Hebei Finance University

This paper presents a Multi-Load-Case topology optimization framework for aluminum alloy wheels to overcome the limitations of empirical rear-cavity lightweight designs. To balance structural integrity and mass reduction without altering the aerodynamic outboard styling, a region-constrained topology optimization was conducted. By employing a compromise programming method based on strain energy ratios, the weighting coefficients for bending fatigue and 13° impact load cases were scientifically calibrated. Furthermore, manufacturing constraints, including a 10 mm minimum member size and draw directions, were incorporated to ensure direct compatibility with conventional casting. The results demonstrate that the optimized depth-gradient cavities successfully reduced the peak von Mises stress for bending fatigue by 19.25% (from 133.9 to 108.13 MPa) and for the 13° impact by 14.57% (from 74.63 to 63.76 MPa), alongside a slight mass reduction of 0.53%. This approach offers a mathematically rigorous and industrially viable paradigm for the multi-objective lightweight design of high-performance automotive components.

Under the “dual carbon” goals, enhancing the energy supply for communication base stations is crucial for energy conservation and emission reduction. An individual base station with wind/photovoltaic (PV)/storage system exhibits limited scalability, resulting in poor economy and reliability. To address this, a collaborative power supply scheme for communication base station group is proposed. This paper establishes a capacity optimization configuration model for such integrated system and introduces a hybrid solution methodology combining random scenario analysis, Nondominated Sorting Genetic Algorithm II (NSGA-II), and Generalized Power Mean (GPM). Typical scenarios are solved using NSGA-II to generate a candidate solution set, which is then refined under operational constraints. The GPM method is applied to determine the final configuration by accounting for attribute correlations. A case study on a Chinese base station group, considering uncertainties in renewable generation, demonstrates the feasibility and effectiveness of the proposed approach.

Wind/PV/storage system for communication base station has drawn much attention recently. Considering the insufficient scale effect and poor reliability performance of wind/PV/storage system for a single communication base station at present, the collaborative mode of wind/PV/storage system for communication base station group provides an effective solution. This paper is devoted to optimizing capacity configuration of wind/PV/storage system for communication base station group, considering the uncertainty of wind power, photovoltaic power and load. A multi-objective interval optimization model is constructed with economy, reliability, environmental protection, and social benefits as objective functions, considering the impact of communication load on energy storage charging and discharging. Combining the proposed generalized interval power mean (GIPM) operator with NSGA-II, the interval optimization-NSGA-II-GIPM method is provided to solve the model. Taking the base station group in China as an example, numerical analysis is conducted to verify the effectiveness of the given model and method.

In this article, we introduce a framework called Financial Strategy Reinforcement Learning (FSRL) to address the challenges posed by dynamic and complex financial markets, which relies on modeling multi-strategy choices as Markov decision processes (MDP) to dynamically adapt to a wide variety of market conditions and optimize risk and return. This study combines a finite state machine (FSM) with a standardized backtest environment, which has the benefit of ensuring that the robustness and repeatability of the strategy can be evaluated. We conducted validation experiments using major market indexes in China and the United States, and the results of the experiments show that the FSRL framework has advantages over traditional methods. It achieves a higher Sharpe ratio, a higher return, and a better risk control effect. This research provides a scalable and innovative solution for promoting quantitative trading and dynamic strategy integration.

Although the body of research on supply chain security is growing, few of the studies are quantitative. Researchers have investigated the influence of specialized agglomerations on many aspects of China’s economy, but there is little study on supply chain security. This study develops an evaluation framework for global supply chain security and employs location quotient to evaluate the specialized agglomeration. The paper selects the relevant variables of China’s manufacturing sectors to construct panel data and adopts a mixed effect model to verify the impact of specialized agglomeration on the supply chain security of China’s manufacturing sector. The empirical evidence demonstrates that specialized agglomeration positively influences the supply chain security of China’s manufacturing sector. Specialized agglomeration has a greater impact on China’s high-end manufacturing industry than its low-end manufacturing industry. This study further verifies that there is no turning point in the impact of specialized agglomeration on the supply chain security of China’s manufacturing industry, and the two are purely linear relationships.

This study presents a revolutionary understanding of how value-based leadership enhances the intrinsic work motivation of Chinese university faculty. A novel serial mediation model is introduced, highlighting the interplay between growth mindset and teaching self-efficacy in transmitting the impact of leadership to increased intrinsic motivation. Utilizing a comprehensive sample of 394 faculty members from across China, advanced SmartPLS 3.0 analytics were employed to validate the model. The results demonstrate a significant positive effect of value-based leadership on faculty intrinsic motivation, partially mediated by the sequential influence of nurturing a growth mindset and strong teaching self-efficacy. The findings provide fresh theoretical perspectives and practical strategies for researchers, university leaders, administrators, and policymakers seeking to elevate the intrinsic work motivation of China's academic faculty to new levels.