This study aims to fill in the gap by exploring the interrelationship among academic emotions, classroom engagement and self-efficacy in EFL learning among Chinese non-English majors in smart classrooms. A total of 409 non-English majors in their first year from a Chinese university completed the revised version of the academic emotions scale, classroom engagement scale and self-efficacy scale and their interrelationship has been analysed by Structural Equation Modelling. Positive emotion significantly enhances classroom engagement, while negative emotion does not. Classroom engagement has a significant effect on promoting self-efficacy, which is influenced by both positive and negative emotions, with positive emotions having a greater impact. Specifically, classroom engagement mediates the relationship between positive emotion and self-efficacy, whereas it does not mediate between negative emotion and self-efficacy. Smart classrooms can stimulate students’ positive academic emotions, increase their engagement in learning so as to enhance their self-efficacy.

With the rapid development of micro-machining technology, the feature size of object parts becomes smaller whilst the roundness tolerance must be critically verified at sub-micrometers or nanometers. Therefore, establishing a method is critically important for evaluating roundness errors to guarantee the machining quality. A progressive search method is proposed based on the minimum zone criterion in the Cartesian coordinate system in this paper. The least-square center of the measured points is used as the initial reference center by establishing a search circle model for progressively approaching the minimum zone circle center. To testify to the feasibility and performance of the proposed method, comparison and simulation experiments are implemented. The results demonstrated that the progressive search method is effective, reliable, and can evaluate roundness error accurately and quickly with not more than 0.1 s and 10 times.

A micro–nano coordinate measuring machine (CMM) is an instrument for high-precision measurement of micro-precision parts. The top of its probe is a microsphere with a diameter of tens to hundreds of micrometres. When the probe microsphere touches the part for measurement, its accuracy is affected by the surface morphology of the microsphere. A tuning fork resonant probe used for micro–nano CMMs is used to measure the contour of the micropore in automotive fuel injection nozzles in this study. Combined with the self-made optical fiber microsphere cross-sectional circle parameters at the top of the tuning fork probe, precise measurement of micropore diameter and roundness is achieved. During the experiment, the microsphere and micropore were measured by two independent systems, and thus, the error caused by the initial measurement angle of the microsphere and micropore is evaluated. The experimental results indicate that the measured micropore diameter is 194.542 µm and the roundness is 2.551 µm. The error caused by the initial measurement angle evaluated by the cubic Hermitian interpolation method can be ignored relative to the measurement results. The micropore structure parameters are precisely measured by the resonant probe combined with the morphology information of its top microsphere in this study, providing a research method for improving the measurement accuracy of micro–nano CMMs by combining microsphere morphology features.