• Journal of Chest Surgery
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• v.55 no.2
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• pp.143-150
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• 2022

Background: The effectiveness of extracorporeal membrane oxygenation (ECMO) for patients with refractory cardiogenic shock or cardiac arrest is being established, and serum lactate is well known as a biomarker of end-organ perfusion. We evaluated the efficacy of pre-ECMO lactate for predicting 6-month survival in patients with acute coronary syndrome (ACS) undergoing ECMO. Methods: We reviewed the medical records of 148 patients who underwent veno-arterial (VA) ECMO for ACS between January 2015 and June 2020. These patients were divided into survivors and non-survivors based on 6-month survival. All clinical data before and during ECMO were compared between the 2 groups. Results: Patients' mean age was 66.0±10.5 years, and 116 (78.4%) were men. The total survival rate was 45.9% (n=68). Cox regression analysis showed that the pre-ECMO lactate level was an independent predictor of 6-month mortality (hazard ratio, 1.210; 95% confidence interval [CI], 1.064-1.376; p=0.004). The area under the receiver operating characteristic curve of pre-ECMO lactate was 0.64 (95% CI, 0.56-0.72; p=0.002; cut-off value=9.8 mmol/L). Kaplan-Meier survival analysis showed that the cumulative survival rate at 6 months was significantly higher among patients with a pre-ECMO lactate level of 9.8 mmol/L or less than among those with a level exceeding 9.8 mmol/L (57.3% vs. 31.8%, p=0.0008). Conclusion: A pre-ECMO lactate of 9.8 mmol/L or less may predict a favorable outcome at 6 months in ACS patients undergoing VA-ECMO. Further research aiming to improve the accuracy of predictions of reversibility in patients with high pre-ECMO lactate levels is essential.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.2
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• pp.48-55
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• 2022

The color image of the brand comes first and is an important visual element that leads consumers to the consumption of the product. To express more effectively what the brand wants to convey through design, the printing market is striving to print accurate colors that match the intention. In 'offset printing' mainly used in printing, colors are often printed in CMYK (Cyan, Magenta, Yellow, Key) colors. However, it is possible to print more accurate colors by making ink of the desired color instead of dotting CMYK colors. The resulting ink is called 'spot color' ink. Spot color ink is manufactured by repeating the process of mixing the existing inks. In this repetition of trial and error, the manufacturing cost of ink increases, resulting in economic loss, and environmental pollution is caused by wasted inks. In this study, a deep learning algorithm to predict printed spot colors was designed to solve this problem. The algorithm uses a single DNN (Deep Neural Network) model to predict printed spot colors based on the information of the paper and the proportions of inks to mix. More than 8,000 spot color ink data were used for learning, and all color was quantified by dividing the visible light wavelength range into 31 sections and the reflectance for each section. The proposed algorithm predicted more than 80% of spot color inks as very similar colors. The average value of the calculated difference between the actual color and the predicted color through 'Delta E' provided by CIE is 5.29. It is known that when Delta E is less than 10, it is difficult to distinguish the difference in printed color with the naked eye. The algorithm of this study has a more accurate prediction ability than previous studies, and it can be added flexibly even when new inks are added. This can be usefully used in real industrial sites, and it will reduce the attempts of the operator by checking the color of ink in a virtual environment. This will reduce the manufacturing cost of spot color inks and lead to improved working conditions for workers. In addition, it is expected to contribute to solving the environmental pollution problem by reducing unnecessarily wasted ink.

• Korean Journal of Clinical Laboratory Science
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• v.55 no.1
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• pp.29-36
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• 2023

