Journal of the Earthquake Engineering Society of Korea
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제6권4호
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pp.65-73
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2002
It has been recognized that the damage control must become a more explicit design consideration. In an effort to develop design methods based on performance it is clear that the evaluation of the nonlinear response is required. The methods available to the design engineer today are nonlinear time history analyses, monotonic static nonlinear analyses, or equivalent static analyses with simulated nonlinear influences. Some building codes propose the capacity spectrum method based on the nonlinear static analysis(pushover analysis) to determine the earthquake-induced demand given by the structure pushover curve. These procedures are conceptually simple but iterative and time consuming with some errors. This paper presents a nonlinear direct spectrum method(NDSM) to evaluate seismic performance of structures, without iterative computations, given by the structural initial elastic period and yield strength from the pushover analysis, especially for MDF(multi degree of freedom) systems. The purpose of this paper is to investigate the accuracy and confidence of this method from a point of view of various earthquakes and unloading stiffness degradation parameters. The conclusions of this study are as follows; 1) NDSM is considered as practical method because the peak deformations of nonlinear system of MDF by NDSM are almost equal to the results of nonlinear time history analysis(NTHA) for various ground motions. 2) When the results of NDSM are compared with those of NTHA. mean of errors is the smallest in case of post-yielding stiffness factor 0.1, static force by MAD(modal adaptive distribution) and unloading stiffness degradation factor 0.2~0.3.
Yoo, Jeong-Ju;Cho, Eun Ju;Lee, Bora;Kim, Sang Gyune;Kim, Young Seok;Lee, Yun Bin;Lee, Jeong-Hoon;Yu, Su Jong;Kim, Yoon Jun;Yoon, Jung-Hwan
Gut and Liver
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제12권6호
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pp.714-721
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2018
Background/Aims: Recently reported prognostic models for primary biliary cholangitis (PBC) have been shown to be effective in Western populations but have not been well-validated in Asian patients. This study aimed to compare the performance of prognostic models in Korean patients and to investigate whether inflammation-based scores can further help in prognosis prediction. Methods: This study included 271 consecutive patients diagnosed with PBC in Korea. The following prognostic models were evaluated: the Barcelona model, the Paris-I/II model, the Rotterdam criteria, the GLOBE score and the UK-PBC score. The neutrophil-to-lymphocyte ratio (NLR) was analyzed with reference to its association with prognosis. Results: For predicting liver transplant or death at the 5-year and 10-year follow-up examinations, the UK-PBC score (areas under the receiver operating characteristic curve [AUCs], 0.88 and 0.82) and GLOBE score (AUCs, 0.85 and 0.83) were significantly more accurate in predicting prognosis than the other scoring systems (all p<0.05). There was no significant difference between the performance of the UK-PBC and GLOBE scores. In addition to the prognostic models, a high NLR (>2.46) at baseline was an independent predictor of reduced transplant-free survival in the multivariate analysis (adjusted hazard ratio, 3.74; p<0.01). When the NLR was applied to the prognostic models, it significantly differentiated the prognosis of patients. Conclusions: The UK-PBC and GLOBE scores showed good prognostic performance in Korean patients with PBC. In addition, a high NLR was associated with a poorer prognosis. Including the NLR in prognostic models may further help to stratify patients with PBC.
