Beijing Foreign Studies University

The progressive income tax system is a major model innovation in personal tax changes. Based on the historical observation of the US personal income tax system, it is conducive to the dialectical analysis of the rule of law value, theoretical connotation, and comparative advantages of the progressive income tax system. The benefit theory explains the effectiveness of the progressive income tax system in distributing benefits; the sacrifice theory integrates the welfare of the individual and the state in the progressive income tax; the faculty theory emphasizes the concern for the individual's “ability”; and the justice theory clarifies the systemic significance of the progressive income tax system from the perspective of the rule of law for the development of society. These four theories provide a systematic evaluation of the progressive income tax system from different perspectives, which can help people better understand the reasons for the emergence of this tax system. On this basis, the comparative observation of the system advantages of the progressive tax can also highlight the rationale of a progressive income tax system in terms of social governance.

The emergence of the Russia-Ukraine conflict, therefore presents seismic movements in the global politics, leading towards economic sanctions against Russia as a prominent mechanism in the conflict and diplomatic pressure among many. The sanctions would not only restrict economic activities in and out of Russia but also draw attention to the security of international commercial norms and dispute resolution mechanisms. Justifiably, commercial economic sanctions have recently played a growing critical role in transnational trade. The enterprises that come under sanctions face the dilemma of how to fulfill the contracts and agreements while under the sanctions. This paper tries to raise and discuss the issue of the validity of the international commercial arbitration clause and the arbitrability of the disputes in the background of the economic sanction. It will study through a case analysis the disputes related to the validity of the arbitration clause and the arbitrability of disputes under sanctions. A further approach of comparison is used to look into the different stands taken by diverse authorities on these issues. The work finds that though economic sanctions prove some difficulties, the independence of an arbitration clause, as well as the arbitrability principles, still continue to get wide support. In sanction conditions, arbitration is still an effective and proper method of resolving disputes.

Portrait of a Lady on Fire (2019) is a film directed by Cline Sciamma. In 21th century France, female identity and feminism has become a hot topic in society. It touches areas of politics, economics and art. Several feminism films frequently appeared in the 21th century, Portrait of a Lady on Fire belongs to one of them. It portrays the relationship between two women in the late 18th century, Marianne and Hlose. Hlose is about to be forced to marry, and her worldview and experiences awakes Mariannes rebellious spirit in a patriarchal society. This paper thinks Portrait of a Lady on Fire well discussed female identity and awakening without involving in any male characters. Through applying queer subjectivity theory, the paper is going to discuss how is it possible for the film to achieve this progress. The theory us divided into three aspects: identity fluidity, female gaze, and intersectionality. Portrait of a Lady on Fire provide a new possibility for discussing feminism and patriarchal questions in an all-female environment.

The left inferior frontal gyrus and middle temporal gyrus are core regions in the language network of the brain. This review aims to elucidate the role and research progress of the left inferior frontal gyrus and middle temporal gyrus in language processing as revealed by transcranial magnetic stimulation technology. The left inferior frontal gyrus, traditionally associated with syntactic processing, has recently been implicated in semantic processing. Meanwhile, the middle temporal gyrus is primarily linked to semantic storage and lexical access. However, some studies suggest it may also play a role in syntactic processing, particularly in the processing of complex sentence structures. The interaction between the left inferior frontal gyrus and the middle temporal gyrus remains another area of debate. Some studies have indicated that these two regions operate independently, whereas other studies propose that they collaboratively integrate syntactic and semantic information. Transcranial magnetic stimulation is an important tool for investigating these controversies. By interfering with specific brain regions, research on transcranial magnetic stimulation provides evidence that the left inferior frontal gyrus and middle temporal gyrus are involved in various aspects of language processing. Nevertheless, research on transcranial magnetic stimulation also faces several challenges, including limitations in spatial and temporal resolution, inter-individual variability, and constraints in task design. Addressing these challenges is essential for advancing our understanding of the semantic network.

In the context of the post-truth era, characterized by the diverse manifestations of misinformation across varying cultural backgrounds, older adults, often considered more susceptible to misinformation, require focused research to understand their perceptions regarding its spread. Therefore, this study investigated the third-person perception of misinformation sharing behavior among Chinese older adults ( N = 317), a group that requires greater research attention. Results confirmed the existence of third-person perception in misinformation sharing on WeChat. Furthermore, results indicate that this perception is stronger among individuals with better fact-checking habits, higher misinformation verification abilities, and lower trust in information. Analyzing these findings within the Chinese cultural context, the study bridges the classic third-person effect hypothesis and cultural specificity, offering empirical insights into an underexplored demographic.

