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1. Losses resistant verification of quantum non-Gaussian photon statistics

Author

Checchinato, Riccardo, Littmann, Jan-Heinrich, Lachman, Lukáš, Lee, Jaewon, Höfling, Sven, Schneider, Christian, Filip, Radim, and Predojević, Ana

Subjects
Quantum Physics
Abstract

Quantum non-Gaussian states of light have fundamental properties that are essential for a multitude of applications in quantum technology. However, many of these features are difficult to detect using standard criteria due to optical losses and detector inefficiency. As the statistics of light are unknown, the loss correction on the data is unreliable, despite the fact that the losses can be precisely measured. To address this issue, we employ a loss-mitigated verification technique utilising quantum non-Gaussian witnesses, which incorporate the known optical losses and detector inefficiency into their derivation. This approach allows us to address the considerable challenge of experimentally demonstrating unheralded quantum non-Gaussian states of single photons and photon pairs., Comment: 5 pages, 3 figures and supplemental material (2 pages)

Published
2024

2. Certifiable Deep Learning for Reachability Using a New Lipschitz Continuous Value Function

Author

Li, Jingqi, Lee, Donggun, Lee, Jaewon, Dong, Kris Shengjun, Sojoudi, Somayeh, and Tomlin, Claire

Subjects
Electrical Engineering and Systems Science - Systems and Control
Abstract

We propose a new reachability learning framework for high-dimensional nonlinear systems, focusing on reach-avoid problems. These problems require computing the reach-avoid set, which ensures that all its elements can safely reach a target set despite any disturbance within pre-specified bounds. Our framework has two main parts: offline learning of a newly designed reach-avoid value function and post-learning certification. Compared to prior works, our new value function is Lipschitz continuous and its associated Bellman operator is a contraction mapping, both of which improve the learning performance. To ensure deterministic guarantees of our learned reach-avoid set, we introduce two efficient post-learning certification methods. Both methods can be used online for real-time local certification or offline for comprehensive certification. We validate our framework in a 12-dimensional crazyflie drone racing hardware experiment and a simulated 10-dimensional highway takeover example., Comment: Submitted, under review

