Objective To understand the status quo of problem behavior of children in Henan Province, and to explore the applicability of the Conners Parent Symptom Questionnaire (PSQ) norm test in 3-6 years old children. Methods A total of 775 children aged 3-6 years old in Henan Province were selected to measure their problem behavior by using PSQ. The difference and consistency of the detection rate of Chinese and American norms were analyzed, and the difference between the average score of problem behavior of children in Henan Province and the average score of each factor of the two norms was studied. Results (1) The impulsive-hyperactivity index of boys was significantly higher than that of girls; Children's learning problems show a significant age difference, and the older the children, the higher the score of learning problems; Non-only children show more impulsive-hyperactivity, hyperactivity problems than only children. (2) There are significant differences between the Chinese norm and the American norm in the detection rates of learning problems, impulsive-hyperactivity, anxiety and hyperactivity index. (3) The PSQ scores of children in Henan Province were significantly different from most factors of Chinese and American norm PSQ. Conclusion There are differences in the problem behavior of young children in Henan Province in terms of gender, age, and whether they are only children. The consistency of Chinese and American PSQ norms is poor, and they are no longer applicable to young children in contemporary Henan Province.
In recent years, the pathological diagnosis of glomerular diseases typically involves the study of glomerular his-to pathology by specialized pathologists, who analyze tissue sections stained with Periodic Acid-Schiff (PAS) to assess tissue and cellular abnormalities. In recent years, the rapid development of generative adversarial networks composed of generators and discriminators has led to further developments in image colorization tasks. In this paper, we present a generative adversarial network by Spectral Normalization colorization designed for color restoration of grayscale images depicting glomerular cell tissue elements. The network consists of two structures: the generator and the discriminator. The generator incorporates a U-shaped decoder and encoder network to extract feature information from input images, extract features from Lab color space images, and predict color distribution. The discriminator network is responsible for optimizing the generated colorized images by comparing them with real stained images. On the Human Biomolecular Atlas Program (HubMAP)—Hacking the Kidney FTU segmentation challenge dataset, we achieved a peak signal-to-noise ratio of 29.802 dB, along with high structural similarity results as other colorization methods. This colorization method offers an approach to add color to grayscale images of glomerular cell tissue units. It facilitates the observation of physiological information in pathological images by doctors and patients, enabling better pathological-assisted diagnosis of certain kidney diseases.
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