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BACKGROUND The emergency department (ED) triage system to classify and prioritize patients from high risk to less urgent continues to be a challenge. OBJECTIVE This study, comprising 80,433 patients, aims to develop a machine learning algorithm prediction model of critical care outcomes for adult patients using information collected during ED triage and compare the performance with that of the baseline model using the Korean Triage and Acuity Scale (KTAS). METHODS To predict the need for critical care, we used 13 predictors from triage information: age, gender, mode of ED arrival, the time interval between onset and ED arrival, reason of ED visit, chief complaints, systolic blood pressure, diastolic blood pressure, pulse rate, respiratory rate, body temperature, oxygen saturation, and level of consciousness. The baseline model with KTAS was developed using logistic regression, and the machine learning model with 13 variables was generated using extreme gradient boosting (XGB) and deep neural network (DNN) algorithms. The discrimination was measured by the area under the receiver operating characteristic (AUROC) curve. The ability of calibration with Hosmer–Lemeshow test and reclassification with net reclassification index were evaluated. The calibration plot and partial dependence plot were used in the analysis. RESULTS The AUROC of the model with the full set of variables (0.833-0.861) was better than that of the baseline model (0.796). The XGB model of AUROC 0.861 (95% CI 0.848-0.874) showed a higher discriminative performance than the DNN model of 0.833 (95% CI 0.819-0.848). The XGB and DNN models proved better reclassification than the baseline model with a positive net reclassification index. The XGB models were well-calibrated (Hosmer-Lemeshow test; P>.05); however, the DNN showed poor calibration power (Hosmer-Lemeshow test; P CONCLUSIONS Our study demonstrated that the performance of the XGB model using initial information at ED triage for predicting patients in need of critical care outperformed the conventional model with KTAS.

Whole-genome sequencing (WGS) of human tumors and normal cells exposed to various carcinogens has revealed distinct mutational patterns that provide deep insights into the DNA damage and repair processes. Although ionizing radiation (IR) is conventionally known as a strong carcinogen, its genome-wide mutational impacts have not been comprehensively investigated at the single-nucleotide level. Here, we explored the mutational landscape of normal single-cells after exposure to the various levels of IR. On average, 1 Gy of IR exposure generated ∼16 mutational events with a spectrum consisting of predominantly small nucleotide deletions and a few characteristic structural variations. In ∼30% of the post-irradiated cells, complex genomic rearrangements, such aschromoplexy, chromothripsis, and breakage-fusion-bridge cycles, were resulted, indicating the stochastic and chaotic nature of DNA repair in the presence of the massive number of concurrent DNA double-strand breaks. These mutational signatures were confirmed in the genomes of 22 IR-induced secondary malignancies. With high-resolution genomic snapshots of irradiated cells, our findings provide deep insights into how IR-induced DNA damage and subsequent repair processes operate in mammalian cells.

BACKGROUND Predicting the complications of diabetes mellitus from an early stage would be beneficial for its management. Topic modeling is a posterior procedure to estimate semantic objects in a dataset through a statistical approach. The topic model can play the role of a feature set for supervised classification. OBJECTIVE : We performed a study to predict diabetic retinopathy (DMR), diabetic nephropathy (DMN), and non-alcoholic fatty liver disease (NAFLD) from clinical notes using semi-supervised classification based on topic modeling. METHODS : We applied four types of machine learning algorithms for classification: random forest (RF), gradient boosting machine (GBM), support vector machine (SVM), and fully connected artificial neural network (ANN) We reviewed the topic models through statistical analysis to determine whether these topic models are clinically plausible. RESULTS F1 scores were above 0.8 when predicting all kinds of target diseases with all types of classification methods, and above 0.9 using RF or GBM. Hypertension and dyslipidemia seem to be statistically associated with DMR, DMN, and NAFLD. They may be important clues with which we can predict DMR, DMN, and NAFLD. CONCLUSIONS This study showed that complications of diabetes mellitus that are likely to occur later in life can be predicted from the clinical notes of outpatient departments. We believe that this kind of predictive model could be utilized by patients and physicians in outpatient departments as a useful tool, similar to clinical decision support systems.

BACKGROUND High-quality learning materials are needed for artificial intelligence (AI) development, but are not practically available; this situation is especially poor in the medical field. In particular, annotating medical images (e.g., annotation for tumor area by pathologists) is massive as well as expensive, and subject to privacy protection. These are major limitations for AI developers to approach and reproduce medical image data. OBJECTIVE This study aimed to reduce barriers for AI researchers to access medical image datasets by collating and sharing high-quality medical images with pathologists, and to find applicable ways to apply diagnostic AI assistance to reduce the pathologists’ workload. METHODS Pathology slides of tumors of five organs (liver, colon, prostate, pancreas and biliary tract, and kidney) from histologically confirmed cases were selected for this study. After scanning the slides to obtain whole slide digital images, the patient information was de-identified, and annotation for the tumor area was performed by the pathologist. Next, an AI-assisted annotation process was used in parallel to improve the annotation workload of pathologists and to draw complex lesion boundaries more accurately. This allowed all the data to include the annotations confirmed by experienced pathologists, and to be used as an AI learning dataset. RESULTS A web-based data-sharing platform for AI learning was built, and was unveiled in 2019. In total, 3,100 massive datasets of 5 organ carcinomas were shared through this platform, and were accessible to all researchers. The platform had the advantage that users could search data visually and intuitively; except for commercial purposes, all researchers made free use of the provided dataset for their research. Finally, the platform also provided five image data pre-processing algorithms that could help AI modeling learners. CONCLUSIONS We built and operated a web-based data-sharing platform for AI researchers providing a high-quality digital pathology dataset personally annotated by pathologists. We hope that our experience will help researchers who want to build such a platform in future, by sharing issues gained from collecting and sharing these valuable data.

