Hangzhou Vocational and Technical College

In mixed traffic environments, the spatial distribution of Connected and Automated Vehicles (CAVs) plays a decisive yet previously unquantified role in platoon stability and safety. This study establishes a generalized stability modeling framework for heterogeneous platoons composed of Human-Driven Vehicles (HDVs), Autonomous Vehicles (AVs), and CAVs. By introducing a spatial weighting coefficient (γ), the proposed model captures the influence of longitudinal CAV positioning and allows for flexible representation of any vehicle composition pattern. Linear stability analysis and time-domain simulations are conducted to investigate the interaction between spatial distribution, communication delay, and dynamic response. The results demonstrate that front- and center-loaded CAV configurations effectively suppress velocity perturbations and maintain string stability even under moderate delay, while rear-loaded configurations exhibit early instability. Furthermore, an optimal γ range of 0.3-0.5 is identified to minimize oscillation amplitude, providing a practical guideline for cooperative control strategies in mixed platoons. The findings offer theoretical insights and quantitative evidence for optimizing CAV deployment to enhance stability and robustness in future intelligent transportation systems.

Precision irrigation is crucial for sustainable agriculture, yet conventional single-objective optimization methods struggle to balance conflicting demands such as crop yield, operational cost, and environmental sustainability. This study introduces an Adaptive Multi-Strategy Grey Wolf Optimizer with Reinforcement Learning for Multi-Objective Optimization (AMSGWO-RL-MO) to enhance precision irrigation decision-making. AMSGWO-RL-MO integrates four strategies: standard GWO exploitation, Lévy flight exploration, differential evolution-based diversity enhancement, and Stochastic Elite Opposition-Based Learning. A Q-learning mechanism dynamically adjusts these strategies, adapting to real-time search conditions to select the optimal approach. We constructed a comprehensive three-objective framework incorporating soil moisture dynamics, crop growth models, and environmental impact assessments. Experimental simulations over a 40-day growth cycle demonstrate AMSGWO-RL-MO’s rapid convergence by the sixth generation, consistently achieving a high-quality Pareto front across 30 independent runs. The knee-point solution yielded a mean crop yield of 96.96%, outperforming standard GWO and multi-strategy variants by approximately 3.8%. Statistical analysis confirms its superior robustness and well-distributed solutions along the Pareto front. These results indicate that the RL-driven adaptive mechanism effectively balances exploration and exploitation. The proposed method offers a more diverse array of Pareto-optimal solutions, presenting a broader trade-off space for balancing crop yield and environmental sustainability compared to traditional weighted-sum approaches. This enhancement facilitates scientific agricultural decision-making under various operational constraints.

Plant Derived Nanovesicles (PDNVs) have emerged as promising therapeutic agents for wound healing, particularly in the context of diabetic chronic wounds. These nanovesicles, secreted by plant cells, offer unique advantages such as high accessibility, low immunogenicity, and remarkable stability. Structurally composed of proteins, nucleic acids, and other bioactive molecules, PDNVs play pivotal roles in cell-to-cell communication and the modulation of various physiological processes. This review highlights their multifaceted functions, such as promoting cell proliferation and migration, the exertion of anti-inflammatory and antibacterial effects, and the stimulation of angiogenesis, all of which are critical for the complex process of wound repair. Furthermore, this review seeks to supply a thorough grasp of the current field status and to determine potential research pathways for the future. Special emphasis is placed on the latest advancements in utilizing PDNVs for the treatment of chronic diabetic wounds, unraveling their potential mechanisms and therapeutic impacts.

Traditional wire bonding and die-top system (DTS) interconnect structures suffer from high parasitic parameters and low thermal efficiency, failing to meet the urgent demands of power electronics systems evolving toward higher frequencies and greater power density. Addressing the multiple challenges faced by planar interconnect structuresinsufficient current-carrying capacity alongside conflicting demands for low inductance and low current imbalance-this paper proposes a copper clip (Cu-Clip) three-dimensional topological interconnect structure. Compared to traditional aluminum wire bonding solutions, it reduces junction temperature by $17.92^{\circ} \mathrm{C}$ while decreasing resistance and stress by $30.92 \%$ and $62.64 \%$, respectively. Combined with an impedance-matched current-sharing scheme, the current imbalance between upper and lower bridge arms was optimized from $27.34 \% / 38.92 \%$ to $9.74 \% / 7.06 \%$, while total parasitic inductance was reduced to 4.37 nH. Furthermore, dual-pulse dynamic testing validated its robustness in realtime scenarios. This study provides a novel low-inductance, high-current-sharing interconnection solution for high-powerdensity power electronic devices.

This article explores introducing enterprise work order management into Western banquet course teaching in technical colleges. The "micro-work order" model decomposes teaching tasks into standardized work orders by simulating real work scenarios, significantly improving students' practical ability and professional quality. Taking the "Western Banquet Service" course as an example, this study constructs a three-dimensional task system of "problem chain-learning chain-evaluation chain", forming a closed-loop teaching of "task perception-skill learning-practical verification-expansion and innovation". The problem chain is oriented towards typical banquet scenarios, the learning chain integrates theoretical knowledge and operational norms, and the evaluation chain combines process assessment and outcome evaluation. This design provides a reproducible paradigm for vocational education teaching activities, effectively bridging classroom teaching and enterprise needs.