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The Application of Discourse Cohesion Theory in the 2024 Government Work Report
Full text linkAs an official medium and important channel for external communication, the translation of the Government Work Report into another language must maintain the coherence and cohesion of the discourse, which has a significant impact on the national image and the effectiveness of cultural value dissemination. Guided by discourse cohesion theory, this study analyzes the challenges in translating the report to demonstrate how various cohesive devices play a role in the translation of such texts. The article focuses on five aspects of translation: reference, substitution, ellipsis, conjunction, and lexical collocation, with specific examples provided for illustration. Given the notable differences between English and Chinese cohesive devices, translation methods such as addition, omission, and repetition are required to achieve effective translation outcomes. Under the guidance of cohesion theory, translators can develop a stronger awareness of discourse and a global perspective on translation, thereby enhancing the external communication effectiveness of the translated text
Research on the Ideological and Political Teaching Mode of Civil Engineering Construction Course under the Background of Emerging Engineering Education
Full text linkThe construction of Emerging Engineering Education (3E) imposes higher requirements on the training of engineering talents. Integrating ideological and political education into professional courses has become a key pathway to enhance students’ comprehensive qualities. This paper, considering the learning characteristics of junior students majoring in civil engineering and the actual teaching situation of the Civil Engineering Construction course, proposes a three-dimensional ideological and political teaching mode of “Case Guidance - Project Driving - Ability Progression”. This model uses real engineering cases as the carrier and project-based teaching as the driving force. Through a three-stage ability cultivation system of “cognition -- practice – innovation”, it achieves the organic integration of professional knowledge imparting, engineering ability training, and ideological value shaping. Teaching practice indicates that this model helps enhance students’ professional identity, engineering ethics awareness, and practical innovation ability, providing an operable reform approach for the ideological and political construction of engineering courses
Legal Controversies and Institutional Construction of Deep-Sea Mining within the Framework of International Law of the Sea
Full text linkUse of minerals in the international seabed area (the “Area”) can be deemed one of the most important frontiers in today’s modern international law by virtue of its own value of minerals from the “Area” and conflicting matter of the fragile eco-system of “Area”. Following the United Nations Convention on the Law of the Sea (UNCLOS), The area and its resource were called “the common heritage of mankind”, it will be necessary to create some kind of a system that is effective, fair and is with a sound premise for protecting environment in future. However, while the International Seabed Authority (ISA) is transitioning from regulating exploration to formulating the Mining Code for exploitation, deep-seated legal controversies have arisen. These disputes revolve around how to implement the precautionary principle, how to distribute the financial benefits of equitably, what the gaps in liability for environmental damage are, and what procedural pressure is caused by the so-called “two-year rule”. This paper analyzes these legal controversies, and explores the conflict between the rights of the sponsors and the environmental obligations of the international community. It criticizes the current draft regulations and suggests the reform of the institutions to enhance the ISA’s ability of independent surveillance and to create a tight financial mechanism. By studying in detail the legal framework and the current situation of negotiations, this study believes that a more scientific bottom line that can be legally compliant and based on the spirit of the United Nations Convention on the Law of the Sea needs to be established. The paper finishes with some very specific institutional constructions that can make sure deep sea mining will be able to add to world’s collective lot, and not just its detriment
Social Insurance Burden and Firms’ Outward FDI: Evidence From Chinese Enterprise Data
Full text linkThis study examines how the social insurance burden affects firms’ decisions to invest abroad. We construct a structural investment model to show that higher domestic labor costs induced by social insurance contributions diminish the relative profitability of local operations and consequently enhance the incentive for firms’ outward foreign direct investment (OFDI). Using panel data on Chinese listed firms from 2007 to 2022, we employ a two-way fixed effects regression to test the causal relationship between firms’ social insurance burden and their decision and scale of OFDI. The results indicate that heavier social insurance burden significantly increase firms’ OFDI activities. Furthermore, this relationship is moderated by firms’ productivity and risk preference. In addition, we find that the positive effects are more pronounced among non-state-owned firms, those operating in the manufacturing sector, and firms located in the eastern regions of the country. The results demonstrate that social insurance policies play an important role in firms’ globalization strategies. Policymakers should balance social welfare financing with measures to maintain firms’ competitiveness in international markets
Bridging Information Asymmetry through AI-driven FinTech: The Role of Digital Footprint Analytics in Financial Inclusion