Background/Objectives This study investigates the relationship between dairy-egg-meat (DEM) consumption, physical exercise, and mild cognitive impairment (MCI) among Chinese older adults, focusing on gender-specific patterns and potential moderating effects. Methods Using data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS), we conducted a longitudinal analysis of 14,640 participants aged 55 and above, followed from 2008 to 2018. The study utilized Cox Proportional Hazard Models to examine the associations between baseline DEM consumption and MCI incidence. A composite DEM consumption measure, ranging from 0 to 3, with exercise assessed as a binary interaction variable. Cognitive function was evaluated using the Chinese version of the Mini-Mental State Exam, with MCI diagnosed using aging-associated cognitive decline (AACD) criteria. Results The overall MCI prevalence was 11.54%, with significant gender differences. The proportion of MCI among females (13.68%) was higher compared to males (8.85%). Moderate to high DEM consumption demonstrated protective effects against MCI with gender-specific patterns, showing a significant protective effect of exercise for high DEM consumption (HR = 0.780). Conclusions The study reveals a complex, gender-specific relationship between DEM consumption and MCI risk. Exercise emerges as a significant moderator, particularly for males, highlighting the importance of integrated dietary and physical activity approaches to cognitive health. The findings underscore the need for gender-sensitive interventions targeting nutrition and physical activity among older adults.

Blended learning has been widely recognized as a valuable practice that contributes to students’ academic achievement. However, this mode of education is accompanied by constraining factors that influence students’ motivation in the process of learning and that influence their knowledge internalization. In this study, a qualitative inquiry was made into students who were enrolled in a blended learning course of English reading at a university in China during which self-assessment was required alongside learning. Through a case study approach and a thematic analysis of data sources (e.g., interviews with the students and their self-assessment journals), the study shows that blended learning benefitted but also challenged the students, while self-assessment helped them critically reflect upon their learning pace by identifying progress and issues, restoring their motivation to undertake blended learning and facilitating their knowledge construction. Ultimately, both students’ self-assessment and blended learning became relatively stable, with both practices individually benefiting the students, and formed a mutually feeding and interactive loop that benefited students holistically. The study concludes by assessing the pedagogical usefulness of synergizing blended learning and self-assessment to support students’ academic development.

Neurological diseases, such as Alzheimers disease (AD) and Parkinsons disease (PD), have long posed significant health challenges due to their complex pathogenesis and the profound impact they have on patients' quality of life. Traditional treatments often fall short of providing radical cures, particularly hindered by barriers like the blood-brain barrier (BBB). In recent years, biopharmaceuticalsleveraging advanced technologies such as genetic engineering and cell engineeringhave emerged as promising therapeutic alternatives. This paper summarizes biopharmaceutical strategies for treating these two neurological diseases, analyzes the advantages and disadvantages of biopharmaceutical technologies in disease treatment, and provides a detailed description of the pathogenesis and clinical manifestations of these diseases. The conclusion highlights that biopharmaceutical technology has become one of the most effective means for treating neurological diseases, but it still faces obstacles and limitations. Future advancements require technological improvements and clinical trials to enhance treatment success rates and refine preventive measures for neurological diseases.

In recent years, far-right parties have become a prominent force in European politics. Europe faces complex challenges, including debt crises, refugee influxes, and the growing social inequality brought about by globalization, which pose significant governance challenges. This paper analyzes the varied developmental trajectories of populist parties across different European countries and examines both internal and external influencing factors.By integrating an analysis of government effectiveness, party structures, and societal demands, this study proposes a theoretical framework to examine the rise of far-right populist parties. Using cases from France, Germany, Sweden, Belgium, and Italy, the article identifies eight situation of far-right party emergence, shedding light on how these factors shape their survival and evolution.