Published
2024

3. The Llama 3 Herd of Models

Author

Dubey, Abhimanyu, Jauhri, Abhinav, Pandey, Abhinav, Kadian, Abhishek, Al-Dahle, Ahmad, Letman, Aiesha, Mathur, Akhil, Schelten, Alan, Yang, Amy, Fan, Angela, Goyal, Anirudh, Hartshorn, Anthony, Yang, Aobo, Mitra, Archi, Sravankumar, Archie, Korenev, Artem, Hinsvark, Arthur, Rao, Arun, Zhang, Aston, Rodriguez, Aurelien, Gregerson, Austen, Spataru, Ava, Roziere, Baptiste, Biron, Bethany, Tang, Binh, Chern, Bobbie, Caucheteux, Charlotte, Nayak, Chaya, Bi, Chloe, Marra, Chris, McConnell, Chris, Keller, Christian, Touret, Christophe, Wu, Chunyang, Wong, Corinne, Ferrer, Cristian Canton, Nikolaidis, Cyrus, Allonsius, Damien, Song, Daniel, Pintz, Danielle, Livshits, Danny, Esiobu, David, Choudhary, Dhruv, Mahajan, Dhruv, Garcia-Olano, Diego, Perino, Diego, Hupkes, Dieuwke, Lakomkin, Egor, AlBadawy, Ehab, Lobanova, Elina, Dinan, Emily, Smith, Eric Michael, Radenovic, Filip, Zhang, Frank, Synnaeve, Gabriel, Lee, Gabrielle, Anderson, Georgia Lewis, Nail, Graeme, Mialon, Gregoire, Pang, Guan, Cucurell, Guillem, Nguyen, Hailey, Korevaar, Hannah, Xu, Hu, Touvron, Hugo, Zarov, Iliyan, Ibarra, Imanol Arrieta, Kloumann, Isabel, Misra, Ishan, Evtimov, Ivan, Copet, Jade, Lee, Jaewon, Geffert, Jan, Vranes, Jana, Park, Jason, Mahadeokar, Jay, Shah, Jeet, van der Linde, Jelmer, Billock, Jennifer, Hong, Jenny, Lee, Jenya, Fu, Jeremy, Chi, Jianfeng, Huang, Jianyu, Liu, Jiawen, Wang, Jie, Yu, Jiecao, Bitton, Joanna, Spisak, Joe, Park, Jongsoo, Rocca, Joseph, Johnstun, Joshua, Saxe, Joshua, Jia, Junteng, Alwala, Kalyan Vasuden, Upasani, Kartikeya, Plawiak, Kate, Li, Ke, Heafield, Kenneth, Stone, Kevin, El-Arini, Khalid, Iyer, Krithika, Malik, Kshitiz, Chiu, Kuenley, Bhalla, Kunal, Rantala-Yeary, Lauren, van der Maaten, Laurens, Chen, Lawrence, Tan, Liang, Jenkins, Liz, Martin, Louis, Madaan, Lovish, Malo, Lubo, Blecher, Lukas, Landzaat, Lukas, de Oliveira, Luke, Muzzi, Madeline, Pasupuleti, Mahesh, Singh, Mannat, Paluri, Manohar, Kardas, Marcin, Oldham, Mathew, Rita, Mathieu, Pavlova, Maya, Kambadur, Melanie, Lewis, Mike, Si, Min, Singh, Mitesh Kumar, Hassan, Mona, Goyal, Naman, Torabi, Narjes, Bashlykov, Nikolay, Bogoychev, Nikolay, Chatterji, Niladri, Duchenne, Olivier, Çelebi, Onur, Alrassy, Patrick, Zhang, Pengchuan, Li, Pengwei, Vasic, Petar, Weng, Peter, Bhargava, Prajjwal, Dubal, Pratik, Krishnan, Praveen, Koura, Punit Singh, Xu, Puxin, He, Qing, Dong, Qingxiao, Srinivasan, Ragavan, Ganapathy, Raj, Calderer, Ramon, Cabral, Ricardo Silveira, Stojnic, Robert, Raileanu, Roberta, Girdhar, Rohit, Patel, Rohit, Sauvestre, Romain, Polidoro, Ronnie, Sumbaly, Roshan, Taylor, Ross, Silva, Ruan, Hou, Rui, Wang, Rui, Hosseini, Saghar, Chennabasappa, Sahana, Singh, Sanjay, Bell, Sean, Kim, Seohyun