Abstract: Objective: To investigate the effects of Sirtuin-1 (Sirt1)/Runt-related transcription factor 2 (Runx2) signaling pathway on the healing of tibial fracture in rats. Methods: Rat models of tibial fracture were established and hen divide d into fracture group (Fra group) and resveratrol treatment group (RES group). Next, the healing of fracture was exami ned by X-ray inspection. Bone marrow mesenchymal stem cells (BMSCs) were isolated from rats and cultured in vitro. Results: Rat models of tibial fracture were successfully established, and BMSCs were isolated and cultured.RES pro moted the healing of fracture in rats and the gene expressions of Sirt1 and Runx2 at fracture ends and in osteobla sts induced in vitro. According to alizarin red staining assay, RES facilitated the osteogenic differentiation of BMSCs , while EX-527 inhibited their osteogenic differentiation. QRT-PCR results revealed that the messenger ribonuc leic acid (mRNA) expressions of Sirt1 and Runx2 at tibial fractures at 24 h after fracture were significantly higher than th ose in sham group, and they were the highest in RES group. In addition, the mRNA expression levels of Sirt1 and Runx 2 were overtly higher in induction group and RES co-induction group than those in control group, whereas the indu ction with EX 527 evidently inhibited the mRNA expressions of Sirt1 and Runx2 at 2 w and 3 w. At 3 w after oste ogenic induction of BMSCs, both induction group and RES co-induction group had significantly increased protein exp ression levels of Sirt1 and Runx2. Conclusions: The Sirt1/Runx2 signaling pathway facilitates the healing of tibial fra cture in rats.

Abstract:With the widespread application of Fully Automatic Operation (FAO) systems in urban rail transit, passenger flow control has become a key factor in ensuring their efficient and safe operation. This paper delves into the challenges of passenger flow control in FAO systems by leveraging deep learning technologies. It constructs deep learning models, integrates multi - source data, designs intelligent control strategies, and proposes an efficient intelligent passenger flow control scheme. The aim is to help improve the service quality and operational efficiency of the system and promote the sustainable development of urban rail transit.

Abstract：With the global explosive growth of urban rail transit, urban rail transit tunnels (core transit arteries) have become more complex and lengthy, facing rising safety risks from natural factors, mechanical wear, and corrosion. Traditional monitoring methods (manual inspections, basic fixed-point sensors) are inefficient, narrowly covered, and low in data accuracy, failing to meet modern safety needs. This study develops an intelligent safety monitoring system for such tunnels using IoT and Big Data. It designs core components: IoT sensor networks, Big Data management, and machine learning-based safety assessment algorithms. A Shanghai case study shows the system detected minor structural displacements (0.5–1.5 mm) and abnormal gas concentrations, cutting unplanned disruptions by ~30%. It also establishes evaluation indicators and proposes optimizations (5G, edge computing), addressing traditional monitoring shortcomings.

Abstract:With the intensification of global climate change, extreme rainfall events are occurring more frequently. Due to their unique geographical location and climatic conditions, coastal cities have become high-risk areas for waterlogging disasters. Beihai City in Guangxi, a significant coastal tourist destination in Southern China, faces multiple pressures including typhoon-induced rainstorms, storm surges, sea-level rise, and urban surface hardening, making its waterlogging problem increasingly prominent and severely constraining its sustainable development and public safety. This paper takes Beihai City as a case study. It begins by deeply analyzing the specific causes of its waterlogging issues, including the 胁迫 of extreme weather under climate change, the inherent vulnerability of its coastal geographical environment, the hydrological effects of rapid urbanization, and the capacity shortcomings of the existing drainage system. Based on this analysis, the paper proposes the construction of a comprehensive governance system characterized by "Ecology as the Foundation, Grey-Green Combination, Smart Empowerment, and Multi-level Resilience". This system integrates multiple strategies such as Sponge City initiatives (green infrastructure), upgrades to traditional grey infrastructure, smart water management, and Nature-based Solutions (NbS). Finally, tailored to Beihai's specific context, the paper proposes a phased and actionable implementation path alongside policy recommendations, aiming to provide theoretical reference and practical paradigms for similar coastal cities in China to address climate risks and enhance waterlogging prevention capacity.

Abstract:This paper comprehensively explores the profound impact of artificial intelligence (AI) on the automotive industry. By analyzing various aspects such as manufacturing, driving experience, mobility, and future trends, it reveals how AI is revolutionizing the automotive sector. AI has enabled smart factories, improved vehicle safety and user experience, and transformed mobility patterns. However, challenges like job displacement and safety concerns need to be addressed. Despite these, the potential benefits are immense, and with continuous technological evolution, AI will drive more innovation in the automotive industry.