Sim, Tae Jin;Cho, Jae Wan;Lee, Mi Jin;Jung, Haewon;Park, Jungbae;Seo, Kang Suk
Journal of The Korean Society of Clinical Toxicology
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제19권2호
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pp.72-82
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2021
Purpose: A high anion gap (AG) is known to be a significant risk factor for serious acid-base imbalances and death in acute poisoning cases. The strong ion difference (SID), or strong ion gap (SIG), has recently been used to predict in-hospital mortality or acute kidney injury (AKI) in patients with systemic inflammatory response syndrome. This study presents a comprehensive acid-base analysis in order to identify the predictive value of the SIG for disease severity in severe poisoning. Methods: A cross-sectional observational study was conducted on acute poisoning patients treated in the emergency intensive care unit (ICU) between December 2015 and November 2020. Initial serum electrolytes, base deficit (BD), AG, SIG, and laboratory parameters were concurrently measured upon hospital arrival and were subsequently used along with Stewart's approach to acid-base analysis to predict AKI development and in-hospital death. The area under the receiver operating characteristic curve (AUC) and logistic regression analysis were used as statistical tests. Results: Overall, 343 patients who were treated in the intensive care unit were enrolled. The initial levels of lactate, AG, and BD were significantly higher in the AKI group (n=62). Both effective SID [SIDe] (20.3 vs. 26.4 mEq/L, p<0.001) and SIG (20.2 vs. 16.5 mEq/L, p<0.001) were significantly higher in the AKI group; however, the AUC of serum SIDe was 0.842 (95% confidence interval [CI]=0.799-0.879). Serum SIDe had a higher predictive capacity for AKI than initial creatinine (AUC=0.796, 95% CI=0.749-0.837), BD (AUC=0.761, 95% CI=0.712-0.805), and AG (AUC=0.660, 95% CI=0.607-0.711). Multivariate logistic regression analyses revealed that diabetes, lactic acidosis, high SIG, and low SIDe were significant risk factors for in-hospital mortality. Conclusion: Initial SIDe and SIG were identified as useful predictors of AKI and in-hospital mortality in intoxicated patients who were critically ill. Further research is necessary to evaluate the physiological nature of the toxicant or unmeasured anions in such patients.
Seo, Han-Na;Chae, Seung-Beom;Lim, Hyo-In;Han, Sim-Hee;Lee, Kiwoong
Journal of Forest and Environmental Science
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제37권4호
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pp.315-322
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2021
The aim of this study was to investigate the sensitivity to environmental stress, and changes in the photosynthesis capacity in Abies koreana seedlings by age and to suggest the most effective age for restoration. To identify these physiological characteristics of A. koreana, the chlorophyll fluorescence and photosynthetic capacity of 1-, 2-, 3-, 5- and 6-year-old A. koreana seedlings were observed from June 2020 to June 2021. The maximum quantum efficiency of Photosystem II (Fv/Fm), a chlorophyll fluorescence measurement parameter, was strongly positively correlated with the monthly average temperature (1-year-old seedling: r=0.8779, 2-year-old seedling: r=0.8605, 3-year-old seedling: r=0.8697, 5-year-old seedlings: r=0.8085, and 6-year-old seedlings: r=0.8316). The Fv/Fm values were the lowest in winter (November 2020-March 2021). In addition, the Fv/Fm values of 1-, 2-, and 3-year-old seedlings in winter were lower than that of 5- and 6-year-old seedlings, while the Fv/Fm values in summer were relatively higher than those in winter. Further, the Fv/Fm values of seedlings of all ages decreased in August 2020, when the monthly average temperature was the highest. In particular, 1-year-old to 3-year-old seedlings showed Fv/Fm values less than 0.8. Further, the photosynthetic capacity measured in August 2020 increased with increasing seedling age. The analysis of variance results for summer Fv/Fm values showed significant differences in age-specific averages (p<0.05), and Duncan's multiple range test showed significant differences between 5- and 6-year-old seedlings and 1-, 2-, and 3-year-old seedlings (p<0.05). These results suggested that the 5- and 6-year-old seedlings were less sensitive to environmental stress and showed better photosynthetic capacity than the 1-, 2-, and 3-year-old seedlings. Therefore, 5-year-old or older A. koreana seedlings can be used as restoration materials because they can show increased adaptability and stable growth during transplantation due to their relatively high environmental resistance and photosynthetic capacity.
