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: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：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 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: 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.