Abstract：Due to the complex geological conditions, enclosed construction environment, and intensive technical links involved, tunnel engineering faces numerous uncertain risks during the construction phase, which may easily lead to safety accidents, construction delays, and economic losses. Focusing on risk management in tunnel construction, this paper systematically sorts out the classification and characteristics of construction risks, and constructs a full-process management framework covering "risk identification, assessment, response, and monitoring". Combined with engineering cases, it analyzes the specific manifestations of geological risks, technical risks, management risks, and environmental risks, introduces the Analytic Hierarchy Process (AHP) and Fuzzy Comprehensive Evaluation Method to establish a risk assessment model, and proposes targeted risk response strategies and dynamic monitoring schemes. The research shows that a scientific risk management system can effectively reduce the probability of risks in tunnel construction, ensure the safe and efficient progress of the project, and provide a reference for risk management in similar tunnel engineering construction.

Abstract：Metro station tunnel groups are often characterized by dense intersection layouts, which introduce unique challenges such as intricate stress distributions, difficult construction operations, and heightened vulnerability to safety hazards. To address these issues, this study takes the tunnel group of Nanning Qingxiushan Metro Station as a case study, establishing a three-dimensional numerical model that is calibrated with on-site monitoring data. The research focuses on investigating the mechanical response mechanisms of the tunnel group during construction, including surrounding rock deformation patterns, stress evolution laws, and plastic zone development characteristics. Special emphasis is placed on analyzing the dynamic mechanical behavior of the left-line tunnel during its connection with the cross-passage. The results indicate that the tunnel structure is significantly affected by the eccentric load from the upper foundation pit: the surrounding rock at the intersection of the tunnel on the eccentrically loaded side exhibits substantially larger displacement and stress compared to the non-eccentrically loaded side. Additionally, the excavation of the cross-passage induces significant disturbance to the intersection area, resulting in concentrated plastic strain. When the left-line tunnel is breached to connect with the cross-passage, tensile stress is generated at the vault of the breached lining, and severe stress concentration occurs at the arch shoulder and arch foot. The implementation of targeted deformation control measures is proven effective in ensuring the structural stability of the tunnel group. This research provides technical support for the design and construction of similar metro tunnel group intersection projects.

Abstract:Against the background of globalization and the deepening exchange of higher education concepts, Ideological and Political Education (IPE) in Chinese universities and Civic Education (CE) in foreign universities, as two important educational practices oriented to cultivating "qualified social members", show obvious differences in educational logic and practical paths due to the influence of cultural traditions, social systems and educational goals. This study adopts a cross-cultural research perspective, combines literature analysis and comparative research methods, and takes representative universities in China, the United States, Germany and the United Kingdom as research cases. It first clarifies the core connotation of the educational logic of Chinese university IPE and foreign university CE, then combs their typical practical paths, and finally summarizes the similarities and differences between the two educational models and their mutual enlightenment. The research finds that Chinese university IPE takes "cultivating socialist builders and successors" as the core logic, with distinct value guidance and systematic practice support; foreign university CE focuses on "shaping citizens’ political literacy and public participation ability", with obvious emphasis on individual autonomy and diversified practice carriers. The cross-cultural comparison of the two not only helps to promote the international exchange of higher education value education experience, but also provides a reference for the optimization of the localization practice of Chinese university IPE and the innovation of foreign university CE.

Abstract:With the advancement of the "China Education Modernization 2035" strategy, artificial intelligence has become the core driving force for the transformation of higher education. This article systematically analyzes the internal mechanism and practical path of empowering university teaching reform with artificial intelligence, reveals the current challenges faced, and proposes corresponding governance strategies. Research shows that reform can be promoted from three aspects: developing specialized intelligent tools for disciplines and enhancing technological adaptability; Establish data governance standards to prevent ethical risks; Adhere to a student-centered approach and balance the application of technology with the essence of education. This study provides a theoretical framework and practical path for the reform of university teaching in the era of artificial intelligence, which is of great significance for promoting the high-quality development of higher education.

