Global Academic Frontiers publishes forward-looking articles from different fields. The goal is to showcase the latest research, insights, and perspectives on global academic topics. Each issue contains thought-provoking articles published by scholars from different fields, covering the latest research achievements in science, technology, culture, society, and other fields. Publishing Schedule Q1 (January–March)、Q2 (April–June)、Q3 (July–September)、Q4 (October–December).
Editorial Office of Global Academic Frontiers
Research on the application of data enhancement and image restoration based on Generative Adversarial Network (GAN)
Generative adversarial network GAN can generate high-quality synthetic data through the adversarial training of generator and discriminator, so as to provide diversified training samples in data enhancement and image restoration, and improve the generalization ability of the model, which makes it have excellent performance in dealing with various tasks and can output high-quality data and pictures. Starting from the basic principles and main variants of GAN, this paper analyzes in detail the application cases, effect evaluation and challenges of GAN in data enhancement and image restoration, and looks forward to the future development direction of GAN.
Copyright (c) 2025 Wen Xin (Author) https://creativecommons.org/licenses/by/4.0
The Application of Laser Forming Technology in Additive Manufacturing and Its Quality Monitoring
This paper conducts an in-depth investigation into the field of Selective Laser Melting (SLM) within additive manufacturing (AM) technology, providing a detailed analysis of its market background, current status, and development prospects. As a revolutionary pioneer in future manufacturing, AM technology has rapidly emerged in recent years and found widespread application in high-end manufacturing sectors such as scientific research, healthcare, military industry, aerospace, and aviation. SLM technology, as a critical branch of AM, has become a focal point in numerous fields due to its advantages of high precision, high efficiency, and material diversity. This paper first outlines the industry background of AM technology, including its development history, primary methods, and technical characteristics. Subsequently, by comparatively analyzing the key technical parameters of major domestic and international SLM printing equipment brands, the current market status of SLM technology is revealed. In the competitor analysis, the paper focuses on the latest advancements in melt pool temperature monitoring technology and powder spreading detection technology. It points out the limitations of traditional temperature measurement techniques in aspects such as single-point measurement, accuracy, and response speed. The innovative approaches adopted in this project—namely, photoelectric sensor-fused thermal imaging processing technology and artificial intelligence (AI)-based machine vision inspection methods—are introduced. Furthermore, the paper explores future development trends for SLM technology, including product line expansion, service upgrades, and the positive impact of policy support and industry development. Through the research conducted in this project, we deeply appreciate the critical importance of technological innovation for enhancing the forming success rate of SLM technology and reducing material and energy costs.
Copyright (c) 2025 Yuhang Yao, Yicheng Shi (Author) https://creativecommons.org/licenses/by/4.0
From Competency Assessment to Curriculum Reform: How Does Artificial Intelligence Empower Higher Vocational Education?
This study explores the impact of Artificial Intelligence (AI) on vocational education, focusing on its role in competency assessment and curriculum reform. With the rapid evolution of technology, AI is poised to revolutionize how vocational training is delivered and assessed. By utilizing a quantitative research approach, a survey was conducted with 100 vocational students currently engaged in AI-integrated training. The findings reveal that while AI-based training provides personalized learning experiences, its direct impact on competency assessment was less significant than expected. In contrast, student engagement emerged as a critical factor influencing the effectiveness of AI in enhancing learning outcomes.
Copyright (c) 2025 Haoheng Tian, Xin Zeng, Lijia Huang, Linjia Song (Author) https://creativecommons.org/licenses/by/4.0
Discussion on problems caused by uneven deployment of 5G network edge computing nodes
This study focuses on the issue of uneven deployment of edge computing nodes in 5G networks. A multi-regional simulation model was constructed, and four key performance indicators were evaluated: average end-to-end latency, node load balance, request success rate, and resource utilization. Various optimization techniques, including automated scheduling and network slicing, were employed to control the simulation. The simulation results show that the average latency decreased from 54.8ms to 35.9ms, the load balance increased to 0.72, the request success rate rose to 91.7%, and the resource utilization improved to 74.6%. The study demonstrates that deploying optimized control strategies can significantly alleviate the performance bottleneck caused by uneven node distribution, thereby enhancing the overall service capability and resource utilization of the edge computing system.