Sonia, Edunov, Sergey, Nie, Shaoliang, Narang, Sharan, Raparthy, Sharath, Shen, Sheng, Wan, Shengye, Bhosale, Shruti, Zhang, Shun, Vandenhende, Simon, Batra, Soumya, Whitman, Spencer, Sootla, Sten, Collot, Stephane, Gururangan, Suchin, Borodinsky, Sydney, Herman, Tamar, Fowler, Tara, Sheasha, Tarek, Georgiou, Thomas, Scialom, Thomas, Speckbacher, Tobias, Mihaylov, Todor, Xiao, Tong, Karn, Ujjwal, Goswami, Vedanuj, Gupta, Vibhor, Ramanathan, Vignesh, Kerkez, Viktor, Gonguet, Vincent, Do, Virginie, Vogeti, Vish, Petrovic, Vladan, Chu, Weiwei, Xiong, Wenhan, Fu, Wenyin, Meers, Whitney, Martinet, Xavier, Wang, Xiaodong, Tan, Xiaoqing Ellen, Xie, Xinfeng, Jia, Xuchao, Wang, Xuewei, Goldschlag, Yaelle, Gaur, Yashesh, Babaei, Yasmine, Wen, Yi, Song, Yiwen, Zhang, Yuchen, Li, Yue, Mao, Yuning, Coudert, Zacharie Delpierre, Yan, Zheng, Chen, Zhengxing, Papakipos, Zoe, Singh, Aaditya, Grattafiori, Aaron, Jain, Abha, Kelsey, Adam, Shajnfeld, Adam, Gangidi, Adithya, Victoria, Adolfo, Goldstand, Ahuva, Menon, Ajay, Sharma, Ajay, Boesenberg, Alex, Vaughan, Alex, Baevski, Alexei, Feinstein, Allie, Kallet, Amanda, Sangani, Amit, Yunus, Anam, Lupu, Andrei, Alvarado, Andres, Caples, Andrew, Gu, Andrew, Ho, Andrew, Poulton, Andrew, Ryan, Andrew, Ramchandani, Ankit, Franco, Annie, Saraf, Aparajita, Chowdhury, Arkabandhu, Gabriel, Ashley, Bharambe, Ashwin, Eisenman, Assaf, Yazdan, Azadeh, James, Beau, Maurer, Ben, Leonhardi, Benjamin, Huang, Bernie, Loyd, Beth, De Paola, Beto, Paranjape, Bhargavi, Liu, Bing, Wu, Bo, Ni, Boyu, Hancock, Braden, Wasti, Bram, Spence, Brandon, Stojkovic, Brani, Gamido, Brian, Montalvo, Britt, Parker, Carl, Burton, Carly, Mejia, Catalina, Wang, Changhan, Kim, Changkyu, Zhou, Chao, Hu, Chester, Chu, Ching-Hsiang, Cai, Chris, Tindal, Chris, Feichtenhofer, Christoph, Civin, Damon, Beaty, Dana, Kreymer, Daniel, Li, Daniel, Wyatt, Danny, Adkins, David, Xu, David, Testuggine, Davide, David, Delia, Parikh, Devi, Liskovich, Diana, Foss, Didem, Wang, Dingkang, Le, Duc, Holland, Dustin, Dowling, Edward, Jamil, Eissa, Montgomery, Elaine, Presani, Eleonora, Hahn, Emily, Wood, Emily, Brinkman, Erik, Arcaute, Esteban, Dunbar, Evan, Smothers, Evan, Sun, Fei, Kreuk, Felix, Tian, Feng, Ozgenel, Firat, Caggioni, Francesco, Guzmán, Francisco, Kanayet, Frank, Seide, Frank, Florez, Gabriela Medina, Schwarz, Gabriella, Badeer, Gada, Swee, Georgia, Halpern, Gil, Thattai, Govind, Herman, Grant, Sizov, Grigory, Guangyi, Zhang, Lakshminarayanan, Guna, Shojanazeri, Hamid, Zou, Han, Wang, Hannah, Zha, Hanwen, Habeeb, Haroun, Rudolph, Harrison, Suk, Helen, Aspegren, Henry, Goldman, Hunter, Damlaj, Ibrahim, Molybog, Igor, Tufanov, Igor, Veliche, Irina-Elena, Gat, Itai, Weissman, Jake, Geboski, James, Kohli, James, Asher, Japhet, Gaya, Jean-Baptiste, Marcus, Jeff, Tang, Jeff, Chan, Jennifer, Zhen, Jenny, Reizenstein, Jeremy, Teboul, Jeremy, Zhong, Jessica, Jin, Jian, Yang, Jingyi, Cummings, Joe, Carvill, Jon, Shepard, Jon, McPhie, Jonathan, Torres, Jonathan, Ginsburg, Josh, Wang, Junjie, Wu, Kai, U, Kam