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Driving fatigue poses a serious threat to road safety. To detect fatigue accurately and thereby improve vehicle safety, this paper proposes a novel semi-dry electrode with the ability to automatically replenish the conductive fluid for monitoring driving fatigue. This semi-dry electrode not only integrates the advantages of both wet and dry electrodes but also incorporates an automatic conductive fluid replenishment mechanism. This design significantly extends the operational lifespan of the electrode while mitigating the limitations of manual replenishment, particularly the risk of signal interference. Additionally, this study adopts a transfer learning approach to detect driving fatigue by analyzing electroencephalography (EEG) signals. The experimental results indicate that this method effectively addresses the issue of data sparsity in real-time fatigue monitoring, overcomes the limitations of traditional algorithms, shows strong generalization performance and cross-domain adaptability, and achieves faster response times with enhanced accuracy. The semi-dry electrode and transfer learning algorithm proposed in this study can provide rapid and accurate detection of driving fatigue, thereby enabling timely alerts or interventions. This approach effectively mitigates the risk of traffic accidents and enhances both vehicle and road traffic safety.

Graphite like C 3 N 4 (g-C 3 N 4 ) was synthesized facilely via the low temperature thermal condensation of melamine between 300–650°C. The results showed that the products maintained as melamine when the temperature is below 300°C. With the increase of temperature, the products were transformed into carbon nitride and amorphous g-C 3 N 4 successively. The morphology of products was changed from spherical nanoparticles of melamine into layer carbon nitride and g-C 3 N 4 with the increase of temperature. The photoluminescence spectra showed that the carbon nitride products have continuous tunable photoluminescence properties in the visible region with increasing temperature. With the help of steady state, transient state time-resolved photoluminescence spectra and Raman microstructural characterization, a novel tunable photoluminescence mechanism was founded systematically, which is mainly related to the two dimensional π-conjugated polymeric network and the lone pair of the carbon nitride.

Power battery is one of the core components of electric vehicles (EVs) and a major contributor to the environmental impact of EVs, and reducing their environmental emissions can help enhance the sustainability of electric vehicles. Based on the principle of stiffness equivalence, the steel case of the power cell is replaced with lightweight materials, a life cycle model is established with the help of GaBi software, and its environmental impact is evaluated using the CML2001 method. The results can be summarized as follows: (1) Based on the four environmental impact categories of GWP, AP, ADP (f), and HTP, which are the global warming potential (GWP), acidification potential (AP), abiotic depletion potential (ADP (f)) and human toxicity potential (HTP), the environmental impact of lightweight materials is lower than that of the steel box. Among them, the aluminum alloy box has the largest reduction, and the Carbon Fiber Sheet Molding Compound (CF-SMC) box is the second. (2) In the sensitivity analysis of electric structure, an aluminum alloy box is still the most preferable choice for environmental impact. (3) In the sensitivity analysis of driving mileage, the aluminum alloy box body is also the best choice for vehicle life. (4) Quantitative assessment using substitution factors measures the decrease in greenhouse gas emissions following the substitution of steel battery box with lightweight materials. The adoption of aluminum alloy battery box can lead to a reduction of 1.55 tons of greenhouse gas emissions, with a substitution factor of 1.55 tC sb −1 . In the case that composite materials have not been recycled commercially on a large scale, aluminum alloy is still one of the best materials for the integrated environmental impact of the whole life cycle of the battery boxes.

Since its inception, the frequency diverse array (FDA) has attracted extensive attention and research because of its unique properties. However, most of the research primarily focuses on linear geometry FDA, with fewer studies on planar FDA. This letter proposes a design method based on planar rectangular FDA (PRFDA), which adjusts the frequency of each array element nonlinearly so that the beam direction of planar rectangular FDA can change linearly or nonlinearly with time, forming the desired transmit beampattern. Theoretical analysis and simulation results verify the effectiveness of the proposed method. We begin by deriving the precise transmit beampattern for the PRFDA and analyzing the impact of its diverse frequency offset settings on beam direction. Building on this groundwork, we propose a DM method rooted in the PRFDA framework, facilitating linear or nonlinear scanning of its beam across three‐dimensional space.

In recent years, connected automated vehicles (CAVs) have attracted much attention, and the coordination strategy of CAVs in isolated intersections has been widely discussed. However, these algorithms for isolated intersections cannot be directly applied in a multi-intersection road network (MiRN). The coordination strategy in the MiRN requires further investigation. This paper proposes a two-tier strategy for CAV coordination in the MiRN. First, we analyze the coordination problem in isolated intersections and formulate it as a mixed-integer programming problem. Then, for the MiRN, we propose a consensus prediction method to estimate the travel time for CAVs with different paths. Finally, a novel coordination approach is given, showing how to determine the optimal path for CAVs. The experimental results demonstrate the efficiency of the proposed strategy under various traffic flow rates. Compared with the fixed signal time assignment method and the actuated signal time assignment method, our method reduces the average travel time by about 74–83% under different flow rates. We also evaluate the impact of parameters on the strategy’s performance and provide some suggestions for setting these parameters.

This study investigates how dynamic fluctuations in matrix stiffness affect the behavior of cardiac fibroblasts (CFs) within a three-dimensional (3D) hydrogel environment. Using hybrid hydrogels with tunable stiffness, we created an in vitro model to mimic the varying stiffness of the cardiac microenvironment. By manipulating hydrogel stiffness, we examined CF responses, particularly the expression of α-smooth muscle actin (α-SMA), a marker of myofibroblast differentiation. Our findings reveal that increased matrix stiffness promotes the differentiation of CFs into myofibroblasts, while matrix softening reverses this process. Additionally, we identified the role of focal adhesions and integrin β1 in mediating stiffness-induced phenotypic switching. This study provides significant insights into the mechanobiology of cardiac fibrosis and suggests that modulating matrix stiffness could be a potential therapeutic strategy for treating cardiovascular diseases.

