• Tuberculosis and Respiratory Diseases
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• v.85 no.1
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• pp.74-79
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• 2022

Background: The effect of underlying chronic obstructive pulmonary disease (COPD) on coronavirus disease 2019 (COVID-19) during a pandemic is controversial. The purpose of this study was to examine the prognosis of COVID-19 according to the underlying COPD. Methods: COVID-19 patients were assessed using nationwide health insurance data. Comorbidities were evaluated using the modified Charlson Comorbidity Index (mCCI) which excluded COPD from conventional CCI scores. Baseline characteristics were assessed. Univariable and multiple logistic and linear regression analyses were performed to determine effects of variables on clinical outcomes. Ages, sex, mCCI, socioeconomic status, and underlying COPD were selected as variables. Results: COPD patients showed older age (71.3±11.6 years vs. 47.7±19.1 years, p<0.001), higher mCCI (2.6±1.9 vs. 0.8±1.3, p<0.001), and higher mortality (22.9% vs. 3.2%, p<0.001) than non-COPD patients. The intensive care unit admission rate and hospital length of stay were not significantly different between the two groups. All variables were associated with mortality in univariate analysis. However, underlying COPD was not associated with mortality unlike other variables in the adjusted analysis. Older age (odds ratio [OR], 1.12; 95% confidence interval [CI], 1.11-1.14; p<0.001), male sex (OR, 2.29; 95% CI, 1.67-3.12; p<0.001), higher mCCI (OR, 1.30; 95% CI, 1.20-1.41; p<0.001), and medical aid insurance (OR, 1.55; 95% CI, 1.03-2.32; p=0.035) were associated with mortality. Conclusion: Underlying COPD is not associated with a poor prognosis of COVID-19.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.6
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• pp.35-50
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• 2022

As the water shortage has become a noticeable issue due to climate change, forests play an importance role as the provider of water supply service. There is, however, little information about the relationships between the factors used in the estimation of water supply service and coarse pore fraction of forest soil which determines the potential of water supply. To find out whether there would be an amelioration in the scoring system of water supply service estimation, we examined all factors except meteorological one and additionally, analyzed 4 extra factors that might be related with coarse pore fraction of soil. A total of 2,214 soil samples were collected throughout South Korea to measure coarse pore fractions from 2015 to 2020. First, the result of average coarse pore fraction of all samples showed 32.98±6.59% which was consistent with previous studies. And the results of non-parametric analysis of variance indicated that only two of eleven factors that was used in the scoring system matched the results of coarse pore fraction of forest soils. Tree canopy coverage showed no difference among categories, and slope also showed no significance at level of 0.05 in the linear regression analysis. Additionally, the applicability of 4 extra factors were confirmed, as the result of coarse pore fractions of soil samples were different for various categories of each factor. Therefore, the scoring system of water supply service of forest should be revised to improve accuracy.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.170-170
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• 2022

Grain filling traits of rice were traced to determine the critical temperature that ceased grain filling process, from the late transplanted temperate rice varieties in the field conditions of2020 and 2021. The tested three varieties were transplanted six times with four target heading dates of 20 Aug. (control), 10 Sep., 20 Sep. and 30 Sep. Nine times of sampling were made from a week after heading with three replicates for each treatment. Development of grain filling percentage, grain dry weight and milled rice weight demonstrated sigmoid curves in the first and second transplants of 2020, and in the first to third transplants of 2021. The three grain filling traits in the 2020 third transplants and in the 2021 fourth transplants initially increased with the progress of grain development, and reached the peaks at certain time points, then decreased thereafter. Non-linear regression analyses, performed for the traits in the transplants that showed sigmoid curves except control, indicated that 95% of the final data (95% FD) was attained when the seven-day moving temperature (Sd-MovT) was 8.4-9.6℃, which excluded the cases when the temperature before the dates of 95% FD was lower than that on the dates of 95% FD. Sd-MovT on the date of peak data was 8.5-9.8℃ in the 2020 third transplants and 6.9-8.3℃ in the 2021 fourth transplants. Grain development was observed when seven-day mean temperature (Sd-MT) from 35 to 41 days after heading date was 9.4-10.8℃ in the 2020 third transplants and 10.1-11.9℃ in the 2021 fourth transplants. But Sd-MT of 8.7-9.1℃ in 2020 and 6.9-7.6℃ in 2021, at 42-48 days after heading, resulted in no progress of grain development. Overall, Sd-MovT at the point of stagnated grain development appeared in the range of 6.9-9.8℃. The lowest Sd-MT that showed the progress of grain development was 9.4-9.5℃ and the highest Sd-MT that showed no grain development was 9.1℃, both of which appeared in Odae and Haiami of the 2020 third transplants Therefore it is concluded that critical temperature for the grain development of temperate rice in natural conditions exists between 9.1℃ and 9.5℃.

