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The aim of this study was to conduct a systematic literature review (SLR) on vlog marketing. The focus was to analyse the major themes in this field and provide insights for future research directions.

The authors reviewed a total of 49 peer-reviewed publications that include the search terms “vlog” or “video blog” in their titles, keywords and abstracts, retrieved from digital databases Scopus and Web of Science, up to the end of July 2023. Thematic analysis was used to examine and synthesise the articles.

The authors found 19 sub-themes and identified four major themes that emerged from the literature: (1) endorsement outcomes, (2) vlogger characteristics, (3) consumer credibility and (4) vlog content crafting.

There are many unanswered questions in the literature, suggesting that vlog marketing research is still in its infancy, and that in-depth further studies are required for a more comprehensive understanding of the field. This study has identified potential avenues for future research that may contribute to the existing body of knowledge and valuable insights on vlog marketing.

Sustainable urban rail transit requires noise barriers. However, these barriers’ durability varies due to the differing aerodynamic impacts they experience. The purpose of this paper is to investigate the aerodynamic discrepancies of trains when they meet within two types of rectangular noise barriers: fully enclosed (FERNB) and semi-enclosed with vertical plates (SERNBVB). The research also considers the sensitivity of the scale ratio in these scenarios.

A 1:16 scaled moving model test analyzed spatiotemporal patterns and discrepancies in aerodynamic pressures during train meetings. Three-dimensional computational fluid dynamics models, with scale ratios of 1:1, 1:8 and 1:16, used the improved delayed detached eddy simulation turbulence model and slip grid technique. Comparing scale ratios on aerodynamic pressure discrepancies between the two types of noise barriers and revealing the flow field mechanism were done. The goal is to establish the relationship between aerodynamic pressure at scale and in full scale.

The aerodynamic pressure on SERNBVB is influenced by the train’s head and tail waves, whereas for FERNB, it is affected by pressure wave and head-tail waves. Notably, SERNBVB's aerodynamic pressure is more sensitive to changes in scale ratio. As the scale ratio decreases, the aerodynamic pressure on the noise barrier gradually increases.

A train-meeting moving model test is conducted within the noise barrier. Comparison of aerodynamic discrepancies during train meets between two types of rectangular noise barriers and the relationship between the scale and the full scale are established considering the modeling scale ratio.

This study aims to understand the influence of raceway surface topography on the temperature rise characteristics of silicon nitride (Si₃N₄) full ceramic ball bearing and improve its service life.

The arithmetic average height S_a, skewness S_sk and kurtosis S_ku in the three-dimensional surface roughness parameters are used to quantitatively characterize the surface topography of the raceway after superfinishing. The bearing life testing machine is used to test the Si₃N₄ full ceramic ball bearing using polytetrafluoroethylene (PTFE) cage under dry friction conditions, and the self-lubricating full ceramic ball bearing heat generation model is established.

With the decrease of S_a and S_sk on the raceway surface and the increase of S_ku, the average height of the raceway surface decreases, and the peaks and valleys tend to be symmetrically distributed on the average surface, and the surface texture becomes tighter. This kind of raceway surface topography is beneficial to form a thin and uniform filamentous PTFE transfer film with a wide coverage area on the raceway surface based on consuming less cage materials and improving the temperature rise characteristics of hot isostatic pressing silicon nitride full ceramic ball bearings.

The research results provide a theoretical basis for the reasonable selection of Si₃N₄ ring raceway processing technology and have important significance for improving the working characteristics and service life of Si₃N₄ full ceramic ball bearings under dry friction conditions.

To investigate whether the actual effects of eight drape characteristics of virtual fabrics can be manifested in the Style 3D software.

Image analysis was conducted using MATLAB software to obtain the drape characteristics of virtual fabrics. Pair the drape characteristics of the real and virtual fabrics for difference. The S-W method was used to conduct a normality test to obtain the correlation of paired samples. A paired sample t-test was performed to obtain the significance values.

The simulation restoration performance of the drape coefficient, number of undulations, maximum undulation angle, minimum undulation angle and undulation angle uniformity was good. However, there are differences in the simulation performance of the other three indicators: maximum undulation amplitude, minimum undulation amplitude and undulation amplitude uniformity compared to the drape characteristics of real fabrics.

Provides reference value for the improvement of Style3D software in virtual fabric simulation and finds the main influential parameters and their impact levels that contribute to the realistic representation of virtual fabrics in software. It provides a theoretical basis for course teaching in digital fashion.

The purpose of this study is to make property price forecasts for the Chinese housing market that has grown rapidly in the last 10 years, which is an important concern for both government and investors.

This study examines Gaussian process regressions with different kernels and basis functions for monthly pre-owned housing price index estimates for ten major Chinese cities from March 2012 to May 2020. The authors do this by using Bayesian optimizations and cross-validation.

The ten price indices from June 2019 to May 2020 are accurately predicted out-of-sample by the established models, which have relative root mean square errors ranging from 0.0458% to 0.3035% and correlation coefficients ranging from 93.9160% to 99.9653%.

The results might be applied separately or in conjunction with other forecasts to develop hypotheses regarding the patterns in the pre-owned residential real estate price index and conduct further policy research.

This study aims to investigate the mechanism of the misinformation spread based on the elaboration likelihood model and the effects of four factors – emotion, topic, authority and richness – on the depth, breadth and structural virality of misinformation spread.