SummaryTissue regeneration involves a multi-step process composed of diverse cellular hierarchies and states that are also implicated in tissue dysfunction and pathogenesis. Here, we leveraged single-cell RNA sequencing analysis in combination within vivolineage tracing and organoid models to fine-map trajectories of alveolar lineage cells during injury repair and regeneration. We identified Damage-Associated Transient Progenitors (DATPs) as a distinct AT2-lineaged population arising during alveolar regeneration. Specifically, we found that IL-1β, secreted by interstitial macrophages, primes a subset ofIl1r1+AT2 cells for conversion into DATPs, via aHif1a-mediated glycolysis pathway, that are functional mediators for mature AT1 cell differentiation. Importantly, we show that chronic inflammation mediated by IL-1β prevents differentiation into AT1 cells, leading to aberrant accumulation of DATPs and impaired alveolar differentiation. Our step-wise fine-mapping of cell fate transitions demonstrates how the inflammatory niche impedes alveolar regeneration by directing stem cell fate behavior.

In the wide-angle (WA) images embedded in an around-view monitor system, the subject(s) in the peripheral region is normally small and has little information. Furthermore, since the outer region suffers from the non-uniform blur phenomenon and artifact caused by the inherent optical characteristic of WA lenses, its visual quality tends to deteriorate. According to our experiments, conventional image enhancement techniques rarely improve the degraded visual quality of the outer region of WA images. In order to solve the above-mentioned problem, this paper proposes a joint sharpness enhancement (SE) and super-resolution (SR) algorithm which can improve the sharpness and resolution of WA images together. The proposed SE algorithm improves the sharpness of the deteriorated WA images by exploiting self-similarity. Also, the proposed SR algorithm generates super-resolved images by using high-resolution information which is classified according to the extended local binary pattern-based classifier and learned on a pattern basis. Experimental results show that the proposed scheme effectively improves the sharpness and resolution of the input deteriorated WA images. Even in terms of quantitative metrics such as just noticeable blur, structural similarity, and peak signal-to-noise ratio. Finally, the proposed scheme guarantees real-time processing such that it achieves 720p video at 29 Hz on a low cost GPU platform.

본 연구는 중학생들의 스포츠 관람에 대한 영향력과 중요성을 살펴보고자 진행되었다. 본 연구의 목적은 중학생들의 인구통계학적 특성(성별, 학년)과 스포츠 관람 특성(관람경험, 관람매체, 관람빈도, 관람시간)이 학생들의 학습몰입과 심리적 행복감에 미치는 영향을 알아보기 위한 것이다. 연구대상은 D광역시 소재 중학생 총 447명으로 하고, 자료수집은 설문지를 활용하였다. 수집된 자료는 SPSS 21.0 통계 프로그램을 활용하여 분석하였다. 구체적으로는 성별과 관람 유·무에 따른 학습몰입과 심리적 행복감의 차이는 독립표본 t검증을 실시하였고, 학년과 관람매체에 따른 차이는 일원변량분석(one-way ANOVA)을 사용하였다. 유의한 차이가 나타난 변인은 Duncan을 이용하여 사후분석을 실시하였다. 다음으로 관람빈도와 관람시간, 학습몰입, 심리적 행복감 간의 상관을 알아보기 위해 상관분석(correlation analysis)을 실시하였으며, 스포츠 관람 특성이 학습 몰입과 심리적 행복감에 미치는 영향을 알아보기 위해 다중회귀분석(multiple regression analysis)을 실시하였다. 연구결과 첫째, 성별 및 학년과 관람경험 유·무에 따라 학습몰입은 차이가 있는 것으로 나타났다. 둘째, 스포츠 관람경험이 있는 학생이 스포츠 관람경험이 없는 학생보다 심리적 행복감이 더 높은 것으로 나타났다. 셋째, 관람빈도는 학습몰입과 심리적 행복감에 유의한 상관이 나타나지 않았으며 관람시간은 학습몰입의 하위요인인 구체적 피드백과 심리적 행복감의 하위요인인 만족감과 행복감에 유의한 상관관계가 나타났다. 넷째, 스포츠 관람빈도와 시간은 학습몰입에 유의한 영향을 미치지 않는 것으로 나타났다. 다섯째, 스포츠 관람시간은 심리적 만족감과 심리적 행복감에 유의한 정적인 영향을 미치는 것으로 나타났다.

