Surgical Management of a Mandible Subcondylar Fracture

Open reduction and anatomic reduction can create better function for the temporomandibular joint, compared with closed treatment in mandible fracture surgery. Therefore, the double miniplate fixation technique via mini-retromandibular incision was used in order to make the most stable fixation when performing subcondylar fracture surgery. Those approaches provide good visualization of the subcondyle from the posterior edge of the ramus, allow the surgeon to work perpendicularly to the fracture, and enable direct fracture management. Understanding the biomechanical load in the fixation of subcondylar fractures is also necessary in order to optimize fixation methods. Therefore, we measured the biomechanical loads of four different plate fixation techniques in the experimental model regarding mandibular subcondylar fractures. It was found that the loads measured in the two-plate fixation group with one dynamic compression plate (DCP) and one adaption plate showed the highest deformation and failure loads among the four fixation groups. The loads measured in the one DCP plate fixation group showed higher deformation and failure loads than the loads measured in the two adaption plate fixation group. Therefore, we conclude that the selection of the high profile plate (DCP) is also important in order to create a stable load in the subcondylar fracture

Fast Knowledge Graph Completion using Graphics Processing Units

Knowledge graphs can be used in many areas related to data semantics such as question-answering systems, knowledge based systems. However, the currently constructed knowledge graphs need to be complemented for better knowledge in terms of relations. It is called knowledge graph completion. To add new relations to the existing knowledge graph by using knowledge graph embedding models, we have to evaluate $N\times N \times R$ vector operations, where $N$ is the number of entities and $R$ is the number of relation types. It is very costly. In this paper, we provide an efficient knowledge graph completion framework on GPUs to get new relations using knowledge graph embedding vectors. In the proposed framework, we first define "transformable to a metric space" and then provide a method to transform the knowledge graph completion problem into the similarity join problem for a model which is "transformable to a metric space". After that, to efficiently process the similarity join problem, we derive formulas using the properties of a metric space. Based on the formulas, we develop a fast knowledge graph completion algorithm. Finally, we experimentally show that our framework can efficiently process the knowledge graph completion problem

Pioneering EEG Motor Imagery Classification Through Counterfactual Analysis

The application of counterfactual explanation (CE) techniques in the realm of electroencephalography (EEG) classification has been relatively infrequent in contemporary research. In this study, we attempt to introduce and explore a novel non-generative approach to CE, specifically tailored for the analysis of EEG signals. This innovative approach assesses the model's decision-making process by strategically swapping patches derived from time-frequency analyses. By meticulously examining the variations and nuances introduced in the classification outcomes through this method, we aim to derive insights that can enhance interpretability. The empirical results obtained from our experimental investigations serve not only to validate the efficacy of our proposed approach but also to reinforce human confidence in the model's predictive capabilities. Consequently, these findings underscore the significance and potential value of conducting further, more extensive research in this promising direction

Consensus of Corporate E-Learning System Stakeholders Regarding the Satisfaction of End-Users

The purpose of this study is to call attention to the consensus of stakeholders of corporate e-Learning system regarding success. We identified the critical success factors (contents, technical features, management, and organizational support) as major components of corporate eLearning systems and questioned whether stakeholders’ consensus on the importance of these components facilitates the implementation of these components to achieve good quality or well. We also questioned whether the influence of these components on user satisfaction could be moderated by contextual factors. Based on empirical testing of 18 eLearning user companies, we verified that the consensus of stakeholders regarding the importance of content, technological features, and organizational support has a positive influence on the perceived quality of these factors in their e-Learning systems, which in turn is positively related to user satisfaction. The learning subjects and learning style did significantly moderate the influences of these perceived qualities on user satisfaction

Nb-doped TiO2 air-electrode for advanced Li-air batteries

As new substrate materials to replace a conventional carbon substrate, TiO2 and Nb-doped TiO2 air-electrodes for Li-air batteries were investigated. Through a simple two-step process, we successfully synthesized anatase Nb-doped TiO2 nanoparticles and demonstrated the potential applicability of TiO2-based materials for use in Li-air battery electrode. An air-electrode with Nb-doped TiO2 nanoparticles could deliver a higher discharge capacity than a bare TiO2 electrode due to the enhanced conductivity, which implies the importance of facile electron transport during the discharge process. © 2014 The Ceramic Society of Japan and the Korean Ceramic Society.

The role of income and frequency of dental visits in the relationship between dental sealant use and resin fillings after extended coverage: a retrospective cohort study

Background Prevention and treatment services use is closely associated with socioeconomic factors, such as income. This study aimed to investigate the relationship between implementing the sealant program and resin fillings restoration and to explore the role of income and frequency of dental visits in this relationship. Methods This retrospective cohort study used the cohort database from the National Health Information Database of the National Health Insurance Service. The study population comprised 494,731 children born in 2007. A logistic regression model for the experience of resin fillings and a linear regression model for weighted utilization of them were used to identify the independent effects of dental sealants, income, and frequency of dental visits. All analyses were conducted using the SAS Enterprise Guide version 7.1 (SAS Institute Inc., Cary, NC, USA). Results The ratio based on income level was almost proportional in all groups except the medical aid group, which had a rate as high as that of the wealthier group. Children without sealants were 1.05 times more likely to have resin fillings than others after adjusting for income level and frequency of visiting dental clinics in the final model. However, an opposite relationship between sealant experiences and resin fillings was observed in the previous model without dental visits. The gap in the weighted resin filling scores according to socioeconomic variables showed a similar tendency. Conclusions Income and frequency of dental visits might be confounding factors for the relationship between dental sealant and resin fillings. It is necessary to consider the complex relationship between socioeconomic indicators and service use while studying oral health inequality.The study was financed by the National Health Insurance Service in the Republic of Korea, grant number 20210504DCF-0

Performance Analysis of Free-Space Information Sharing in Full-Duplex Semantic Communications

In next-generation Internet services, such as Metaverse, the mixed reality (MR) technique plays a vital role. Yet the limited computing capacity of the user-side MR headset-mounted device (HMD) prevents its further application, especially in scenarios that require a lot of computation. One way out of this dilemma is to design an efficient information sharing scheme among users to replace the heavy and repetitive computation. In this paper, we propose a free-space information sharing mechanism based on full-duplex device-to-device (D2D) semantic communications. Specifically, the view images of MR users in the same real-world scenario may be analogous. Therefore, when one user (i.e., a device) completes some computation tasks, the user can send his own calculation results and the semantic features extracted from the user's own view image to nearby users (i.e., other devices). On this basis, other users can use the received semantic features to obtain the spatial matching of the computational results under their own view images without repeating the computation. Using generalized small-scale fading models, we analyze the key performance indicators of full-duplex D2D communications, including channel capacity and bit error probability, which directly affect the transmission of semantic information. Finally, the numerical analysis experiment proves the effectiveness of our proposed methods