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5. Correction: 2023 Korean Society of Echocardiography position paper for diagnosis and management of valvular heart disease, part I: aortic valve disease

Author

Lee, Sun Hwa, Yoon, Se Jung, Sun, Byung Joo, Kim, Hyue Mee, Kim, Hyung Yoon, Lee, Sahmin, Shim, Chi Young, Kim, Eun Kyoung, Cho, Dong Hyuk, Park, Jun Bean, Seo, Jeong Sook, Son, Jung Woo, Kim, In Cheol, Lee, Sang Hyun, Heo, Ran, Lee, Hyun Jung, Park, Jae Hyeong, Song, Jong Min, Lee, Sang Chol, Kim, Hyungseop, Kang, Duk Hyun, Ha, Jong Won, and Kim, Kye Hun

Published
2024
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7. 2023 Korean Society of Echocardiography position paper for diagnosis and management of valvular heart disease, part I: aortic valve disease

Author

Lee, Sun Hwa, Yoon, Se-Jung, Sun, Byung Joo, Kim, Hyue Mee, Kim, Hyung Yoon, Lee, Sahmin, Shim, Chi Young, Kim, Eun Kyoung, Cho, Dong-Hyuk, Park, Jun-Bean, Seo, Jeong-Sook, Son, Jung-Woo, Kim, In-Cheol, Lee, Sang-Hyun, Heo, Ran, Lee, Hyun-Jung, Park, Jae-Hyeong, Song, Jong-Min, Lee, Sang-Chol, Kim, Hyungseop, Kang, Duk-Hyun, Ha, Jong-Won, and Kim, Kye Hun

Published
2024
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9. 2023 Korean Society of Echocardiography position paper for the diagnosis and management of valvular heart disease, part II: mitral and tricuspid valve disease

Author

Shim, Chi Young, Kim, Eun Kyoung, Cho, Dong-Hyuk, Park, Jun-Bean, Seo, Jeong-Sook, Son, Jung-Woo, Kim, In-Cheol, Lee, Sang-Hyun, Heo, Ran, Lee, Hyun-Jung, Lee, Sahmin, Sun, Byung Joo, Yoon, Se-Jung, Lee, Sun Hwa, Kim, Hyung Yoon, Kim, Hyue Mee, Park, Jae-Hyeong, Hong, Geu-Ru, Jung, Hae Ok, Kim, Yong-Jin, Kim, Kye Hun, Kang, Duk-Hyun, Ha, Jong-Won, and Kim, Hyungseop

Published
2024
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14. Know Your Self-supervised Learning: A Survey on Image-based Generative and Discriminative Training

Author

Ozbulak, Utku, Lee, Hyun Jung, Boga, Beril, Anzaku, Esla Timothy, Park, Homin, Van Messem, Arnout, De Neve, Wesley, and Vankerschaver, Joris

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence
Abstract

Although supervised learning has been highly successful in improving the state-of-the-art in the domain of image-based computer vision in the past, the margin of improvement has diminished significantly in recent years, indicating that a plateau is in sight. Meanwhile, the use of self-supervised learning (SSL) for the purpose of natural language processing (NLP) has seen tremendous successes during the past couple of years, with this new learning paradigm yielding powerful language models. Inspired by the excellent results obtained in the field of NLP, self-supervised methods that rely on clustering, contrastive learning, distillation, and information-maximization, which all fall under the banner of discriminative SSL, have experienced a swift uptake in the area of computer vision. Shortly afterwards, generative SSL frameworks that are mostly based on masked image modeling, complemented and surpassed the results obtained with discriminative SSL. Consequently, within a span of three years, over $100$ unique general-purpose frameworks for generative and discriminative SSL, with a focus on imaging, were proposed. In this survey, we review a plethora of research efforts conducted on image-oriented SSL, providing a historic view and paying attention to best practices as well as useful software packages. While doing so, we discuss pretext tasks for image-based SSL, as well as techniques that are commonly used in image-based SSL. Lastly, to aid researchers who aim at contributing to image-focused SSL, we outline a number of promising research directions., Comment: Published in Transactions on Machine Learning Research