• Korean Journal of Radiology
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• v.22 no.3
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• pp.464-475
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• 2021

Objective: This study aimed to evaluate the tumor doubling time of invasive lung adenocarcinoma according to the International Association of the Study for Lung Cancer (IASLC)/American Thoracic Society (ATS)/European Respiratory Society (ERS) histologic classification. Materials and Methods: Among the 2905 patients with surgically resected lung adenocarcinoma, we retrospectively included 172 patients (mean age, 65.6 ± 9.0 years) who had paired thin-section non-contrast chest computed tomography (CT) scans at least 84 days apart with the same CT parameters, along with 10 patients with squamous cell carcinoma (mean age, 70.9 ± 7.4 years) for comparison. Three-dimensional semiautomatic segmentation of nodules was performed to calculate the volume doubling time (VDT), mass doubling time (MDT), and specific growth rate (SGR) of volume and mass. Multivariate linear regression, one-way analysis of variance, and receiver operating characteristic curve analyses were performed. Results: The median VDT and MDT of lung cancers were as follows: acinar, 603.2 and 639.5 days; lepidic, 1140.6 and 970.1 days; solid/micropapillary, 232.7 and 221.8 days; papillary, 599.0 and 624.3 days; invasive mucinous, 440.7 and 438.2 days; and squamous cell carcinoma, 149.1 and 146.1 days, respectively. The adjusted SGR of volume and mass of the solid-/micropapillary-predominant subtypes were significantly shorter than those of the acinar-, lepidic-, and papillary-predominant subtypes. The histologic subtype was independently associated with tumor doubling time. A VDT of 465.2 days and an MDT of 437.5 days yielded areas under the curve of 0.791 and 0.795, respectively, for distinguishing solid-/micropapillary-predominant subtypes from other subtypes of lung adenocarcinoma. Conclusion: The tumor doubling time of invasive lung adenocarcinoma differed according to the IASCL/ATS/ERS histologic classification.

• Journal of Korean Dental Hygiene Science
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• v.2 no.2
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• pp.31-39
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• 2019

Background: The purpose of this study was to investigate the effect of self-perception of halitosis on oral health behaviors of college students according to whether they worked in a non-service or service-related job. Methods: A self-reporting questionnaire of 150 university students working in service jobs and 150 university students working in non-service jobs in the metropolitan area was conducted from 26th April to 5th May 2018. The survey tool consisted of 3 general topic areas. There were 5 questions on oral health awareness behavior, 3 questions related to their self-perception of halitosis, and 8 questions on their oral health care practice. All were measured on the Likert 5-point scale. The frequency of their oral health behaviors and their self-perception of halitosis were analyzed according to the subjects' occupation. Pearson's correlation analysis and a linear regression analysis were conducted to confirm the influence of the two. The significance level for the statistical significance test was set to α = 0.05 (two-tailed). Results: In both the service and non-service groups, a coated tongue and food debris were found to influence halitosis(x²=10.95, p=0.027). According to the t-test, taking into account the self-perception of halitosis and oral health behaviors, both were higher in those that had a service job. Self-perception of halitosis and oral health behaviors were found to have a negative correlation(γ=-0.11, p<0.05). As the self-perception of halitosis increased, oral health care practices also increased(Beta=-0.185, p=0.020). Conclusions: Systematic interventions such as oral health programs and health promotion are needed to improve the oral health of service workers.

• The korean journal of orthodontics
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• v.41 no.2
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• pp.87-97
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• 2011

Objective: Facial asymmetry is usually evaluated from the difference in length and angulation of the maxilla and mandible. However, asymmetric position or shape of the condyle can also affect the expression of asymmetry. The purpose of this study was to evaluate the correlation between condylar asymmetry and chin point deviation in facial asymmetry. Methods: Cone-beam CT images of fifty adult skeletal Class III patients were studied. Thirty patients who had more than 4 mm menton deviation were categorized in the asymmetric group. Twenty patients with less than 4 mm menton deviation were assigned to the symmetric group. Anteroposterior and transverse condyle positions were evaluated from the cranial base. The greatest mediolateral diameter (GMD) of the condyle in the axial plane and angulation to the coronal plane were measured. The height and volume of the condyles were evaluated. Results: The symmetric group had no statistical difference between both condyles in position, angulation, GMD, height and volume. In the asymmetric group, the non-deviated side condyle was larger in GMD, height and volume than the deviated side. There was no statistical difference in condyle position and angulation. The GMD, height difference and condylar volume ratio (non-deviated/deviated) were positively correlated with chin deviation. From the linear regression analysis, condylar volume ratio was a significant factor affecting chin deviation. Conclusions: These findings suggests that the non-deviated side condyle is larger than the deviated side. In addition, condylar asymmetry can affect the expression of facial asymmetry.