Meaning-centered coping is regarded as an effective strategy for managing stress and preventing mental disorders. However, it remains unclear how it influences mental health by affecting both the self and social connection dimensions. This study investigated 856 college students through a questionnaire, examining how meaning-centered coping affects their mental health (depression and anxiety). Additionally, this study explored the roles of interdependent self-construal and school connectedness as mediators in this process. The results indicate that meaning-centered coping influences mental health either via the mediation of school connectedness alone (indirect effect for depression: β = −0.08, 95% CI [−0.11, −0.04]; for anxiety: β = −0.06, 95% CI [−0.10, −0.03]) or via the sequential mediation of interdependent self-construal and school connectedness (indirect effect for depression: β = −0.08, 95% CI [−0.11, −0.05]; for anxiety: β = −0.06, 95% CI [−0.10, −0.04]). This study reveals that college students who are skilled at seeking and reconstructing their sense of meaning can effectively cope with stress and alleviate related depression and anxiety. This coping mechanism operates through perceived school connectedness or through activated interdependent self-construal followed by perceived school connectedness, subsequently reducing anxiety and depression induced by chronic stress. This study theoretically deepens the comprehension of the mechanism on meaning-centered coping, while practically, the findings provide valuable insights for educating training college students to leverage the wisdom of meaning theory to sustain their mental health in future challenges.

Background Peripheral nerve injury (PNI) is a public health problem that can lead to sensory and motor deficits as well as neuropathic pain and secondary lesions. We explored the effects of the combination of MaR1 and NGF on sciatic nerve regeneration, reduction of neuropathic pain, and anti-inflammation, and further elucidated the associated molecular mechanisms. Methods After treatment of PC12 (adrenal pheochromocytoma cells) cells with NGF, MaR1 and H₂O₂, changes in proliferation were detected by CCK8; cell migration ability was detected by Transwell; reactive oxygen species (ROS) and apoptosis were detected by flow cytometry; and the mRNA expression of the inflammatory factors IL-1β, IL-6, and TNF-α was detected by qRT-PCR. Western blot detected the protein expression of β-catenin, P62, GSK-3β, LC3B, NF200, S100, MBP; Immunofluorescence analysis of LC3B expression; During recovery experiments, observe changes following treatment with GSK-3β activators and the autophagy agonist rapamycin. PNI model was constructed using 6-week-old male SD rats, NGF, MaR1 or saline was injected locally, and the drug was administered 3 times on alternate days after surgery, sciatic nerve function index analysis and muscle atrophy test were performed after surgery; the gastrocnemius muscle wet weight ratio and HE staining were observed after the samples were taken after surgery, and NF200, S100, MBP, β-catenin, and P62 were detected by Western blot, GSK-3β, LC3B levels; the expression of NF200, β-catenin, P62, GSK-3β, LC3B was detected by immunohistochemistry. Results NGF and MaR1 were non-toxic and the combination of NGF and MaR1 increased the proliferation and migration of PC12 cells, reduced H₂O₂ induced ROS production, inhibited apoptosis, and had a significant anti-inflammatory effect. In vivo studies showed that MaR1 and NGF combined could more effectively promote nerve repair and recovery of sensory and motor functions in SD rats, and reduce gastrocnemius muscle atrophy.The combination of MaR1 and NGF inhibited autophagy through GSK-3β/β-catenin signaling pathway to regulate the growth and repair of sciatic nerve. And the GSK-3β agonist DIF-3 and the autophagy activator rapamycin antagonize this effect. Conclusion The combination of MaR1 and NGF promotes sciatic nerve repair and motor function recovery and reduces local inflammation by inhibiting autophagy through the GSK-3β/β-catenin pathway.

In the semiconductor manufacturing process, precise control of wafer notch angles during ion implantation is critical to prevent channeling effects that can lead to defects. Current detection methods face challenges in identifying wafer notches accurately, particularly under varying conditions. This paper proposes an enhanced YOLOv8 model tailored for small object detection, specifically aimed at improving the accuracy of wafer notch angle detection. By addressing class imbalance issues, introducing a small target detection layer and two new detection heads, and optimizing the global attention mechanism within the model’s backbone, we significantly improve detection performance. Experimental results demonstrate that our improved YOLOv8 model achieves a mean average precision of 93.4%, outperforming existing YOLO versions and other relevant models. This study not only enhances the reliability of wafer notch detection but also offers insights into optimizing object detection algorithms for precision manufacturing applications.

Spent mushroom substrate (SMS)-derived bio-based polyurethane coatings typically exhibit poor hydrophobicity and short nutrient release durations, limiting their ability to satisfy long-term crop requirements. This study developed improved controlled-release urea by preparing water-repellent and compact bio-polymer coatings from recyclable SMS using non-toxic siloxane and nano-SiO2 modifiers through simple processes. The dual modification markedly reduced water absorption (from 6.60% to 4.43%) and porosity (from 6.32% to 3.92%), creating a dense coating with lotus-leaf-like nanoscale surface protrusions and fewer intermembrane pores. As a result, the nitrogen (N) release period of the dual-modified bio-polymer-polyurethane-coated urea (SBPCU) with a 7% coating thickness was extended from 23 days to 42 days. Phytotoxicity assessments confirmed the excellent biosafety of the bio-polymer coating, revealing no adverse effects on maize growth and even promotional effects at low concentrations. This approach offers a sustainable, eco-friendly, and scalable strategy for producing bio-polymer-coated urea from agricultural waste, serving as a viable alternative to petrochemical coatings while improving nutrient use efficiency and biosafety.