Wolfgang Amadeus Mozart, one of the most important composers in the classical period, wrote more than 600 instrumental and vocal works in his life. Among many musical works, besides the well-known symphonies and concertos, his 22operas had a far-reaching impact on later generations. During his settlement in Vienna, Mozart co-wrote with theatre poet Da Pent. Three famous comedy operas, the last one is Woman's Heart, completed in 1790. This paper takes Feudiligi's aria "Hard as a Rock" in Mozart's opera "Woman's Heart" as the object of study, through in-depth analysis of the creative background, Lyric characteristics and musical structure of the work, and summarizes the singing characteristics of "Hard as a Rock". With a summary, I hope to put forward the theoretical basis for the singing of the same type of songs, and summarize the corresponding more optimized learning methods.

The acoustic emission (AE) method as a passive non-destructive monitoring technique is proposed for real-time monitoring of mechanical degradation in underground structures, such as deep geological disposal of high-level nuclear waste (HLW). This study investigates the low-frequency characteristics of AE signals emitted during the fracturing of meter-scale concrete specimens; uniaxial compression tests (UCT) in a lab scale and Goodman jack (GJ) tests in a 1.3 m-long concrete block were conducted while acquiring the AE signals using low-frequency AE sensors. The results indicate a sharp increase in AE energy emission at approximately 60% and 80% of the yield stresses in the UCT and GJ tests, respectively. The collected AE signals were primarily found in two frequency bands: the 4-28 kHz range and the 56-80 kHz range. High-frequency AE signals were captured more as the stress increased in the GJ tests, which was in contrast to the UCT tests. Furthermore, the AE signals obtained from the Goodman jack tests tended to lower RA values than the UCT results. This study presents unique experimental data with low-frequency AE sensors under different loading conditions, which provides insights into field-scale AE monitoring practices.