Published
2023

19. Adherens junctions organize size-selective proteolytic hotspots critical for Notch signalling

Author

Kwak, Minsuk, Southard, Kaden M, Kim, Woon Ryoung, Lin, Annie, Kim, Nam Hyeong, Gopalappa, Ramu, Lee, Hyun Jung, An, Minji, Choi, Seo Hyun, Jung, Yunmin, Noh, Kunwoo, Farlow, Justin, Georgakopoulos, Anastasios, Robakis, Nikolaos K, Kang, Min K, Kutys, Matthew L, Seo, Daeha, Kim, Hyongbum Henry, Kim, Yong Ho, Cheon, Jinwoo, Gartner, Zev J, and Jun, Young-wook

Subjects
Biochemistry and Cell Biology, Biological Sciences, Neurosciences, Aging, Cancer, 1.1 Normal biological development and functioning, Generic health relevance, Amyloid Precursor Protein Secretases, Ligands, Medical and Health Sciences, Developmental Biology, Biochemistry and cell biology
Abstract

Adherens junctions (AJs) create spatially, chemically and mechanically discrete microdomains at cellular interfaces. Here, using a mechanogenetic platform that generates artificial AJs with controlled protein localization, clustering and mechanical loading, we find that AJs also organize proteolytic hotspots for γ-secretase with a spatially regulated substrate selectivity that is critical in the processing of Notch and other transmembrane proteins. Membrane microdomains outside of AJs exclusively organize Notch ligand-receptor engagement (LRE microdomains) to initiate receptor activation. Conversely, membrane microdomains within AJs exclusively serve to coordinate regulated intramembrane proteolysis (RIP microdomains). They do so by concentrating γ-secretase and primed receptors while excluding full-length Notch. AJs induce these functionally distinct microdomains by means of lipid-dependent γ-secretase recruitment and size-dependent protein segregation. By excluding full-length Notch from RIP microdomains, AJs prevent inappropriate enzyme-substrate interactions and suppress spurious Notch activation. Ligand-induced ectodomain shedding eliminates size-dependent segregation, releasing Notch to translocate into AJs for processing by γ-secretase. This mechanism directs radial differentiation of ventricular zone-neural progenitor cells in vivo and more broadly regulates the proteolysis of other large cell-surface receptors such as amyloid precursor protein. These findings suggest an unprecedented role of AJs in creating size-selective spatial switches that choreograph γ-secretase processing of multiple transmembrane proteins regulating development, homeostasis and disease.

Published
2022

35. Half metals at intermediate energy scales in Anderson-type insulators

Author

Park, Kyung-Yong, Lee, Hyun-Jung, and Kim, Ki-Seok

Subjects
Condensed Matter - Disordered Systems and Neural Networks, Condensed Matter - Strongly Correlated Electrons
Abstract

Although quantum phase transitions involved with Anderson localization had been investigated for more than a half century, the role of spin polarization in these metal-insulator transitions has not been clearly addressed as a function of both the range of interactions and energy scales. Based on the Anderson-Hartree-Fock study, we reveal that the spin polarization has nothing to do with Anderson metal-insulator transitions in three dimensions as far as effective interactions between electrons are long-ranged Coulomb type. On the other hand, we find that metal-insulator transitions appear with magnetism in the case of Hubbard-type local interactions. In particular, we show that the multifractal spectrum of spin $\uparrow$ electrons differs from that of spin $\downarrow$ at the high-energy mobility edge, which indicates the existence of spin-dependent universality classes for metal-insulator transitions. One of the most fascinating and rather unexpected results is the appearance of half metals at intermediate energy scales above the high-energy mobility edge in Anderson-type insulators of the Fermi energy, that is, only spin $\uparrow$ electrons are delocalized while spin $\downarrow$ electrons are Anderson-type localized.

Published
2020
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46. General Conclusion

Author

Lee, Hyun Jung, Krajewski, Markus, Editor-in-Chief, Bendel, Petra, Series Editor, Bielefeldt, Heiner, Series Editor, Frewer, Andreas, Series Editor, Pirner, Manfred L., Series Editor, and Lee, Hyun Jung

Published
2022
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47. Case Analysis: Same-Sex Marriage

Author

Lee, Hyun Jung, Krajewski, Markus, Editor-in-Chief, Bendel, Petra, Series Editor, Bielefeldt, Heiner, Series Editor, Frewer, Andreas, Series Editor, Pirner, Manfred L., Series Editor, and Lee, Hyun Jung

Published
2022
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