Beijing Language and Culture University

To address the limitations of traditional dominance relation-based rough sets in handling information systems with partial order relations, this paper proposes a multi-attribute decision-making method based on entanglement dominance relation. First, the definition of the existing entanglement domain is revised, and the concept of entanglement dominance relation is introduced. The properties of the entanglement domain and its computation method-the improved Bron-Kerbosch algorithm are discussed. On this basis, a secondary ranking method is proposed, in which the subsets of the entanglement domain are first externally ordered, and then the objects within each subset are internally ordered according to specified rules. Finally, an empirical analysis of logistics supply chain performance evaluation is conducted to verify the effectiveness and dominance of the proposed method. The results demonstrate that this method can more accurately reflect the superiority and inferiority relation among objects, providing a new perspective and solution for multi-attribute decision-making problems.

Using immunotherapy to treat breast cancer, one of the most common cancers that affects women and the second most common cancer among women in the United States, has achieved many successes. However, how to solve the problem of cancer resistance to therapies caused by myeloid-derived suppressor cells and immunosuppressive tumor microenvironment remains a major challenge. To improve the performance of immunotherapy, we chose to explore the three putative therapeutic approaches including anti IL 8 antibody injection, PDH inhibition, and the use of tasquinimod, then combining them to observe anti-tumor effects in a murine model. We anticipate the greatest decrease of tumor volume in triple combination, concluding the feasibility of our method on treating breast cancer.

The proposed study examines the teaching competence of teachers in an English subject in one of the major senior high schools within an underdeveloped region of Henan Province, China in the context of continuous changes in the field of education with an emphasis on equity and quality, language proficiency, instructional practices and reflection, and the implementation of curriculum remain the main problems of teachers. Besides that, this research hypothesizes the need-based training, reflective systems of teaching, and fairly distributing all available resources to facilitate sustainable development of teachers and minimizing inequality in education in the questionable areas.

The increasingly frequent use of ChatGPT in higher education raises questions about its impact on how students critically read a range of academic texts. However, empirical evidence examining the relationship between the dependence and critical use of ChatGPT and college students' critical reading ability is limited. Three aspects were investigated in this study: students' dependence on ChatGPT, their critical use of ChatGPT, and how these relate to students' critical reading skills. This study aimed to examine university students, specifically 79 students at a public university in Indonesia. Students were given a critical reading test, which was in the form of an essay, and there was also a questionnaire to measure students' dependency and critical use of ChatGPT. The results were descriptive, showing that the students' level of ChatGPT dependency was moderate (mean = 3.10) and their level of critical use was quite good (mean = 3.87). For critical reading scores, results ranged from 31.25 to 92.19, with an average in the moderate category. The results of multiple linear regression show that neither critical use nor dependence on ChatGPT has a statistically significant relationship with students’ critical reading skills (β = 0.164, p = 0.151; β = −0.071, p = 0.530). Overall, these results indicate that students' engagement with ChatGPT has not had a clear or significant effect on their critical reading performance. Further research is needed to confirm these findings. These findings indicate that reliance on AI and critical use of ChatGPT alone may not be sufficient to influence students' critical reading abilities, suggesting that other factors may also play a role. Therefore, future research should involve a more diverse population and develop more specific, contextually relevant instruments, particularly those linking ChatGPT use to critical reading skills, while also considering other mediating variables.

From the perspective of cross-cultural communications, translation is frequently perceived as a cross-cultural process influenced by ideological forces. The history of the multiple Chinese retranslations of On the Road—a cornerstone of American Beat literature—published in mainland China between the 1960s and the early twenty-first century serves as a compelling testament to this notion. Over the decades, this novel has been translated into five distinct Chinese editions, with interpretations of the original text fluctuating significantly—from being dismissed as literary trash to being celebrated as a literary classic. By situating these shifts in textual interpretation within the historical and sociocultural context of mainland China, this paper seeks to demonstrate that the relationship between ideology and translation is neither linear nor unidirectional. Instead, it often exhibits more intricate dynamics. On one hand, there are evident cases of manipulation, or what might be described as collusion, between translation and prevailing ideologies. On the other hand, translation can also evolve independently of ideological frameworks, occasionally diverging to the extent of challenging or even subverting dominant ideologies. Such a phenomenon underscores the inherent autonomy of translation as sociocultural acts.

ABSTRACT This study investigates the impact of age on foreign language aptitude (FLA) constituents and their underlying cognitive‐affective mechanisms. We recruited 85 Chinese‐English bilingual participants, categorized into two age groups: 44 adolescents aged 13–17 and 41 adults aged 18–25. Results revealed a double dissociation: adolescents outperformed adults in implicit language aptitude (ILA), while adults excelled in explicit language aptitude (ELA). Mediation analyses showed that selective attention (SA) fully accounted for age differences in ELA, whereas time perception partially mediated the age‐ILA relationship. These findings suggest that age influences FLA through distinct cognitive and affective pathways, with positive effects on ELA and negative effects on ILA. Based on these results, we propose the dual‐pathway model of age‐driven FLA (DP‐AFLA), which provides a framework for understanding how distinct cognitive‐affective mechanisms shape age‐related FLA patterns. This study advances theoretical understanding of age‐related FLA dynamics and offers practical insights for age‐tailored language instructional strategies.

ABSTRACT This study used Latent Profile Analysis to identify foreign language teachers’ perception profiles of Generative AI (GenAI), revealing three distinct profiles: Sceptical Adopters with moderate negative perceptions (i.e. anxiety and risk) and ease of use, and the lowest levels of other positive perceptions (i.e. usefulness, controllability, confirmation, and satisfaction), Confident Enthusiasts with the lowest negative and high positive perceptions, and Cautious Optimists with high levels of both positive and negative perceptions. Personal and environmental factors significantly influenced these profiles. Confident Enthusiasts had the highest intention to continue using GenAI, followed by Cautious Optimists, whose intention was higher than that of Sceptical Adopters. The study highlights the need for technology acceptance theories to consider the coexistence of positive and negative perceptions in influencing technology adoption.