The authors collected 2,514 misinformation microblogs and 142,006 reposts from Weibo, used deep learning methods to identify the emotions and topics of misinformation and extracted the structural characteristics of the spreading network using the network analysis method.

Results show that misinformation has a smaller spread size and breadth than true news but has a similar spread depth and structural virality. The differential influence of emotions on the structural characteristics of misinformation propagation was found: sadness can promote the breadth of misinformation spread, anger can promote depth and disgust can promote depth and structural virality. In addition, the international topic, the number of followers, images and videos can significantly and positively influence the misinformation's spread size, depth, breadth and structural virality.

The influencing factors of the structural characteristics of misinformation propagation are clarified, which is helpful for the detection and management of misinformation.

This study aims to systematically reveal the complex interaction between uncertainty and the international commodity market (CRB).

A composite uncertainty index and five categorical uncertainty indices, together with wavelet analysis and detrended cross-correlation analysis, were used. First, in the time-frequency domain, the coherency and lead-lag relationship between uncertainty and the commodity markets were investigated. Furthermore, the transmission direction of the cross-correlation over different lag periods and asymmetry in this cross-correlation under different trends were identified.

First, there is significant coherency between uncertainties and CRB mainly in the short and medium terms, with natural disaster and public health uncertainties tending to lead CRB. Second, uncertainty impacts CRB more markedly over shorter lag periods, whereas the impact of CRB on uncertainty gradually increases with longer lag periods. Third, the cross-correlation is asymmetric and multifractal under different trends. Finally, from the perspective of lag periods and trends, the interaction of uncertainty with the Chinese commodity market is significantly different from its interaction with CRB.

First, this study comprehensively constructs a composite uncertainty index based on five types of uncertainty. Second, this study provides a scientific perspective on examining the core and diverse interactions between uncertainty and CRB, as achieved by investigating the interactions of CRB with five categorical and composite uncertainties. Third, this study provides a new research framework to enable multiscale analysis of the complex interaction between uncertainty and the commodity markets.

This study provides a configurational examination of how policy designs influence the innovation performance of the emergency industry in China.

This study employs the Data Envelopment Analysis Malmquist index (DEA-Malmquist) to quantify the innovation performance of the emergency industry and then codes the innovation policies to calculate the syntactic components based on institutional grammar tools (IGTs). The configurations of syntactic components were determined by applying the fuzzy-set qualitative comparative analysis (fsQCA).

The results indicate that rules- and norms-oriented policy designs would improve the innovation performance of China's emergency industry. In the developed provinces, the “Deontic” and “aIm” combinations in the policy are useful for improving performance. In the developing provinces, the ambiguity of the “aIm” and “Context” conditions in the policy is leading to low performance. Additionally, a lack of strategy-oriented policy design would also result in poor performance.

Most previous studies used substitute variables to understand policy impacts. This study contributes to identifying the impacts of the syntactic components of policy designs on the innovation performance of the emergency industry. The findings can assist policymakers in developing more effective policies to stimulate innovation development in the emergency industry.

In response to the navigation challenges faced by coal mine tunnel inspection robots in semistructured underground intersection environments, many current studies rely on structured map-based planning algorithms and trajectory tracking techniques. However, this approach is highly dependent on the accuracy of the global map, which can lead to deviations from the predetermined route or collisions with obstacles. To improve the environmental adaptability and navigation precision of the robot, this paper aims to propose an adaptive navigation system based on a two-dimensional (2D) LiDAR.

Leveraging the geometric features of coal mine tunnel environments, the clustering and fitting algorithms are used to construct a geometric model within the navigation system. This not only reduces the complexity of the navigation system but also optimizes local positioning. By constructing a local potential field, there is no need for path-fitting planning, thus enhancing the robot’s adaptability in intersection environments. The feasibility of the algorithm principles is validated through MATLAB and robot operating system simulations in this paper.

The experiments demonstrate that this method enables autonomous driving and optimized positioning capabilities in harsh environments, with high real-time performance and environmental adaptability, achieving a positioning error rate of less than 3%.

This paper presents an adaptive navigation system for a coal mine tunnel inspection robot using a 2D LiDAR sensor. The system improves robot attitude estimation and motion control accuracy to ensure safe and reliable navigation, especially at tunnel intersections.

This study aims to investigate the effect of steel fibers on the mechanical and tribological properties of FeS/Cu–Bi self-lubricating materials.

The microstructure of the material was characterized by scanning electron microscopy. Tests on the crushing strength, impact toughness and tribological properties of materials were conducted using a universal electronic testing machine, a 300 J pendulum impact testing machine and an M200 ring-block sliding tribometer, respectively.

The mechanical properties of the material initially increased and then stabilized with increased copper-plated steel-fiber length. When the length of the copper-plated steel fiber was 7 mm, the mechanical properties of the material reached stability. Compared with the material without a copper-plated steel fiber, its crushing strength and impact toughness increased by 32.6% and 53%, respectively. A copper-plated steel fiber with a length of 7 mm lay flat in a copper matrix can strengthen the friction interface and enrich the lubricant. Accordingly, the antifriction and wear resistance of the materials increased by 17.6% and 55%, respectively.

The effects of copper-plated steel fibers on the properties of FeS/Cu–Bi self-lubricating materials were clarified. This work can serve as a reference for improving material performance and its engineering applications.