Web-based CAD/CAM/CAE Pedagogy Combining Domain-Knowledge and E-learning Models with Bezier curve Generation as a Case Study

Yin-Tung ”Albert” Sun,Mike A. Perez 대한산업공학회 2003 Industrial Engineeering & Management Systems Vol.2 No.2

Neutrophil Gelatinase-Associated Lipocalin Cutoff Value Selection and Acute Kidney Injury Classification System Determine Phenotype Allocation and Associated Outcomes

Albert Annemarie,Radtke Sebastian,Blume Louisa,Bellomo Rinaldo,Haase Michael,Stieger Philipp,Hinkel Ulrich Paul,Braun-Dullaeus Rüdiger C.,Albert Christian 대한진단검사의학회 2023 Annals of Laboratory Medicine Vol.43 No.6

Background: We explored the extent to which neutrophil gelatinase-associated lipocalin (NGAL) cutoff value selection and the acute kidney injury (AKI) classification system determine clinical AKI-phenotype allocation and associated outcomes. Methods: Cutoff values from ROC curves of data from two independent prospective cardiac surgery study cohorts (Magdeburg and Berlin, Germany) were used to predict Kidney Disease: Improving Global Outcome (KDIGO)- or Risk, Injury, Failure, Loss of kidney function, End-stage (RIFLE)-defined AKI. Statistical methodologies (maximum Youden index, lowest distance to [0, 1] in ROC space, sensitivity≈specificity) and cutoff values from two NGAL meta-analyses were evaluated. Associated risks of adverse outcomes (acute dialysis initiation and in-hospital mortality) were compared. Results: NGAL cutoff concentrations calculated from ROC curves to predict AKI varied according to the statistical methodology and AKI classification system (10.6–159.1 and 16.85–149.3 ng/mL in the Magdeburg and Berlin cohorts, respectively). Proportions of attributed subclinical AKI ranged 2%–33.0% and 10.1%–33.1% in the Magdeburg and Berlin cohorts, respectively. The difference in calculated risk for adverse outcomes (fraction of odds ratios for AKI-phenotype group differences) varied considerably when changing the cutoff concentration within the RIFLE or KDIGO classification (up to 18.33- and 16.11-times risk difference, respectively) and was even greater when comparing cutoff methodologies between RIFLE and KDIGO classifications (up to 25.7-times risk difference). Conclusions: NGAL positivity adds prognostic information regardless of RIFLE or KDIGO classification or cutoff selection methodology. The risk of adverse events depends on the methodology of cutoff selection and AKI classification system.

Predictive Value of Plasma NGAL:Hepcidin-25 for Major Adverse Kidney Events After Cardiac Surgery with Cardiopulmonary Bypass: A Pilot Study

Albert Christian,Haase Michael,Albert Annemarie,Ernst Martin,Kropf Siegfried,Bellomo Rinaldo,Westphal Sabine,Braun-Dullaeus Rüdiger C.,Haase-Fielitz Anja,Elitok Saban 대한진단검사의학회 2021 Annals of Laboratory Medicine Vol.41 No.4

Background: Neutrophil gelatinase-associated lipocalin (NGAL) and hepcidin-25 are involved in catalytic iron-related kidney injury after cardiac surgery with cardiopulmonary bypass. We explored the predictive value of plasma NGAL, plasma hepcidin-25, and the plasma NGAL:hepcidin-25 ratio for major adverse kidney events (MAKE) after cardiac surgery. Methods: We compared the predictive value of plasma NGAL, hepcidin-25, and plasma NGAL:hepcidin-25 with that of serum creatinine (Cr) and urinary output and protein for primary-endpoint MAKE (acute kidney injury [AKI] stages 2 and 3, persistent AKI >48 hours, acute dialysis, and in-hospital mortality) and secondary-endpoint AKI in 100 cardiac surgery patients at intensive care unit (ICU) admission. We performed ROC curve, logistic regression, and reclassification analyses. Results: At ICU admission, plasma NGAL, plasma NGAL:hepcidin-25, plasma interleukin-6, and Cr predicted MAKE (area under the ROC curve [AUC]: 0.77, 0.79, 0.74, and 0.74, respectively) and AKI (0.73, 0.89, 0.70, and 0.69). For AKI prediction, plasma NGAL:hepcidin-25 had a higher discriminatory power than Cr (AUC difference 0.26 [95% CI 0.00–0.53]). Urinary output and protein, plasma lactate, C-reactive protein, creatine kinase myocardial band, and brain natriuretic peptide did not predict MAKE or AKI (AUC <0.70). Only plasma NGAL:hepcidin-25 correctly reclassified patients according to their MAKE and AKI status (category-free net reclassification improvement: 0.82 [95% CI 0.12–1.52], 1.03 [0.29–1.77]). After adjustment to the Cleveland risk score, plasma NGAL:hepcidin-25 ≥0.9 independently predicted MAKE (adjusted odds ratio 16.34 [95% CI 1.77–150.49], P=0.014). Conclusions: Plasma NGAL:hepcidin-25 is a promising marker for predicting postoperative MAKE.

