Volume 109

With the rise of the Single-Pilot Operation (SPO) mode, the human-machine interaction design of aircraft cockpits faces new challenges. This paper focuses on optimizing human-machine interaction in single-pilot aircraft cockpits by constructing a three-dimensional evaluation system based on the NSGA-II multi-objective optimization strategy. This system comprehensively analyzes the reachability of operating components (), the contrast of color information (), and the cognitive load of pilots (). Data are derived from assumptions and simulation analyses based on literature and theory, covering factors such as pilot characteristics, component layout, color contrast limits, and flight mission complexity. By generating Pareto front solutions, the paper reveals trade-offs among the three objectives, providing a new quantitative decision-making basis and research direction for cockpit design.

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Solid-state lithium metal batteries (SLMBs), recognized as next-generation energy storage systems for their high energy density and intrinsic safety, face commercialization challenges stemming from interfacial instability, lithium dendrite proliferation, and rapid capacity degradation in anode-free configurations. This review analyzes the underlying mechanisms of performance deterioration in SLMBs: (1) the highly reactive lithium metal engages in chemical or electrochemical side reactions with the solid-state electrolyte (SE), leading to a continuous increase in interfacial impedance; (2) Volume fluctuations during lithium deposition/stripping trigger mechanical contact failure; (3) Irreversible lithium consumption in anode-free systems creates a self-amplifying degradation cycle. In order to solve these issues, we focuses on three major modification strategies: (1) Three-dimensional porous current collectors for homogeneous lithium-ion flux regulation and dendrite suppression; (2) Constructing a gradient artificial interfacial layer to inhibit electron leakage and promote ion transport; (3) Developing dynamic self-adaptive interfacial systems that utilize in situ alloying reactions to achieve interface self-healing. In addition, the core contradictions in anode-free systems are furtherly analyzed. Furthermore, we emphasize the critical role of synergistic optimization between current collectors and interfacial layers in enhancing lithium deposition reversibility. By elucidating the fundamental principles and interdependencies of existing modification approaches, this review provides theoretical guidance and innovative design principles for developing high-performance SLMBs with extended cycle life and commercial viability.

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This study investigates the coal multimodal transportation route selection problem by integrating economic and environmental benefits, taking the current coal transportation landscape in China as its research context. Focusing on the transportation network from Shanxi region to Shanghai as a case study, we establish a multi-objective optimization model that comprehensively considers transportation costs, carbon emission costs, and transit time. The NSGA-II algorithm is employed to solve this optimization problem. The results demonstrate that rail-water intermodal transport emerges as an effective solution for optimizing transportation structures. Case analysis reveals that optimal route selections exhibit cost sensitivity, adapting to fluctuations in railway and waterway freight rates. Furthermore, sensitivity analysis indicates that carbon tax rate variations exert limited impact on total transportation costs, while conventional transportation costs maintain their dominant influence. This research provides decision support for sustainable transportation planning in coal logistics systems.

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This paper investigates the DC and AC performance of T-gate Gallium Nitride (GaN) High Electron Mobility Transistors (HEMTs), with a particular emphasis on their high-frequency characteristics under various structure parameters and conditions. The study delves into the impact of different gate structures and the concentration of traps on the RF performance of the devices, including those at the AlGaN/GaN interface and within the GaN buffer layer. Moreover, the analysis includes the examination of short channel effects that can significantly influence the device behavior when the gate length is less than 100nm. Through comprehensive simulations, optimal structural parameters were identified, leading to notable advancements in device performance. Specifically, the devices achieved a remarkable cut-off frequency of 138 GHz and a maximum oscillation frequency of 192 GHz, accompanied by an extremely low gate leakage current, which is lower than 1E-8 mA/mm. These findings highlight the potential of T-gate GaN HEMTs in high-frequency applications.

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This article aims to investigate the effect of Research & Development Expenditure on Apple’s net income. Data from 2010 to 2024, sourced from Statista.com, are analyzed to examine how strategic investments in R&D correlate with financial performance. The method of multiple linear regression is used to analyze the effect of Research & Development Expenditure on Apple’s net income. The effect of advertising spending on Apple’s net income is also considered. The findings indicate a statistically significant positive relationship, suggesting that R&D investments may play a critical role in driving revenue growth. Specifically, each additional billion dollars invested in R&D is associated with an approximate increase of 438 million dollars in revenue. These findings underscore the strategic importance of R&D investments in sustaining and enhancing Apple’s competitive advantage and revenue growth. These insights provide valuable guidance for strategic planning and financial forecasting within the tech sector and beyond, advocating for sustained investment in innovation as a cornerstone of corporate growth strategies. Future studies are recommended to incorporate broader variables and more complex econometric models to deepen understanding of these dynamics.