The present study has numerically investigated a dynamic methane leak and dispersion in a confined space. To establish a numerical prediction based engineering model of dynamic gas leak and dispersion in a confined space, numerical experiments are conducted for variation of a key parameter–leak hole size. Based on the numerical results data, an engineering model is developed. The parameters related to lower flammable limit of the methane were quantitatively analyzed to compare the potential risk due to a gas leak. To quantitatively investigate the flammable region, the longitudinal and transverse directional length is defined and studied. We found that the ratio between longitudinal and transverse directional length can be a bridge to model the flammable region. The aspect ratio of the flammable region is fitted by an exponential function to show the relation with time. Then, an oval-shape model is presented to predict flammable region. Oval-shape model is completed by the combination of aspect ratio relation and a function for transverse length. Finally, we compared the developed engineering model (oval-shape model) and numerical results. The engineering model can predict the flammable region quite well when it reaches steady state. It is expected that the established engineering model is valuable for the Quantitative risk assessment (QRA), initial emergency strategy preparation when a fuel gas leak accident happened in a Combined cycle power plant (CCPP). We hope it is also can be a kind of data base for power plant operation manual.

Interpretation of noncoding disease variants, which comprise the vast majority of Genome-wide association studies (GWAS) hits, remains a momentous challenge due to haplotype structure and our limited understanding of the mechanisms and physiological contexts of noncoding elements. GWAS have identified loci underlying human diseases, but assigning the causal nucleotide changes still remain a controversial issue. Here we addressed these issues through the combination of high-density genotyping and epigenomic data using a random forest model to discover the noncoding causal variants. Focusing on autoimmune diseases, we triaged putative causal variants for atopic dermatitis and inflammatory bowel diseases. Making a filtering pipeline, we found three interesting single nucleotide polymorphisms (rs1800630, rs1799964 and rs4796793) in the upstream site of TNF and STAT3 genes, two frequent genes shared in some autoimmune diseases, and show how those variants affect on TNF and STAT3 expression levels. All data and source codes related to this manuscript are available at https://github.com/jieunjung511/Autoimmune-research.

The application of appropriate rules for drug–drug interactions (DDIs) could substantially reduce the number of adverse drug events. However, current implementations of such rules in tertiary hospitals are problematic as physicians are receiving too many alerts, causing high override rates and alert fatigue. We investigated the potential impact of Korean national DDI rules in a drug utilization review program in terms of their severity coverage and the clinical efficiency of how physicians respond to them. Using lists of high-priority DDIs developed with the support of the U.S. government, we evaluated 706 contraindicated DDI pairs released in May 2015. We evaluated clinical log data from one tertiary hospital and prescription data from two other tertiary hospitals. The measured parameters were national DDI rule coverage for high-priority DDIs, alert override rate, and number of prescription pairs. The coverage rates of national DDI rules were 80% and 3.0% at the class and drug levels, respectively. The analysis of the system log data showed an overall override rate of 79.6%. Only 0.3% of all of the alerts (n = 66) were high-priority DDI rules. These showed a lower override rate of 51.5%, which was much lower than for the overall DDI rules. We also found 342 and 80 unmatched high-priority DDI pairs which were absent in national rules in inpatient orders from the other two hospitals. The national DDI rules are not complete in terms of their coverage of severe DDIs. They also lack clinical efficiency in tertiary settings, suggesting improved systematic approaches are needed., Graphical Abstract

We numerically investigated the influence of crack size on gas leakage characteristics in a confined space. The real scale model of underground Combined cycle power plant (CCPP) was taken for simulating gas leakage characteristics for different crack sizes such as 10 mm, 15 mm and 20 mm. The commercial code of Fluent (v.16.1) was used for three-dimensional simulation. In particular, a risk region showing such a probability of ignition was newly suggested with the concept of Lower flammable limit (LFL) of methane gas used in the present study to characterize the gas propagation and the damage area in space. From the results, the longitudinal and transverse leakage distances were estimated and analyzed for quantitative evaluation of risk area. The crack size was found to have a great impact on the longitudinal leakage distance, showing an increasing tendency with the crack size. In case of a crack size of 20 mm, the longitudinal leakage distance suddenly increased after 180 s, whereas it remained constant after 2 s in the other cases. This is because a confinement effect, which is caused by circulation flows in the whole space, increased the gas concentration near the gas flow released from the crack. The confinement effect is thus closely associated with the released mass flow rate changing with the crack size. This result would be useful in designing the gas detector system for preventing accidents in the confined space as like CCPP.

This paper presents a method of designing specific high-order dependency factor on the linear chain conditional random fields (CRFs) for named entity recognition (NER). Named entities tend to be separated from each other by multiple outside tokens in a text, and thus the first-order CRF, as well as the second-order CRF, may innately lose transition information between distant named entities. The proposed design uses outside label in NER as a transmission medium of precedent entity information on the CRF. Then, empirical results apparently demonstrate that it is possible to exploit long-distance label dependency in the original first-order linear chain CRF structure upon NER while reducing computational loss rather than in the second-order CRF., To appear in the 7th Named Entities Workshop (co-located with ACL 2018). 2018/07, Melbourne, Australia. (Short paper) 5 pages including 1 reference page, 1 figure