Hou, Saxena, Karan, Prasad, Karthik, Khandelwal, Kartikay, Zand, Katayoun, Matosich, Kathy, Veeraraghavan, Kaushik, Michelena, Kelly, Li, Keqian, Huang, Kun, Chawla, Kunal, Lakhotia, Kushal, Huang, Kyle, Chen, Lailin, Garg, Lakshya, A, Lavender, Silva, Leandro, Bell, Lee, Zhang, Lei, Guo, Liangpeng, Yu, Licheng, Moshkovich, Liron, Wehrstedt, Luca, Khabsa, Madian, Avalani, Manav, Bhatt, Manish, Tsimpoukelli, Maria, Mankus, Martynas, Hasson, Matan, Lennie, Matthew, Reso, Matthias, Groshev, Maxim, Naumov, Maxim, Lathi, Maya, Keneally, Meghan, Seltzer, Michael L., Valko, Michal, Restrepo, Michelle, Patel, Mihir, Vyatskov, Mik, Samvelyan, Mikayel, Clark, Mike, Macey, Mike, Wang, Mike, Hermoso, Miquel Jubert, Metanat, Mo, Rastegari, Mohammad, Bansal, Munish, Santhanam, Nandhini, Parks, Natascha, White, Natasha, Bawa, Navyata, Singhal, Nayan, Egebo, Nick, Usunier, Nicolas, Laptev, Nikolay Pavlovich, Dong, Ning, Zhang, Ning, Cheng, Norman, Chernoguz, Oleg, Hart, Olivia, Salpekar, Omkar, Kalinli, Ozlem, Kent, Parkin, Parekh, Parth, Saab, Paul, Balaji, Pavan, Rittner, Pedro, Bontrager, Philip, Roux, Pierre, Dollar, Piotr, Zvyagina, Polina, Ratanchandani, Prashant, Yuvraj, Pritish, Liang, Qian, Alao, Rachad, Rodriguez, Rachel, Ayub, Rafi, Murthy, Raghotham, Nayani, Raghu, Mitra, Rahul, Li, Raymond, Hogan, Rebekkah, Battey, Robin, Wang, Rocky, Maheswari, Rohan, Howes, Russ, Rinott, Ruty, Bondu, Sai Jayesh, Datta, Samyak, Chugh, Sara, Hunt, Sara, Dhillon, Sargun, Sidorov, Sasha, Pan, Satadru, Verma, Saurabh, Yamamoto, Seiji, Ramaswamy, Sharadh, Lindsay, Shaun, Feng, Sheng, Lin, Shenghao, Zha, Shengxin Cindy, Shankar, Shiva, Zhang, Shuqiang, Wang, Sinong, Agarwal, Sneha, Sajuyigbe, Soji, Chintala, Soumith, Max, Stephanie, Chen, Stephen, Kehoe, Steve, Satterfield, Steve, Govindaprasad, Sudarshan, Gupta, Sumit, Cho, Sungmin, Virk, Sunny, Subramanian, Suraj, Choudhury, Sy, Goldman, Sydney, Remez, Tal, Glaser, Tamar, Best, Tamara, Kohler, Thilo, Robinson, Thomas, Li, Tianhe, Zhang, Tianjun, Matthews, Tim, Chou, Timothy, Shaked, Tzook, Vontimitta, Varun, Ajayi, Victoria, Montanez, Victoria, Mohan, Vijai, Kumar, Vinay Satish, Mangla, Vishal, Albiero, Vítor, Ionescu, Vlad, Poenaru, Vlad, Mihailescu, Vlad Tiberiu, Ivanov, Vladimir, Li, Wei, Wang, Wenchen, Jiang, Wenwen, Bouaziz, Wes, Constable, Will, Tang, Xiaocheng, Wang, Xiaofang, Wu, Xiaojian, Wang, Xiaolan, Xia, Xide, Wu, Xilun, Gao, Xinbo, Chen, Yanjun, Hu, Ye, Jia, Ye, Qi, Ye, Li, Yenda, Zhang, Yilin, Zhang, Ying, Adi, Yossi, Nam, Youngjin, Yu, Wang, Hao, Yuchen, Qian, Yundi, He, Yuzi, Rait, Zach, DeVito, Zachary, Rosnbrick, Zef, Wen, Zhaoduo, Yang, Zhenyu, and Zhao, Zhiwei

