Guangdong Polytechnic of Science and Technology

Stance expressions and markers are a heated topic in global linguistic research, with style stance adverbs as a core form of stance markers, classified alongside epistemic and attitude stance adverbs. This study employs an AI-powered corpus-based comparative analysis method to probe into 11 top English style stance adverbs in the Chinese Learners of English Corpus, British National Corpus and Corpus of Contemporary American English. AI instruments are applied to optimize corpus data retrieval, statistical analysis and positional distribution mapping and make comparative analyses of their use characteristics and positional distribution of the style stance adverbs between Chinese English learners and native speakers to probe into their interpersonal pragmatic functions and use characteristics. The research findings reveal significant discrepancies: Chinese learners overuse style stance adverbs with a narrow vocabulary range, and misapply spoken-language positional conventions (initial/final placement) in written discourse resulting from insufficient understanding of their structural and functional features in academic contexts. This study deeps and widens stance adverb research and provides guidance for EFL teaching and learners' pragmatic competence improvement.

With the increasingly serious problem of environmental pollution, air purifier has become an important equipment to improve indoor air quality. In this study, an intelligent air purifier based on STM32 F407VGT6 single chip micro computer is designed. The air quality is monitored by sensors, the fan and other components are controlled by single chip microcomputer to realize automatic purification. Its features encompass air quality monitoring, adjustable wind speed with multi-speed modes, configurable safety thresholds, remote operation via Wi-Fi connectivity, and user-defined parameter customization. The hardware/software design is detailed herein. Experimental validation confirms stable operation, effective PM2.5/formaldehyde reduction, AQI maintenance within optimal ranges, rapid responsiveness, and intuitive controls, which render it suitable for residential and office use with strong market prospects.

This paper proposes a decentralized operational planning framework for integrated transmission and distribution (TN–DN) networks that enables coordinated yet autonomous decision-making between network operators. A fully nonlinear alternating-current optimal power flow (AC-OPF) model is formulated for both TN and DN subsystems to capture voltage and reactive-power constraints accurately. A iterative coordination mechanism is introduced to preserve data privacy while ensuring operational consistency through limited exchange of active and reactive power at boundary buses. To solve the resulting high-dimensional, highly constrained nonlinear optimization problem efficiently, an enhanced particle swarm optimization (PSO) algorithm is developed, incorporating time-varying learning coefficients, adaptive local search, and chaotic diversity control to accelerate convergence and improve solution quality. In addition, a robust max–min optimization strategy is integrated to identify worst-case sudden generator outages without relying on scenario enumeration or probabilistic assumptions. The approach is validated on standard IEEE test systems. Numerical results show that the decentralized framework attains solutions close to centralized optimality while lowering computational effort, improving scalability, and enhancing resilience to generator contingencies, demonstrating its practical suitability for coordinated TN–DN operation planning.

To address heavy metal pollution in river and lake sediments amid China's urbanization, this study developed an iron-based biochar stabilizer using corn straw modified by chemical-physical methods. The modification significantly increased the biochar's surface roughness, forming a 50 – 200 nm iron oxide adhesion layer. While its specific surface area slightly decreased from 418 m²/g to 376 m²/g, the proportion of mesopores rose, creating more sites for heavy metal adsorption. Characterization results show that the iron-based biochar binds heavy metals through surface functional groups like -OH and C=O, demonstrating stable adsorption performance for various heavy metals (including Cr(VI), Cd(II), Pb(II), and As(III)). Compared with unmodified biochar, it improved the average solidification rates of Zn, Cu, Cr, Pb, Ni, and as by 23.5 %, 18.7 %, 27.3 %, 25.1 %, 19.8 %, and 21.2 %, respectively. Notably, the solidification of Cr(VI) was particularly effective due to the redox catalytic action of Fe³⁺/Fe². After adsorption, the material's porosity recovered to 72 %, indicating enhanced recyclability through iron-based modification. The leaching concentration of heavy metals in the treated sediment meets national standards, and the treatment cost is over 60 % lower than that of traditional technologies. Additionally, the solidified sediment can be safely reused for land improvement or building material production, offering an economical and efficient resource-oriented solution for controlling heavy metal pollution in sediments.

Front-illuminated GaN-based p-i-n photodiodes (PDs) incorporating indium-surfactant -assisted (ISA) Mg-δ-doped p-GaN were fabricated and systematically characterized. Hall-effect measurements at room temperature revealed a hole concentration of~1.5 × 1018 cm−3 in the ISA Mg-δ-doped p-GaN, significantly higher than that of uniformly Mg-doped p-GaN (~3.7 × 1017 cm−3). Devices employing ISA Mg-δ-doped p-GaN exhibited reduced leakage current, enhanced responsivity, faster response speed, improved reliability, and lower noise current compared to control PDs. These comprehensive performance enhancements, attributed to the improved crystalline quality and the optimized electric field distribution, suggest significant potential in practical UV applications.

Objective: From the perspective of sustainable governance, this study explores the evolutionary trajectory of "landscape gene" research in China to understand how policy frameworks and legal instruments shape the preservation of traditional settlements.Methods: Utilizing bibliometric tool CiteSpace , a quantitative analysis was conducted on literature from the CNKI database (2003–2025), focusing on the intersection of heritage conservation, environmental law, and digital governance.Results: The research reveals that landscape gene studies in China have evolved through three logical dimensions: theoretical ontology construction, multi-scale empirical verification, and methodological innovation driven by strategic policy responses. Since 2017, the field has entered a phase of intensive growth, shifting from qualitative descriptions to digital and intelligent integration.Conclusion: The evolution of landscape gene research is deeply intertwined with China’s national strategies, such as "Rural Revitalization" and the "Protection of Traditional Villages," reflecting a transition from spontaneous academic interest to a policy-led governance model. To enhance the sustainable development of cultural landscapes, future research must further integrate legal-spatial frameworks with digital technology, ensuring that heritage conservation is supported by robust institutional mechanisms and internationalized theoretical standards.