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BackgroundDue to pressure from academic competition and future career planning, anxiety disorder has become one of the common psychological issues among college students. Anxiety disorder not only affects their learning but also causes interference in their daily lives. Psychological health education aims to help students understand and manage their emotions, while ideological and political education focuses on cultivating students’ values, worldviews, and outlook on life. The research aims to explore the effectiveness of combining mental health education with ideological and political education in the treatment of anxiety disorder in students.Subjects and MethodsThe study Divided 112 translation major students with anxiety and depression disorders into an experimental group and a control group. The control group received routine ideological and political education, while the experimental group received innovative teaching through joint human-machine interaction and collaborative translation. The teaching lasted for two months. The study used the Hamilton Anxiety Scale (HAMA) to evaluate the intervention of anxiety and depression disorders in students.ResultsBefore the experiment, there was no significant difference in the degree of anxiety and depression disorder between the two groups of students (P>0.05); Two months later, the degree of anxiety and depression disorder in the experimental group students was significantly improved, and was significantly lower than that in the control group students (P<0.05).ConclusionsInnovative teaching combined with human-machine interaction and collaborative translation can significantly alleviate students’ anxiety and depression levels, effectively improving their learning effectiveness and mental state.Acknowledgement2021 Philosophy and Social Science Research Project of Hubei Provincial Department of Education, Exploration and Research on Human-computer Interaction Collaborative Translation Mode in the Context of Internet+, Scientific Research Platform (No. 21y258).

Dynamics of a semiconductor laser subject to moderate optical feedback operating in the low-frequency fluctuation regime is numerically investigated. Multimode Lang-Kobayashi (LK) equations show that the low-frequency intensity dropout including the total intensity and sub-modes intensity is accompanied by sudden dropout simultaneously, which is in good agreement with experimental observation. The power fluctuation is quite annoying in practical applications, therefore it becomes important to study the mechanism of power fluctuation. It is also shown that many factors, such as spontaneous emission noise and feedback parameter, may influence power fluctuation larger than previously expected.