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Gross Domestic Product (GDP) has been drawn much attention by people because GDP could show the finance situation of a country. Therefore, this study employs the Auto Regressive Integrated Moving Average (ARIMA) model to forecast the real GDP of United Kingdom, Germany, and France for the next three years (2025-2027). Utilizing quarterly real GDP data from 2015 to 2024, the paper identifies optimal ARIMA parameters () for each country and analyzes the implications of the forecasted trends. This study demonstrates the model's effectiveness in capturing economic trends through its interpretable structure and reliable differencing approach. The study also explores the limitations of ARIMA, such as its linearity assumption, and discusses the potential of integrating machine learning (ML) techniques to enhance forecasting accuracy in economic applications. The results indicate varying economic trajectories for the three nations, with policy and external factors like geopolitical events and post-pandemic recovery influencing outcomes. This work promises to be a reference for these countries.

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This paper investigates the issue of conflict resolution between spatiotemporal conflict airspace requirements in low-altitude airspace planning. Regarding to the complex constraints of this multi-objective optimization problem, the quadratic constraints in the problem are relaxed by linear approximation method and the mixed-integer linear multi-objective programming model is established through absolute value linearization and multidimensional Boolean product linearization methods. Subsequently, specific scenarios are designed, and the user airspace application data is simulated. Using the solver to analyze the simulation data, and the results indicate that as the demand scale increases, the solving time increases exponentially, and the solving effectiveness gradually declines after exceeding a certain scale. Finally, through the analyzing of the linear relaxation method, combining with specific data, the deviation of the model from the actual problem is calculated. Due to the relatively small theoretical error, it is proven that this linearized model is applicable to solving the low-altitude airspace conflict resolution problem.

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This study embarks on a comprehensive journey into the intricate and multifaceted world of economic growth models, with a particular emphasis on the mathematical principles that underpin and drive them. At its very core, it meticulously examines the Solow Growth model, a fundamental and highly influential theory that has long been a cornerstone in the realm of economics. Through the sophisticated application of differential equations, the Solow model constructs a dynamic and powerful framework designed to analyze the long - term evolution of economies with remarkable precision. Capital accumulation, which encompasses the gradual process by which an economy builds up its stock of physical capital, such as machinery and infrastructure, as well as human capital through education and training, is identified as a key driver of growth. Meanwhile, labor or population growth supplies the necessary workforce for production, ensuring the continuous operation of economic activities. Technological progress, often considered the most transformative and game - changing factor, continuously enhances productivity by introducing new methods, tools, and knowledge. Together, these elements are not only crucial for gaining a deep - rooted understanding of the underlying mechanisms of economic growth but also for formulating well - informed policies that can effectively foster sustainable development in the long run.

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This paper mainly focuses on the Weierstrass Functions. Firstly, several properties of the Weierstrass Functions are introduced. Process of solving the conjecture suggested by Mandelbrot in 1977, that the graphs of Weierstrass type of functions have Hausdorff dimension. Since existing studies have proved such result with additional conditions through various approaches, this paper provides necessary information indicating this evolving progress in methodology. Given the intertwined relationship between the two, this paper also includes different methods utilized to prove that the Box-counting dimension of the graphs of Weierstrass type of functions is the given number above. In addition, the possible application of Weierstrass Functions and its relation to, for example, financial market are also included. Providing the summary of works, this paper look forward to the final solution to this long-lasting conjecture.

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Cancer poses a significant threat to global health due to its continuously rising incidence rate, high mortality rate, and recurrence rate. Nowadays, traditional cancer treatment methods have limitations, while new therapies such as phototherapy are emerging continuously. With the continuous development of science and technology, an increasing number of nanomaterials are being applied in photothermal therapy and photodynamic therapy within phototherapy, bringing new opportunities for cancer treatment. Among them, carbon-based nanomaterials, including carbon quantum dots, graphene and its derivatives, carbon nanotubes, fullerenes, etc., exhibit great potential in the field of cancer phototherapy because of their unique structures and properties, such as a high specific surface area and strong light absorption ability. For example, carbon quantum dots can be used to construct drug carrier systems and trigger immunogenic cell death. Graphene derivatives can enhance the efficacy of photodynamic therapy. Carbon nanotubes can achieve photothermal ablation and reduce the drug resistance of tumor cells. Functionalized fullerenes can be used for photothermal treatment. However, challenges still remain, including the poor biocompatibility of nanomaterials and the limitations of phototherapy itself. In the future, developing biodegradable nanomaterials, designing multifunctional treatment platforms, and combining photothermal therapy/photodynamic therapy with other treatment methods will continue to be key research directions in the field of biomedicine.

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