Copyright (c) 2025 Jinghua Cui, Jiulong Zhang, Linluo Yao (Author) https://creativecommons.org/licenses/by/4.0
A Study of the Impact of ESG on Corporate Carbon Performance -- Based on the mediating effect of New quality productivity
To investigate whether corporate ESG can improve corporate carbon performance and facilitate the achievement of China's "dual-carbon" objective, we utilize panel data from China's A-share-listed companies spanning 2015 to 2022. We develop new quality productivity indicators through principal component analysis and empirically assess the impact and mechanisms of ESG on corporate carbon performance using bidirectional fixed-effects, mediated-effects, and moderated-effects models. The influence and mechanism of ESG on corporate carbon performance are experimentally analyzed utilizing a two-way fixed effects model, a mediation effects model, and a moderating effects model. Research indicates that (i) strong ESG performance can markedly enhance corporate carbon performance; this conclusion remains valid following various robustness and endogeneity assessments, including substituting core explanatory variables, lagging explanatory variables by one period, and augmenting the standard error of clustering at the city level. (ii) Mechanism analysis indicates that ESG performance enhances the carbon performance of firms both directly and indirectly by fostering advancements in new quality productivity. (iii) The examination of moderating effects indicates that company financialization enhances the favorable influence of ESG on corporate carbon performance. Heterogeneity study indicates that ESG exerts a more pronounced influence in the eastern area, among non-state-owned firms, and within non-heavily polluting enterprises. Consequently, to advance the low-carbon transformation of the economy, it is essential to stratify the policy design. Incentives for ESG can be enhanced for non-state-owned enterprises, manufacturing sectors, and the eastern region, while technology subsidies or differentiated assessment criteria are required for state-owned enterprises, heavily polluting industries, and the central and western regions to address the structural disparities in ESG practices and to encourage non-manufacturing industries to pursue synergistic avenues of digital transformation and ESG integration.
Copyright (c) 2025 Ying Wu, Yu Liao, Dai-Yun Li (Author) https://creativecommons.org/licenses/by/4.0
E-commerce Empowering the Digital Transformation of Small and Medium-sized Enterprises Driven by New Quality Productivity
This article explores the impact of e-commerce on the digital transformation of small and medium-sized enterprises driven by new quality productivity. It is analyzed that the digital transformation of small and medium-sized enterprises is confronted with predicaments such as technological application gaps, inefficient allocation of production factors, and weak industrial collaboration. Elaborate on the paths by which e-commerce helps small and medium-sized enterprises break through the predicament of transformation through mechanisms such as technological innovation, factor reorganization and industrial upgrading. Through case analysis, the practical promoting effects of e-commerce on enhancing the technological application capabilities of small and medium-sized enterprises, optimizing the allocation of production factors, and strengthening the level of industrial collaboration are demonstrated. Put forward policy suggestions such as strengthening technological infrastructure, promoting the marketization of factors, and building industrial communities to remove obstacles for the digital transformation of small and medium-sized enterprises and facilitate their high-quality development.
Copyright (c) 2025 Shiying Du, Linrong Wu, Yiming Pan, Huifang Hu (Author) https://creativecommons.org/licenses/by/4.0
Can the financial background of executives affect the digital transformation of enterprises?
The financial background of executives can provide financial consulting for enterprises and enhance effective interaction between enterprises and the financial industry, but the academic community has not yet clarified the impact of executive financial background on the digital transformation of enterprises. This article combines the macro pursuit of high-quality national development and examines the relationship between executive financial background and digital transformation of Chinese A-share listed companies from 2012 to 2022. Research has found that: The financial background of executives has a significant positive correlation with the digital transformation of enterprises. After key variable replacement, the above research results remain robust. This article reveals the impact and pathways of executive finance background on green investors under the background of high-quality economic development, enriches the research on executive characteristics and corporate financing constraints, and provides theoretical support and practical inspiration for executive recruitment decisions and structural design in enterprises.
Copyright (c) 2025 Chenghui Li (Author) https://creativecommons.org/licenses/by/4.0
Liminal Transformation in the Rites of Passage: Identity Fluidity in Mohsin Hamid’s The Reluctant Fundamentalist
In the novel The Reluctant Fundamentalist, Mohsin Hamid, the 2017 Booker Prize winner, employs a transnational narrative to explore the fluidity of liminal identity. The protagonist, Changez, embarks on a journey from Lahore to Princeton for education, then works at a top global investment bank, and ultimately returns to his homeland in search of self-redefinition. This multi-layered experience mirrors the three stages of the rites of passage proposed by Arnold van Gennep: separation, liminality, and reintegration. Confronted with fragmented memories of domestic space, disciplinary violence in urban environments, and identity struggles within psychological realms, Changez navigates his growth crisis through ritualistic practices that ultimately resolve transitional identity conflicts and reconstruct a cohesive identity. Hamid metaphorically reflects evolving East-West relations through the subtly shifting dynamics between Changez and an American traveler in the Lahore teahouse. The novel not only reveals the marginality and heterogeneity of transnational identities but also interrogates the construction and negotiation of liminal identities within multicultural intersections.
