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The advent of precision diagnostics in pediatric dentistry is shifting towards ensuring early detection of dental diseases, a critical factor in safeguarding the oral health of the younger population. In this study, an innovative approach is introduced, wherein Discrete Wavelet Transform (DWT) and Generative Adversarial Networks (GANs) are synergized within an Image Data Fusion (IDF) framework to enhance the accuracy of dental disease diagnosis through dental diagnostic systems. Dental panoramic radiographs from pediatric patients were utilized to demonstrate how the integration of DWT and GANs can significantly improve the informativeness of dental images. In the IDF process, the original images, GAN-augmented images, and wavelet-transformed images are combined to create a comprehensive dataset. DWT was employed for the decomposition of images into frequency components to enhance the visibility of subtle pathological features. Simultaneously, GANs were used to augment the dataset with high-quality, synthetic radiographic images indistinguishable from real ones, to provide robust data training. These integrated images are then fed into an Artificial Neural Network (ANN) for the classification of dental diseases. The utilization of the ANN in this context demonstrates the system's robustness and culminates in achieving an unprecedented accuracy rate of 0.897, 0.905 precision, recall of 0.897, and specificity of 0.968. Additionally, this study explores the feasibility of embedding the diagnostic system into dental X-ray scanners by leveraging lightweight models and cloud-based solutions to minimize resource constraints. Such integration is posited to revolutionize dental care by providing real-time, accurate disease detection capabilities, which significantly reduces diagnostical delays and enhances treatment outcomes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Postsacrectomy hernias are uncommon and can present with different signs and symptoms, including constipation, fecal incontinence, bowel obstruction, pain, and posterior bulging. We report a 50-year-old man who underwent sacrectomy for malignant fibrosarcoma complicated with sacral hernia. He presented with obstructive symptoms resulting from a strictured segment of herniated sigmoid colon and underwent bowel resection along with repair of his hernia. We additionally present a review of the literature and treatment of this rare disease.

Analysis of mass transfer resistances was performed for an aerated submerged fixed-film reactor (ASFF) for the treatment of waste water containing a mixture of sucrose and ammonia. Both external and internal mass transfer resistances were considered in the analysis, and characterized as a function of feed flow-rate and concentration. Results show that, over a certain operating regime, external mass transfer resistance in the system was greater for sucrose removal than ammonia. This is because the reaction rates for carbon removal were much larger than those of nitrogen. As a result, existence of any form of mass transfer resistance caused by inadequate mixing or diffusion limitations, strongly affects the overall removal rates of carbon more than nitrogen. Effects of the internal måss transfer resistance were virtually non-existent for ammonia removal. This behaviour was found over two orders of magnitude range for the effective diffusivity for ammonia, and one order of magnitude for the film specific surface area. However, over the same parameters' range, it is found that sucrose removal was strongly affected upon lowering its effective diffusivity and increasing the film specific surface area.