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

Modern artificial intelligence (AI) systems are powered by foundation models. This paper presents a new set of foundation models, called Llama 3. It is a herd of language models that natively support multilinguality, coding, reasoning, and tool usage. Our largest model is a dense Transformer with 405B parameters and a context window of up to 128K tokens. This paper presents an extensive empirical evaluation of Llama 3. We find that Llama 3 delivers comparable quality to leading language models such as GPT-4 on a plethora of tasks. We publicly release Llama 3, including pre-trained and post-trained versions of the 405B parameter language model and our Llama Guard 3 model for input and output safety. The paper also presents the results of experiments in which we integrate image, video, and speech capabilities into Llama 3 via a compositional approach. We observe this approach performs competitively with the state-of-the-art on image, video, and speech recognition tasks. The resulting models are not yet being broadly released as they are still under development.

Published
2024

4. Obstructing two-torsion in the rational knot concordance group

Author

Lee, Jaewon

Subjects
Mathematics - Geometric Topology, 57K10
Abstract

It is well known that there are many 2-torsion elements in the classical knot concordance group. On the other hand, it is not known if there is any torsion element in the rational knot concordance group $\mathcal{C}_\mathbb{Q}$. Cha defined the algebraic rational concordance group $\mathcal{AC}_\mathbb{Q}$, an analogue of the classical algebraic concordance group, and showed that $\mathcal{AC}_\mathbb{Q}\cong\mathbb{Z}^\infty\oplus\mathbb{Z}_2^\infty\oplus\mathbb{Z}_4^\infty$. The knots that represent 2-torsions in $\mathcal{AC}_\mathbb{Q}$ potentially have order $2$ in $\mathcal{C}_\mathbb{Q}$. In this paper, we provide an obstruction for knots of order $2$ in $\mathcal{AC}_\mathbb{Q}$ from being of finite order in $\mathcal{C}_\mathbb{Q}$. Moreover, we give a family consisting of such knots that generates an infinite rank subgroup of $\mathcal{C}_\mathbb{Q}$. We also note that Cha proved that in higher dimensions, the algebraic rational concordance order is the same as the rational knot concordance order. Our obstruction is based on the localized von Neumann $\rho$-invariant., Comment: 22 pages, 5 figures

Published
2024

5. Fast Global Localization on Neural Radiance Field

Author

Kong, Mangyu, Lee, Seongwon, Lee, Jaewon, and Kim, Euntai

Subjects
Computer Science - Robotics
Abstract

Neural Radiance Fields (NeRF) presented a novel way to represent scenes, allowing for high-quality 3D reconstruction from 2D images. Following its remarkable achievements, global localization within NeRF maps is an essential task for enabling a wide range of applications. Recently, Loc-NeRF demonstrated a localization approach that combines traditional Monte Carlo Localization with NeRF, showing promising results for using NeRF as an environment map. However, despite its advancements, Loc-NeRF encounters the challenge of a time-intensive ray rendering process, which can be a significant limitation in practical applications. To address this issue, we introduce Fast Loc-NeRF, which leverages a coarse-to-fine approach to enable more efficient and accurate NeRF map-based global localization. Specifically, Fast Loc-NeRF matches rendered pixels and observed images on a multi-resolution from low to high resolution. As a result, it speeds up the costly particle update process while maintaining precise localization results. Additionally, to reject the abnormal particles, we propose particle rejection weighting, which estimates the uncertainty of particles by exploiting NeRF's characteristics and considers them in the particle weighting process. Our Fast Loc-NeRF sets new state-of-the-art localization performances on several benchmarks, convincing its accuracy and efficiency., Comment: Preprint, Under review

Published
2024

6. SUTRA: Scalable Multilingual Language Model Architecture

Author

Bendale, Abhijit, Sapienza, Michael, Ripplinger, Steven, Gibbs, Simon, Lee, Jaewon, and Mistry, Pranav

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract

In this paper, we introduce SUTRA, multilingual Large Language Model architecture capable of understanding, reasoning, and generating text in over 50 languages. SUTRA's design uniquely decouples core conceptual understanding from language-specific processing, which facilitates scalable and efficient multilingual alignment and learning. Employing a Mixture of Experts framework both in language and concept processing, SUTRA demonstrates both computational efficiency and responsiveness. Through extensive evaluations, SUTRA is demonstrated to surpass existing models like GPT-3.5, Llama2 by 20-30% on leading Massive Multitask Language Understanding (MMLU) benchmarks for multilingual tasks. SUTRA models are also online LLMs that can use knowledge from the internet to provide hallucination-free, factual and up-to-date responses while retaining their multilingual capabilities. Furthermore, we explore the broader implications of its architecture for the future of multilingual AI, highlighting its potential to democratize access to AI technology globally and to improve the equity and utility of AI in regions with predominantly non-English languages. Our findings suggest that SUTRA not only fills pivotal gaps in multilingual model capabilities but also establishes a new benchmark for operational efficiency and scalability in AI applications.