Copyright (c) 2025 Zhao Bin (Author) https://creativecommons.org/licenses/by/4.0
Analysis of Differentiated Marketing Strategies
This article systematically expounds the basic theory of marketing strategy and deeply analyzes the connotation and implementation points of differentiated marketing strategy. In the context of increasingly fierce market competition, enterprises need to accurately position customer needs and develop personalized market strategies in order to gain unique competitive advantages. This study verified the application effect and profit potential of differentiated marketing strategies in different industries through multiple business case analyses, revealing their significant effectiveness in enhancing brand value and user loyalty. This article has important reference value for academic research and practical operation in understanding and promoting differentiated marketing strategies.
Copyright (c) 2025 Jiayue Gao, Ruiqianyu Hu, Hongbin Xiong (Author) https://creativecommons.org/licenses/by/4.0
Research on the green extraction process and high-value application of amino acids based on synthetic biology in tea dry cakes
As the main by-product of tea seed oil extraction, tea dry cake is rich in amino acid resources, but its complex cellulose-lignin structure limits the efficient release of amino acids. In this study, an engineered strain of Corynebacterium glutamicum was constructed based on synthetic biology techniques Combined with the high-efficiency amino acid circulation extraction device (patent number: CN202310001234), the efficient extraction of free amino acids is realized. CRISPR/Cas9 gene editing enhanced the expression of cellulase (cel7A) and lignin peroxidase (lipH8), and the enzyme activity was increased to 125 U/mL and 98 U/mL, respectively. Combined with dynamic nozzle positioning (accuracy ±1 mm), multi-stage filtration (0.45μm filter element) and fin heat dissipation system (temperature control ≤35°C), the total extraction rate of amino acids reached 85.7%, and the purity was 95.3%, which was 52% more efficient than the traditional extraction method. The cleaning rate of the extracted amino acid compound detergent is 85% at 25°C, which is 23% higher than that of traditional APG. This study provides a green and efficient industrialization solution for the recycling of tea dry cakes.
Copyright (c) 2025 Jiang Gaojin, Peng Ying, Hongbin Xiong (Author) https://creativecommons.org/licenses/by/4.0
Hydrological controls on nutrient dynamics and load estimation in an agricultural watershed: a case study in Rock Creek, Ohio
This study investigates the spatiotemporal variability of nutrient concentrations (soluble reactive phosphorus, SRP; total phosphorus, TP; and nitrate, NO₃⁻) and their relationships with hydrological conditions in the Rock Creek watershed, a representative agricultural basin in northwestern Ohio. High-temporal-resolution water quality and discharge data were analyzed over a two-year period (2010–2011) to elucidate seasonal trends, flow-nutrient correlations, and to compare nutrient load estimation methods. The results demonstrate that nutrient transport in the watershed is strongly event-driven, with SRP and TP concentrations peaking during high-flow periods (spring snowmelt and summer/fall storms), exhibiting significant positive correlations with discharge (log-transformed R² = 0.27–0.47). In contrast, nitrate concentrations displayed a distinct seasonal pattern, with a spring flush followed by declining concentrations, suggesting depletion of legacy storage. Notably, flow-weighted mean concentrations (FWMC) exceeded arithmetic means by 2–3 times, revealing that conventional averaging methods underestimate nutrient loads during high-flow events. These findings emphasize the dominance of non-point source pollution during episodic runoff events and underscore the need for targeted management strategies to mitigate nutrient pollution in similar agricultural watersheds.
Copyright (c) 2025 Yiwen Xiong, Zeyi Cao, Peng Liu (Author) https://creativecommons.org/licenses/by/4.0
Research on the challenges and countermeasures of applying artificial intelligence in green supply chain management
The global proliferation of sustainable development principles has elevated Green Supply Chain Management (GSCM) to a critical position within corporate environmental governance and strategic management frameworks. Concurrently, the accelerated advancement of artificial intelligence (AI) technologies has emerged as a transformative catalyst for supply chain digitalization. The integration of AI in GSCM demonstrates significant potential for enhancing environmental performance, optimizing resource utilization efficiency, and facilitating carbon neutrality objectives. Nevertheless, this technological convergence presents substantial implementation challenges across multiple dimensions. This study conducts a comprehensive examination of the principal barriers hindering AI adoption in GSCM through data, technology, organization, and ethics, while proposing targeted mitigation strategies and optimization approaches. The research outcomes aim to contribute both theoretical foundations and practical implementation guidelines for enterprises pursuing sustainable transformation and intelligent supply chain modernization.
