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This study aims to enhance the bioavailability and antioxidant function of vitamin E (VE) by combining it with inositol and choline, exploring their synergistic effects and underlying mechanisms.

An oxidative stress model in mouse hepatocytes was established using hydrogen peroxide to assess the antioxidant effects of combined VE, inositol and choline treatments. Cell viability, the levels of reactive oxygen species (ROS) and malondialdehyde (MDA) and antioxidant enzymes, including superoxide dismutase (SOD) and catalase (CAT), were measured to evaluate protective effects. α-Tocopherol (α-T) and α-tocopherol transfer protein (α-TTP) levels were assessed to determine VE bioavailability. Transcriptome sequencing was conducted to identify gene expression changes and pathways impacted by the treatment.

An optimal oxidative stress model was established with 641 µM hydrogen peroxide for 6 h. The combination of 20 µM VE, 1.5 mM inositol and 0.3 mM choline significantly improved cell viability, reduced ROS and MDA levels and increased SOD and CAT activities, indicating enhanced antioxidant protection. In addition, α-T and α-TTP levels were higher with this combination, suggesting improved VE bioavailability. Transcriptome analysis revealed that the treatment modulated key pathways linked to inflammation, cancer and lipid metabolism, particularly impacting interleukin-17 and nuclear factor kappa-light-chain-enhancer of activated B cells signaling, cytokine interactions and the alcoholic liver disease pathway.

This study demonstrates a novel approach for improving VE’s bioavailability and effectiveness through its combination with inositol and choline, providing insights that could inform antioxidant therapies and liver health interventions.

Heterogeneous risk disclosure has been proven to improve the efficiency of new stock issuance, but excessive risk disclosure during the IPO may lead to irrational underestimation of the company, which is different from the original intention of management's detailed disclosure. Therefore, this study aims to examine the impact of IPO heterogeneous risk disclosure on earnings management motivations from the information transfer perspective of earnings management.

The sample includes 2,000 listed companies listed firms on Shanghai and Shenzhen Stock Exchanges from 2007 to 2022. This study uses the pretrained ERNIE model to measure text similarity in the prospectus to measure the heterogeneity of IPO risk disclosure.

This study empirically finds that heterogeneous IPO risk disclosure suppresses the opportunistic motivation of earnings management because managers tend to use earnings management to leverage information transmission functions. Such an effect is more pronounced in firms with higher analyst attention, lower marketization levels and non-state-owned. And heterogeneous risk disclosure may inhibit management’s over-investment behavior, thereby reducing the possibility of management engaging in opportunistic earnings management. Besides, price discounts are used to distinguish opportunistic and non-opportunistic earnings management and carry out a quasi-natural experimental design to demonstrate that marketization can enhance the relationship between heterogeneous risk disclosure and earnings management.

This study contributes evidence regarding the economic consequences of managerial earnings management behavior related to heterogeneous IPO risk disclosure. It supports highlighted firms in the IPO risk information disclosure to mitigate potential adverse outcomes through earnings management. This contributes to the literature and enhances information transparency in the capital market, fostering the healthy development of China’s capital market.

This paper aims to facilitate reliable online diagnosis of early faults in the stator winding inter-turn short circuits of induction motors (IMs) under various operating conditions.

A novel fault characteristic component, the characteristic current amplitude, is proposed for the fault. Defined as the product of short-circuit coefficient and short-circuit current, the characteristic current is derived from the positive and negative-sequence components of the stator-side current and voltage.

Simulation models of the IMs pre- and postfault, along with an experimental platform for the motor’s inter-turn short circuit, were established. The characteristic current amplitude proves more robust against voltage unbalance and load variations, which offers enhanced reliability and sensitivity for early fault diagnosis of inter-turn short circuit in IMs stator windings.

A novel feature is proposed. Compared with negative-sequence current, which is considered as a traditional fault feature, the characteristic current amplitude exhibits a greater robustness against the imbalanced conditions, which simultaneously possesses the attributes of both reliability and expeditiousness in fault detection.

This paper aims to investigate how information and communication technology (ICT) services and digital finance affect the development of international tourism.

The two-way fixed effect panel regression model, spatial econometric model, panel threshold regression model and panel quantile regression model are used. Data on tourism, economic and social development in 198 Chinese cities from 2011 to 2020 are analyzed.

This study finds that digital economy including ICT services and digital finance has significantly promoted the development of international tourism industry, while there is a negative spatial spillover effect. The promotion effect of international tourism increases significantly after digital innovation reaches the threshold value. International tourism is benefiting more from digital economy with the development of international tourism industry.

The development quality of international tourism industry has not been analyzed due to data limitations, and the mechanism has not been tested.

This study creatively reveals the development of international tourism industry in the digital economy era from ICT services and digital finance perspectives. This study also shows the spatial, nonlinear and asymmetric relationship between digital economy and international tourism.

In situ 3D reconstruction is the basis for measuring and monitoring large-scale working environments such as construction sites and coal mining surfaces. The purpose of this paper is to address the difficulties of on-site 3D reconstruction in large-scale dynamic environments. Based on panoramic rotating light detection and ranging sensors, a dynamic environment 3D reconstruction method combining occupancy grid and point cloud segmentation is proposed.

The algorithm fully combines the information between point clouds to process the points in the region of interest, improving the processing speed of the occupancy grid method and the accuracy of dynamic object filtering. Furthermore, this paper also proposes an incremental long-short horizon segmentation and reconstruction workflow, which performs different levels of point cloud differential segmentation for various types of dynamic objects.

This paper designs detailed physical and simulation experiments in different environments to verify the advantages and reliability of the algorithm. The entire system showed satisfactory performance in experiments.

The proposed dynamic environment 3D reconstruction method can effectively complete the 3D reconstruction of complex work environments, and the proposed incremental long-short horizon segmentation and reconstruction workflow further improves the accuracy of dynamic object removal.

Indoor hallways are the most common and indispensable part of people’s daily life, commercial and industrial activities. This paper aims to achieve high-precision and dense 3D reconstruction of the narrow and long indoor hallway and proposes a 3D, dense 3D reconstruction, indoor hallway, rotating LiDAR reconstruction system based on rotating LiDAR.

This paper develops an orthogonal biaxial rotating LiDAR sensing device for low texture and narrow structures in hallways, which can capture panoramic point clouds containing rich features. A discrete interval scanning method is proposed considering the characteristics of the indoor hallway environment and rotating LiDAR. Considering the error model of LiDAR, this paper proposes a confidence-based point cloud fusion method to improve reconstruction accuracy.

In two different indoor hallway environments, the 3D reconstruction system proposed in this paper can obtain high-precision and dense reconstruction models. Meanwhile, the confidence-based point cloud fusion algorithm has been proven to improve the accuracy of 3D reconstruction.

A 3D reconstruction system was designed to obtain a high-precision and dense indoor hallway environment model. A discrete interval scanning method suitable for rotating LiDAR and hallway environments was proposed. A confidence-based point cloud fusion algorithm was designed to improve the accuracy of LiDAR 3D reconstruction. The entire system showed satisfactory performance in experiments.

This study aims to propose a cloud platform architecture considering information sharing based on blockchain to realize the security and convenience of enterprise information sharing in the automotive supply chain.

A bilateral matching model considering enterprises information contribution stimulates information sharing and improves the efficiency and quality of supply and demand matching. Three smart contracts are used to complete the information sharing process and match supply and demand in the automotive supply chain.

The system is tested on the local Ganache private chain, and the decentralized web page is designed based on the architecture prototype.

Solve the problem of information island in automobile supply chain.