Biomarker-Guided Risk Assessment for Acute Kidney Injury: Time for Clinical Implementation?

Albert Christian,Haase Michael,Albert Annemarie,Zapf Antonia,Braun-Dullaeus Rüdiger Christian,Haase-Fielitz Anja 대한진단검사의학회 2021 Annals of Laboratory Medicine Vol.41 No.1

Acute kidney injury (AKI) is a common and serious complication in hospitalized patients, which continues to pose a clinical challenge for treating physicians. The most recent Kidney Disease Improving Global Outcomes practice guidelines for AKI have restated the importance of earliest possible detection of AKI and adjusting treatment accordingly. Since the emergence of initial studies examining the use of neutrophil gelatinase-associated lipocalin (NGAL) and cycle arrest biomarkers, tissue inhibitor metalloproteinase-2 (TIMP-2) and insulin-like growth factor-binding protein (IGFBP7), for early diagnosis of AKI, a vast number of studies have investigated the accuracy and additional clinical benefits of these biomarkers. As proposed by the Acute Dialysis Quality Initiative, new AKI diagnostic criteria should equally utilize glomerular function and tubular injury markers for AKI diagnosis. In addition to refining our capabilities in kidney risk prediction with kidney injury biomarkers, structural disorder phenotypes referred to as “preclinical-” and “subclinical AKI” have been described and are increasingly recognized. Additionally, positive biomarker test findings were found to provide prognostic information regardless of an acute decline in renal function (positive serum creatinine criteria). We summarize and discuss the recent findings focusing on two of the most promising and clinically available kidney injury biomarkers, NGAL and cell cycle arrest markers, in the context of AKI phenotypes. Finally, we draw conclusions regarding the clinical implications for kidney risk prediction.

Urinary Biomarkers may Complement the Cleveland Score for Prediction of Adverse Kidney Events After Cardiac Surgery: A Pilot Study

Christian Albert,Michael Haase,Annemarie Albert,Siegfried Kropf,Rinaldo Bellomo,Sabine Westphal,Mark Westerman,Rüdiger Christian Braun-Dullaeus,Anja Haase-Fielitz 대한진단검사의학회 2020 Annals of Laboratory Medicine Vol.40 No.2

Background: The ability of urinary biomarkers to complement established clinical risk prediction models for postoperative adverse kidney events is unclear. We assessed the effect of urinary biomarkers linked to suspected pathogenesis of cardiac surgery-induced acute kidney injury (AKI) on the performance of the Cleveland Score, a risk assessment model for postoperative adverse kidney events. Methods: This pilot study included 100 patients who underwent open-heart surgery. We determined improvements to the Cleveland Score when adding urinary biomarkers measured using clinical laboratory platforms (neutrophil gelatinase-associated lipocalin [NGAL], interleukin-6) and those in the preclinical stage (hepcidin-25, midkine, alpha-1 microglobulin), all sampled immediately post-surgery. The primary endpoint was major adverse kidney events (MAKE), and the secondary endpoint was AKI. We performed ROC curve analysis, assessed baseline model performance (odds ratios [OR], 95% CI), and carried out statistical reclassification analyses to assess model improvement. Results: NGAL (OR [95% CI] per 20 concentration-units wherever applicable): (1.07 [1.01–1.14]), Interleukin-6 (1.51 [1.01–2.26]), midkine (1.01 [1.00–1.02]), 1-hepcidin-25 (1.08 [1.00–1.17]), and NGAL/hepcidin-ratio (2.91 [1.30–6.49]) were independent predictors of MAKE and AKI (1.38 [1.03–1.85], 1.08 [1.01–1.15], 1.01 [1.00–1.02], 1.09 [1.01–1.18], and 3.45 [1.54–7.72]). Category-free net reclassification improvement identified interleukin-6 as a model-improving biomarker for MAKE and NGAL for AKI. However, only NGAL/hepcidin-25 improved model performance for event- and event-free patients for MAKE and AKI. Conclusions: NGAL and interleukin-6 measured immediately post cardiac surgery may complement the Cleveland Score. The com