Proceedings of the Korea Water Resources Association Conference
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한국수자원학회 2015년도 학술발표회
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pp.217-217
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2015
The objective of this study was mainly to evaluate the water resources potential of Lake Tana Basin (LTB) by using Soil and Water Assessment Tool (SWAT). From SWAT simulation of LTB, about 5236 km2 area of LTB is gauged watershed and the remaining 9878 km2 area is ungauged watershed. For calibration of model parameters, four gauged stations were considered namely: Gilgel Abay, Gummera, Rib, and Megech. The SWAT-CUP built-in techniques, particle swarm optimization (PSO) and generalized likelihood uncertainty estimation (GLUE) method was used for calibration of model parameters and PSO method were selected for the study based on its performance results in four gauging stations. However the level of sensitivity of flow parameters differ from catchment to catchment, the curve number (CN2) has been found the most sensitive parameters in all gauged catchments. To facilitate the transfer of data from gauged catchments to ungauged catchments, clustering of hydrologic response units (HRUs) were done based on physical similarity measured between gauged and ungauged catchment attributes. From SWAT land use/ soil use/slope reclassification of LTB, a total of 142 HRUs were identified and these HRUs are clustered in to 39 similar hydrologic groups. In order to transfer the optimized model parameters from gauged to ungauged catchments based on these clustered hydrologic groups, this study evaluates three parameter transfer schemes: parameters transfer based on homogeneous regions (PT-I), parameter transfer based on global averaging (PT-II), and parameter transfer by considering Gilgel Abay catchment as a representative catchment (PT-III) since its model performance values are better than the other three gauged catchments. The performance of these parameter transfer approach was evaluated based on values of Nash-Sutcliffe efficiency (NSE) and coefficient of determination (R2). The computed NSE values was found to be 0.71, 0.58, and 0.31 for PT-I, PT-II and PT-III respectively and the computed R2 values was found to be 0.93, 0.82, and 0.95 for PT-I, PT-II, and PT-III respectively. Based on the performance evaluation criteria, PT-I were selected for modelling ungauged catchments by transferring optimized model parameters from gauged catchment. From the model result, yearly average stream flow for all homogeneous regions was found 29.54 m3/s, 112.92 m3/s, and 130.10 m3/s for time period (1989 - 2005) for region-I, region-II, and region-III respectively.
Roots play important roles in water and nutrient uptake and in response to various environmental stresses. Investigating diversification of cultivars through root phenotyping is important for crop improvement in adzuki beans. Therefore, we analyzed the morphological and architectural root traits of 22 adzuki bean cultivars using 2-dimensional (2D) root imaging. Plants were grown in plastic tubes [6 cm (diameter) × 40 cm (height)] in a greenhouse from July 25th to August 28th. When the plants reached the 2nd or 3rd trifoliate leaf stage, the roots were removed and washed with tap water to remove soil particles. Clean root samples were scanned, and the scanned images were analyzed using the WinRHIZO Pro software. The cultivars were analyzed based on six root phenotypes [total root length (TRL), surface area (SA), average diameter (AD), and number of tips (NT) were included as root morphological traits (RMT); and link average length (LAL) and link average diameter (LAD) were included as root architectural traits (RAT)]. According to the analysis of variance (ANOVA), a significant difference was observed between the cultivars for all root morphological traits. Distribution analysis demonstrated that all root traits except LAL followed a normally distributed curve. In the correlation test, the most important morphological trait, TRL, showed a strong positive correlation with SA (r = 0.97***) and NT (r = 0.94***). In comparison, between RMT and RAT, TRL showed a significantly negative correlation with LAL (r = -0.50***); however, TRL did not show a correlation with LAD. Based on RMT and RAT, we identified the cultivars that ranked 5% from the top and bottom. In particular, the cultivar "IT 236657" showed the highest TRL, SA, and NT, while the cultivar "IT 236169" showed the lowest values for TRL, SA, and NT. In addition, the coefficient of variance for the six tested root traits ranged from (14.26-40%) which suggested statistical variability in root phenotypes among the 22 adzuki bean varieties. Thus, this study will help to select target root traits for the adzuki bean breeding program in the future, generating climate-resilient adzuki beans, especially for drought stress, and may be useful for developing biotic and abiotic stress-tolerant cultivars based on better root trait attributes.
Journal of the Korea institute for structural maintenance and inspection
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제26권4호
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pp.1-10
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2022
In this study, to evaluate the possibility of using a steel spring as a displacement-dependent damping device, tensile loading and cyclic loading tests were performed. The main experimental variables were the type of steel (SAE9254 and SS275), the spring constant (700 N/mm, 1,000 N/mm, and 1,400 N/mm), and the presence or absence of heat treatment for SAE9254. As a result of the tensile test, the ratios of the measured spring constant to the design spring constant of the steel springs made with SAE9254 ranged from 1.08 to 1.13, while the ratios of the design spring constant and the measured spring constant of the steel springs made with SS275 ranged from 0.86 to 0.97. After yielding, the slope values of the load-displacement curve of the SAE9254 with/without heat treatment were about 240~251 N/mm and 92 N/mm, respectively, but the slope values of the load-displacement response of SS275 were almost zero. According to the uniaxial cyclic loading test results, all specimens were satisfied with three conditions for a displacement-dependent damping device in KDS 41 17 00 (2019): the maximum force and minimum force at zero displacement, the maximum force and minimum force at the maximum displacement, and the energy dissipation capacity. In addition, the equivalent damping ratios of steel springs made with SAE9254(non-heat treatment) and SS275 were approximately 2.8 times and 1.9 times greater, respectively, than that of steel springs made with SAE9254.
