人工智能赋能在线实验教学行为分析

教学行为分析作是教学质量分析的重要组成部分，也是教学引导与反馈机制的重要依据。文章阐述了人工智能（AI）的含义及发展历程，重点分析总结了教学行为分析方法及AI在教学行为分析上的应用。文章以东南大学电工电子在线实验为研究平台，探索分析了AI技术在实验教学行为分析上的可行性，梳理了基于专家系统的在线实验分析系统的设计思路，充分探讨了“智能”教育在实验教学中的深刻内涵。     

4-Methyl-2,4-bis(4-hydroxyphenyl)pent-1-ene,a Major Active Metabolite of Bisphenol A,Triggers Pancreatic β-Cell Death via a JNK/AMPKα Activation-Regulated Endoplasmic Reticulum Stress-Mediated Apoptotic Pathway

4-methyl-2,4-bis(4-hydroxyphenyl)pent-1-ene (MBP), a major active metabolite of bisphenol A (BPA), is generated in the mammalian liver. Some studies have suggested that MBP exerts greater toxicity than BPA. However, the mechanism underlying MBP-induced pancreatic β-cell cytotoxicity remains largely unclear. This study demonstrated the cytotoxicity of MBP in pancreatic β-cells and elucidated the cellular mechanism involved in MBP-induced β-cell death. Our results showed that MBP exposure significantly reduced cell viability, caused insulin secretion dysfunction, and induced apoptotic events including increased caspase-3 activity and the expression of active forms of caspase-3/-7/-9 and PARP protein. In addition, MBP triggered endoplasmic reticulum (ER) stress, as indicated by the upregulation of GRP 78, CHOP, and cleaved caspase-12 proteins. Pretreatment with 4-phenylbutyric acid (4-PBA; a pharmacological inhibitor of ER stress) markedly reversed MBP-induced ER stress and apoptosis-related signals. Furthermore, exposure to MBP significantly induced the protein phosphorylation of JNK and AMP-activated protein kinase (AMPK)α. Pretreatment of β-cells with pharmacological inhibitors for JNK (SP600125) and AMPK (compound C), respectively, effectively abrogated the MBP-induced apoptosis-related signals. Both JNK and AMPK inhibitors also suppressed the MBP-induced activation of JNK and AMPKα and of each other. In conclusion, these findings suggest that MBP exposure exerts cytotoxicity on β-cells via the interdependent activation of JNK and AMPKα, which regulates the downstream apoptotic signaling pathway.     

Effect of the thicknesses of the Al2SiO5 ion conductor on the opto-electrical properties for all-solid electrochromic devices

In this study, an all-solid-state electrochromic device (ECD) with the structure of ITO/WO₃/Al₂SiO₅/NiO_x/ITO was prepared, and the effect of the Al₂SiO₅ solid electrolyte thicknesses on the opto-electrical performance was investigated. The microstructure and surface morphology were characterized using XRD, SEM and AFM, and the surface morphology and degree of surface looseness demonstrate a significant influence on the opto-electrical properties of ECDs. The charge transfer dynamics at the solid-solid interface were characterized using EIS to obtain an ionic conductivity of 4.637 × 10^-8 S/cm. CV, CA and UV–Visible spectra were employed to record the in situ electrochemical and optical properties. The results revealed that the highest optical modulation was 44.58%, the coloring and bleaching times were 14.8 s and 3.7 s, and the highest coloring efficiency was 98.17 cm²/C, which indicates that excellent opto-electrical properties were obtained. When the thickness increases, the degree of surface dense morphology transforms, and the loose morphology is more favorable for ion conductivity, which improves the opto-electrical properties. The results in this study provide insights into the understanding of Al³⁺-based all-solid-state ECDs, which promote the exploration of new types of Al³⁺ ionic conductors for all-solid-state ECDs.     

