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The maturity of artificial intelligence technology and the emergence of AI-generated content (AIGC) tools have endowed college students with a human-AIGC tools collaboration learning mode. However, there is still a great controversy about its impact on learning effect. This paper is aimed at investigating the impact of the human-AIGC tools collaboration on the learning effect of college students.

In this paper, a hypothesized model was constructed to investigate the effects of dependence, usage purpose, trust level, frequency, and proficiency of using AIGC tools on the learning effect, respectively. This paper distributed questionnaires through random sampling. Then, the improved Analytic Hierarchy Process (AHP) was used to assign weights and normalize data. Lastly, one-way ANOVA and multiple linear regression analyses were used to measure and analyze variables, revealing the mechanism of influence.

The usage purpose, frequency, and proficiency of using AIGC tools have a significant positive effect on learning. Being clear about the usage purpose of AIGC tools and matching the specific study tasks will enhance the learning effect. College students should organically integrate AIGC tools into each learning process, which is conducive to building a learning flow applicable to oneself, improving efficiency, and then enhancing learning effects. The trust level in AIGC tools is significant, but positively and weakly correlated, indicating that college students need to screen the generated content based on their knowledge system framework and view it dialectically. The dependence on AIGC tools has a negative and significant effect on learning effect. College students are supposed to systematically combine self-reflection and the use of AIGC tools to avoid overdependence on them.

Based on the findings, the learning suggestions for college students in human-machine collaboration in the AIGC era are proposed to provide ideas for the future information-based education system. For further research, scholars can expand on different groups, professions, and fields of study.

Previous studies have focused more on the impact of AIGC on the education system. This paper analyzed the impact of the various factors of using AIGC tools in the learning process on the learning effect from the perspective of college students.

The purpose of this paper is twofold: to identify, evaluate and structure the research that focusses on omni-channel retailing from the perspective of logistics and supply chain management; and to reveal the intellectual foundation of omni-channel retailing research.

The paper applies a multi-method approach by conducting a content-analysis-based literature review of 70 academic papers. Based on the reference lists of these papers, the authors performed a citation and co-citation analysis based on the 34 most frequently cited papers. This analysis included multidimensional scaling, a cluster analysis and factor analysis.

The study reveals the limited consideration of logistics and supply chain management literature in the foundation of the omni-channel retailing research. Further, the authors see a dominance of empirical research as compared to conceptual and analytical research. Overall, there is a focus on the Western retail context in this research field. The intellectual foundation is embedded in the marketing discipline and can be characterised as lacking a robust theoretical foundation.

The contribution of this research is identifying, evaluating and structuring the literature of omni-channel research and providing an overview of the state of the art of this research area considering its interdisciplinary nature. This paper thus supports researchers looking to holistically comprehend, prioritise and use the underpinning literature central to the phenomena of omni-channel retailing. For practitioners and academics alike, the findings can trigger and support future research and an evolving understanding of omni-channel retailing.

This paper aims to under the laboratory environment, the corrosion behavior of X80 pipeline steel in oilfield injection water in eastern China was studied by immersion test.

First, the corrosion product film was immersed in oilfield injection water and the effect on the corrosion behavior and the corrosion reaction mechanism were constantly observed during this period. The effect was displayed by potentiodynamic polarization curve and electrochemical impedance spectrums (EIS) measurements. Second, scanning electron microscopy, energy dispersive spectroscopy and X-ray diffraction were used to observe and test the corrosion product film immersed in the oilfield water for 30 days.

The results indicate that the tendency of metal corrosion becomes weaker at an early stage, but strengthened later, which means the corrosion rate is accelerating. Besides, it is indicated by impedance spectroscopy that with the decreasing of the capacitance arc radius, the reaction resistance is reducing in this progress. Meanwhile, the character of Warburg impedance could be found in EIS, which means that the erosional components are more likely to penetrate the product film to reach the matrix. The corrosion product is mainly composed of the inner Fe₃O₄ layer and outer shell layer, which contains a large number of calcium carbonate granular deposits. It is this corrosion under fouling that produces severe localized corrosion, forming many etch pits on the metal substrate.

The experiment chose the X80 steel, the highest-grade pipeline steel used in China, to conduct the static immersion test in the injection water coming from an oilfield in eastern China. Accordingly, the corrosion mechanism and the effect of corrosion product film on the corrosion of pipeline steel were analyzed and discussed.

This paper aims to provide a review on the process of additive manufacturing of ceramic materials, focusing on partial and full melting of ceramic powder by a high-energy laser beam without the use of binders.

Selective laser sintering or melting (SLS/SLM) techniques are first introduced, followed by analysis of results from silica (SiO₂), zirconia (ZrO₂) and ceramic-reinforced metal matrix composites processed by direct laser sintering and melting.

At the current state of technology, it is still a challenge to fabricate dense ceramic components directly using SLS/SLM. Critical challenges encountered during direct laser melting of ceramic will be discussed, including deposition of ceramic powder layer, interaction between laser and powder particles, dynamic melting and consolidation mechanism of the process and the presence of residual stresses in ceramics processed via SLS/SLM.

Despite the challenges, SLS/SLM still has the potential in fabrication of ceramics. Additional research is needed to understand and establish the optimal interaction between the laser beam and ceramic powder bed for full density part fabrication. Looking into the future, other melting-based techniques for ceramic and composites are presented, along with their potential applications.

The purpose of this study is to present a novel approach for the evaluation of tribological properties of brake friction materials (BFM).

In this study, a BFM was newly formulated with 16 different ingredients and produced using an industrial hot compression molding process. Experimentation was carried out on the brake tester, which was developed for this purpose according to SAE J661 standards. The braking applications, sliding speed and braking pressure were considered as performance parameters, whereas coefficient of friction (CoF) and wear rate as output parameters. The influence of the performance parameters on the output was studied using response surface plots. Analysis of variance and regression analysis was accomplished for post-experimental evaluation of results. Multi-criteria decision-making (MCDM) and multi-objective genetic algorithm (MOGA) were applied for estimating the most critical performance parameter combination to evaluate the BFM.

The present experimental model was significant and effectively used to predict the performance. MCDM generates the optimal values for the parameters braking applications, braking pressure (Bar) and sliding speed (rpm) as 1000, 30 and 915, whereas MOGA as 1008, 10.503 and 462.8202, respectively.

An efficient model for performance evaluation of the BFM considering maximum CoF and minimum wear rate was experimentally presented and statistically verified. Also, the two multi-objective optimization methodologies were implemented and compared. A comparison between the results of MCDM and MOGA reveals that MOGA yields 30% better results than MCDM.