Purpose: This study aims to measure the mandibular movement using JT-3D system and provide a range of mandibular movement that can serve as a good reference for diagnosing the temporomandibular disorder. Materials and Methods: This study was conducted in 60 young male and female adults. The maximum opening and closing movement was recorded using JT-3D system, and by regarding 5 times of repetitive movement as 1 cycle of movement, total 3 cycles of movement were recorded. During the maximum opening, vertical position of lower jaw, antero-posterior position, lateral deflection position, and maximum opening distance were recorded. To evaluate the reproducibility of JT-3D system, statistical analysis were conducted (α = 0.05). Results: During the maximum opening, the average value appeared at 31.56 mm vertically and 24.42 mm rearwardly, lateral deflection position 0.72 mm, and maximum opening distance 40.32 mm. There was no statistical significance in all measured values for three cycles of movement recorded with JT-3D system (P > 0.05). Conclusion During the maximum opening, the average value appeared at 0.72 mm in lateral deflection position and the maximum opening distance at 40.32 mm, and the analysis on the maximum opening of lower jaw using JT-3D system showed sufficiently reproducible results.

Background: and Purpose Alterations in human brain functional networks with maturation have been explored extensively in numerous electroencephalography (EEG) and functional magnetic resonance imaging studies. It is known that the age-related changes in the functional networks occurring prior to adulthood deviate from ordinary trajectories of networkbased brain maturation across the adult lifespan. Methods: This study investigated the longitudinal evolution of resting-state EEG-based functional networks from early childhood to adolescence among 212 pediatric patients (age 12.2± 3.5 years, range 4.4–17.9) in 6 frequency bands using 8 types of functional connectivity measures in the amplitude, frequency, and phase domains. Results: Electrophysiological aspects of network-based pediatric brain maturation were characterized by increases in both functional segregation and integration up to middle adolescence. EEG oscillations in the upper alpha band reflected the age-related increases in mean node strengths and mean clustering coefficients and a decrease in the characteristic path lengths better than did those in the other frequency bands, especially for the phase-domain functional connectivity. The frequency-band-specific age-related changes in the global network metrics were influenced more by volume-conduction effects than by the domain specificity of the functional connectivity measures. Conclusions We believe that this is the first study to reveal EEG-based functional network properties during preadult brain maturation based on various functional connectivity measures. The findings potentially have clinical applications in the diagnosis and treatment of age-related brain disorders.

This paper describes a community effort to improve earlier versions of the full-text corpus of Genomics & Informatics by semi-automatically detecting and correcting PDF-to-text conversion errors and optical character recognition errors during the first hackathon of Genomics & Informatics Annotation Hackathon (GIAH) event. Extracting text from multi-column biomedical documents such as Genomics & Informatics is known to be notoriously difficult. The hackathon was piloted as part of a coding competition of the ELTEC College of Engineering at Ewha Womans University in order to enable researchers and students to create or annotate their own versions of the Genomics & Informatics corpus, to gain and create knowledge about corpus linguistics, and simultaneously to acquire tangible and transferable skills. The proposed projects during the hackathon harness an internal database containing different versions of the corpus and annotations.

This paper describes a community effort to improve earlier versions of the full-text corpus of Genomics & Informatics by semi-automatically detecting and correcting PDF-to-text conversion errors and optical character recognition errors during the first hackathon of Genomics & Informatics Annotation Hackathon (GIAH) event. Extracting text from multi-column biomedical documents such as Genomics & Informatics is known to be notoriously difficult. The hackathon was piloted as part of a coding competition of the ELTEC College of Engineering at Ewha Womans University in order to enable researchers and students to create or annotate their own versions of the Genomics & Informatics corpus, to gain and create knowledge about corpus linguistics, and simultaneously to acquire tangible and transferable skills. The proposed projects during the hackathon harness an internal database containing different versions of the corpus and annotations.