Solid-State Ionic Liquid Additive Enhances Mobility in Conjugated Polymer Field-Effect Transistors

Albert Buertey Buer,조제웅 한국고분자학회 2024 한국고분자학회 학술대회 연구논문 초록집 Vol.49 No.1

역삼투 공정을 위한 모델링 총설 및 새로운 복합적 막오염도의 제안

Albert S. Kim 한국막학회 2017 멤브레인 Vol.27 No.4

해수담수화는 최근 전 세계적으로 대두되고 있는 물부족 현상을 해결하기 위한 최적 기술 중 하나이다. 막분리 및 투과 현상의 근본적인 이해는 차후의 막여과 기술의 발전을 위해서 뿐만 아니라, 현재 막기술 증진을 위한 통합적 디자인, 최적화 제어법, 그리고 중장기적 유지관리를 위해서도 매우 중요하다. 이에, 본 연구는 물질 전달 및 여과 현상에 대한 기존 의 주요 모델들을 상세히 재검토하고, 통계물리학에 근간하여 주요 막분리 현상들을 이론적으로 분석하며, 원천적 모델에 기 초한 물리적 의미와 그들이 실제 막공정에서 미치는 영향들에 대해서 함축적으로 토의하고자 한다. 이론적 재검토의 과정에 서 새로이 유도된 복합적 막오염도(Combined Fouling Index (CFI))의 소개도 포함한다. Seawater desalination is currently considered to be one of the primary technologies to resolve the global water scarcity problem. A basic understanding of membrane filtration phenomena is significant not only for further technological development but also for integrated design, optimal control, and long-term maintenance. In this vein, the present work reviews the major transport and filtration models, specifically related to reverse osmosis phenomena, provides theoretical insights based on statistical mechanics, and discusses model-based physical meanings as related to their practical implications.

Review of Basics Reverse Osmosis Process Modeling: A New Combined Fouling Index Proposed

Albert S. Kim 한국막학회 2017 멤브레인 Vol.27 No.4

Seawater desalination is currently considered to be one of the primary technologies to resolve the global water scarcity problem. A basic understanding of membrane filtration phenomena is significant not only for further technological development but also for integrated design, optimal control, and long-term maintenance. In this vein, the present work reviews the major transport and filtration models, specifically related to reverse osmosis phenomena, provides theoretical insights based on statistical mechanics, and discusses model-based physical meanings as related to their practical implications.

Who’s Afraid of the Big Bad Data? Some Critical Reflections on the Programme to Open Access to Health Data (The Catalan Approach)

Albert Ruda-Gonzalez 이화여자대학교 생명의료법연구소 2017 Asia Pacific Journal of Health Law & Ethics Vol.11 No.1

Recently, the regional government of Catalonia (Spain) has approved a programme to link the health information that is generated in this region. According to its description, the whole of health data of users of the health system will be interconnected in an absolutely anonymized and safe way. The aim of the programme, called PADRIS, is to promote and facilitate research and innovation in medicine and health sciences. The paper comments on such a programme from a critical perspective, bearing in mind its implications with regard to patients’ rights, in particular privacy and data protection.

The Role of Business Capabilities in Supporting Organization Agility and Performance During the COVID-19 Pandemic: An Empirical Study in Indonesia

Albert Surya WANASIDA,Innocentius BERNARTO,Niko SUDIBJO,Agus PURWANTO 한국유통과학회 2021 The Journal of Asian Finance, Economics and Busine Vol.8 No.5

This study aims to analyze the important role of business analytics capability, information quality, and innovation capability in influencing organization agility and organization performance during the Covid-19 pandemic. Data was collected from 76 companies from various sectors in Indonesia. Structural Equation Model-Partial Least Square (SEM-PLS) analysis was conducted to analyze the relationship between variables and test a series of hypotheses. Importance-Performance Matrix Analysis (IPMA), a useful analysis approach in PLS-SEM, is used, which extends the results of the estimated path coefficient (importance) by adding a dimension that considers the average values of the latent variable scores (performance). The IPMA approach examines not only the performance of an item but also the importance of that item. The results show that business analytics capability has a significant effect on information quality and innovation capability which then affects organization agility. Organizational performance is influenced by organizational agility. IPMA results show that organizational agility has the highest level of impact on organizational performance. This study will assist companies in planning business analytics, improving information quality, increasing innovation capability, and ultimately increasing agility and performance during the Covid-19 pandemic. This study will add to existing knowledge about previous literature, especially in the Covid-19 pandemic situation.