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Chae Minki,Na Ji Ung,Lee Jang Hee,Shin Dong Hyuk 대한응급의학회 2023 Clinical and Experimental Emergency Medicine Vol.10 No.1
Objective: A cardiothoracic ratio ≥0.50 is widely used as an indicator of cardiomegaly, but associations between the cardiothoracic ratio and left ventricular systolic dysfunction (LVSD) have not been investigated previously. We conducted this study to investigate the relationship between cardiothoracic ratio measured using computed tomography (CT) and left ventricular ejection fraction (LVEF), and to determine the optimal cardiothoracic ratio for predicting left ventricular systolic dysfunction (LVSD). Methods: A retrospective cross-sectional study was performed using data from patients who underwent both chest CT and echocardiography at the emergency department from January 1 to December 31, 2021. The patients were classified as normal, or having mild, moderate, and severe LVSD based on their LVEF, and the cardiothoracic ratios of each group were compared. The receiver operating characteristic (ROC) curve analyses were used to identify the optimal cardiothoracic ratio for prediction of mild, moderate, and severe LVSD. Results: The final study population included 444 patients. The median CT-measured cardiothoracic ratio was 0.54 for patients with normal LVEF, and 0.60 for patients with LVSD (P<0.001). The optimal CT-measured cardiothoracic ratios for predicting mild, moderate, and severe LVSD were 0.56, 0.59, and 0.60, and their areas under the ROC curve were 0.653, 0.690, and 0.680, and negative predictive values were 90%, 94%, and 98%, respectively. Conclusion: The best cutoff value for a CT-measured cardiothoracic ratio suggestive of LVSD was 0.56, which is very different from the 0.50 value typically considered an abnormal cardiothoracic ratio. The CT-measured cardiothoracic ratio ≥0.56 can be used as a rough indicator of mild LVSD, and a ratio <0.60 can exclude severe LVSD with a high degree of confidence.
Failure Analysis of a Water Wall Boiler Tube for Power Generation in a District Heating System
Minki Hong,Hobyung Chae,Woo Cheol Kim,Jung‑Gu Kim,Heesan Kim,Soo Yeol Lee 대한금속·재료학회 2019 METALS AND MATERIALS International Vol.25 No.5
Corrosion failure of materials often exposed to the corrosive environment in district heating systems is critical for operationand maintenance of the facility. It is important to establish a prevention method from an accurate prognosis on the cause ofthe corrosion failure. In this study, a failure analysis on the water wall boiler tube in a district heating system was carried out. The fracture occurred in an open window shape with a significant internal wall thinning that formed Na- and Fe-oxide bycaustic corrosion. Tensile residual stress in the hoop direction developed inside the tube weakened the protective magnetitelayer by accelerating the caustic corrosion, from which hydrogen atoms diffused into the alloy forming cavities or microvoidsat the grain boundaries. Furthermore, high temperature creep promoted the evolution of the cavities only inside thetube where there were tensile residual stresses. Consequently, a combination of hydrogen embrittlement and thermal creepinitiated the cracks at the grain boundaries inside the tube, and the cracks propagated at the grain boundaries along the axialdirection exhibiting an intergranular feature on the inside. Then, it gradually propagated toward the outside, finally exhibitinga transgranular fracture mode on the outside.
Toward a grey box approach for cardiovascular physiome
Minki Hwang,Chae Hun Leem,Eun Bo Shim 대한약리학회 2019 The Korean Journal of Physiology & Pharmacology Vol.23 No.5
The physiomic approach is now widely used in the diagnosis of cardiovascular diseases. There are two possible methods for cardiovascular physiome: the traditional mathematical model and the machine learning (ML) algorithm. ML is used in almost every area of society for various tasks formerly performed by humans. Specifically, various ML techniques in cardiovascular medicine are being developed and improved at unprecedented speed. The benefits of using ML for various tasks is that the inner working mechanism of the system does not need to be known, which can prove convenient in situations where determining the inner workings of the system can be difficult. The computation speed is also often higher than that of the traditional mathematical models. The limitations with ML are that it inherently leads to an approximation, and special care must be taken in cases where a high accuracy is required. Traditional mathematical models are, however, constructed based on underlying laws either proven or assumed. The results from the mathematical models are accurate as long as the model is. Combining the advantages of both the mathematical models and ML would increase both the accuracy and efficiency of the simulation for many problems. In this review, examples of cardiovascular physiome where approaches of mathematical modeling and ML can be combined are introduced.
Stress Corrosion Cracking of a Copper Pipe in a Heating Water Supply System
Hobyung Chae,Huai Wang,Minki Hong,Woo Cheol Kim,Jung‑Gu Kim,Heesan Kim,Soo Yeol Lee 대한금속·재료학회 2020 METALS AND MATERIALS International Vol.26 No.7
Stress corrosion cracking behavior of a copper pipe and its mechanism were investigated in a heating water supply systemusing both metallurgical and mechanical analyses. The X-ray diffraction and energy dispersive spectroscopy measurementsshowed that uniform cupric oxide and cuprous oxide were formed during service on the inside surface of the pipe, whilemalachite and cupric oxide were the main corrosion products on the outer surface of the pipe. Many corrosion pits wereobserved around the cracking areas on the outer surface by optical microscopy. Finite element modeling highlighted a regionwith large hoop stresses mainly brought about by the bolt load, where it became susceptible to stress corrosion cracking(SCC). The morphology of the fracture surface revealed an intergranular mode towards the outer surface but a mixed interandtrans-granular mode near the inner surface. Based on the obtained results, a phenomenological 4-stage fracture processis proposed to describe the failure process of the copper pipe, in which the SCC initiated from the corrosion pits on the outersurface, propagated along the axial direction and penetrated towards the inner surface until final fracture.
Toward a grey box approach for cardiovascular physiome
Hwang, Minki,Leem, Chae Hun,Shim, Eun Bo The Korean Society of Pharmacology 2019 The Korean Journal of Physiology & Pharmacology Vol.23 No.5
The physiomic approach is now widely used in the diagnosis of cardiovascular diseases. There are two possible methods for cardiovascular physiome: the traditional mathematical model and the machine learning (ML) algorithm. ML is used in almost every area of society for various tasks formerly performed by humans. Specifically, various ML techniques in cardiovascular medicine are being developed and improved at unprecedented speed. The benefits of using ML for various tasks is that the inner working mechanism of the system does not need to be known, which can prove convenient in situations where determining the inner workings of the system can be difficult. The computation speed is also often higher than that of the traditional mathematical models. The limitations with ML are that it inherently leads to an approximation, and special care must be taken in cases where a high accuracy is required. Traditional mathematical models are, however, constructed based on underlying laws either proven or assumed. The results from the mathematical models are accurate as long as the model is. Combining the advantages of both the mathematical models and ML would increase both the accuracy and efficiency of the simulation for many problems. In this review, examples of cardiovascular physiome where approaches of mathematical modeling and ML can be combined are introduced.