Published
2024

7. Achieving Optical Refractive Index of 10-Plus by Colloidal Self-Assembly

Author

Kim, NaYeoun, Huh, Ji-Hyeok, Cho, YongDeok, Park, Sung Hun, Kim, Hyeon Ho, Rho, Kyung Hun, Lee, Jaewon, and Lee, Seungwoo

Subjects
Physics - Optics, Condensed Matter - Materials Science
Abstract

This study demonstrates the developments of self-assembled optical metasurfaces to overcome inherent limitations in polarization density (P) within natural materials, which hinder achieving high refractive indices (n) at optical frequencies. The Maxwellian macroscopic description establishes a link between P and n, revealing a static limit in natural materials, restricting n to approximately 4.0 at optical frequencies. Optical metasurfaces, utilizing metallic colloids on a deep-subwavelength scale, offer a solution by unnaturally enhancing n through electric dipolar (ED) resonances. Self-assembly enables the creation of nanometer-scale metallic gaps between metallic nanoparticles (NPs), paving the way for achieving exceptionally high n at optical frequencies. This study focuses on assembling polyhedral gold (Au) NPs into a closely packed monolayer by rationally designing the polymeric ligand to balance attractive and repulsive forces, in that polymeric brush-mediated self-assembly of the close-packed Au NP monolayer is robustly achieved over a large-area. The resulting monolayer of Au nanospheres (NSs), nanooctahedras (NOs), and nanocubes (NCs) exhibits high macroscopic integrity and crystallinity, sufficiently enough for pushing n to record-high regimes. The study underlies the significance of capacitive coupling in achieving an unnaturally high n and explores fine-tuning Au NC size to optimize this coupling. The achieved n of 10.12 at optical frequencies stands as a benchmark, highlighting the potential of polyhedral Au NPs in advancing optical metasurfaces.

Published
2024

21. Enhancing Inter-Patient Performance for Arrhythmia Classification with Adversarial Learning Using Beat-Score Maps.

Author

Jeong, Yeji, Lee, Jaewon, and Shin, Miyoung

Subjects
DATABASES, INDIVIDUAL differences, ELECTROCARDIOGRAPHY, CLASSIFICATION, GENERALIZATION, ARRHYTHMIA
Abstract

Research on computer-aided arrhythmia classification is actively conducted, but the limited generalization capacity constrains its applicability in practical clinical settings. One of the primary challenges in deploying such techniques in real-world scenarios is the inter-patient variability and the consequent performance degradation. In this study, we leverage our previous innovation, the n-beat-score map (n-BSM), to introduce an adversarial framework to mitigate the issue of poor performance in arrhythmia classification within the inter-patient paradigm. The n-BSM is a 2D representation of the ECG signal, capturing its constituent beat characteristics through beat-score vectors derived from a pre-trained beat classifier. We employ adversarial learning to eliminate patient-dependent features during the training of the beat classifier, thereby generating the patient-independent n-BSM (PI-BSM). This approach enables us to concentrate primarily on the learning characteristics associated with beat type rather than patient-specific features. Through a beat classifier pre-trained with adversarial learning, a series of beat-score vectors are generated for the beat segments that make up a given ECG signal. These vectors are then concatenated chronologically to form a PI-BSM. Utilizing PI-BSMs as the input, an arrhythmia classifier is trained to differentiate between distinct types of rhythms. This approach yields a 14.27% enhancement in the F1-score in the MIT-BIH arrhythmia database and a 4.97% improvement in cross-database evaluation using the Chapman–Shaoxing 12-lead ECG database. [ABSTRACT FROM AUTHOR]

Published
2024
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22. PAR2‐mediated cellular senescence promotes inflammation and fibrosis in aging and chronic kidney disease.

