The application of criminal law methods to model and regulate relevant behaviors in civil cases has been one of the hot topics in the research of criminal law scholars in China in recent years. However, due to the solidification of research models and the limited theoretical breakthroughs, current scholars still study the characteristics of financial crimes based on the temporal and spatial characteristics of crimes in criminology, while ignoring the common sense that law constrains behavior. Based on this, this paper proposes an abstract model named the Morohusi – C. Y. HU Model, and takes the recent illegal real estate securitization case of “Shenfangli” as an example to identify and evaluate the suspected financial criminal behavior of the “Shenfangli” platform. Through detailed analysis, the financial behavior analysis module in the model concludes that its capital flow has a bottom-up “pyramid-shaped” characteristic, and calculates its profit amount in detail; while the financial behavior evaluation module in the model suggests possible convictions, namely, the combined punishment of the crimes of illegally absorbing public deposits and organizing and leading pyramid selling activities. Therefore, criminal law modeling research based on behavior analysis has certain universality, and can establish different specific application models according to specific cases.

In the context of the rapid global development of artificial intelligence (AI), China is also actively advancing the research and application of related technologies. This paper focuses on Chinese A-share listed companies from 2016 to 2023 and explores the impact of corporate AI applications on labor productivity. A model is constructed in which labor productivity is measured by the natural logarithm of revenue per employee. The application indicator is built using the number of AI-related keywords in annual reports, with control variables set accordingly. Empirical results show that AI applications significantly improve labor productivity, with companies that exhibit good growth, strong cash flow, and large scale performing better in terms of productivity. Robustness checks confirm the validity of these conclusions. The study demonstrates that AI holds immense potential in corporate applications, and companies can build industrial ecosystems to promote its widespread use, enhancing labor productivity and contributing to high-quality economic development.

Exploring the influence mechanism of social media users’ disinformation verification intention is of great significance to social media rumor governance, social risk control, improvement of health information content ecology and improvement of the correction mechanism of disinformation. Due to the differentiation of user information behavior among different groups of social media users, it is necessary to take group characteristics into account. This study takes the integrated model of planned behavior theory and norm activation model as the theoretical framework model, and discusses the moderating effect of digital generations. Based on 492 sample data, structural equation model is used to verify and analyze the influencing factors of disinformation verification intention from the perspectives of egoism and altruism. The results showed that attitude toward the behavior, perceived behavioral control and personal norm positively affected the social media users’ disinformation verification intention, and subjective norm had no significant impact on the verification intention; awareness of consequences affected the verification intention through the chain mediation effect; digital generations only moderated the influence of perceived behavioral control and verification intention. The research results provide reference for future research and practice of disinformation governance.

With the improvement and maturity of China's capital markets, data-driven quantitative trading, known for its objectivity, high frequency, and automation, has gradually developed into an important trading method in the financial market. This paper addresses the overfitting phenomenon in quantitative trading, quantifying the overfitting rate using the concept of information coefficient. By applying the overfitting rate to optimize the Kelly formula extended to continuous time, the paper derives the overfitting rate-improved Kelly score. Finally, a specific order placement application example is provided based on the theory of linear regression, and a comparative analysis with the fractional Kelly criterion is conducted.

Blockchain technology transforms banking by solving issues in international money transfers. The decentralized blockchain system prevents tampering and removes intermediaries to speed up transactions and lower costs while protecting data integrity. Our investigation focuses on how blockchain prevents financial fraud while allowing users to see transaction data in real-time and making international financial systems work better. This research analyzes how blockchain works in financial transactions and shows its effects on payment times, cost savings, and protection against fraud through data studies. Despite demonstrating powerful disruption blockchain struggles with processing delays and lacks defined standards while integrating technology proves challenging. This research explores why organizations find it difficult to use blockchain technology and suggests methods that can help to use blockchain effectively in daily operations. This research examines how blockchain technology affects global finance operations and shows its benefits for international payments while explaining its potential to transform worldwide financial systems.

New-quality productive forces, driven primarily by technological innovation, optimize the allocation of educational resources through digital means, thereby advancing the equalization of education between urban and rural areas. This research demonstrates that the development of new-quality productive forces significantly narrows the gap in primary school advancement rates between urban and rural areas, particularly when controlling for variables such as digital infrastructure. The findings also reveal a significant lag effect, with the most pronounced impact observed in the first lag period. Robustness tests further confirm that the positive effect of developing new-quality productive forces on reducing urban-rural educational disparities is both stable and significant, highlighting its critical role in addressing educational inequality. To maximize these benefits, efforts should focus on cultivating new-quality productive forces, optimizing digital infrastructure, fostering innovation in educational technology, and implementing targeted, region-specific policies. Promoting balanced resource sharing and establishing comprehensive evaluation and adjustment mechanisms are also crucial to ensuring the long-term effectiveness of these efforts. These measures collectively contribute to achieving regional cultural "literacy."

Foreign Direct Investment (FDI) plays a key role in the global economy, and its protection is often ensured through provisions in Bilateral Investment Treaties (BITs), particularly the Fair and Equitable Treatment (FET) standard. However, when the host country's actions lead to substantive devaluation of an investor's assets, often referred to as indirect expropriation, investors frequently invoke FET clauses to seek redress. Both FET and indirect expropriation are vaguely defined in international law, resulting in considerable space for interpretation by arbitral tribunals. Due to the protective nature of these provisions, tribunals often interpret these standards in favor of investors, which may lead to an imbalanced protection of investor rights. This imbalance can, in turn, encroach upon the sovereignty of host states and their ability to regulate in the public interest. Although Tribunals recently have taken some measures to restrict the interpretation of FET and indirect expropriation in dispute, these two treatments still face the risk of being abused by investors and becoming a “pocket clause”. This paper uses case studies and legal analysis to explore the ways in which such unbalanced interpretations undermine the interests of host states, particularly with respect to their regulatory and sovereign powers. This paper further proposes potential reforms of FET and indirect expropriation aimed at restricting the interpretation space of Tribunals while sustaining the flexibility of these two treatments, rebalancing the interests of both foreign investors and host countries.

As urbanization accelerates, cities face mounting challenges in developing sustainable public transportation systems that balance environmental, economic, and social needs. Green public transportation projects, such as electric buses, metro systems, and low-carbon transit solutions, are integral to mitigating climate change and improving urban air quality. However, implementing these initiatives requires effective project management that integrates sustainability across economic, social, and environmental dimensions. This paper evaluates the main challenges in implementing sustainable project management (SPM) within green public transportation projects, focusing on financial constraints, technological barriers, regulatory issues, and stakeholder engagement. By analyzing case studies from the Asian Development Bank (ADB) and the European Investment Bank (EIB), this study identifies key strategies to improve the success rates of such projects. These strategies involve integrating well-established project management methodologies such as PRINCE2, Agile, and Lean, alongside recommendations for future improvements in the field.