This study proposes a spirometry reference equation suitable for Asian migrant workers undergoing special health examinations. The study participants were divided according to their region: Central Asia, Northeast Asia, and South Asia Pacific. We confirmed results of the spirometry analysis of migrant workers and the interpretation consistency between the prediction equations. Based on this data, we propose a reference equation suitable for domestic migrant workers and suggest a scaling factor applicable to the spirometer wherein the reference equation is not easily applicable. The kappa-values obtained for men and women, respectively, between the global lung function initiative 2012 (GLI2012)-Southeast Asian and the Southeast Asian equations were 0.819 and 0.770, between the GLI2012-Southeast Asian and the South Asian equations were 0.881 and 0.866, and between the GLI2012-Northeast Asian and the Central Asian equations were 0.831 and 0.833. We propose applying the GLI2012-Northeast Asian equation for Northeast Asian and Central Asian countries, whereas the GLI2012-Southeast Asian equation was found to be more suitable for predicting Southeast Asian and South Asian populations. For spirometry, we recommend applying a scaling factor of 0.87 to the Dr. Choi equation, wherein the GLI2012-Southeast Asian equation is not applicable.

• Journal of Gastric Cancer
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• v.23 no.2
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• pp.355-364
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• 2023

Background: There are no clear guidelines to determine whether to perform D1 or D1+ lymph node dissection in early gastric cancer (EGC). This study aimed to develop a nomogram for estimating the risk of extraperigastric lymph node metastasis (LNM). Materials and Methods: Between 2009 and 2019, a total of 4,482 patients with pathologically confirmed T1 disease at 6 affiliated hospitals were included in this study. The basic clinicopathological characteristics of the positive and negative extraperigastric LNM groups were compared. The possible risk factors were evaluated using univariate and multivariate analyses. Based on these results, a risk prediction model was developed. A nomogram predicting extraperigastric LNM was used for internal validation. Results: Multivariate analyses showed that tumor size (cut-off value 3.0 cm, odds ratio [OR]=1.886, P=0.030), tumor depth (OR=1.853 for tumors with sm2 and sm3 invasion, P=0.010), cross-sectional location (OR=0.490 for tumors located on the greater curvature, P=0.0303), differentiation (OR=0.584 for differentiated tumors, P=0.0070), and lymphovascular invasion (OR=11.125, P<0.001) are possible risk factors for extraperigastric LNM. An equation for estimating the risk of extraperigastric LNM was derived from these risk factors. The equation was internally validated by comparing the actual metastatic rate with the predicted rate, which showed good agreement. Conclusions: A nomogram for estimating the risk of extraperigastric LNM in EGC was successfully developed. Although there are some limitations to applying this model because it was developed based on pathological data, it can be optimally adapted for patients who require curative gastrectomy after endoscopic submucosal dissection.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2B
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• pp.187-197
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• 2008

This study is to assess the impact of future land use change on hydrology and water quality in Gyungan-cheon watershed ($255.44km^2$) using SWAT (Soil and Water Assessment Tool) model. Using the 5 past Landsat TM (1987, 1991, 1996, 2004) and $ETM^+$ (2001) satellite images, time series of land use map were prepared, and the future land uses (2030, 2060, 2090) were predicted using CA-Markov technique. The 4 years streamflow and water quality data (SS, T-N, T-P) and DEM (Digital Elevation Model), stream network, and soil information (1:25,000) were prepared. The model was calibrated for 2 years (1999 and 2000), and verified for 2 years (2001 and 2002) with averaged Nash and Sutcliffe model efficiency of 0.59 for streamflow and determination coefficient of 0.88, 0.72, 0.68 for Sediment, T-N (Total Nitrogen), T-P (Total Phosphorous) respectively. The 2030, 2060 and 2090 future prediction based on 2004 values showed that the total runoff increased 1.4%, 2.0% and 2.7% for 0.6, 0.8 and 1.1 increase of watershed averaged CN value. For the future Sediment, T-N and T-P based on 2004 values, 51.4%, 5.0% and 11.7% increase in 2030, 70.5%, 8.5% and 16.7% increase in 2060, and 74.9%, 10.9% and 19.9% increase in 2090.