Copyright (c) 2025 Xiangfei Ji (Author) https://creativecommons.org/licenses/by/4.0
Research on export competitiveness of new energy vehicles in Yangtze River Delta region
As the energy crisis and automobile industry develop, the global automobile industry competition has shifted from individual product competition to comprehensive strength competition among industrial clusters. In recent years, China’s new energy automobile industry has developed rapidly, with the trend of automobile industry cluster becoming more evident. The Yangtze River Delta region, with its strong vehicle and parts manufacturing base, has become a typical representative of China’s new energy vehicle export industry. Research on the export competitiveness of new energy vehicles in the Yangtze River Delta can reflect the overall development of China’s new energy automobile industry to a certain extent. It also has important theoretical significance and practical value for enhancing the competitiveness of the new energy automobile industry in the Yangtze River Delta and even the whole country.
Copyright (c) 2025 Xiaozhan Yang (Author) https://creativecommons.org/licenses/by/4.0
From Shallow Cooperation to Deep Synergy: Triple Breakthroughs in Guangdong-Hong Kong-Macau Greater Bay Area's Higher Education Cluster Development
As an important carrier of national strategic development, the key task of Guangdong-Hong Kong-Macau Greater Bay Area construction is to build a scientific and technological innovation hub with international influence. Under this framework, promoting the coordinated evolution of higher education clusters has become a strategic supporting factor for regional development. The cultivation of international higher education clusters not only provides high-end intellectual resources and compound talent reserves for the construction of Greater Bay Area's science and technology innovation hub, but also creates a historic opportunity for universities in the region to break down barriers and deepen collaborative innovation mechanisms. By strengthening the strategic consensus of higher education cluster development, optimizing resource allocation and spatial layout, systematically exploring the coordinated development path of Guangdong-Hong Kong-Macau Greater Bay Area's higher education clusters, and then building an international higher education network system with distinct levels, gradient connection and close interaction, it will become an important engine driving the high-quality development of the world-class bay area.
Guangdong-Hong Kong-Macau Greater Bay Area
Copyright (c) 2025 Nie Hui (Author) https://creativecommons.org/licenses/by/4.0
Understanding Wage Disparities Through Educational Attainment
This paper investigates the causal effect of education on wages using data from the 2018 American Community Survey (ACS) accessed through IPUMS. Our paper tests the causal effect of educational attainment on wages using individual-level data by using quarter of birth as an instrumental variable for education. We hypothesize that higher education leads to significantly higher wages. Based on our IV regression model, we find that each additional year of education is associated with approximately a 20.8% increase in log wages. These results support the importance of education in explaining wage differences, although other factors such as gender also play a notable role.
Copyright (c) 2025 Jiayi Zhang, Xiaoran Han (Author) https://creativecommons.org/licenses/by/4.0
AI-Powered Precision Medicine: Transforming Healthcare through Intelligent Imaging and Surgical Ecosystem Innovation
The integration of artificial intelligence (AI) into precision medicine has revolutionized healthcare by enhancing diagnostic accuracy, optimizing treatment strategies, and improving surgical outcomes. This paper explores the transformative potential of AI in precision medicine, with a focus on intelligent imaging analysis and surgical ecosystem innovation. AI-driven techniques, such as machine learning and deep learning, have demonstrated remarkable capabilities in analyzing medical images, enabling early and accurate disease detection, particularly in cancer and cardiovascular conditions. Additionally, AI has significantly advanced surgical precision through robotic-assisted procedures and augmented reality, reducing complications and improving patient recovery. The paper also highlights the integration of diverse data sources, including genomics and wearable sensors, to provide comprehensive patient insights. Despite these advancements, challenges such as ethical considerations, data privacy, and algorithmic bias remain critical barriers to widespread adoption. The paper concludes by emphasizing the need for interdisciplinary collaboration, robust validation, and regulatory oversight to fully realize the potential of AI in precision medicine. By addressing these challenges, AI-powered precision medicine holds immense promise for delivering personalized, efficient, and equitable healthcare solutions.
