본 연구에서는 자기공명 탄성도 검사에 병렬 영상 기법(Philips사의 SENSE)을 적용하여 호흡 정지 시간을 단축시키고, 진단적으로 유용한 영상을 획득하는데 적용 가능한 SENSE 인자의 범위를 알아보고자 하였다. 팬텀 실험과 자원자 실험을 진행하였고, 각 실험은 SENSE 인자를 증가시켜가며 촬영하였다. 영상 평가는 경직도 95% 신뢰도 지도(stiffness 95% confidence map)에서 경직도 수치를 측정하고, 파동 영상은 영상의학과 전문의 1명과 방사선사 4명이 블라인드 테스트 하였다. 통계학적 분석은 비모수 통계인 크러스칼-왈리스 검정을 이용하였고, 사후 분석은 본페로니 교정을 이용하였다. 연구 결과 경직도 수치는 SENSE 인자 2부터 3.5까지 통계적으로 유의미한 차이를 보이지 않았고, 파동 영상의 평가 결과 2부터 3.5까지 4점 이상의 높은 점수를 유지하였으며, 사후 분석 결과에서도 큰 차이를 보이지 않았다. 반면에, 호흡 정지 시간은 20.9초에서 12.1초로 약 8.8초 감소했다. 따라서 호흡 정지 시간이 짧은 환자 검사 시 SENSE 인자를 적절히 증가시켜 검사의 성공률을 높이고, 더불어 진단적 가치가 있는 영상을 획득할 수 있을 것으로 사료된다.

Since the outbreak of coronavirus disease 2019 (COVID-2019), the infection has spread worldwide due to the highly contagious nature of severe acute syndrome coronavirus (SARS-CoV-2). To manage SARS-CoV-2, the development of diagnostic assays that can quickly and accurately identify the disease in patients is necessary. Currently, nucleic acid-based testing and serology-based testing are two widely used approaches. Of these, nucleic acid-based testing with quantitative reverse transcription-PCR (RT-qPCR) using nasopharyngeal (NP) and/or oropharyngeal (OP) swabs is considered to be the gold standard. Recently, the use of saliva samples has been considered as an alternative method of sample collection. Compared to the NP and OP swab methods, saliva specimens have several advantages. Saliva specimens are easier to collect. Self-collection of saliva specimens can reduce the risk of infection to healthcare providers and reduce sample collection time and cost. Until recently, the sensitivity and accuracy of the data obtained using saliva specimens for SARS-CoV-2 detection was controversial. However, recent clinical research has found that sensitive and reliable data can be obtained from saliva specimens using RT-qPCR, with approximately 81% to 95% correspondence with the data obtained from NP and OP swabs. These data suggest that self-collected saliva is an alternative option for the diagnosis of COVID-19.

One of the most demanded competencies of an oral health professional such as an oral pathologist is the ability to make clinical decisions. The purpose of this study was to examine the neurological differences between beginners and experts in the clinical decision-making process which consisting of complex, dynamic and sophisticated cognitive processes, and to identify the characteristics of experts based on the brain by comparing EEG activity. This study conducted experimental design with 10 dentists with more than 10 years of clinical experience and 10 students with short clinical experience as beginners as a fourth year student before graduation. The hypothesis-oriented algorithm proposed in HOAC II was used. As a standard, the clinical decision-making stage of the dentist was divided into three stages, and an event was developed and an experiment was designed for measuring EEG for each stage. The cerebral activity distribution patterns of the two groups were measured with EEG, compared and analyzed with pre-processing process using EEGlab. As a result, the difference in the auditory information was not noticeable between the novice and the expert, but the difference between the group of the novice and the expert appeared in the visual data and the radiographic data. In the case of beginners, the activity was higher in the left hemisphere, and in the case of experts, both brains were activated. The results of this study are intended to present objective information based on brain-based analysis of differences that appear in the clinical decision-making process of experts and beginners. It can be used as basic research data to present the brain-based characteristic analysis of dentist experts.

