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Temperature and humidity coupling has a more significant effect on the failure properties of bonded joints than a single factor, and there is not enough research on this. In this paper, joints bonded with strong toughness structural adhesives are selected for the experimental analysis of joints aged for 240 h, 480 h, and 720 h at temperatures of 40 °C and 60 °C and a humidity of 95% and 100%. The sequential double Fick’s model was used to fit the water absorption of the joints, and the comparison yielded that the water absorption of the adhesive was in accordance with Fick’s law. The quasi-static tensile tests revealed that the reduction in mechanical properties of the joints was positively correlated with the moisture content in the environment, while the competing mechanisms of post-temperature curing and hydroplasticization resulted in a slight increase in the failure strength and energy uptake of the aged joints, which is in agreement with the experimental results of the Fourier infrared spectroscopy. A combination of macroscopic failure sections and scanning electron microscope (SEM) images yielded that the failure mode of the joints changed from cohesive failure to interfacial failure with increasing ageing time. In addition, reliability analyses for the fatigue testing of joints are expected to provide guidance for the life design of bonding technology in the vehicle service temperature range.

Herein, a Sc(OTf)3-catalyzed (3+2) annulation of 2-indolylmethanols with propargylic alcohols is reported. The reaction proceeds via a Friedel–Crafts-type allenylation/5-exo-annulation cascade. In the reaction, 2-indolylmethanol is used as a three-carbon synthon, and propargyl alcohol is used as a two-carbon synthon. This method provides a direct and high-yield pathway for synthetically useful cyclopenta[b]indoles. In general, the method features easily accessible substrates with broad scope and generality, the formation of multiple bonds with high efficiency, and easy scale-up.

This paper conducts a preliminary exploration of Artificial Intelligence (AI) for emotion recognition, particularly in its business applications. Employing adaptive technologies like machine learning algorithms and computer vision, AI systems analyze human emotions through facial expressions, speech patterns, and physiological signals. Ethical considerations and responsible deployment of these technologies are emphasized through an intense literature review. The study employs a comprehensive bibliometric analysis, utilizing tools such as VOSViewer, to trace the evolution of emotion-aware AI in business. Three key steps involve surveying the literature on emotion analysis, summarizing information on emotion in various contexts, and categorizing methods based on their areas of expertise. Comparative studies on emotion datasets reveal advancements in model fusion methods, exceeding human accuracy and enhancing applications in customer service and market research. The bibliometric analysis sheds light on a shift towards sophisticated, multimodal approaches in emotion recognition research, addressing challenges such as imbalanced datasets and interpretability issues. Visualizations depict keyword distributions in research papers, emphasizing the significance of “emotion recognition” and “deep learning.” The study concludes by offering insights gained from network visualization, showcasing core keywords and their density in research papers. Based on the literature, a SWOT analysis is also conducted to identify the strengths, weaknesses, opportunities, and threats associated with applying emotion recognition to business. Strengths include the technology’s high accuracy and real-time analysis capabilities, enabling diverse applications such as customer service and product quality improvement. However, weaknesses include data bias affecting the AI model’s quality and challenges in processing complex emotional expressions. Opportunities lie in the increasing number of studies, market size, and improving research outcomes, while threats include privacy concerns and growing competition.

Wheat bran (WB) is the primary by-product of wheat processing and contains a high concentration of bioactive substances such as polyphenols. This study analyzed the qualitative and quantitative components of polyphenols in wheat bran and their effects on ulcerative colitis (UC) using the dextran sulfate sodium (DSS)-induced colitis model in mice. The potential mechanism of wheat bran polyphenols (WBP) was also examined. Our findings indicate that the main polyphenol constituents of WBP were phenolic acids, including vanillic acid, ferulic acid, caffeic acid, gallic acid, and protocatechuic acid. Furthermore, WBP exerted remarkable protective effects against experimental colitis. This was achieved by reducing the severity of colitis and improving colon morphology. Additionally, WBP suppressed colonic inflammation via upregulation of the anti-inflammatory cytokine IL-10 and downregulation of pro-inflammatory cytokines (TNF-α, IL-6, IL-1β) in colon tissues. Mechanistically, WBP ameliorated DSS-induced colitis in mice by inhibiting activation of the MAPK/NF-κB pathway. In addition, microbiome analysis results suggested that WBP modulated the alteration of gut microbiota caused by DSS, with an enhancement in the ratio of Firmicutes/Bacteroidetes and adjustments in the number of Helicobacter, Escherichia-Shigella, Akkermansia, Lactobacillus, Lachnospiraceae_NK4A136_group at the genus level. To conclude, the findings showed that WBP has excellent prospects in reducing colonic inflammation in UC mice.

There are few studies on the shape and structure of the channel-type induction heating tundish on multi-physics field. Computational fluid dynamics has been used to study the influence of the structure of the tundish on the macroscopic transport behavior of the tundish with channel induction heating. The results show that increasing the depth of the molten pool is conducive to dynamic behavior of multiphase, the deeper the molten pool, the larger the active area, the longer residence time, the more inclusions removal and the higher ratio of plug to dead volume. Meanwhile, the larger the channel diameter, the more inclusions removal in the receiving chamber and channel. The channel induction heating has enough ability to increase the superheat and temperature compensate for the heat loss caused by the excessive residence time of the molten steel in the tundish. The change in the channel structure is crucial to the macroscopic transport behavior of the fluid. The change in channel diameter has the greatest effect on the multi-physics field in the molten pool.