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Treatment of condylar fractures in patients with edentulous mandibles or no-occlusion reference is particularly challenging due to the absence of important anatomical structures and landmark for occlusion analysis. In this case, a 69-year-old female maxillary oligodontia victim suffered from a traumatic accident with a right facial contusion, resulting in a right-side subcondylar and mandibular ramus fracture with right ramus height loss. In the preoperative planning, the 3-dimensionalimage of the left-side mandible was highlighted by the navigation software. A mirror image of the left-side mandible was made and superimposed on the right side of the face. Surgical intervention with an endoscope and 3-dimensional navigation-assisted open reduction and internal fixation of the right-side subcondylar and ramus fracture was performed. The patient recovered well with no restriction in mandibular movement, no limitation in mouth opening, and a satisfied esthetic outcome.

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The main causes of damage to industrial machinery are aging, corrosion, and the wear of parts, which affect the accuracy of machinery and product precision. Identifying problems early and predicting the life cycle of a machine for early maintenance can avoid costly plant failures. Compared with other sensing and monitoring instruments, sound sensors are inexpensive, portable, and have less computational data. This paper proposed a machine tool life cycle model with noise reduction. The life cycle model uses Mel-Frequency Cepstral Coefficients (MFCC) to extract audio features. A Deep Neural Network (DNN) is used to understand the relationship between audio features and life cycle, and then determine the audio signal corresponding to the aging degree. The noise reduction model simulates the actual environment by adding noise and extracts features by Power Normalized Cepstral Coefficients (PNCC), and designs Mask as the DNN's learning target to eliminate the effect of noise. The effect of the denoising model is improved by 6.8% under Short-Time Objective Intelligibility (STOI). There is a 3.9% improvement under Perceptual Evaluation of Speech Quality (PESQ). The life cycle model accuracy before denoising is 76%. After adding the noise reduction system, the accuracy of the life cycle model is increased to 80%.

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RESUMEN

Background and Objectives: Nail bed and germinal matrix loss due to wide excision for fingertip tumors or malignancy are occasionally encountered complications. These defects also result from severely comminuted fingertip crush injuries. Large-area dorsal finger or toenail bed defects, which usually present with phalangeal bone exposure, remain challenging regardless of the usage of different reconstruction strategies. This study aimed to evaluate the clinical outcome of a staged operation with an acellular dermal matrix coverage and subsequent skin graft as reconstruction for defects of total nail bed, germinal matrix loss, and bone exposure. Materials and Methods: From April 2018 to October 2019, four patients with total nail bed, germinal matrix, and bone exposure loss after surgery were enrolled in our series. A staged operation of the acellular dermal matrix coverage with subsequent skin graft was performed on these patients. Skin graft take rate, oncological prognosis, and cosmetic outcome were evaluated. Patients were followed up for 5-13 months. An excellent skin graft take rate with a satisfying aesthetic result without local malignancy recurrence was noted. Minimal functional deficit and donor site morbidity were reported. Results: A staged operation with acellular dermal matrix coverage and subsequent skin graft proves to serve as a feasible strategy for patients who experience total nail bed, germinal matrix loss, and bone exposure after surgery. Conclusions: This reconstruction method provides a reliable repair result, satisfying aesthetic outcomes, as well as having minimal functional deficits and donor site morbidity.

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