Full text linkFinancial inclusion—broadly defined as the availability and equality of opportunities to access financial services—is widely recognized as critical for fostering economic growth, reducing poverty, and promoting equitable development (Berg, T., Burg, V., Gombović, A., & Puri, M., 2020). Nevertheless, despite global initiatives aimed at expanding financial access, a substantial number of individuals and small businesses, particularly in developing countries, remain excluded from traditional financial systems due to insufficient credit histories and inadequate financial documentation (Demirgüç-Kunt et al., 2022). Central to this issue is information asymmetry, a longstanding theoretical challenge articulated by foundational economic theories, including those of Akerlof (1970) and Stiglitz & Weiss (1981). These indicate how asymmetrical information between borrowers and lenders generates adverse selection and moral hazard, ultimately resulting in credit rationing and the systematic exclusion of otherwise creditworthy but information-poor segments of society.In recent years, the rapid development of financial technology (FinTech) powered by artificial intelligence (AI) has fundamentally reshaped the possibilities for overcoming informational barriers. Unlike traditional credit assessment methodologies that depend heavily on structured financial data such as credit bureau reports, income verification, and collateral evaluations, emerging AI-driven credit scoring systems incorporate large-scale behavioral data—often termed “digital footprints”—derived from non-traditional sources including smartphone metadata, social media interactions, e-commerce behaviors, and even geolocation patterns (Berg, T., Burg, V., Gombović, A., & Puri, M., 2020). Recent empirical studies have demonstrated that these novel data sources can outperform traditional financial data in predicting loan repayment behavior, thus substantially reducing information asymmetry and enabling lenders to extend financial services to previously underserved groups (Berg et al., 2020). Leading fintech companies such as Tala in the United States (which primarily serves Southern Africa and Southeast Asia) and Sesame Credit in China’s Ant Financial Services Group exemplify the transformative potential of AI-driven financial innovation. Tala, for instance, utilizes machine learning algorithms that analyze smartphone usage patterns to reliably estimate creditworthiness, enabling real-time unsecured loan approvals for individuals with no formal credit histories (Björkegren, D., & Grissen, D., 2019). Similarly, Zhima Credit has leveraged diverse behavioral indicators—ranging from online transaction consistency to social interaction networks—to deliver precise risk assessments, thereby broadening access not only to credit but also to various consumer services (Zhang, Q., & Li, X. 2023). These case studies highlight how digital footprint analytics can be broadly applied to help mitigate adverse selection and significantly reduce financial exclusion.Despite the transformative benefits, the integration of AI into credit assessment systems raises profound ethical and regulatory concerns. Critical issues include the opacity of algorithmic decision-making processes (“black box” models), the potential perpetuation of existing biases and inequalities embedded in historical datasets, and the privacy implications of intensive personal data use (Raghavan, M., Barocas, S., Kleinberg, J., & Levy, K. 2020). For instance, recent research has highlighted the unintended amplification of gender bias in AI-driven financial services, wherein ostensibly neutral algorithms disproportionately disadvantage women due to embedded socio-economic inequalities within training data (Arora & Gupta, 2025). Addressing these challenges requires robust governance frameworks, algorithmic transparency standards, and informed regulatory oversight, such as those advocated by recent developments in the European Union’s General Data Protection Regulation (GDPR) and emerging algorithmic fairness guidelines (Binns, 2024). Building upon these insights, this paper critically examines the role of AI in bridging information asymmetry within FinTech, with an emphasis on how digital footprints and behavioral analytics are reshaping credit access and financial inclusion. By synthesizing theoretical perspectives on asymmetric information with cutting-edge empirical evidence from recent studies and practical case analyses, this research aims to elucidate both the opportunities and limitations inherent in the AI-enabled transformation of financial decision-making. Furthermore, the paper offers actionable policy recommendations designed to balance technological innovation with ethical responsibility, alongside clearly defined directions for future interdisciplinary research in economics, data science, and regulatory policy.Building on existing theories, this study further incorporates the “Rice Theory” (Talhelm et al., 2014; Dong et al., 2024), which argues that cultural orientations influenced by agricultural practices (particularly rice farming) affect individuals’ social behaviors and cooperative tendencies. Applying this theory to financial technology (FinTech) adoption, we propose that users from collectivist cultural backgrounds—commonly associated with regions historically reliant on rice farming—may exhibit distinct patterns of interaction and acceptance toward digital financial services, thereby influencing the degree of information asymmetry and financial inclusion outcomes within FinTech ecosystems
An Investigation into the Impact of Future Expectations on the Desire for Multiple Children among Young Adults of Childbearing Age
Full text linkInvestigating the multi-child fertility intentions of young people of childbearing age holds significant implications for exploring population structural transformation. Against the backdrop of China's current severe demographic challenges, examining the influence of future expectations on young people's willingness to have multiple children helps uncover the underlying logic of their reproductive decisions—particularly the pathways through which asset expectations, subjective class expectations, and social security expectations shape their multi-child fertility intentions. This study utilizes data from the 2023 China General Social Survey database. It employs a binary logistic regression model to empirically analyze the impact effects of each dimension of expectations and employs heterogeneity analysis to reveal differences among various age and gender groups. The results indicate: Within the asset expectations dimension, housing area exerts a highly significant positive influence on young adults' willingness to have multiple children, while annual household income has a significantly negative effect. Subjective class expectations exert a significant positive influence on young people's willingness to have multiple children; commercial health insurance within the social security expectations dimension exerts a highly significant negative effect on young people's willingness to have multiple children. Furthermore, the impact of each dimension varies across different age groups and genders. Based on these findings, only by formulating targeted measures according to group characteristics can the desired effect of promoting willingness to have multiple children be achieved