• Journal of Life Science
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• v.20 no.7
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• pp.1012-1018
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• 2010

The aim of this study was to determine whether Alzheimer's amyloid precursor protein (APP) is dysregulated in adipose tissues of C57BL/6 male mice by high-fat diet (HFD) induced obesity, aging, or streptozotocin (STZ)-induced diabetes. APP mRNA expression was examined by quantitative real-time PCR (QPCR) in subcutaneous (SAT) and epididymal adipose tissues (EAT) from mice in 8 different condition groups. By combining conditions of age (16 weeks/26 weeks of age), diet (normal diet (ND)/high-fat diet), and induction of diabetes (non-diabetic/diabetic), 88 mice were divided into 8 different groups. QPCR demonstrated that APP expression in SAT was significantly increased by about two-fold in HFD-induced obese mice compared to both 16 week-old and 26 week-old mice in the ND group (16 weeks p=0.001; 26 weeks p<0.0001), but no changes in EAT was found. Particular effects of aging on APP gene expression were not observed in either adipose tissue depots. Significantly decreased APP expression was found in SAT in STZ-induced diabetic mice fed on ND or HFD at 16 weeks of age (ND p<0.05; HFD p<0.01). Linear regression analysis demonstrated that APP expression levels correlated with body weight in both the non-diabetic group (R=0.657, p<0.0001, n=39) and the diabetic group (R=0.508, p=<0.0001, n=49), but did not correlate with plasma glucose levels, which suggests that decreased APP expression in STZ-induced diabetic mice is most likely due to weight loss rather than hyperglycemia. These data confirm APP dysregulation by weight changes in humans and suggest a possible role linking midlife obesity with the later development of amyloidogenesis in the brain of older patients with Alzheimer's disease.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.107-122
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• 2017

Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.

• Sleep Medicine and Psychophysiology
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• v.24 no.1
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• pp.32-37
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• 2017

Objectives: A supine sleep position increases sleep apneas compared to non-supine positions in obstructive sleep apnea syndrome (OSAS). However, supine position time (SPT) is not highly associated with apnea-hypopnea index (AHI) in OSAS. We evaluated the correlation among sleep-related variables and SPT in OSAS. Methods: A total of 365 men with OSAS were enrolled in this study. We analyzed how SPT was correlated with demographic data, sleep structure-related variables, OSAS-related variables and heart rate variability (HRV). Multiple linear regression analysis was conducted to investigate the factors that affected SPT. Results: SPT had the most significant correlation with total sleep time (TST ; r = 0.443, p < 0.001), followed by sleep efficiency (SE ; r = 0.300, p < 0.001). Snoring time (r = 0.238, p < 0.001), time at < 90% SpO2 (r = 0.188, p < 0.001), apnea-hypopnea index (AHI ; r = 0.180, p = 0.001) and oxygen desaturation index (ODI ; r = 0.149, p = 0.004) were significantly correlated with SPT. Multiple regression analysis revealed that TST (t = 7.781, p < 0.001), snoring time (t = 3.794, p < 0.001), AHI (t = 3.768, p < 0.001) and NN50 count (t = 1.993, p = 0.047) were associated with SPT. Conclusion: SPT was more highly associated with sleep structure-related parameters than OSAS-related variables. SPT was correlated with TST, SE, AHI, snoring time and NN50 count. This suggests that SPT is likely to be determined by sleep structure, HRV and the severity of OSAS.

• Sleep Medicine and Psychophysiology
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• v.22 no.1
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• pp.11-19
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• 2015

Objectives: Whether daytime sleepiness is proportional to the severity of sleep apnea in obstructive sleep apnea syndrome (OSAS) is controversial. In this study we investigated how insomnia severity affects the association between daytime sleepiness and sleep apnea severity in OSAS. Methods: The present study included 235 male subjects who were diagnosed with OSAS based on clinical history and nocturnal polysomnography. Pearson's correlation analysis was conducted among sleep and mood-related self-reported data, polysomnographic data and demographic data of all subjects. Based on Pittsburgh Sleep Quality Index (PSQI), the subjects were divided into 2 groups; group A (n = 75; $PSQI{\leq}5$) and group B (n = 160; PSQI > 5). Partial correlation analysis was performed between the Epworth Sleepiness Scale (ESS) and other data in both groups. Multiple linear regression analysis was conducted to investigate the factors which affected the ESS in group A. Results: Pearson's correlation analysis showed weak or non-existent correlations between ESS and apnea severity data such as apnea-hypopnea index (AHI) (r = 0.148, p = 0.023), apnea index (AI) (r = 0.137, p = 0.036), hypopnea index (HI) (r = 0.058, p = 0.377), oxygen desaturation index (ODI) (r = 0.149, p = 0.022) and arousal total index (ATI) (r = 0.129, p = 0.048). Positive correlations between ESS and apnea severity data such as AHI ($r_p=0.313$, p = 0.008), AI ($r_p=0.339$, p = 0.004), ODI ($r_p=0.289$, p = 0.015) and ATI ($r_p=0.256$, p = 0.031) were observed only in group A. Multiple regression analysis showed that AI (t = 2.996, p = 0.004) and BAI (t = 2.721, p = 0.008) were associated with ESS in group A. Conclusion: The correlation between daytime sleepiness and sleep apnea severity was shown only in group A. This result suggests that associations between daytime sleepiness in OSAS and sleep apnea severity will become prominent when controlling for insomnia-related variables.