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The purpose of this study is to investigate the effects of high-temperature oxidation tests and gas thermal shock tests on IC10 simulated components with thermal barrier coatings under different temperatures and oxidation times.

In the high-temperature oxidation test, specimens were oxidized at three different temperatures of 850, 980, and 1,100 °C for durations of 10, 20, 50, 100, 200, and 300 h, respectively. In the gas thermal shock test, specimens were pre-oxidized for 10, 20, 50, and 100 h, followed by a high-temperature gas thermal shock test at 1,100 °C.

In the high-temperature oxidation tests, with increasing oxidation time, the oxidation layer thickened, and the air-film holes diameter decreased. The microstructure of the bond coat transitioned from strip-like to block-like, and internal cracks transformed from numerous and short to larger and deeper. Below the bond coat, a noticeable disappearance layer of strengthening phase appeared, with increasing thickness. The strengthening phase in the substrate transitioned from regular square shapes to circles as temperature increased. In gas thermal shock tests at 1,100 °C, the oxidation weight gain ratio increased with longer pre-oxidation times, whereas the erosion weight loss ratio gradually decreased.

The originality and significance of this study lie in its departure from the typical subjects of high-temperature oxidation and thermal shock tests. Unlike common research targets, this study focuses on IC10 simulative specimens with thermal barrier coatings and air-film holes. Furthermore, it investigates the effects of varying temperatures and oxidation durations.

At present, the enzyme washing process is widely used in hemp garment in the industry. However, it has many disadvantages. First, it is inefficient and labor-intensive, which can only be produced in small quantities and will take much time for workers to check. Second, its cost is high. The strength loss of the garment is up to 20 percent, with a bad damage. Presently, the enzyme washing process of the gray fabric is not industrialized. The purpose of this paper is to obtain a stable and efficient process for the enzyme washing of the gray fabric.

The whiteness, weight loss rate, strength, dyeing property and fabric style of enzyme washed gray fabrics were studied.

The results showed that the enzyme treated fabric has soft handle, smooth surface, good elasticity and high levelness, as well as low strength reduction rate under the optimized condition of bath ratio of 1:12, cellulase dosage of 0.3 percent, pectinase dosage of 1 g/L, treatment temperature of 55°C, treatment time of 80 min and pH of 6.

First, the process is environment friendly, green and sustainable and, second, it will make the industrialization of the enzyme washing process of gray fabrics, with a high commercial value.

To maximize health synergistic benefits and provide a scientific foundation for enhancing air pollution control policies, this research proposed a causal inference framework with a decomposition ensemble prediction model for comprehensive policy assessment.

We introduced the CD-OASVR-Ensemble-CC method, a policy assessment approach that combined machine learning-based decomposition ensemble prediction (CD-OASVR-Ensemble) with counterfactual contrast (CC) analysis. The CD-OASVR-Ensemble model incorporated support vector regression (SVR) optimized through swarm intelligent optimization algorithms (OA), complete ensemble empirical model decomposition of adaptive noise (CD) and a linear ensemble model (Ensemble). This approach was applied to analyze patterns in historical PM2.5 data and predict the future trend. The predicted PM2.5 served as a counterfactual trend, enabling an evaluation of the policy’s environmental and health effects.

Analysis of prediction errors confirmed the proposed CD-OASVR-Ensemble model’s accuracy and robustness in predicting PM2.5 levels. The findings indicated that the implementation of “Regulation 2019” led to a significant reduction in PM2.5 concentration, preventing an estimated 7,960 premature deaths and saving approximately 2,602.95 m yuan in health-related economic costs.

This study introduces an innovative framework for evaluating the environmental effect of policies, with a specific emphasis on health synergistic benefits.

Continuous annealing (CA) units usually lack a physical shapemeter; consequently, real-time display and closed-loop control of the strip shape are impossible to achieve.

A shape model for the CA process is established in this study. Specifically, a virtual shapemeter and closed-loop control system based on the advanced parameter acquisition system and information transmission of CA units are developed in C++ programming language. This system realises real-time dynamic shape display, closed-loop control and shape prediction by collecting raw data of steel coils and parameters during CA.