Weighted regularized extreme learning machine to model the discharge coefficient of side slots

In the current research, a modern learning machine algorithm named “Weighted Regularized Extreme Learning Machine (WRELM)" is implemented for the first time for the simulation of the coefficient of discharge of side slots. For this purpose, an effective variable on the coefficient of discharge of side slots is firstly introduced, then five distinctive WRELM models are produced by it for the estimation of the coefficient. In the next stage, a database is created for verification of WRELM results. it should be mentioned that 70% of the data are utilized for training the WRELM models, while the rest (i.e. 30%) for testing them. After that, the optimal number of hidden layer neurons as well as the best activation function of the WRELM algorithm are chosen. In addition, the best regularization parameter and also the weight function of the WRELM are achieved. By conducting a sensitivity analysis, the most effective variable for the simulation of the coefficient of discharge along with the WRELM superior model is introduced. The WRELM superior model estimates values of the coefficient of discharge with the maximum exactness and the highest correlation. For instance, the estimations of the correlation coefficient and scatter index for this model are computed to be 0.930 and 0.051, respectively. The sensitivity analysis shows that the ratio of the side slot crest height to its length and the Froude number should be considered as the most important input variables. A comparison between the WRELM with the ELM displays that the former works much better. Furthermore, an uncertainty analysis is executed for both models. Eventually, an equation is suggested for the estimation of the coefficient of discharge and a partial derivative sensitivity analysis is performed on it.     

Phase composition,microstructure and thermophysical properties of the Srx(Zr0.9Y0.05Yb0.05)O1.95+x ceramics

Sr_x(Zr_0.9Y_0.05Yb_0.05)O_1.95+x (x=1.0, 0.9, 0.8, 0.7) ceramics were prepared by solid state reaction sintering. The sintered Sr_1.0(Zr_0.9Y_0.05Yb_0.05)O_2.95 is a single-phase solid solution while the sintered Sr_x(Zr_0.9Y_0.05Yb_0.05)O_1.95+x (x=0.9?0.7) are composites, and a significant grain growth inhibition is observed in the sintered Sr_x(Zr_0.9Y_0.05Yb_0.05)O_1.95+x (x=1.0, 0.9). Rare-earth elements distribution in the bulk materials indicates that Yb and Y preferentially substitute Zr-sites in SrZrO₃, and the highest solubility of RE₂O₃ in pure SrZrO₃ is ～0.8 mol%. The sintered Sr_x(Zr_0.9Y_0.05Yb_0.05)O_1.95+x have high thermal expansion coefficients up to ～11.0×10^?6 K^-1 (1200°C). Sr_0.8(Zr_0.9Y_0.05Yb_0.05)O_2.75 has the lowest thermal conductivity of 1.38 W·m^-1·K^-1 at 800°C. Sr_x(Zr_0.9Y_0.05Yb_0.05)O_1.95+x (x=1.0, 0.9, 0.8) show no phase transition from 600 to 1400°C, whereas Sr_x(Zr_0.9Y_0.05Yb_0.05)O_1.95+x (x=0.9, 0.8) have excellent high-temperature phase stability over the whole investigated temperature range. Therefore, Sr_x(Zr_0.9Y_0.05Yb_0.05)O_1.95+x (x=1.0, 0.9, 0.8) are considered as promising TBCs materials that might be operated at higher temperatures compared to YSZ.     

Multiple material domain‐based computational tools for ease assessment of modal parameter in photonic crystal fibers

We report here the development of two computational tools PCFPS (Photonic Crystal Fiber Parameter Study) and PCFPA (Photonic Crystal Fiber Parameter Analysis), equipped with graphical user interface (GUI) for modeling of photonic crystal fiber. The tools are based on different structural parameters, and they provide characteristic analysis of the modal parameters from the structural parameters. The main feature of PCFPS is that it enables the user to find out the values of each defining modal parameter that has an immense contribution towards the manufacture of photonic crystal fiber. Additionally, PCFPA allows the user to observe the variation in the modal parameters with respect to the changes in structural parameters (such as d, Λ, d/Λ, and λ/>Λ). Besides their ease of use, these two schemes have high computational precision and adaptability, giving a novel platform to optical engineers to modulate the microstructured fibers according to their requirement.     

Surface generation mechanism of ceramic matrix composite in ultrasonic assisted wire sawing

Ceramic matrix composites (CMC) are highly required in many fields of science and engineering. However, the CMC parts always have poor surface finish. This study attempts to improve cutting performance of CMC material by combing the advantages of ultrasonic assisted cutting and diamond wire sawing. Cutting force, surface roughness, machined edge and tool wear are analyzed based on experimental results. It shows that the oscillatory movement of tool edges provides positive effect on particle ejection and residual material reduction. Ductile chip formation can be achieved due to the small tip radius of grits. Obvious decrease in cutting force, surface roughness and tool wear are obtained. Moreover, burrs, fuzzing and fracture are reduced. Meanwhile, both the surface characteristics and shape accuracy are significantly improved. These results provide a valuable basis for application of ultrasonic assisted wire sawing and understanding of CMC cutting mechanisms.