EUS는 탐촉자를 위나 십이지장에 위치시킬 수 있어 췌장에서 가장 가까운 곳에서 췌장을 관찰할 수 있으므로 매우 작은 췌장종괴도 인지할 수 있다. 또한 종괴 자체에 대한 감별이 어려울 경우 EUS를 통한 조직 검사는 합병증을 최소화하면서 조직학적 확진율을 높일 수 있다. CE-EUS는 종괴의 특성을 파악하기 어려울 때 도움이 된다. 진단뿐만 아니라 치료에서도 EUS를 활용하고 있는데, 에탄올을 이용한 화학적 소작술 또는 RFA 수술 혹은 경과 관찰이라는 이분법적 치료 방식의 간극을 메워주는 비수술적 치료 방법으로 새롭게 시도되고 있다. PNET의 진단 및 치료에 EUS는 다양하게 활용되고 있으며, 향후 지속적인 발전이 기대된다.

The Korea Astronomy and Space Science Institute (KASI) has been developing a next-generation coronagraph (NGC) in cooperation with NASA to measure the coronal electron density, temperature, and speed simultaneously, using four different optical filters around 400 nm. KASI organized an expedition to demonstrate the coronagraph measurement scheme and the instrumental technology during the 2017 total solar eclipse (TSE) across the USA. The observation site was in Jackson Hole, Wyoming, USA. We built an eclipse observation system, the Diagnostic Coronal Experiment (DICE), composed of two identical telescopes to improve the signal-to-noise ratio. The observation was conducted at four wavelengths and three linear polarization directions in the limited total eclipse time of about 140 seconds. We successfully obtained polarization data for the corona but we were not able to obtain information on the coronal electron temperature and speed due to the low signal-to-noise ratio of the optical system and strong emission from prominences located at the western limb. In this study, we report the development of DICE and the observation results from the eclipse expedition. TSE observation and analysis with our self-developed instrument showed that a coronagraph needs to be designed carefully to achieve its scientific purpose. We gained valuable experience for future follow-up NASA-KASI joint missions: the Balloon-borne Investigation of the Temperature and Speed of Electrons in the Corona (BITSE) and the COronal Diagnostic EXperiment (CODEX).

This study is to develop a diagnostic model for the effective introduction of smart factories in the manufacturing industry, to diagnose SMEs that have difficulties in building their own smart factory compared to large enterprise, to identify the current level and to present directions for implementation. IT, AT, and OT experts diagnosed 18 SMEs using the "Smart Factory Capacity Diagnosis Tool" developed for smart factory level assessment of companies. They analyzed the results and assessed the level by smart factory diagnosis categories. Companies' smart factory diagnostic mean score is 322 out of 1000 points, between 1 level (check) and 2 level (monitoring). According to diagnosis category, Factory Field Basic, R&D, Production/Logistics/Quality Control, Supply Chain Management and Reference Information Standardization are high but Strategy, Facility Automation, Equipment Control, Data/Information System and Effect Analysis are low. There was little difference in smart factory level depending on whether IT system was built or not. Also, Companies with large sales amount were not necessarily advantageous to smart factories. This study will help SMEs who are interested in smart factory. In order to build smart factory, it is necessary to analyze the market trends, SW/ICT and establish a smart factory strategy suitable for the company considering the characteristics of industry and business environment.

The hand held voltammetry systems searched diabetic assay using glucose sensor of fluorine nafion doped carbon nanotube electrode (FCNE). An inexpensive graphite carbon pencil was used as an Ag/AgCl reference and Pt counter electrode. Upon combining and using three electrode systems, optimum square wave (SW) stripping results were attained to 1.0-9.0 ug/L with 8 points. Statistic RSD precision was of 6.02 % with n=15 in 0.1 mg/L glucose. After a total of 200 second accumulation times, analytical detection limit of 0.8 ug/L was obtained. This developed technique was applied to urine samples from diabetic patients urine for fluid analysis, it was determined that the sensor can be used with a diagnostics in the ex vivo of live cells and non treated biological fluid.