Military Politics, the U.S. Jim Crow Navy, and the Heroic Legacy of Doris (“Dorie”) Miller
Full text linkThis paper is about the famous Black Navy man, Doris (“Dorie”) Miller, a World War II hero who also fought the forces of evil in the United States Navy and abroad. This is to say that Miller had to confront a military that was discriminatory, unequal, and segregated — that is, in terms of race. However, Miller became a pioneering member of the U.S. Navy who encouraged other Black sailors to be everything that they could be, even though he and others like him were at the bottom of the Navy’s hierarchy, as enlisted men.Furthermore, “Dorie” Miller held his head high, as he chose his own path to make changes in a segregated world and racist, military institution. Of course, racial changes never came easy for him during his short naval career. Nevertheless, working below deck on warships, in a menial, supportive role (Messman Second Class), Miller rose to the occasion and became a fierce fighting man, by taking control of big Navy guns on the respective warship he was assigned — without specialized training — which was predominantly in the hands, so to speak, of only white seamen at that time. But Miller still became a naval combatant and military hero
Multi-Objective Programming-Based Tour Route Planning
Full text linkThis paper develops personalized 144-hour itineraries for foreign tourists in China, accounting for differences in preferences, attraction density, travel time, and the combined cost of admission and transportation. For Problem 1, multi-source appendix data were merged into a single Excel sheet and attractions with missing ratings were removed. Ratings were then sorted, showing 5 as the maximum score; 2,563 attractions achieved this level, and cities were grouped by their counts of 5-point (BS) attractions. Among 334 cities with BS attractions, 16 cities have at least 15 such sites, with the top ten including Sansha, Wujiaqu, Yuxi, Yiyang, Tianmen, Yantai, Weifang, Greater Khingan Range, Alar, and Xingtai.For Question 2, an evaluation system covering city scale, environmental protection, cultural heritage, and transport convenience was built. After standardization, indicator weights were derived via the entropy method and combined with TOPSIS to rank cities; SPSS produced the “Top 50 Most Desirable Cities for Foreign Tourists.”For Questions 3–5, attraction clustering along the southeast coast was used to reduce travel time, and multi-objective integer programming models were solved in Matlab. The resulting itineraries cover 14 cities (124.8 hours, 1,812 yuan), 13 cities under stronger cost constraints (107.38 hours, 868 yuan), and a mountain-themed 10-city route (111.95 hours, 1,443 yuan)
Research on the Correlativity of Daily Schedule Sequences and Academic Achievement among Senior High School Students Based on Dimensional Statistical Analysis
Full text linkBased on the survey data of 54,102 eighth-grade students in Shanghai, this study adopts statistical methods such as multiple regression analysis, threshold model and Shapley value decomposition to explore the correlation between senior high school students’ daily schedule sequences (including sleep duration, study time, homework burden, electronic device use and extracurricular activities) and academic achievement. The study finds that both sleep duration and study time have a significant inverted U-shaped relationship with academic achievement, with the optimal interval of sleep duration being 7-9 hours and that of study time being 2-4 hours. Homework burden is negatively correlated with academic achievement, especially for rural students, excessive homework burden will significantly inhibit their academic performance. There is an obvious “substitution effect” in the use of electronic devices: excessive recreational use crowds out study time, while moderate educational use has a positive impact on academic achievement. The results of Shapley value decomposition show that sleep duration contributes the most to the explanation of academic achievement, followed by study time, and homework burden has the most significant negative impact. The findings provide an empirical basis for optimizing senior high school students’ schedules and improving their academic achievement
Effects of Concrete Compressive Strength and Thickness on the Natural Frequency of a Prestressed Concrete Wind Tower
Full text linkIn wind tower design, the natural frequency must remain within a safe working range to avoid resonance. This study investigates the effects of concrete thickness and compressive strength on the first natural frequency of a 100 m prestressed concrete tower supporting a 5 MW turbine. Sixty-four models were analyzed using finite element modal analysis. The tower was modeled using 4 m Class 1 3D Bernoulli beam segments, each subdivided into ten elements, and the turbine was represented by a concentrated mass at the top. Two studies were conducted for concrete classes C30, C40, C50, and C60: one varying both base and top thickness (study 1), and another varying only the base thickness (study 2). For a given concrete class, increasing thickness resulted in a higher natural frequency, but with decreasing impact as thickness grew, indicating a tendency toward stabilization. Likewise, higher concrete strength increased the natural frequency, although the effect diminished at higher strength levels. For all geometries, the natural frequencies relative to C50 were 85.6% for C30, 93.3% for C40, and 103.9% for C60