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“Beauty Servitude” as Metaphor in Contemporary Chinese Discourse: An Invitational Rhetorical Perspective
Full text linkThis study investigates the contested metaphor of “beauty servitude” (fu mei yi) in contemporary Chinese public discourse, examining how women’s beauty practices are rhetorically framed in relation to labor, obligation, agency, and structural constraint. Using qualitative rhetorical analysis, the study analyzes a public debate as its primary data source. The analysis combines high-frequency word statistics with inductive qualitative coding to identify recurring metaphorical patterns and argumentative strategies. Adopting invitational rhetoric as an analytical lens, this study shows that the metaphor both enables and constrains public understanding. While it invites attention to structural power and gender inequality, it may also limit recognition of women’s embodied experiences and self-defined agency
Simulation Research on Adaptive Control System of Combine Harvester Feeding Rate Based on Fuzzy PID
Full text linkDuring field operations, combine harvesters frequently encounter significant fluctuations in feeding rates attributable to the stochastic nature of crop density and uneven growth patterns. These irregularities often precipitate critical mechanical failures, such as threshing drum blockages and engine stalling. To mitigate these operational risks, this study proposes a robust adaptive control strategy for feeding rate regulation rooted in fuzzy logic. Initially, a mathematical model of the system dynamics is constructed by analyzing the nonlinear coupling between the harvester’s forward speed and the feeding rate, incorporating characteristics of significant inertia and pure time delay. Addressing the inherent limitations of conventional PID algorithms—specifically their inadequate parameter adaptability and weak disturbance rejection under complex, time-varying conditions—a fuzzy adaptive PID controller is designed. This controller utilizes the feeding rate error () and its rate of change as inputs to facilitate online, real-time tuning of the proportional, integral , and derivative parameters via a fuzzy inference mechanism. Simulation experiments conducted on the MATLAB/Simulink platform demonstrate that, compared to traditional PID control, the proposed system reduces overshoot by approximately 14.2% (from 18.3% to 4.1%) when subjected to step changes in crop density. Furthermore, the settling time is significantly truncated, and steady-state error is effectively eliminated. These results corroborate that the proposed control strategy exhibits superior robustness and dynamic tracking capabilities, thereby satisfying the rigorous requirements for automated operation in modern precision agriculture
Announcement of Retraction
Full text linkThe editorial board announced this article has been retracted on March 6, 2026.If you have any further question, please contact us at: [email protected] Article Title: Announcement of RetractionAuthor/s: Harry GrantJournal Title: Modern Management Science & EngineeringISSN: 2052-2576Volume and Number: Vol. 8, No. 1, 2026Pages: 121-132DOI: https://doi.org/10.22158/mmse.v8n1p12
Research on the Reform of Consumption Tax from the Perspective of the Postponement of Collection Links
Full text linkAgainst the backdrop of tax reduction and fee reduction, China proposed the reform of adjusting the collection link of consumption tax and transferring consumption tax revenue to local governments in 2019. So far, China has clarified the next direction of consumption tax reform: moving the collection link back to the wholesale or retail stage to expand local revenue sources, guide consumers to regulate their consumption behavior, and improve the consumption environment. Combining the current development status of consumption tax and the existing problems in its collection link, this paper elaborates on the necessity of postponing the collection link of consumption tax, and analyzes its feasibility—such as the support from local governments and consumer goods manufacturers. The implementation of policies related to the postponement of consumption tax collection may lead to some problems that urgently need to be solved, including increased tax costs, difficulties in tax collection and administration, and the broken balance of interests among governments, enterprises, and consumers. This paper also puts forward reasonable suggestions for the optimization of the postponement of China’s consumption tax collection link from the perspective of different subjects, taking into account the balance of interests of the government, enterprises, and consumers, so as to make the consumption tax policy more perfect and reasonable, create a standardized and orderly consumption environment, and give full play to the regulatory role of consumption tax in economic life
Research on the Linkage between Chinese and American Stock Markets
Full text linkThis article selects the VAR model to explore the performance linkage between Chinese and American stock markets. Firstly, this article selects the Shanghai and Shenzhen 300 Index and the Dow Jones Index as representative variables of the Chinese and American stock markets, uses daily data from March 1, 2017 to December 29, 2023 to construct and estimate VAR models, conduct model estimation, and analyze impulse responses. Finally, it concludes that there is a lag effect linkage between Chinese and American stock markets, with both indices showing positive volatility. The Dow Jones Index has a positive impact on the Shanghai and Shenzhen 300 Index, and vice versa. Based on this conclusion, it suggests that when formulating cross-border investment and risk management strategies, one should consider the impact of significant events affecting both Chinese and American stock markets
Generative AI and the Shaping of Academic Voice: Language, Normalization, and Epistemic Justice in AI-mediated Assessment
Full text linkDespite the potential of Generative Artificial Intelligence (GenAI) to support research and academic production, attention must be paid to its implications for human learning and the development of voices and epistemologies in multilingual contexts. A central concern in critiques of GenAI is that language is frequently treated as a transparent medium, rather than as a site where biases and hierarchies are produced and reproduced by AI systems. This paper argues that GenAI intersects with existing hierarchies of academic knowledge production, assessment, and validation, especially in relation to the voices of multilingual authors. This study reports findings from an empirical analysis of academic writing produced by multilingual Master’s students under contrasting assessment conditions: a restricted digital examination environment and an unrestricted setting with full access to online tools. Rather than seeking to detect AI use, the analysis examines how different assessment regimes shape register consistency, source integration, authorial voice and linguistic diversity. Findings suggest that unrestricted environments are associated with higher surface-level academic quality, but also with increased pressures toward normalization, potentially erasing linguistic diversity, weakening authorial voice and marginalizing alternative rhetorical and epistemic traditions. The paper concludes by advocating language-aware approaches to GenAI to enable epistemic justice and language diversity