• Animal Bioscience
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• v.35 no.10
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• pp.1545-1555
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• 2022

Objective: Our study aimed to investigate the effects of a 2% increase in dietary total digestible nutrients (TDN) value during the growing (7 to 12 mo of age) and fattening (13 to 30 mo of age) period of Hanwoo steers. Methods: Two hundred and twenty Hanwoo steers were assigned to one of two treatments: i) a control group (basal TDN, BTDN, n = 111 steers, growing = 70.5%, early fattening = 71.0%, late fattening = 74.0%) or high TDN (HTDN, n = 109 steers, growing = 72.6%, early = 73.1%, late = 76.2%). Growth performance, carcass traits, blood parameters, and gene expression of longissimus dorsi (LD) (7, 18, and 30 mo) were quantified. Results: Steers on the BTDN diets had increased (p≤0.02) DMI throughout the feeding trial compared to HTDN, but gain did not differ appreciably. A greater proportion of cattle in HTDN received Korean quality grade 1 (82%) or greater compared to BTDN (77%), while HTDN had a greater yield grade (29%) than BTDN (20%). Redness (a^*) of LD muscle was improved (p = 0.021) in steers fed HTDN. Feeding the HTDN diet did not alter blood parameters. Steers fed HTDN diet increased (p = 0.015) the proportion of stearic acid and tended to alter linoleic acid. Overall, saturated, unsaturated, monounsaturated, and polyunsaturated fatty acids of LD muscle were not impacted by the HTDN treatment. A treatment by age interaction was noted for mRNA expression of myosin heavy chain (MHC) IIA, IIX, and stearoyl CoA desaturase (SCD) (p≤0.026). No treatment effect was detected on gene expression from LD muscle biopsies at 7, 18, and 30 mo of age; however, an age effect was detected for all variables measured (p≤0.001). Conclusion: Our results indicated that feeding HTDN diet could improve overall quality grade while minimum effects were noted in gene expression, blood parameters, and growing performance. Cattle performance prediction in the feedlot is a critical decision-making tool for optimal planning of cattle fattening and these data provide both benchmark physiological parameters and growth performance measures for Hanwoo cattle feeding enterprises.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.284-301
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• 2023

The changes in rice climatic yield potential (CYP) across the Korean Peninsula are evaluated based on the new climate change scenario produced by the National Institute of Agricultural Sciences with 18 ensemble members at 1 km resolution under a Shared Socioeconomic Pathway (SSP) and Representative Concentration Pathways (RCP) emission scenarios. To overcome the data availability, we utilize solar radiation f or CYP instead of sunshine duration which is relatively uncommon in the climate prediction f ield. The result show that maximum CYP(CYPmax) decreased, and the optimal heading date is progressively delayed under warmer temperature conditions compared to the current climate. This trend is particularly pronounced in the SSP5-85 scenario, indicating faster warming, except for the northeastern mountainous regions of North Korea. This shows the benef its of lower emission scenarios and pursuing more efforts to limit greenhouse gas emissions. On the other hand, the CYPmax shows a wide range of feasible futures, which shows inherent uncertainties in f uture climate projections and the risks when analyzing a single model or a small number of model results, highlighting the importance of the ensemble approach. The f indings of this study on changes in rice productivity and uncertainties in temperature and solar radiation during the 21st century, based on climate change scenarios, hold value as f undamental information for climate change adaptation efforts.

• Progress in Medical Physics
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• v.22 no.3
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• pp.140-147
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• 2011

The purpose of this study was to estimate internal motion using molecular sieve for quantitative improvement of lung tumor and to localize lung tumor in the small animal PET image by evaluated data. Internal motion has been demonstrated in small animal lung region by molecular sieve contained radioactive substance. Molecular sieve for internal lung motion target was contained approximately 37 kBq Cu-64. The small animal PET images were obtained from Siemens Inveon scanner using external trigger system (BioVet). SD-Rat PET images were obtained at 60 min post injection of FDG 37 MBq/0.2 mL via tail vein for 20 min. Each line of response in the list-mode data was converted to sinogram gated frames (2~16 bin) by trigger signal obtained from BioVet. The sinogram data was reconstructed using OSEM 2D with 4 iterations. PET images were evaluated with count, SNR, FWHM from ROI drawn in the target region for quantitative tumor analysis. The size of molecular sieve motion target was $1.59{\times}2.50mm$. The reference motion target FWHM of vertical and horizontal was 2.91 mm and 1.43 mm, respectively. The vertical FWHM of static, 4 bin and 8 bin was 3.90 mm, 3.74 mm, and 3.16 mm, respectively. The horizontal FWHM of static, 4 bin and 8 bin was 2.21 mm, 2.06 mm, and 1.60 mm, respectively. Count of static, 4 bin, 8 bin, 12 bin and 16 bin was 4.10, 4.83, 5.59, 5.38, and 5.31, respectively. The SNR of static, 4 bin, 8 bin, 12 bin and 16 bin was 4.18, 4.05, 4.22, 3.89, and 3.58, respectively. The FWHM were improved in accordance with gate number increase. The count and SNR were not proportionately improve with gate number, but shown the highest value in specific bin number. We measured the optimal gate number what minimize the SNR loss and gain improved count when imaging lung tumor in small animal. The internal motion estimation provide localized tumor image and will be a useful method for organ motion prediction modeling without external motion monitoring system.