This paper presents a wide-frequencyrange, low-power transceiver with an automatic impedance-matching calibration for TV-white-space (TVWS) application. The wide-range automatic impedance matching calibration (AIMC) is proposed for the Drive Amplifier (DA) and LNA. The optimal S22 and S11 matching capacitances are selected in the DA and LNA, respectively. Also, the Single Pole Double Throw (SPDT) switch is integrated to share the antenna and matching network between the transmitter and receiver, thereby minimizing the systemic cost. An N-path filter is proposed to reject the large interferers in the TVWS frequency band. The current-driven mixer with a 25% duty LO generator is designed to achieve the high-gain and low-noise figures; also, the frequency synthesizer is designed to generate the wide-range LO signals, and it is used to implement the FSK modulation with a programmable loop bandwidth for multi-rate communication. The TVWS transceiver is implemented in 0.13 μm, 1-poly, 6-metal CMOS technology. The die area of the transceiver is 4 mm x 3 mm. The power consumption levels of the transmitter and receiver are 64.35 mW and 39.8 mW, respectively, when the output-power level of the transmitter is +10 dBm at a supply voltage of 3.3 V. The phase noise of the PLL output at Band 2 is -128.3 dBc/Hz with a 1 MHz offset.

This paper presents a wideband Current-Reused Voltage Controlled Oscillator (VCO) with 2-Step Automatic Amplitude Calibration (AAC). Tuning range of the proposed VCO is from 1.95 ㎓ to 3.15 ㎓. The mismatch of differential voltage is within 0.6 %. At 2.423 ㎓, the phase noise is -116.3 ㏈c/㎐ at the 1 ㎒ offset frequency with the current consumption of 2.6 ㎃. The VCO is implemented 0.13 ㎜ CMOS technology. The layout size is 720 × 580 ㎟.

In Korea, there were 224,000 new cases of cancer and 75,334 deaths caused by cancer in 2013, which was three times more than the number of death caused by heart disease, the second leading cause of death. This study proposes a biomarker positivity analysis system based on clinical data, for personalized diagnosis and therapy of cancer. Data of 78,912 cases were obtained from immunopathology and surgical pathology reports. Data on sex, age, organ, diagnosis, and biomarkers were entered into a database. To verify the reliability of the clinical data, an additional 50,450 cases from positivity-related research papers were added. The proposed biomarker positivity analysis system makes it possible to extract and combine information for searching. The positivity values are in graphical and tabular format for ease of use. With a link to the internal network of the hospital, real-time pathology reports are available. Twenty-five pathology specialists are chosen as subjects to further confirm the reliability of this system; primary assessment results demonstrate a satisfaction level of 4.7 out of 5 and a concordance rate of 79% with positive data under the same conditions as reported in the literature. In the present study, analysis methods and platforms using large volumes of clinical and literature data are developed for cancer prognoses. It is expected that these tools will benefit both healthcare professionals and non-professionals involved in cancer diagnosis and treatment.

To date, the demand for Combined Cycle Power Plant (CCPP) has been continuously increased to overcome the problemof air pollution and lack of energy. In particular, the underground CCPP is exposed to substantial fire and explosion risksinduced by gas leakage. The present study conducted numerical simulations to examine the fire behavior and gas leakagecharacteristics for a restricted region including gas turbine and other components used in a typical CCPP system. The com-mercial code of FLUENT V.14 was used for simulation. From the results, it was found that flammable limit distribution ofleakage gas affects fire behavior. Especially, the flame is propagated in an instant in restricted region with LNG gas. In addi-tion, consequence analysis factors such as critical temperature and radiation heat flux are introduced. These results would beuseful in making the safety guidelines for the underground CCPP. 1. 서론 복합발전플랜트는 LNG 연료를 이용하여 1차로 가스터빈을 구동하고, 가스터빈에서 나오는 배기가스 열을보일러에 통과시켜 2차로 증기터빈을 구동하는 방식이다. 따라서 열효율이 높고 공해가 적기 때문에 지속적으로 수요가 증가하고 있다. 이런 수요를 충족하기 위해현재 국내 최초로 지하 복합발전플랜트가 건설 중이다.하지만지하 공간의 특수성으로 인해 가스 누출에 의한화재 및 폭발과 같은 잠재적인 위험요소를 가지고 있다.이와 같은 화재, 폭발 사고가 발생하게 되면 막대한 인명·재산 피해를 입기 때문에 위험요소에 대한 정량적인 데이터를 기반으로 안전 시스템이 구축되어야 한다.따라서 현재 위험도 정량화 기법(Quantitative RiskAssessment, QRA)에 대한 연구가 활발히 진행 중에 있다. QRA는 시스템 정의, 위험성 정의, 사고 시나리오정의, 전산유체역학(Computational Fluid Dynamics, CFD)해석, 사고결과 정량화의 순서로 진행 되며, 각 시스템의 특성 및 위험 요인에 따라서 다양한 결과를 도출할수 (1)있다 . 최근에 수치해석을 활용한 피해를 예측하는연구가 활발히 진행 중에 (2)있다. 김기평 등은 LNG 수송선 내에서 가스 누출에 의한 피해를 예측하였고, vent-ing system과 같은 사고저감 방법을 제안하였다. Yet