The application of artificial intelligence (AI) in customer service becomes ubiquitous. In response to the advocacy in the “2021 Coordinated Plan on Artificial Intelligence”, it is crucial to understand how to leverage AI customer service chatbots for societal welfare. Across two scenario studies and one lab experiment, this research investigates the impact of AI chatbots’ communication styles on consumers’ subsequent prosocial intentions irrelevant to the AI-human interaction contents. The combined evidence suggests that consumers exhibit higher prosocial intentions after interacting with social-oriented (vs. task-oriented) AI chatbots. The findings reveal the chain-mediating roles of social presence and empathy. Moreover, the current research investigates the boundary effect of consumers’ goal focus (process focus vs. outcome focus), and shows that AI chatbots’ communication styles have stronger impact on prosocial intentions for customers with outcome focus. These results revealed the important externality of the AI application in marketplace and provide a novel perspective for companies to implement the corporate social responsibility (CSR) strategy.

To address the challenges of label sparsity and feature incompleteness in structured data, a self-supervised representation learning method based on multi-view consistency constraints is proposed in this paper. Robust modeling of high-dimensional sparse tabular data is achieved through integration of a view-disentangled encoder, intra- and cross-view contrastive mechanisms, and a joint loss optimization module. The proposed method incorporates feature clustering-based view partitioning, multi-view consistency alignment, and masked reconstruction mechanisms, thereby enhancing the model’s representational capacity and generalization performance under weak supervision. Across multiple experiments conducted on four types of datasets, including user rating data, platform activity logs, and financial transactions, the proposed approach maintains superior performance even under extreme conditions of up to 40% feature missingness and only 10% label availability. The model achieves an accuracy of 0.87, F1-score of 0.83, and AUC of 0.90 while reducing the normalized mean squared error to 0.066. These results significantly outperform mainstream baseline models such as XGBoost, TabTransformer, and VIME, demonstrating the proposed method’s robustness and broad applicability across diverse real-world tasks. The findings suggest that the proposed method offers an efficient and reliable paradigm for modeling sparse structured data.

With the increasing frequency of China–Africa interactions, the importance of Swahili in China–Africa relations is steadily growing. However, there is still a notable lack of research on Swahili news corpora and discourse analysis. This study adopts both quantitative and qualitative methods to examine China’s national image construction through media under the critical discourse analysis (CDA) framework. Focusing on the mainstream media China Radio International (CRI), a micro corpus was built to analyse word frequency, word clusters and concordance lines, with the aim of exploring linguistic features and discourse structures of news reports. The findings indicate that by covering China’s efforts in promoting China–Africa affairs with positive discourse, CRI generally holds a positive attitude in news reports to construct a responsible global actor role. Meanwhile, CRI’s discourse construction also exhibits an imbalance in lexical choice with a tendency to emphasize positive achievements while downplaying challenges and difficulties. This reflects underlying power dynamics, socio-cultural influences, and ideological tendencies. This study could provide a reference for optimizing the construction of China’s image in Africa through African indigenous language media.

Driven by the global green transformation and carbon neutrality, new energy vehicle (NEV) industry has become the core area of international competition and cooperation. In recent years, the policy environment of the European NEV industry has changed significantly, especially under the influence of De-Risking policy, raising regulatory barriers while reshaping market dynamics. Chinese NEV enterprises are facing both challenges and opportunities in entering the European market. These shifts have driven up compliance and production costs, altered investment flows, and intensified supply chain restructuring. As a result, Chinese NEV manufacturers not only face higher entry costs, but also must navigate changing consumer demand and competitive pressures in an increasingly protectionist environment. This study focuses on two Chinese NEV companies, BYD and Geely, and explores their expansion strategies, supply chain localization, and technology cooperation models in the European market. The study finds that, despite the increased barriers to enter into the European market, Chinese firms can still maintain their competitive advantage by strengthening supply chain localization, deepening cooperation with European firms, and promoting technological innovation. This study helps to understand the evolution of European NEV industry policies and provides a reference for Chinese NEV enterprises to formulate internationalization strategies.