Research on the Reproduction of Original Text Style in the English Translation of Chinese Architectural Aesthetics
Full text linkChinese architectural aesthetics, imbued with profound philosophical thought, cultural connotations, and artistic spirit, sees its English translation as a vital component of China's "going global" strategy for culture. However, the significant disparities between Chinese and Western thinking patterns, aesthetic systems, and linguistic structures pose a core challenge: how to accurately convey the aesthetic essence and unique style of the original text in the translation. This paper aims to systematically investigate the issue of style reproduction in the English translation of texts on Chinese architectural aesthetics. It focuses on the stylistic features of such texts at the lexical, syntactic, rhetorical, and textual levels, and the challenges encountered during cross-cultural transfer. By constructing an integrated analytical framework encompassing "Linguistic," "Cultural," and "Aesthetic" dimensions, this study selects English translations of classical and contemporary architectural texts, such as The Craft of Gardens and Chinese Architecture: Art and Artisanship, for detailed comparative case analysis. The findings reveal a trend in style reproduction strategies, shifting from a dominance of "domestication" towards a balance between "foreignization" and "compensation." Successful translations manage to preserve the poetic quality, ambiguity, and philosophical depth of the original texts within the acceptability limits of the target readers, through creative use of English lexicon and syntax, flexible handling of culture-specific terms, and skillful transplantation of rhetorical imagery. The study concludes that the reproduction of style in translating Chinese architectural aesthetics is a dynamic and creative process of "rewriting," whose ultimate goal is to achieve cultural fidelity and aesthetic equivalence, rather than mechanical word-for-word correspondence. This research holds theoretical and practical significance for enhancing the quality of translating Chinese architectural culture and deepening the dialogue between Chinese and Western architectural aesthetics
Teachers’ Strategies, Challenges, and Discipline Among Modern-Day Learners in the Classroom at Sinunuc National High School, Zamboanga City
Full text linkThis study examined the teachers’ strategies, challenges, and levels of discipline among modern-day learners at Sinunuc National High School in Zamboanga City. Using a mixed-method design, the quantitative phase involved thirty (30) Senior High School students who assessed the extent of teachers’ strategies and student discipline through a structured survey. The qualitative phase consisted of interviews with five (5) Senior High School teachers to explore the challenges encountered in maintaining classroom order. Descriptive statistics and regression analysis were utilized for quantitative data, while thematic analysis was employed for qualitative responses. Results revealed that teachers consistently used effective communication strategies, behavioral interventions, and collaborative problem-solving techniques to promote discipline. Students demonstrated a high level of discipline characterized by respect, compliance, and responsibility. Regression results showed that teachers’ strategies significantly predicted 68% of the variance in students’ discipline, indicating a strong relationship between teacher practices and student behavior. Findings highlight the importance of positive reinforcement, participatory rule-setting, restorative approaches, and consistent communication. Recommendations include strengthening student-centered strategies, enhancing teacher training, and sustaining collaborative discipline practices to improve classroom management and learner engagement
Research on the Construction of an Educational Service Quality Evaluation System Driven by Artificial Intelligence Technology
Full text linkIn the context of high-quality educational development, the scientific and objective evaluation of educational service quality has become a key concern in educational governance and management. Traditional evaluation approaches face limitations in indicator design, data sources, and result application, which restrict their ability to reflect the dynamic and multidimensional nature of educational service processes. With the deepening application of artificial intelligence in education, its strengths in multi-source data processing, pattern recognition, and intelligent analysis offer new possibilities for improving evaluation systems. Based on a systematic review of existing studies and the foundations of AI applications, this research constructs an educational service quality evaluation system centered on data integration and intelligent analysis. The study focuses on evaluation framework design, indicator system construction, and evaluation model development, and examines how artificial intelligence supports comprehensive assessment and result feedback. A case study is conducted to validate the feasibility and effectiveness of the proposed system. The findings demonstrate that artificial intelligence can enhance the scientific rigor, dynamic adaptability, and practical value of educational service quality evaluation, contributing to the modernization of educational governance
Application of Data Mining Techniques in Customer Segmentation for Commercial Banks
Full text linkCommercial banks are able to use Data Mining Technology (DMT) to improve their capability to segment customers or gain more thorough insight into their value. By developing DMT research methodologies that incorporate a variety of techniques including clustering methods, classification algorithms and other techniques to analyze multiple dimensions (e.g., customer transaction history and consumer behavior), conclusions can be drawn from the resultant output. Results of the research show that DMT can uncover previously unrecognized patterns of demand among customers, allowing for the design of individualized products and providing banks with a scientific framework for determining the optimal allocation of marketing resources