Gas leakage and dispersion in the underground LNG power plant can lead to serious fire and explosion accident. In thisstudy, computational fluid dynamics simulation was applied to model the dynamic process of gas leakage and dispersion phe-nomena in a closed space. To analyze the risk assessment factor, such as the flammable volume ratio, transient simulationswere carried out for different scenarios. The simulation results visualized the gas distribution with time in the closed space.The flammable volume ratio was introduced for quantitative analysis the fire/explosion probability. 기호설명 : 파공에 의한 누출가스의 질량유량, kg/sC d : 파공형상에 의한 상수, 무차원A h : 파공의 단면적, m 2 P 0 : 파이프의 내부압력, Paγ : 정적비열에 대한 정압비열의 비율, 무차원W g : 가스의 분자량, kg/molR : 가스의 기체상수, kJ/kg·KT : 가스의 온도, KK : 누출속도에 의한 상수, 무차원η : 가연영역 체적분율, 무차원V FR : 가연영역의 부피, m 3 V Domain : 밀폐공간 전체의 부피, m 3 ρ : 유체의 밀도, kg/m 3 1. 서론 최근 에너지 고갈 문제와 환경 문제로 인하여 청정에너지 자원의 활용이 각광받고 있다. 이 중 천연 가스를액화한 액화천연가스(LNG)는 무독성이며 공해가 거의발생하지 않기 때문에 이를 이용한 설비가 크게 늘고있다. 그러나 LNG가스는 높은 압력으로 공급되기 때문에, LNG가스 연료를 이용하여 동작하는 설비에서 가스의 누출이 발생 시 화재나 폭발 등의 심각한 사고로 이어질 수 있다

Laboratory test names are used as basic information to diagnose diseases. However, this kind of medical information is usually written in a natural language. To find this information, lexicon based methods have been good solutions but they cannot find terms that do not have abbreviated expressions, such as "neuts" that means "neutrophils". To address this issue, similar word matching can be used; however, it can be disadvantageous because of significant false positives. Moreover, processing time is longer as the size of terms is bigger. Therefore, we suggest a novel q-gram based algorithm, named modified triangular area filtering, to find abbreviated laboratory test terms in clinical documents, minimizing the possibility to impair the lexicons' precision. In addition, we found the terms using the methodology with reasonable processing time. The results show that this method can achieve 92.54 precision, 87.72 recall, 90.06 f1-score in test sets when edit distance threshold(τ) = 3.

Background: Despite the advances in the diagnosis and treatment of heart failure (HF), the current hospital-oriented framework for HF management does not appear to be sufficient to maintain the stability of HF patients in the long term. The importance of self-care management is increasingly being emphasized as a promising long-term treatment strategy for patients with chronic HF. Objective: The objective of this study was to evaluate whether a new information communication technology (ICT)–based telehealth program with voice recognition technology could improve clinical or laboratory outcomes in HF patients. Methods: In this prospective single-arm pilot study, we recruited 31 consecutive patients with chronic HF who were referred to our institute. An ICT-based telehealth program with voice recognition technology was developed and used by patients with HF for 12 weeks. Patients were educated on the use of this program via mobile phone, landline, or the Internet for the purpose of improving communication and data collection. Using these systems, we collected comprehensive data elements related to the risk of HF self-care management such as weight, diet, exercise, medication adherence, overall symptom change, and home blood pressure. The study endpoints were the changes observed in urine sodium concentration (uNa), Minnesota Living with Heart Failure (MLHFQ) scores, 6-min walk test, and N-terminal prohormone of brain natriuretic peptide (NT-proBNP) as surrogate markers for appropriate HF management. Results: Among the 31 enrolled patients, 27 (87%) patients completed the study, and 10 (10/27, 37%) showed good adherence to ICT-based telehealth program with voice recognition technology, which was defined as the use of the program for 100 times or more during the study period. Nearly three-fourths of the patients had been hospitalized at least once because of HF before the enrollment (20/27, 74%); 14 patients had 1, 2 patients had 2, and 4 patients had 3 or more previous HF hospitalizations. In the total study population, there was no significant interval change in laboratory and functional outcome variables after 12 weeks of ICT-based telehealth program. In patients with good adherence to ICT-based telehealth program, there was a significant improvement in the mean uNa (103.1 to 78.1; P=.01) but not in those without (85.4 to 96.9; P=.49). Similarly, a marginal improvement in MLHFQ scores was only observed in patients with good adherence (27.5 to 21.4; P=.08) but not in their counterparts (19.0 to 19.7; P=.73). The mean 6-min walk distance and NT-proBNP were not significantly increased in patients regardless of their adherence. Conclusions: Short-term application of ICT-based telehealth program with voice recognition technology showed the potential to improve uNa values and MLHFQ scores in HF patients, suggesting that better control of sodium intake and greater quality of life can be achieved by this program. [JMIR Mhealth Uhealth 2017;5(10):e127]

The edges of the wide angle (WA) image generally have poor definition and resolution, which often causes deterioration of the around view monitor (AVM) image quality. This paper proposes a convolutional neural network (CNN)-based preprocessing and a multi-frame-based view transformation to solve this problem, and presents an AVM system based on these methods. First, we analyze the general distortion characteristics of the WA image, and propose a preprocessing using the CNN learning model based on the analysis result. Next, in the view transformation (VT) of the outer edge of the WA image, the inherent problem of low pixel density is solved through motion compensation and hole filling using adjacent frames. Experimental results show that the AVM images by the proposed methods are superior to general AVM images in terms of objective image quality as well as subjective image quality.