• Journal of The Korean Society of Grassland and Forage Science
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• v.29 no.3
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• pp.253-262
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• 2009

The present study was conducted to develop a rapid and accurate method of evaluating chemical composition of total mixed ration (TMR) for dairy cows using near infrared reflectance spectroscopy (NIRS). A total of 253 TMR samples were collected from TMR manufacturers and dairy farms in Korea. Prior to NIR analysis, TMR samples were dried at $65^{\circ}C$ for 48 hour and then ground to 2 mm size. The samples were scanned at 2 nm interval over the wavelength range of 400-2500 nm on a FOSS-NIR Systems Model 6500. The values obtained by NIR analysis and conventional chemical methods were compared. Generally, the relationship between chemical analysis and NIR analysis was linear: $R^2$ and standard error of calibration (SEC) were 0.701 (SEC 0.407), 0.965 (SEC 0.315), 0.796 (SEC 0.406), 0.889 (SEC 0.987), 0.894 (SEC 0.311), 0.933 (SEC 0.885) and 0.889 (SEC 1.490) for moisture, crude protein, ether extract, crude fiber, crude ash, acid detergent fiber (ADF) and neutral detergent fiber (NDF), respectively. In addition, the standard error of prediction (SEP) value was 0.371, 0.290, 0.321, 0.380, 0.960, 0.859 and 1.446 for moisture, crude protein, ether extract, crude fiber, crude ash, ADF and NDF, respectively. The results of the present study showed that the NIR analysis for unknown TMR samples would be relatively accurate. Use of the developed NIR calibration curve can obtain fast and reliable data on chemical composition of TMR. Collection and analysis of more TMR samples will increase accuracy and precision of NIR analysis to TMR.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12C
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• pp.1173-1183
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• 2006

In this paper, we propose an efficient method for improving visual quality of AR-FGS (Adaptive Reference FGS) which is adopted as a key scheme for SVC (Scalable Video Coding) or H.264 scalable extension. The standard FGS (Fine Granularity Scalability) adopts AR-FGS that introduces temporal prediction into FGS layer by using a high quality reference signal which is constructed by the weighted average between the base layer reconstructed imageand enhancement reference to improve the coding efficiency in the FGS layer. However, when the enhancement stream is truncated at certain bitstream position in transmission, the rest of the data of the FGS layer will not be available at the FGS decoder. Thus the most noticeable problem of using the enhancement layer in prediction is the degraded visual quality caused by drifting because of the mismatch between the reference frame used by the FGS encoder and that by the decoder. To solve this problem, we exploit the principle of cyclical block coding that is used to encode quantized transform coefficients in a cyclical manner in the FGS layer. Encoding block coefficients in a cyclical manner places 'higher-value' bits earlier in the bitstream. The quantized transform coefficients included in the ealry coding cycle of cyclical block coding have higher probability to be correctly received and decoded than the others included in the later cycle of the cyclical block coding. Therefore, we can minimize visual quality degradation caused by bitstream truncation by adjusting weighting factor to control the contribution of the bitstream produced in each coding cycle of cyclical block coding when constructing the enhancement layer reference frame. It is shown by simulations that the improved AR-FGS scheme outperforms the standard AR-FGS by about 1 dB in maximum in the reconstructed visual quality.