• Korean Journal of Radiology
• /
• 제23권8호
• /
• pp.811-820
• /
• 2022

Objective: To develop a model incorporating radiomic features and clinical factors to accurately predict acute ischemic stroke (AIS) outcomes. Materials and Methods: Data from 522 AIS patients (382 male [73.2%]; mean age ± standard deviation, 58.9 ± 11.5 years) were randomly divided into the training (n = 311) and validation cohorts (n = 211). According to the modified Rankin Scale (mRS) at 6 months after hospital discharge, prognosis was dichotomized into good (mRS ≤ 2) and poor (mRS > 2); 1310 radiomics features were extracted from diffusion-weighted imaging and apparent diffusion coefficient maps. The minimum redundancy maximum relevance algorithm and the least absolute shrinkage and selection operator logistic regression method were implemented to select the features and establish a radiomics model. Univariable and multivariable logistic regression analyses were performed to identify the clinical factors and construct a clinical model. Ultimately, a multivariable logistic regression analysis incorporating independent clinical factors and radiomics score was implemented to establish the final combined prediction model using a backward step-down selection procedure, and a clinical-radiomics nomogram was developed. The models were evaluated using calibration, receiver operating characteristic (ROC), and decision curve analyses. Results: Age, sex, stroke history, diabetes, baseline mRS, baseline National Institutes of Health Stroke Scale score, and radiomics score were independent predictors of AIS outcomes. The area under the ROC curve of the clinical-radiomics model was 0.868 (95% confidence interval, 0.825-0.910) in the training cohort and 0.890 (0.844-0.936) in the validation cohort, which was significantly larger than that of the clinical or radiomics models. The clinical radiomics nomogram was well calibrated (p > 0.05). The decision curve analysis indicated its clinical usefulness. Conclusion: The clinical-radiomics model outperformed individual clinical or radiomics models and achieved satisfactory performance in predicting AIS outcomes.

• 새물리
• /
• 제68권12호
• /
• pp.1315-1323
• /
• 2018

본 연구에서는 폐 커피분말을 열처리 조건에 따른 탄화과정을 거쳐 리튬 이온 이차전지의 음극 활물질 재료로 응용하기 위한 실험을 진행하였다. 이차전지의 음극 활물질로 사용한 커피분말은 커피 껍질이 아닌 커피 알맹이로부터 얻은 것으로, 커피를 내리고 남은 커피분말을 공기 중에서 건조하고 $Ar/H_2$ 분위기에서 열처리하여 기공(pore)이 있는 활성 탄소 분말 형태로 얻을 수 있었다. 전기화학적인 특성을 조사한 결과 약 0.2 V에서 Li의 삽입, 0.01 V에서 Li의 탈리가 관찰되었다. $700^{\circ}C$에서 열처리된 시료에 대해 1000 mA/g의 전류밀도로 1000 사이클 충방전 후 측정된 비용량은 303 mAh/g 이었으며 99.5% 이상의 쿨롱(Coulomb) 효율을 나타내었다. 폐 커피분말을 이용한 리튬이온이차전지는 기공으로 인한 표면적 증가와 이온 및 전자전도 특성 개선으로 전기화학적인 성능 향상을 보였으며, 또한 재활용을 통한 전지 제조 가격을 낮출 수 있는 이점이 있다.

• Nuclear Engineering and Technology
• /
• 제55권5호
• /
• pp.1802-1813
• /
• 2023

Conjugate heat transfer between liquid metal and solid is a common phenomenon in a liquid-metal-cooled fast reactor's fuel assembly and heat exchanger, dramatically affecting the reactor's safety and economy. Therefore, comprehensively studying the sophisticated conjugate heat transfer in a liquid-metal-cooled fast reactor is profound. However, it has been evidenced that the traditional Simple Gradient Diffusion Hypothesis (SGDH), assuming a constant turbulent Prandtl number (Pr_t,, usually 0.85 - 1.0), is inappropriate in the Computational Fluid Dynamics (CFD) simulations of liquid metal. In recent decades, numerous studies have been performed on the four-equation model, which is expected to improve the precision of liquid metal's CFD simulations but has not been introduced into the conjugate heat transfer calculation between liquid metal and solid. Consequently, a four-equation model, consisting of the Abe k - ε turbulence model and the Manservisi k_𝜃 - ε_𝜃 heat transfer model, is applied to study the conjugate heat transfer concerning liquid metal in the present work. To verify the numerical validity of the four-equation model used in the conjugate heat transfer simulations, we reproduce Johnson's experiments of the liquid lead-bismuth-cooled turbulent pipe flow using the four-equation model and the traditional SGDH model. The simulation results obtained with different models are compared with the available experimental data, revealing that the relative errors of the local Nusselt number and mean heat transfer coefficient obtained with the four-equation model are considerably reduced compared with the SGDH model. Then, the thermal-hydraulic characteristics of liquid metal turbulent pipe flow obtained with the four-equation model are analyzed. Moreover, the impact of the turbulence model used in the four-equation model on overall simulation performance is investigated. At last, the effectiveness of the four-equation model in the CFD simulations of liquid sodium conjugate heat transfer is assessed. This paper mainly proves that it is feasible to use the four-equation model in the study of liquid metal conjugate heat transfer and provides a reference for the research of conjugate heat transfer in a liquid-metal-cooled fast reactor.