Dental panoramic radiographs (DPRs) provide information required to potentially evaluate bone density changes through a textural and morphological feature analysis on a mandible. This study aims to evaluate the discriminating performance of deep convolutional neural networks (CNNs), employed with various transfer learning strategies, on the classification of specific features of osteoporosis in DPRs. For objective labeling, we collected a dataset containing 680 images from different patients who underwent both skeletal bone mineral density and digital panoramic radiographic examinations at the Korea University Ansan Hospital between 2009 and 2018. Four study groups were used to evaluate the impact of various transfer learning strategies on deep CNN models as follows: a basic CNN model with three convolutional layers (CNN3), visual geometry group deep CNN model (VGG-16), transfer learning model from VGG-16 (VGG-16_TF), and fine-tuning with the transfer learning model (VGG-16_TF_FT). The best performing model achieved an overall area under the receiver operating characteristic of 0.858. In this study, transfer learning and fine-tuning improved the performance of a deep CNN for screening osteoporosis in DPR images. In addition, using the gradient-weighted class activation mapping technique, a visual interpretation of the best performing deep CNN model indicated that the model relied on image features in the lower left and right border of the mandibular. This result suggests that deep learning-based assessment of DPR images could be useful and reliable in the automated screening of osteoporosis patients.

This paper presents a Spread Spectrum Clock Generator (SSCG) based on Relaxation oscillator using Up/Down Counter. The current is controlled by a counter and the spread spectrum of the Relaxation Oscillator. A Relaxation Oscillator with temperature compensation using the BGR and ADC is presented. The current to determine the frequency of the Relaxation Oscillator can be controlled. The output frequency of the temperature can be compensated by adjusting the current according to the temperature using the code that is the output from the ADC and BGR. EMI Reduction of SSCG is 11 dB, and Spread down frequency is 150 kHz. The current consumption is 600 μA from 5V and the operating frequency is from 2.3 MHz to 5.75 MHz. The rate of change of the output frequency with temperature was approximately ±1 %. The SSCG is fabricated in a 0.35um CMOS process with active area 250um x 440um.

Color-plus-depth video format has been increasingly popular in 3-D video applications, such as auto-stereoscopic 3-D TV and freeview TV. The performance of these applications is heavily dependent on the quality of depth maps since intermediate views are synthesized using the corresponding depth maps. This paper presents a novel framework for obtaining high-quality multiview color-plus-depth video using a hybrid sensor, which consists of multiple color cameras and depth sensors. Given multiple high-resolution color images and low quality depth maps obtained from the color cameras and depth sensors, we improve the quality of the depth map corresponding to each color view by increasing its spatial resolution and enforcing interview coherence. Specifically, a new up-sampling method considering the interview coherence is proposed to enhance multiview depth maps. This approach can improve the performance of the existing up-sampling algorithms, such as joint bilateral up-sampling and weighted mode filtering, which have been developed to enhance a single-view depth map only. In addition, an adaptive approach of fusing multiple input low-resolution depth maps is proposed based on the reliability that considers camera geometry and depth validity. The proposed framework can be extended into the temporal domain for temporally consistent depth maps. Experimental results demonstrate that the proposed method provides better multiview depth quality than the conventional single-view-based methods. We also show that it provides comparable results, yet much more efficiently, to other fusion approaches that employ both depth sensors and stereo matching algorithm together. Moreover, it is shown that the proposed method significantly reduces bit rates required to compress the multiview color-plus-depth video.

The purpose of this study was to compare fracture resistances of K3 nickel-titanium files made from different thermal treatments. K3 (SybronEndo, Orange, CA), K3XF (SybronEndo), and experimentally heat treated K3 (K3H) were used. For the cyclic fatigue test, the samples were rotated with up-and-down motion in the artificial canal with the curvature of 60 degrees until the fracture occurred. The number of cycles to fracture (NCF) was measured. For the torsional fracture test, the samples were tightly bound and rotated until the fracture occurred. Elastic modulus (EM), ultimate torsional strength (UTS), and angle of rotation to fracture (ARF) were measured. The results were statistically analyzed by one-way ANOVA. The NCF of K3H was higher than those of K3 and K3XF (P<0.05). The EM of K3XF and K3H was lower than that of K3 (P<0.05). There was no significant difference in UTS. The ARF of K3XF was higher than that of K3 (P<0.05). K3XF and K3H showed more flexibility than K3. The maximum torsional angle of K3XF was higher than that of K3, but there was no significant difference on the UTS in all three groups.

The remarkable regenerative capacity of the lung suggests that stem cells could be of therapeutic importance in diverse lung diseases; however, the successful exploitation of lung stem cell biology has long been hampered by our inability to maintain and expand adult lung stem cells while retaining their multi-lineage potential $\textit{in vitro}$. Recently, advances in our understanding of stem cell niches and the role of key signalling modulators in controlling stem cell maintenance and differentiation have fuelled the development of new $\textit{in vitro}$ three-dimensional (3D) culture technologies that sustain the stem cell-driven formation of near-physiological, self-organizing structures called organoids. Here we review basic approaches to organoid model systems and highlight recent achievements in the generation of organoids from adult stem and progenitor cells of both the murine and human lungs. We evaluate current applications in studying cellular changes in proliferation, differentiation, plasticity, and cell polarity, and cellular and molecular crosstalk of epithelial cells with stroma. Advantages and limitations of organoids for clinical use are also discussed.