The check-in process is a crucial aspect of airport management, requiring effective coordination between the terminal and airlines. Emergencies and the pandemic have exacerbated challenges in managing the check-in process, resulting in long queues and extended waiting times, particularly during peak departure periods. Predicting check-in waiting times accurately can optimize terminal operations and enhance passengers’ departure experience. Therefore, there is an urgent need for airports to possess predictive capabilities to fully leverage their facilities. This paper presents a machine learning-based approach for predicting passenger check-in waiting time. Firstly, this paper collects real data from one of the largest worldwide airports in its major domestic terminal from September 2021 to January 2022. Next, the collected data is analyzed and processed, with continuous features categorized to derive meaningful response variables. Moreover, this paper compares various machine learning classifiers and optimizes the best-performing classifiers, such as Gradient Boosting Machine (GBM) and Random Forest (RF), and discusses the impact of thresholds and features on the accuracy of the models. Based on real-world data analysis, Gradient Boosting Machine exhibits the highest multi-class classification accuracy (0.790; 0.731) and F1-score (0.648; 0.479) compared to other models, achieving an overall AUC of 0.95. The experimental findings suggest practical applications for airport management in both current and future prediction scenarios. This model has been applied in the airport system to facilitate the rational allocation of check-in resources.

Research conducted on alphabetic languages has yielded findings suggesting that readers tend to allocate more time towards processing the final words of a sentence or clause, commonly referred to as the wrap-up effect. Several theoretical accounts of the wrap-up effect advocate causal mechanisms that are supposed to generalize over readers of all languages yet are based on a small selection of written languages and writing systems. Whether the wrap-up effect occurs in naturally unspaced, logographic languages such as Chinese remains unclear. We carried out an eye movement study focused on simplified Chinese reading, intending to discern whether the wrap-up effect at the end of the sentence is modulated by visual complexity. Native readers of Mandarin Chinese were tasked with reading sentences featuring target words manipulated in terms of visual complexity (high vs. low) and word position (final or medial) in the sentence. We found that words at the end of sentences were processed as quickly or even faster than those in the sentence-medial position depending on the eye-movement measure, and that the complexity of characters did not affect the wrap-up effect. This reversed or null wrap-up effect calls for a revision of proposed theoretical accounts grounded in the processing of alphabetic languages. The findings suggest that sentence processing in simplified Chinese is highly incremental, and the information-theoretical account is the one that does not contradict the observed direction of the wrap-up effect.

As China’s digital economy sectors rapidly expand, the growing demand for coal-based electricity has become a significant source of CO2 emissions. However, the mechanism driving these emissions within supply chains remain unclear, hindering targeted carbon management. This study addresses this gap by providing a comprehensive analysis of CO2 emissions thorough the whole supply chain perspective, covering income-, production-, betweenness-, and consumption-based perspectives, along with upstream and downstream supply chain paths. It employs Leontief and Ghosh input-output (IO) frameworks and structural path analysis. The results indicate: (1) The core industry sector of the digital economy (CIDE) ranks highest in CO2 emissions from consumption-based perspective, while the industrial digitalization sector (IDS) ranks highest from both consumption- and betweenness-based perspectives. (2) Inter provincial flows are the main source driving the digital economy sectors’ supply chain embodied CO2 emissions from consumption-based perspective, while labor compensation is the primary source driving its enabled CO2 emissions from income-based perspective. (3) High-carbon upstream and downstream supply chain paths driven by the digital economy sectors are short, with the power and heat production and supply sector and IDS playing crucial roles within these chains. Based on these findings, policy recommendations are provided to optimize supply chain structures, promote green consumption, and integrate carbon management into sector-specific strategies to reduce emissions across both upstream and downstream paths.

This article examines representations and discussions of Eileen Gu, a biracial athlete who represented China in the 2022 Winter Olympics and won two gold medals and one silver medal, on Chinese state-owned and social media. Despite Gu’s unprecedented achievement, her identity drew controversy in China. This comparative study of media discourses on Gu reveals how Chinese identity is contested in a global context. The analysis suggests that state-owned and social media use different rhetoric to discuss Gu’s Chinese identity as either a state of being or a process of becoming. State-owned media highlight Chinese identity as a “being” by emphasizing Gu’s kinship and cultural ties to China, thus acknowledging her essentialized identity as a Chinese. Social media, represented by Zhihu , underscore Chinese identity as a “becoming” that is not only based on connections to China but also on reiterated performances of Chinese culture and commitment. Social media users largely negate Gu’s Chinese identity due to her perceived failure to provide sufficient evidence that she has become Chinese. The two modes of rhetoric reflect the state’s and ordinary citizens’ respective relationships with global elites, which have shaped their varied framings of Gu.