concentration gradient can be realized by changing the numbers and positions of the bubbles that enable the mixing of fluids in the main channel, and the amplitude of the applied voltage. This new device is easy to fabricate, responsive, and biocompatible, and therefore has great application prospects. In particular, it is suitable for biological research with high requirements for temporal controllability.

Heart rate (HR) is an important indicator reflecting the overall physical and mental health of the human body, playing a crucial role in diagnosing cardiovascular and neurological diseases. Recent research has revealed that variations in the light absorption of human skin captured through facial video over the cardiac cycle, due to changes in blood volume, can be utilized for non-contact HR estimation. However, most existing methods rely on single-modal video sources (such as RGB or NIR), which often yield suboptimal results due to noise and the limitations of a single information source. To overcome these challenges, this paper proposes a multimodal information fusion architecture named the spatiotemporal sensitive network (SS-Net) for non-contact heart rate estimation. Firstly, spatiotemporal feature maps are utilized to extract physiological signals from RGB and NIR videos effectively. Next, a spatiotemporal sensitive (SS) module is introduced to extract useful physiological signal information from both RGB and NIR spatiotemporal maps. Finally, a multi-level spatiotemporal context fusion (MLSC) module is designed to fuse and complement information between the visible light and infrared modalities. Then, different levels of fused features are refined in task-specific branches to predict both remote photoplethysmography (rPPG) signals and heart rate (HR) signals. Experiments conducted on three datasets demonstrate that the proposed SS-Net achieves superior performance compared to existing methods.