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Spectrogram is an image that can record voice information, which can be analyzed by analyzing the received image. Spectrograms are used in mechanical fault diagnosis systems to answer questions such as the location, type, and extent of the fault. It is the main tool for analyzing vibration parameters. In actual use, there are three types of spectrograms, namely linear amplitude spectrum, logarithmic amplitude spectrum, and self-power spectrum. The ordinate of the linear amplitude spectrum has a clear physical dimension and is the most commonly used. In this paper, the feature extraction information of rural acoustic landscape is mainly carried out through spectral images, which can effectively improve the segmentation efficiency, ensure the integrity of information, and determine the feasibility of establishing acoustic landscape in rural areas. This article aims to study the analysis of rural acoustic landscape in Guilin, Guangxi, based on the segmentation and extraction of spectral image feature information, through the segmentation and extraction of spectral image feature information, and then analyze the advantages and disadvantages of rural acoustic landscape. In this article, the Gabor wavelet filtering method is proposed to filter and analyze the spectral image. Through the detailed analysis of the insect and bird calls of the forest community near the village of Guilin, Guangxi, finally, the satisfaction and attention of the rural villagers to the acoustic landscape are investigated. The experimental results show that the sound of insects and birds reaches the maximum in spring and the minimum in autumn and winter. Moreover, the attention of rural villagers to acoustic landscape is also very high, with satisfaction of 87.12% and attention of 92.68%.

of the pediatric IBD population had at least 1 mental health concern over this time period, and the most common psychiatric diagnoses were depression alone (67%), anxiety alone (3%), or both depression and anxiety (30%). About 36% of patients were prescribed a psychotropic medication and hydroxyzine (53%), sertraline (33%), and fluoxetine (25%) were the most prescribed therapeutics. 24% of patients utilized some form of mental health service but 49% of patients taking psychotropic medications did not appear to receive any formal mental health services. Patients who developed a psychiatric disorder reported more IBD-related symptoms at the time of their diagnosis compared to those without any history of psychiatric diagnoses (t(136)51.99, P5.02). Conclusion(s): Our results suggest there are high levels of depression and/or anxiety in children with IBD seen at URMC during the time of the COVID-19 pandemic. Additionally, increased IBD symptoms at the time of diagnosis were associated with increased rates of psychopathology. Taken together, these findings suggest that more anxiety and depression screening is needed for pediatric IBD patients and that mental health services may be underutilized in the pediatric IBD population. Future directions include combining and comparing this data set with a previous pre-pandemic study performed at our institution to determine the full impact of COVID-19 on this population.

The feature extraction of Gaofen-2 Remote Sensing Image (RSI) has problems such as poor extraction accuracy and large noise reduction error. Therefore, this paper designs an RSI feature extraction method based on high score 2 wavelet transform (WT). The RSI is collected with the help of Gaofen-2 satellite and high-resolution remote sensing technology, the key points of the image are determined through the Gaussian difference scale space, and the key points of the edge are judged by the peak curvature value of the difference function at the edge junction, so as to complete the RSI acquisition. Specific filtering and spatial domain transformations are used to remove image noise and improve the quality of RSI. The mean shift (MS) algorithm is used to iteratively find the area with the most dense sample points in the RSI space, complete the image analysis, and realize the preprocessing of the high score 2 RSI. The linear features of the RSI are determined by the WT algorithm, and the image threshold is set for feature extraction of the high score 2 RSI. The experimental results show that in the RSI noise reduction error analysis of different methods, the noise reduction error curve of the sample RSI of the method proposed in this paper has the lowest trend, which is always lower than 2%. Compared with the two methods proposed before, the error is higher. At the same time, in the accuracy analysis of key point feature extraction, the proposed scheme has better accuracy. Therefore, it can be seen that this method has better comprehensive performance, and the proposed method can effectively improve the feature extraction accuracy of RSI and reduce the noise in RSI.