Copyright (c) 2025 Chunlei Wang, Jie Cao, Manzhi Xia, Jianying Kang, Jinlian Liang (Author) https://creativecommons.org/licenses/by/4.0
Lithium battery charge state estimation based on improved Unscented Kalman filtering
The state of charge (SOC) of lithium batteries is one of the key parameters to ensure their safe operation. In response to the traditional untraceable Kalman filtering (UKF) algorithm in the process of estimating the state of charge (SOC), the covariance matrix is non-positively determined, which leads to the termination of the algorithm. In this paper, an improved trace-free Kalman filtering method with singular value decomposition Unscented Kalman filtering (SVD-UKF) is proposed to estimate the SOC. singular value decomposition is used instead of Cholesky decomposition to improve the accuracy and stability of SOC estimation. First, a second-order RC equivalent circuit model is established, a lithium battery experimental platform is built to obtain charge/discharge data, and the parameters of the second-order RC model are identified by combining the hybrid pulse charge/discharge test and the 1stopt software, and then the battery SOC estimation is carried out by using the improved untraceable Kalman filtering algorithm, and the SVD-UKF estimation results have a smaller error with the actual value compared with the traditional UKF through experimental analysis, the estimation accuracy is high, and the real value can be converged quickly when the initial value is inaccurate, and the average absolute error is reduced by about 14.5% compared with the traditional UKF, which has good accuracy and robustness.
Copyright (c) 2025 Changchang Li (Author) https://creativecommons.org/licenses/by/4.0
Models and Mechanisms of Effective Rural Operation for Promoting Common Prosperity: A Longitudinal Case Study of the "Guzhu Model" from a Symbiotic Perspective
Achieving common prosperity for all people is the essential requirement of Chinese-style modernization, and the weakest key link at present is the common prosperity of farmers and rural areas. Taking Guzhu Village in Changxing County as a typical case, this paper adopts the longitudinal single case study method to explore the process, operation mode and mechanism of the village's road to common prosperity from the perspective of symbiosis theory. The results show that: (1) Guzhu Village has experienced different stages of development in the process of common prosperity, and each stage has produced different symbiotic effects. Individual villagers have given birth to the bud of rural development, but their lack of knowledge, cognition and management ability can't achieve high-quality rural development. The gradual participation of the government, associations and operating companies has injected new energy into promoting rural areas towards common prosperity. (2) The village focuses on multiple symbiotic subjects and operates collaboratively with the help of symbiotic environment. Effective collaboration between symbiotic units has become the key to rural common prosperity. The symbiotic model respects the core position of villagers, effectively promotes the participation and recognition of all villagers, turns the ecological advantages and resource advantages in the village into economic advantages and development advantages, and realizes the villagers' material wealth, spiritual and cultural wealth and ecological harmony in the village. Research suggestions: In the process of rural development, we can inject new energy into the village by maintaining the dominant position of villagers, introducing new units such as operating companies, making full use of resource endowments to broaden the path of increasing income and getting rich, giving full play to the synergy among symbiotic units, and jointly strengthening the rural collective economy.
Copyright (c) 2025 Zou Yanfen, Cai Bifan (Author) https://creativecommons.org/licenses/by/4.0
Context-Aware Multimodal Feedback System for Enhancing Outcomes-Based Education in Mechanical Engineering
We propose a context-aware multimodal feedback system designed to enhance Outcomes-Based Education (OBE) in mechanical engineering by dynamically adapting feedback modalities to individual learning contexts and performance. The system integrates cognitive diagnosis models to assess student proficiency and an environment-aware modality selector to determine the optimal feedback form, such as visual annotations, haptic cues, or interactive 3D simulations, depending on whether the learning occurs in physical laboratories or digital platforms. A Transformer-based architecture synthesizes personalized feedback by combining diagnostic outputs with contextual data, enabling precision-tailored support for complex engineering concepts. The proposed method replaces conventional static assessment reports with adaptive, multimodal feedback, thereby addressing the limitations of one-size-fits-all approaches in OBE. Furthermore, the system leverages state-of-the-art technologies, including probabilistic programming for scalable cognitive diagnosis and physics-accurate simulations for immersive learning experiences. Experimental validation demonstrates its effectiveness in improving student engagement and mastery of mechanical engineering principles. This work contributes a unified framework that bridges cognitive assessment, environmental context, and multimodal feedback, offering a scalable solution for personalized engineering education. The results highlight the potential of adaptive feedback systems to transform traditional OBE practices by aligning instructional support with individual learning trajectories and real-world engineering scenarios.
