Abstract

This study focuses on parameter optimization and detection signal comparison of planar coil
particle detection sensors, and conducts in-depth analysis of different core materials. Through finite
element simulation analysis and experimental verification, the influence of coil turns, diameter,
thickness and other parameters on magnetic field distribution and particle detection signals was
systematically explored, and the sensor chip structure design was optimized. The study found that a
planar coil with 60 turns and an inner diameter of 1.2 mm performed best. At the same time, the
enhancement effect of different magnetic core materials (including iron core, silicon steel sheet and
permalloy) on the magnetic field and detection signal was investigated. It was found that the
permalloy magnetic core can significantly improve the sensor performance. Copper particles have
effective detection capabilities. This research provides theoretical and experimental basis for
optimizing the detection sensor of metal particle contaminants in oil, and has important academic
value and application prospects.

In recent years, interest in autonomous driving vehicles has grown, both for industrial use and for public and personal transportation. As is well known, although LiDAR sensors and cameras are required to detect obstacles and pedestrians; neural networks and AI to interpret the environment and make decisions; and/or GPS and real-time maps for precise navigation; etc., these vehicles require wheels for movement. This work presents an electromechanical differential that allows controlling the accelerated differential movement required when an autonomous vehicle turns sideways. The name electromechanical differential refers to an arrangement of three accelerators: one to control the vehicle’s acceleration; this accelerator is connected in series with the accelerator that independently controls each drive wheel. Control of the differential acceleration of the rear wheel hub motors, in the case of four-wheel vehicles, is provided by the vehicle’s front-wheel steering system mechanism, considering the Ackerman differential geometry, allowing for minimizing the number of complex automatic control systems, such as sensors and encoders. The front steering pivot, controlled by the steering wheel to indicate the vehicle’s turn, has a square- shaped structure, where the pivot rotates on a hub fixed to the chassis, while the ends of the pivot terminate one in the wheel and the other in the steering rod. This turning motion is associated with the butterfly mechanism of an electric pedal accelerator, which opens and closes with the rotation of the wheel.These ideas can be extrapolated to an electromechanical differential for two- or four- legged robots, either with pivoting on one foot or with differential movement)

The Sustainable Development Goals and the World Health Organization have prioritized mental health as an important goal. Mental health is a critical issue within the global public health sphere. Notably, green spaces are a useful alternative for improving mental health. Many studies have focused on green space and mental health, especially on their connection and relationship. However, this research topic lacks a comprehensive and systematic review. Owing to the lack of critical reviews, this study clarified the trend, progress, status, and focus of studies on green spaces and mental health through the use of bibliometric analysis of literature from 2000 to 2022 within the Web of Science database. The literature analysis within this study specifically focused on the following, including the country/region contribution analysis, the institution contribution analysis, keyword analysis, and highly productive journal analysis. Furthermore, this study systematically recorded the content of green space and mental health (i.e., the measurements of green space, psychological instruments for measuring mental health, and the relationship between green space and mental health) and identified the gap that exists and provided future frontier directions or issues for research (i.e., the quantification of elements from health-oriented green space planning, the equity of green space, and the long-term effects of green space on mental health). These contribute toward comprehending the progress and content of this research topic and further provide a guide, reference, and inspiration for possible future research.

Abstract

Tissue engineering (TE) is aimed towards developing biological substitutes for the repair and replacement damaged tissues. Gelatin methacrylate (GelMA) hydrogels, in particular, have been widely utilized in TE applications because of their ability to mimicthe extracellular matrix, offering high water retention, optical transparency, tunable mechanical properties, and superior biocompatibility. However, a major challenge in TE is the real-time monitoring of scaffold-host interactions, which is essential for ensuring successful scaffold integration. Conventional methods, such as histology, are destructive and limit long-term assessment. Short-wave infrared (SWIR, 900-1700 nm) fluorescence imaging has shown considerable potential for monitoring implants while mitigating autofluorescence from adjacent host tissues. To implement SWIR imaging, we employed single-walled carbon nanotubes (SWCNTs), which offer a promising approach owing to their distinctive optical properties, strong SWIR fluorescence, and photostability. In this study, we created a fluorescently active hydrogel by incorporating SWCNTs into the GelMA matrix. To suspend the SWCNTs, we employed a polymer- assisted dispersion approach using a low-concentration (2%) GelMA solution and subsequently evaluated their optical and physical properties after photocrosslinking within a high-concentration (10%) GelMA matrix. Our current findings indicate that incorporating SWCNTs into GelMA hydrogels does not significantly alter the optical properties of the nanotubes or the physical properties of the hydrogel. These observations highlight the potential of utilizing SWCNT-loaded GelMA hydrogels as advanced biomaterials that can ensure proper tissue integration and enable real-time scaffold monitoring.