Field test results show that the shape predicted by the virtual shapemeter coincides with the measured shape by over 90 per cent, which fully meets the precision requirement of industrial applications.

Moreover, shape quality is effectively improved without increasing hardware investments.

This study aims to investigate the relationships between the perceived neighborhood walkable environment (PNWE), neighborhood interaction (NI) and residents’ mental health, with a focus on examining differences among residents of different age groups.

Using an electronic survey questionnaire, data on PNWE, NI and mental health were collected from 1,159 residents across 205 communities in Shanghai, China. Our study utilized a structural equation modeling (SEM), employing the maximum likelihood estimation method. The structural equation model was fitted using the MPLUS software.

The mental health of young and middle-aged adults is generally poor, and they are at higher risk of depression than children and older adults. The effects of PNWE and NI on the mental health of residents varied among different age groups. As residents get older, their mental health is more affected by the PNWE. In addition, the influence of the PNWE on children and older adults’ mental health is direct and not mediated by NI. For young and middle-aged adults, the influence of the PNWE on their mental health needs to be mediated by NI.

This study marks the first examination of the relationship between PNWE, NI and mental health among different age groups of residents in China. The findings of this research can assist policymakers in gaining a deeper understanding of the underlying mechanisms by which PNWE affects mental health. Furthermore, it can contribute to the development of more targeted walkable environment designs aimed at enhancing mental health among various age groups.

The purpose of this article is to explore the relationship between the attributes of Olympic mascots and their impact on sponsorship effectiveness. Based on a multiattribute model and the introduction of engagement theory and the meaning transfer model, this article uses the 2022 Beijing Winter Olympics mascot “Bing Dwen Dwen” as the research object to empirically analyze the effects and mechanisms of the mascot's attributes on preference, event engagement, sponsorship enterprise trust and sponsorship enterprise attitude, ultimately constructing a sponsorship effectiveness model.

The survey method was used to examine 238 respondents' emotions and attitudes towards companies participating in sponsoring Olympic mascots.

The study found that the main attributes of the mascot include visual and emotional factors, both of which have a positive impact on preference, with emotional factors having a greater influence than visual factors. Visual and emotional factors indirectly affect engagement through preference. Preference and engagement play a completely mediating role in the effect of mascot attributes on sponsorship enterprise trust and sponsorship enterprise attitude.

This study provides practical recommendations for managers to achieve marketing success in sports sponsorship through mascots.

This paper provides a measurement tool for the study of mascot attributes and important support for subsequent research in sponsorship marketing.

Laser powder bed fusion (LPBF) can be used to fabricate complex extrusion die without the limitation of structures. Layer-by-layer processing leads to differences in microstructures and wear properties. This study aims to investigate the microstructure evolution and effects of tungsten carbide (WC) on the wear properties of LPBF-printed 18Ni300.

Economical spherical granulation-sintering-deoxygenation (GSD) WC-reinforced 18Ni300 steel matrix composites were produced by LPBF from powder mixtures of WC and 18Ni300. The effects of WC contents on anisotropic microstructures and wear properties of the composites were investigated.

The relative density is more than 99% for all the composites except 25% WC/18Ni300 composite. The grain sizes distributed on the top cross-section are smaller than those on the side cross-section. After adding WC particles, more high-angle grain boundaries and larger Schmid factor generate, and deformed grains decrease. With increasing WC contents, the hardness first decreases and then increases but the wear volume loss decreases. The side cross-section of the composite has higher hardness and better wear resistance. The 18Ni300 exhibits adhesive wear accompanying with abrasive wear, while plowing and fatigue wear are the predominant wear mechanisms of the composites.

Economical spherical GSD WC particles can be used to improve the wear resistance. The novel WC/18Ni300 composites are suitable for the application under the abrasive wear condition with low stress.

In recent years, a great number of top conferences and workshops on artificial intelligence (AI) were held in China, showing Chinese AI plays an important role in the world. Meanwhile, Chinese government announced an ambitious scheme, “New Generation Artificial Intelligence Development Plan,” for the country to become a world leader in AI technologies by 2030. The AI research in China has covered various aspects, ranging from chips to algorithms. This chapter attempts to give an overview of the recent advances of AI research and development in China, as well as some perspectives on the future development of AI in China.