context-aware multimodal feedback system
Copyright (c) 2025 CUI Fangyuan (Author) https://creativecommons.org/licenses/by/4.0
Mathematical Modeling of Fine Superstring Structure of Hydrogen Atoms
To address the phenomenon of electron clouds in hydrogen atoms and other extra-nuclear electron clouds, a high-dimensional confinement and asymptotic freedom theory of electron pairs is proposed. Furthermore, to resolve the non-contradictory interaction between electrons and protons, a string reaction theory is introduced. The model presented explains not only why electrons do not combine with protons to lose their electron cloud motion properties but also why multiple extra-nuclear electrons do not undergo classical collisions. Additionally, it provides an explanation for the string reaction nature of the photoelectric effect. The model presented herein is supported by previous laboratory results. The paper presents a model of string reaction between electrons and protons, which explains the trajectory of electrons in hydrogen atoms and why electrons can continuously orbit around protons. This innovative model describes that, under certain constraints, electrons can traverse through protons. After traversal, the electrons retain their original physical properties but undergo slight changes in velocity, while the physical properties of the protons remain unchanged. This model explains using string theory, transforming the purely mathematical nature of string theory into an interpretation of the physical phenomena. This demonstrates that string theory is a practical tool that can be applied to physics.
Copyright (c) 2025 Yishi Huang (Author) https://creativecommons.org/licenses/by/4.0
Semantic Segmentation of Nighttime Images Based on Cross-modal Domain Adaptation
Semantic segmentation of nighttime images is crucial for all-weather autonomous perception but faces challenges like low-light noise, motion blur, and cross-domain adaptation limitations. Traditional visible-light methods suffer from sensor constraints (60 dB dynamic range), causing information loss in extreme darkness (<1 lux), while domain adaptation approaches degrade due to day-night noise distribution shifts. This work introduces event cameras (140 dB range, μs-level response) to establish a multimodal cooperative framework. A dual-branch network decouples visible content features and event-based motion features, optimized by cross-modal contrastive loss (CMCL) and hybrid Gaussian kernel MMD loss for modality alignment and domain matching. A dynamic confidence screening (DCS) mechanism integrates optical flow consistency and Bayesian uncertainty to suppress pseudo-label noise (18.5% false detection reduction). Evaluations on DSEC/MVSEC datasets demonstrate 21.3% mIoU gain in extreme low-light, 34.5% boundary IoU improvement in blurred regions, and 14.2% superior cross-domain adaptation (day→night) over state-of-the-art methods. This framework offers a label-efficient and robust solution for nighttime autonomous driving systems, advancing multimodal sensing deployment.
Copyright (c) 2025 Jixing Huang, Yanhe Li, Yuchen Zhang, Xinyue Zhang, Xin-yue Zhang, Ruihan Qi (Author) https://creativecommons.org/licenses/by/4.0
Definition of the scope of property exempted from the localized personal insolvency regime
With the development of commodity economy, borrowing and lending consumption is more and more common. In this consumption pattern, the debtor is very easy to fall into the vicious circle of insolvency. In the individual, the society is a great impediment to the development of exempted property is the most constructive, one of the most innovative approach to personal bankruptcy, its emergence helps the debtor to get rid of the debt dilemma, and promotes a fresh cycle of the social economy. At this point, the definition of the scope of the exempted property is crucial, and it is essentially a product of the game between creditors and debtors around their own interests. Since there are differences in defining the scope of exempted property in different countries due to the level of economic development, politics, history and other factors, it is necessary to draw on extraterritorial legislation and base on China's national conditions when constructing the system of defining the scope of exempted property in China in order to effectively safeguard the balance between the interests of the debtor and the creditors. The main purpose of the exemption system is to ensure that the debtor's basic living and production activities can be sustained. Based on this purpose, balance and flexibility fit the necessary nature of our national conditions, while at the same time safeguarding the property of the debtor's personal exclusivity, in order to respect the basic rights of the debtor as an independent individual. There are a number of possible routes for specifying the scope of exempted property. One is to adopt a single amount, directly setting a fixed amount as the standard amount of exempted property. The second is to combine the type of property with the amount, starting from the type of property and matching the corresponding amount with the characteristics of different types of property. The third is to set a special amount for specific properties, that is, for some special properties, special planning for a specific amount of range. In practical application, each country should be allowed to flexibly choose the method of determining the amount that suits the actual situation of the country based on its own national conditions, legal system and socio-economic situation and other factors.