During the process of B cell development, transcription factors, such as E2A and Ebf1, have been known to play key roles. Although transcription factors and chromatin regulators work in concert to direct the expression of B lineage-specific genes, little is known about the involvement of regulators for chromatin structure during B lymphopoiesis. In this article, we show that deletion of Srg3/mBaf155, a scaffold subunit of the SWI/SNF-like BAF complex, in the hematopoietic lineage caused defects at both the common lymphoid progenitor stage and the transition from pre–pro-B to early pro-B cells due to failures in the expression of B lineage-specific genes, such as Ebf1 and Il7ra, and their downstream target genes. Moreover, mice that were deficient in the expression of Brg1, a subunit of the complex with ATPase activity, also showed defects in early B cell development. We also found that the expression of Ebf1 and Il7ra is directly regulated by the SWI/SNF-like BAF complex. Thus, our results suggest that the SWI/SNF-like BAF complex facilitates early B cell development by regulating the expression of B lineage-specific genes.

Since ubiquitous technology is an emerging paradigm in healthcare, we wanted to evaluate its feasibility in the healthcare area. As a first step, we evaluated the feasibility of the smart bed. In this study, a series of experiments were conducted to evaluate the smart bed.Smart bed is a continuous ballistocardiogram monitoring device developed by Seoul National University. Eleven healthy subjects participated in the study. Each subject slept in the smart bed for two nights. To measure meaningful sleep periods, noisy sections were removed from the original signal. The subject's heart activity was obtained by automatic peak detection, using the AF2 peak detection algorithm. In this study, the feasibility of the smart bed was evaluated in terms of the meaningful sleep periods and the accuracy of automatic peak detection.On an average, 92.8% of sleep duration was meaningful. The accuracy of peak detection algorithm was also evaluated. The algorithm proved to have an accuracy of 95%; thus, we observe that 95% of the peak detection results were correct in comparison with the manual results.Based on the experimental results, we conclude that the smart bed can be a useful device for long-term monitoring in ubiquitous healthcare environments.

OBJECTIVES Measurement of similarities between documents is typically influenced by the sparseness of the term-document matrix employed. Latent semantic indexing (LSI) may improve the results of this type of analysis. METHODS In this study, LSI was utilized in an attempt to reduce the term vector space of clinical documents and newspaper editorials. RESULTS After applying LSI, document similarities were revealed more clearly in clinical documents than editorials. Clinical documents which can be characterized with co-occurring medical terms, various expressions for the same concepts, abbreviations, and typographical errors showed increased improvement with regards to a correlation between co-occurring terms and document similarities. CONCLUSIONS Our results showed that LSI can be used effectively to measure similarities in clinical documents. In addition, correlation between the co-occurrence of terms and similarities realized in this study is an important positive feature associated with LSI.

Objectives Adoption of hospital information systems offers distinctive advantages in healthcare delivery. First, implementation of consolidated hospital information system in Seoul National University Hospital led to significant improvements in quality of healthcare and efficiency of hospital management. Methods The hospital information system in Seoul National University Hospital consists of component applications: clinical information systems, clinical research support systems, administrative information systems, management information systems, education support systems, and referral systems that operate to generate utmost performance when delivering healthcare services. Results Clinical information systems, which consist of such applications as electronic medical records, picture archiving and communication systems, primarily support clinical activities. Clinical research support system provides valuable resources supporting various aspects of clinical activities, ranging from management of clinical laboratory tests to establishing care-giving procedures. Conclusions Seoul National University Hospital strives to move its hospital information system to a whole new level, which enables customized healthcare service and fulfills individual requirements. The current information strategy is being formulated as an initial step of development, promoting the establishment of next-generation hospital information system.

Insulated methods of compact bus duct has been applied a way of coating Epoxy powder. The problem which is caused by degradation during operation is very important in severe environment. Therefore, this study compared and verified many kind of properties ; electrical breakdown by thermal and water aging, v-t characteristic, arc discharge, mechanical properties, bending test and cross cut. Sample D was stable before the to be about decrease in the breakdown test according to temperature change. In case of V-t and arc discharge, it had been kept up suitable characteristic. Also, in case of electrical and mechanical characteristic, both sample D and A have excellent capacity.

This paper introduces experimental investigates of an electrical accident of the distributing cable termination with simulated a shoddy construction. We prepared two termination kites, one is built-in type, the other is heat contraction type. Also, we manufactured cable termination that have simulated defect by badness construction and investigated their insulation characteristics such as ac (35[kV], 1[min]) and impulse (95[kV], ) withstand test. The influence of defects such as thickness decrease, the gap between stress-con of housing and semiconductor and heating time on insulating properties of the termination have been studied. The thickness decrease of an insulator decreases ac breakdown strength suddenly and the breakdown traces of the insulator that is damaged by knife displayed elliptic shape. The gap of between stress-con and semiconductor deteriorates dielectric strength of insulator seriously. In heat contraction type, the ac breakdown voltage became low when the heating time is short.

