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The basic biomechanical laws that apply to the clawed toes of animals with powerful digging abilities and the optimal bionic design of curved soil cultivating components with an analogous contour were researched in a novel way. First, the curvature and profile of the inside contour line of a field mouse's clawed toe were analyzed. The finite element method (FEM) was then used to simulate the working process in order to study the changing characteristics of the working resistance of bionic soil-engaging surfaces and the stress field of the processed soil. A straight-line cultivating component was used for comparative analysis. In accordance with the simulation results, a series of soil cultivating components of varying design were manufactured. An indoor soil bin experiment was carried out to measure their working resistance and validate the results of the FEM analysis. The results of this research would have important values in the optimization design of cultivating components for energy and cost savings.

Background Anxiety can be classified as state anxiety and trait anxiety which present the current level of anxiety and the generalized anxiety tendencies of individuals, respectively. The State-Trait Anxiety Inventory form Y (STAI-Y) is a reliable instrument used to test both the levels of state and trait anxiety across various countries. However, the optimal factor structure of STAI-Y in different populations is not consistent and is not clear in Chinese university students. In addition, the gender invariance is the premise for comparing the scores of STAI-Y between men and women which also need to be verified. Therefore, this study explored the optimal factor structure of STAI-Y and examined whether the optimal factor structure satisfied measurement invariance across gender in Chinese university students. Method A sample of 2117 Chinese university students participated in this study including 748 men and 1369 women. The optimal factor structure was decided by singer group confirmatory factor analysis (CFA) and exploratory structural equation modeling (ESEM). Furthermore, the configural invariance, metric invariance, scalar invariance, and strict invariance models were administrated in multigroup CFA to detect the measurement equivalence of STAI-Y across gender in Chinese university students. The reliability of STAI-Y was tested by Cronbach’s alpha coefficient and McDonald’s omega coefficients. Results The optimal factor structure of STAI-Y was four-factor model and reached strict gender invariance in Chinese university students. Moreover, the STAI-Y also had adequate reliability in Chinese university students. Conclusion This study explored the factor structure and gender invariance of STAI-Y in Chinese university students. In sum, the four-factor structure of STAI-Y obtained the best goodness-of-fit and satisfied gender invariance which deepened the understanding of STAI-Y in Chinese university students.

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