Copyright (c) 2025 Jiayi Wu (Author) https://creativecommons.org/licenses/by/4.0
The influence of college students' views on entrepreneurial success, failure, and market prospects on their entrepreneurial intentions
Entrepreneurship is pivotal in creating job opportunities at the macroeconomic level, serving as a cornerstone of socio-economic progress. At the individual level, it acts as a vital source of income. This research focuses on the impact of attitudes towards entrepreneurial success and failure on the entrepreneurial intentions of university students. It also explores the moderating role of market prospects in this context. Our findings reveal that a positive attitude towards entrepreneurial success significantly boosts entrepreneurial intentions, whereas fear and anxiety about failure have a negative influence. Market prospects, when considered as a control variable, show a notable negative effect when combined with negative attitudes towards failure, indicating that fear of failure further weakens entrepreneurial intentions in unfavorable market conditions. Failure plays a crucial role in shaping entrepreneurial intentions. Through this study, we seek to offer comprehensive guidance to university students in entrepreneurship and foster the healthy development of entrepreneurial endeavors.
Copyright (c) 2025 Yundong Wu, Weijian Kong, Tingting Lv, Xiaoqing Xi, Bowei Liu, Ruofan Lin, Jintao Li (Author) https://creativecommons.org/licenses/by/4.0
The Employment Pressure Of College Students Based On Structural Equation Model and The Return To Start Their Own Businesses Factor Analysis —— Take Guangxi universities as an example
This paper explores the impact mechanism of employment pressure and college students' return to their hometowns for entrepreneurship and employment in Guangxi, based on two major social hotspots. The study uses an employment pressure scale to conduct a questionnaire survey among college students in Guangxi, and constructs a structural equation model (SEM) to deeply analyze the interaction relationships between various influencing factors and their impact mechanisms on returning to start businesses or find employment. The findings show that the overall quality of college students is positively correlated with their willingness to return and start businesses; those with higher overall quality can better identify opportunities in rural areas and possess entrepreneurial capabilities. Employment expectations are negatively correlated with the willingness to return and find employment; high employment expectations make college students more inclined to seek urban jobs. Support for career acquisition is negatively correlated with both the willingness to return and start businesses or find employment, indicating that the current career support system has not effectively guided talent flow to rural areas. These findings have significant reference value for policy formulation, educational guidance, and personal career planning of college students.
Copyright (c) 2025 Zhao Jingru (Author) https://creativecommons.org/licenses/by/4.0
Construction of a Large Language Model-Driven Online Programming Experiment System and Research on Active Learning Paradigm Transformation
Traditional online programming teaching platforms have significant deficiencies in supporting the development of students' abilities. The core issue is concentrated on the unidirectional nature of the evaluation system: it cannot effectively assess engineering elements such as code standardization, style uniformity, and runtime efficiency, nor can it provide students with in-depth suggestions for improvement. To break through this limitation, this paper constructs a new generation of online programming experiment platforms based on large language model technology. The platform can analyze students' code logic in real-time, generate targeted error correction suggestions, explanations of knowledge points, and optimization plans, and supports language interaction to help students quickly understand programming concepts. Experiments show that the platform significantly improves students' programming practice abilities, confirming its value in programming education. It provides an expandable technical solution for the innovation of programming education models and is of great significance in promoting the transformation of programming education from passive infusion to active exploration.
Copyright (c) 2025 Shengying Yang, Chen Lu, Fangfang Qiang (Author) https://creativecommons.org/licenses/by/4.0
How Does Administrative Decentralization Activate Endogenous Rural Development?— The Transformation of R Village and Its Underlying Logic
The rural revitalization strategy, guided by China’s vision for national rejuvenation, emphasizes activating endogenous development in rural areas. Yet in practice, many grassroots initiatives suffer from “floating public projects,” where government dominates while local participation lags. This paper examines how administrative decentralization can effectively stimulate rural endogenous power by analyzing the transformation of R Village—a once-declining bonsai-producing village plagued by governance issues and economic stagnation. Through the downward extension of administrative authority, public resources, and governance concepts, R Village achieved organizational restructuring, industrial revitalization, and community re-engagement. The case demonstrates the potential of a “new endogenous development” model that integrates external support with internal capacity-building. R Village’s shift from a “weak and dispersed” village to a national model offers valuable insights for sustainable rural development and broader rural revitalization efforts.
