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In this paper, we combine two feature extraction algorithms, Empirical Mode Decomposition (EMD) and wavelet packet transform, to analyze the EGG signals of students exposed to vocal music. We extract features from these signals by determining the instantaneous frequency and node signals based on the mean value of the envelope. The EGG signals were cut into short-time smooth signals. The average sample entropy value of the processed EGG signals was calculated to reflect the EEG activities of students under vocal stimulation. Then the EGG signals were used to reflect the changes in the mental health status of college students. In the vocal stimulation experiment, it was found that the students’ psychological comprehensive relaxation reached 85.47% on average, α and the amplitude of the EEG signals was able to reach about ±20. The total score of the psychological health scale of students in the experimental class after the implementation of integrated teaching reached 99.63, which was much higher than that of the control class, which was 91.26, and the difference was significant (P=0.000

Diseases and pests are main stresses to crop production. It is necessary to accurately and quickly monitor and control the stresses dynamically, so as to ensure the food security and the quality and safety of agricultural products, protect the ecological environment, and promote the sustainable development of agriculture. In recent years, with the rapid development of the unmanned aerial vehicle (UAV) industry, UAV agricultural remote sensing has played an important role in the application of crop diseases and pests monitoring due to its high image spatial resolution, strong data acquisition timeliness and low cost. The relevant background of UAV remote sensing monitoring of crop disease and pest stress was introduced, then the current methods commonly used in remote sensing monitoring of crop disease and pest stress by UAV was summarized. The data acquisition method and data processing method of UAV remote sensing monitoring of crop disease and pest stress were mainly discussed. Then, from the six aspects of visible light imaging remote sensing, multispectral imaging remote sensing, hyperspectral imaging remote sensing, thermal infrared imaging remote sensing, LiDAR imaging remote sensing and multiple remote sensing fusion and comparison, the research progress of remote sensing monitoring of crop diseases and pests by UAV worldwide was reviewed. Finally, the unresolved key technical problems and future development directions in the research and application of UAV remote sensing monitoring of crop disease and pest stress were proposed. Such as, the performance of the UAV flight platform needs to be optimized and upgraded, as well as the development of low-cost, lightweight, modular, and more adaptable airborne sensors. Convenient and automated remote sensing monitoring tasks need to be designed and implemented, and more remote sensing monitoring information can be obtained. Data processing algorithms or software should be designed and developed with greater applicability and wider applicability, and data processing time should be shortened by using 5G-based communication networks and edge computing devices. The applicability of the algorithm or model for UAV remote sensing monitoring of crop disease and pest stress needs to be stronger, so as to build a corresponding method library. We hope that this paper can help Chinese UAV remote sensing monitoring of crop diseases and pests to achieve more standardization, informatization, precision and intelligence.

The cross-correlation function (CCF) of seismic noise recorded at two stations often exhibits a prominent burst of energy near zero time. However, the excitation mechanism of such unexpected signals remains unclear. In this study, we demonstrate that this phenomenon arises from constructive interference of body waves radiating from sources near the mid-vertical plane between two receivers. This interference is driven by the occurrence of an inflection point effect in the traveltime difference between waves reaching the two receivers. When noise source distribution is asymmetric, the cumulative effect of such sources results in the generation of zero-time waves. It is noteworthy that a noise source distribution that is either uniform or follows a cos ϕ pattern, with ϕ denoting the azimuth from the centre of the receiver pair, can counteract the formation of these waves. Additionally, our investigation reveals that this constructive interference does not occur in the correlation of 2-D surface waves. We used numerical simulation to support our findings. In conclusion, this study offers a theoretical explanation for the emergence of zero-time waves on the CCF and provides efficient means of investigating the extraction of inter-receiver waves with uneven noise source distribution. [ABSTRACT FROM AUTHOR]