MicroRNAs (miRNAs) have emerged as important regulators of the immune system. However, despite this prominence, our understanding of the function of miRNAs in the early hematopoietic stages is incomplete. In this study, we found that miR-139-5p negatively regulated the proliferation of hematopoietic stem cells and progenitor cells and that downregulation of miR-139-5p expression was associated with hematopoietic malignancy, such as chronic myeloid leukemia (CML). Knockdown of miR-139-5p resulted in myeloid-biased differentiation with expansion of myeloid progenitor cells. In contrast, miR-139-5p expression inhibited the proliferation of hematopoietic progenitors and resulted in the remission of a CML-like disease that is induced by breakpoint cluster region-Abelson (BCR-ABL) transformation. We also found that Brg1 is a functional target of miR-139-5p and that Brg1 is involved in BCR-ABL-induced leukemogenesis. Thus, our results identify miR-139-5p as a key regulator of cellular proliferation during early hematopoiesis and suggest that it is a potent antileukemic molecule.

Clinical narrative text includes information related to a patient’s medical history such as chronological progression of medical problems and clinical treatments. A chronological view of a patient’s history makes clinical audits easier and improves quality of care. In this paper, we propose a clinical Problem-Action relation extraction method, based on clinical semantic units and event causality patterns, to present a chronological view of a patient’s problem and a doctor’s action. Based on our observation that a clinical text describes a patient's medical problems and a doctor's treatments in chronological order, a clinical semantic unit is defined as a problem and/or an action relation. Since a clinical event is a basic unit of the problem and action relation, events are extracted from narrative texts, based on the external knowledge resources context features of the conditional random fields. A clinical semantic unit is extracted from each sentence based on time expressions and context structures of events. Then, a clinical semantic unit is classified into a problem and/or action relation based on the event causality patterns of the support vector machines. Experimental results on Korean discharge summaries show 78.8% performance in the F1-measure. This result shows that the proposed method is effectively classifies clinical Problem-Action relations.

Patient clinical data are distributed and often fragmented in heterogeneous systems, and therefore the need for information integration is a key to reliable patient care. Once the patient data are orderly integrated and readily available, the problems in accessing the distributed patient clinical data, the well-known difficulties of adopting a mobile health information system, are resolved. This paper proposes a mobile clinical information system (MobileMed), which integrates the distributed and fragmented patient data across heterogeneous sources and makes them accessible through mobile devices. The system consists of four main components: a smart interface, an HL7 message server (HMS), a central clinical database (CCDB), and a web server. The smart interface and the HMS work in concert to generate HL7 messages from the existing legacy systems, which essentially send the patient data in HL7 messages to the CCDB to be stored and maintained. The CCDB and the web server enable the physicians to access the integrated up-to-date patient data. By proposing the smart interface approach, we provide a means for effortless implementation and deployment of such systems. Through a performance study, we show that the HMS is reliable yet fast enough to be able to support efficient clinical data communication.

One notable phenotypic change during the differentiation of immature thymocytes into either mature CD4 or CD8 single-positive lineages is the acquisition of a resistance to glucocorticoid (GC)-induced apoptosis. We have previously reported that SRG3 is critical in determining the sensitivity for the GC-induced apoptosis in developing thymocytes. We report here that Notch signaling downregulates the transcriptional activation of SRG3 through N-box and/or E-box elements on its promoter. RBP-J represses SRG3 transcription through the N-box motif. On the other hand, Deltex1 competitively inhibits the binding of p300 to E2A/HEB protein bound to the E-box elements and represses the SRG3 promoter activity. Moreover, enforced expression of Deltex1 restored double-positive (DP) thymocyte survival from the GC-induced apoptosis. Our results suggest that Notch signaling confers differentiating DP thymocytes resistance to GCs by regulating the SRG3 expression through Deltex1, and that Deltex1 and SRG3 may play a significant role during DP thymocyte maturation.

To North Korea's big disappointment, President Bush was re-elected and started his second term on January 20, 2005. On February 10, a few weeks after President Bush's second inauguration, North Korea said it would not attend 6-Party talks aimed at ending its nuclear weapons program unless the United States dropped its “hostile” policy toward the North. Pyongyang also confirmed that it has manufactured an undisclosed number of nuclear weapons to counter this U.S. policy. Considering the conflicting interests between the United States and North Korea, it will be difficult to anticipate how the North Korean nuclear crisis will be resolved. However, the relations between the United States and North Korea seem to remain in a state of tense stagnation rather than falling into a catastrophic phase. North Korea does not expect any concessions from the United States in the 6-Party talks, which only serve as a means of putting pressure on North Korea. North Korea seems convinced that a military option is not likely. North Korea may want to close the door on the United States and concentrate on the stability of its internal affairs. In the meantime, it wants to strengthen its position by extracting more plutonium. The stagnation may continue until the U.S. has enough power to keep the North from continuing to develop its nuclear program, or North Korea has enough leverage to force the United States to make substantial concession to North Korea.