Copyright (c) 2025 Xinyong Lu (Author) https://creativecommons.org/licenses/by/4.0
Mechanized Transformation in Shellfish Aquaculture: Practical Challenges and Intelligentization-Driven Breakthrough Pathways
Under the dual pressure of global aquatic resource constraints and the transformation to a low-carbon economy, intelligent technologies are reshaping the underlying logic of the shellfish farming industry. This paper systematically constructs a three-dimensional analysis framework of "technology - ecology - governance". Through horizontal comparisons of 12 countries and vertical analyses of 38 technological innovation cases, it reveals the three core contradictions of intelligent transformation: regional imbalance in technology supply, ambiguity of rights and responsibilities in data governance, and intergenerational conflicts in benefit distribution. Research has found that China's shellfish industry has achieved partial leadership in areas such as offshore aquaculture robots and AI disease early warning through the "scene-driven innovation" model. However, shortcomings such as a domestic sensor production rate of less than 20% and a digital skill compliance rate of only 11.3% among practitioners are restricting the overall transformation. Propose breakthrough paths such as establishing an "Intelligent Fishery innovation community", piloting a digital twin system for sea areas, and promoting carbon sink credit trading, providing a Chinese solution for the intelligentization of global shellfish farming.
Copyright (c) 2025 Zhu Shenghu, Wang Yuting, Ji Yongjin (Author) https://creativecommons.org/licenses/by/4.0
Towards a Theoretical Framework for the Explainability of Deep Learning Models
Deep learning models have demonstrated outstanding performance in various domains, yet their opaque nature remains a fundamental issue. Explainability aims to bridge this gap by providing insights into model decision-making processes. This paper explores the theoretical foundations of explainability in deep learning, emphasizing mathematical and conceptual perspectives. We investigate the limitations of current approaches and discuss how interdisciplinary methodologies can enhance our understanding of deep learning systems. Additionally, we explore the potential of combining explainability with robustness, fairness, and generalization to create more reliable AI systems. The paper also highlights challenges such as the trade-off between interpretability and predictive power, the scalability of explainability methods, and the lack of standard evaluation metrics. Finally, we propose novel research directions, including topological analysis, causal reasoning, and probabilistic explainability models. A particular focus is placed on the role of human cognition, decision-theoretic frameworks, and explainability as a tool for improving the reliability of deep learning models in high-stakes scenarios. Furthermore, we investigate how explainability techniques can enhance the deployment and optimization of deep learning models in real-world environments, ensuring their ethical and practical applications. This work aims to provide a comprehensive framework for improving the transparency, interpretability, and accountability of AI-driven decision systems.
Copyright (c) 2025 Jiang jialong (Author) https://creativecommons.org/licenses/by/4.0
The Evolution and Future Trajectory of ESG Information Disclosure in China: Building a Harmonized Disclosure System in the Context of Global Integration
This paper examines the evolution and future trajectory of Environmental, Social, and Governance (ESG) information disclosure in China within the context of global integration. As sustainability reporting gains prominence worldwide, China has made significant strides in developing a comprehensive ESG disclosure framework that balances international standards with domestic priorities. Through analysis of recent policy developments, academic research, and industry practices, this study tracks China's journey from initial voluntary environmental reporting to its current structured approach with mandatory disclosure requirements for many listed companies. The research identifies key challenges in China's ESG disclosure system, including data quality concerns, implementation capacity constraints, and the need to harmonize local standards with global frameworks. The paper also examines China's efforts toward global integration, particularly its relationship with International Sustainability Standards Board (ISSB) standards and initiatives under the Belt and Road framework. Looking ahead, China's ESG disclosure system is poised for full implementation by 2030, with increasing focus on digital transformation, expanded mandatory requirements, and enhanced global alignment. The findings provide valuable insights for policymakers, companies, investors, and researchers interested in China's sustainable development and its growing influence on global ESG standards.
Copyright (c) 2025 CUI XIAOTIAN (Author) https://creativecommons.org/licenses/by/4.0
Digital Transformation in Tax Risk Management: A Paradigm Shift through Advanced Technologies
With the advancement of information technology and the transformation of tax collection and management methods, the role of digital technology in tax risk management is becoming increasingly significant. By leveraging digital technology, tax authorities can effectively address challenges such as the growing number of taxes involved and the emergence of more covert tax sources, while also facilitating data screening and risk prevention and control. It is evident that reliance on digital technology and the utilization of data to advance tax risk management reform have emerged as critical topics. This article examines the current challenges in tax risk management against the backdrop of digital technology and the obstacles faced in future development. By thoroughly drawing on the successful experiences of tax risk management in developed countries and continuously enhancing China's tax risk management system, this study aims to explore tax risk management pathways that align with China's national conditions, ultimately seeking to improve the comprehensive governance capabilities of tax authorities and better support the country's economic development.
Copyright (c) 2025 Pengwei Jin (Author) https://creativecommons.org/licenses/by/4.0