The goal of this study is to improve flow and noise performances of existing backward-curved blade centrifugal fan system used for circulating cold air in a refrigerator freezer by optimally designing airfoil shape. The unique characteristics of the system is to drive cold airflow with two volute tongues in combination with duct system in a back side of a refrigerator without scroll housing generally used in a typical centrifugal fan system. First, flow and noise performances of existing fan system were evaluated experimentally. A P-Q curve was obtained using a fan performance tester in the flow experiment, and noise spectrum was measured in an anechoic chamber in the noise experiment. Then, flow characteristics were numerically analyzed by solving the three-dimensional unsteady Navier-Stokes equations and noise analysis was performed by solving the Ffowcs Williams and Hawkins equation with input from the flow simulation results. The validity of numerical results was confirmed by comparing them with the measured ones. Based on the verified numerical method, blade inlet and outlet angles were optimized for maximum flow rate using the two-factor central composite design of the response surface method. Finally, the flow and noise performances of a prototype manufactured with the optimum design were experimentally evaluated, which showed the improvement in flow and noise performance.
Polymer electrolyte membrane fuel cells have the advantage of low operating temperatures and fast startup and response characteristics compared to others. Simulation studies are actively researched because their cost and time benefits. In this study, the resistance of water residual in the gas diffusion layer (GDL) of the unit cell was added to the existing equation to compare the actual data with the model data. The experiments were conducted with a 25 cm2 unit cell, and the samples were separated into stopping times of 0, 10, and 60 minutes following primary impedance measurement, activation, and polarization curve data acquisition. This gives 0, 10, and 60 minutes for the residual water in the GDL to evaporate. Without the rest period, the magnitude of the performance improvement was not significantly different at the same potential and flow rate, but the rest period did improve the performance of the membrane electrode assembly when measuring impedance. By changing the magnitude of the resistance reduction to an overvoltage, the voltage difference between the fuel cell model with and without residual water was compared, and the error rate in the high current density region, which is dominated by concentration losses, was reduced.
Dong Hyun Kim;Jiwoon Seo;Ji Hyun Lee;Eun-Tae Jeon;DongYoung Jeong;Hee Dong Chae;Eugene Lee;Ji Hee Kang;Yoon-Hee Choi;Hyo Jin Kim;Jee Won Chai
Korean Journal of Radiology
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제25권4호
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pp.363-373
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2024
Objective: To develop and evaluate a deep learning model for automated segmentation and detection of bone metastasis on spinal MRI. Materials and Methods: We included whole spine MRI scans of adult patients with bone metastasis: 662 MRI series from 302 patients (63.5 ± 11.5 years; male:female, 151:151) from three study centers obtained between January 2015 and August 2021 for training and internal testing (random split into 536 and 126 series, respectively) and 49 MRI series from 20 patients (65.9 ± 11.5 years; male:female, 11:9) from another center obtained between January 2018 and August 2020 for external testing. Three sagittal MRI sequences, including non-contrast T1-weighted image (T1), contrast-enhanced T1-weighted Dixon fat-only image (FO), and contrast-enhanced fat-suppressed T1-weighted image (CE), were used. Seven models trained using the 2D and 3D U-Nets were developed with different combinations (T1, FO, CE, T1 + FO, T1 + CE, FO + CE, and T1 + FO + CE). The segmentation performance was evaluated using Dice coefficient, pixel-wise recall, and pixel-wise precision. The detection performance was analyzed using per-lesion sensitivity and a free-response receiver operating characteristic curve. The performance of the model was compared with that of five radiologists using the external test set. Results: The 2D U-Net T1 + CE model exhibited superior segmentation performance in the external test compared to the other models, with a Dice coefficient of 0.699 and pixel-wise recall of 0.653. The T1 + CE model achieved per-lesion sensitivities of 0.828 (497/600) and 0.857 (150/175) for metastases in the internal and external tests, respectively. The radiologists demonstrated a mean per-lesion sensitivity of 0.746 and a mean per-lesion positive predictive value of 0.701 in the external test. Conclusion: The deep learning models proposed for automated segmentation and detection of bone metastases on spinal MRI demonstrated high diagnostic performance.
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