Abstract:The use of the internet to commit non-contact indecent acts against children is a concealed form of crime emerging alongside the development of information technology. Currently, judicial interpretations in China have provided a preliminary definition of such acts, laying a fundamental basis for their criminal determination. However, due to the characteristics of this type of act—including non-contact, cross-temporal and cross-spatial nature, and high concealment—judicial practice still faces difficulties in determination at multiple levels. These difficulties include ambiguity in the types and boundaries of objective acts, challenges in proving the perpetrator’s subjective intent, and unclear application standards for aggravating circumstances such as “assembling a crowd” and “committing the act in public places in the presence of others”. To enhance the consistency and operability of judicial decisions, it is necessary to further clarify the types and boundaries of objective acts, establish more targeted rules for inferring subjective intent, and provide interpretations of aggravating circumstances that align with the online context. By doing so, the determination system for this type of crime can be systematically improved, offering clear and reasonable grounds for judgment in judicial practice.

Abstract: With the acceleration of urbanization, the subway has become the backbone of public transportation in large cities. However, the continuously growing passenger flow poses severe challenges to subway operational safety. This paper aims to systematically analyze the intrinsic correlation between subway passenger flow and operational safety. Firstly, it elaborates on the basic connotations of subway safety and the main characteristics of large passenger flows. Secondly, it delves into the multifaceted impacts of large passenger flows on subway safety, including increased loads on facilities and equipment, induced passenger behavior risks, heightened complexity in passenger flow organization, and amplified difficulties in emergency management. Based on this, the paper proposes a set of systematic safety management countermeasures for large subway passenger flows from five dimensions: monitoring and early warning, facility planning, operational management, technological application, and public education. Research indicates a significant nonlinear relationship between subway safety and passenger flow, necessitating a comprehensive governance model that combines "prevention, control, and evacuation" to achieve safe, efficient, and sustainable development of the subway system under high passenger flow pressure.

Abstract：This article analyzes the theoretical basis and technological adaptation logic of artificial intelligence empowering enterprise auditing from the perspective of auditing, combined with the characteristics of AI technology. It constructs a three-layer risk intelligent identification system of "data technology application" and proposes a fourdimensional prevention and control path of "technology system personnel ethics compliance". Research has shown that AI technologies such as machine learning and knowledge graphs can accurately identify financial, internal control, and business risks in enterprises, and the four-dimensional prevention and control path can form a complete audit risk prevention and control loop. The results of this article can improve the theoretical system of "AI+audit", provide practical guidance for audit institutions and enterprises, help improve the efficiency and risk control capabilities of enterprise auditing, and promote the transformation of enterprise auditing towards intelligence.

Abstract:In the context of the transformation of the construction industry towards green and intelligent development, big data analysis provides a new path for optimizing building structure design. This article analyzes the application value of big data analysis in building structure design through literature research and case analysis. It points out the four core problems currently faced, including uneven data quality, difficulties in technology implementation, shortage of professional talents, and data security risks. The causes are analyzed from the dimensions of data management, technology research and development, talent cultivation, and security assurance. On this basis, strategies such as building a standardized data management system, promoting technology adaptation and implementation, improving talent attraction and education mechanisms, and enhancing security guarantee systems are proposed. Research has shown that big data analysis can effectively enhance the scientificity of design, reduce costs, and improve efficiency. Relevant strategies can provide reference for solving practical problems and promoting high-quality development of building structural design.

Abstract: With the acceleration of urbanization and the continuous improvement of people's requirements for travel efficiency and safety, rail transit systems are rapidly developing towards a high degree of automation and intelligence. The in-depth application of automation technologies,such as automatic train operation systems, intelligent dispatching, and driverless operations, has not only significantly enhanced the operational efficiency and reliability of rail systems but also brought revolutionary challenges to traditional operational organizational models and safety management systems. This paper takes "rail" as the physical foundation and "automation" as the technological core, deeply exploring the operational mode innovation driven by automation technologies and systematically analyzing the new types of safety risks that arise. The paper aims to construct a collaborative evolution framework of "technology-operation-safety" and propose a resilient operational system and integrated safety management strategies for automated rail systems, providing theoretical references and practical guidance for the sustainable development of future intelligent rail transit.

With the deepening integration of digital technologies in education, virtual reality (VR) immersive learning has emerged as a transformative medium that breaks through traditional classroom constraints through its three core attributes: immersion, interactivity, and conceptualization. As of 2024, the global VR education market has surpassed $8 billion in value. By creating simulated learning environments—including virtual laboratories and historical scenario reconstructions—VR transforms abstract knowledge into tangible experiential learning content, significantly enhancing learners' engagement and retention. However, existing research reveals notable individual variations in VR immersion learning outcomes: some learners struggle with environmental adaptation and lack sufficient motivation, with psychological traits emerging as the key variable explaining these differences.