Author

Ha, Sugyeong, Kim, Hyun Woo, Kim, Kyung Mok, Kim, Byeong Moo, Kim, Jeongwon, Son, Minjung, Kim, Doyeon, Kim, Mi‐Jeong, Yoo, Jian, Yu, Hak Sun, Jung, Young‐Suk, Lee, Jaewon, Chung, Hae Young, and Chung, Ki Wung

Subjects
FATTY acid oxidation, RENAL fibrosis, CHRONIC kidney failure, KIDNEY diseases, EPITHELIAL cells, CELLULAR aging
Abstract

Cellular senescence contributes to inflammatory kidney disease via the secretion of inflammatory and profibrotic factors. Protease‐activating receptor 2 (PAR2) is a key regulator of inflammation in kidney diseases. However, the relationship between PAR2 and cellular senescence in kidney disease has not yet been described. In this study, we found that PAR2‐mediated metabolic changes in renal tubular epithelial cells induced cellular senescence and increased inflammatory responses. Using an aging and renal injury model, PAR2 expression was shown to be associated with cellular senescence. Under in vitro conditions in NRK52E cells, PAR2 activation induces tubular epithelial cell senescence and senescent cells showed defective fatty acid oxidation (FAO). Cpt1α inhibition showed similar senescent phenotype in the cells, implicating the important role of defective FAO in senescence. Finally, we subjected mice lacking PAR2 to aging and renal injury. PAR2‐deficient kidneys are protected from adenine‐ and cisplatin‐induced renal fibrosis and injury, respectively, by reducing senescence and inflammation. Moreover, kidneys lacking PAR2 exhibited reduced numbers of senescent cells and inflammation during aging. These findings offer fresh insights into the mechanisms underlying renal senescence and indicate that targeting PAR2 or FAO may be a promising therapeutic approach for managing kidney injury. [ABSTRACT FROM AUTHOR]

Published
2024
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27. PCSK9 stimulates Syk, PKCδ, and NF-κB, leading to atherosclerosis progression independently of LDL receptor

Author

Shin, Dasom, primary, Kim, Soungchan, additional, Lee, Hwan, additional, Lee, Hyun-Chae, additional, Lee, Jaewon, additional, Park, Hyun-woo, additional, Fukai, Mina, additional, Choi, EunByule, additional, Choi, Subin, additional, Koo, Bon-Jun, additional, Yu, Ji-Hoon, additional, No, Gyurae, additional, Cho, Sungyoon, additional, Kim, Chan Woo, additional, Han, Dohyun, additional, Jang, Hyun-Duk, additional, and Kim, Hyo-Soo, additional

Published
2024
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31. Uncovering receptor-ligand interactions using a high-avidity CRISPR activation screening platform

Author

Yang, Liping, primary, Sheets, Timothy P., additional, Feng, Yang, additional, Yu, Guojun, additional, Bajgain, Pradip, additional, Hsu, Kuo-Sheng, additional, So, Daeho, additional, Seaman, Steven, additional, Lee, Jaewon, additional, Lin, Ling, additional, Evans, Christine N., additional, Guest, Mary R., additional, Chari, Raj, additional, and St. Croix, Brad, additional

Published
2024
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32. Using engineered broadband micropillar cavity photon pair source based on quantum dots to study two-photon interference and its dependency on temporal correlation, decoherence, and postselection

Author

Lee, Jaewon and Lee, Jaewon

Abstract

Entangled photon pairs play a crucial role in quantum information processing such as quantumkey distribution, linear optical quantum computation, quantum teleportation, entanglement swapping, etc. Quantum dots have gathered much attention due to their deterministic generation of the photon pairs. The emission process of the photon pair in a quantum dot relies on the cascaded spontaneous emission of a three-level system. Time correlations between emitted photons arise because of their time-ordered emissions. The time correlations lead to low purities of photonic states, resulting in deteriorated photon indistinguishability. We explore the visibility of the two-photon interference depending on the coherence times. Furthermore, we investigate the photon indistinguishability in the cascade emissions by executing the temporal post-selection from a triggered two-photon interference. Low photon collection efficiency calls for a photonic structure such as a micropillar cavity. The usual technique is to adopt the Purcell enhancement. However, this benchmark is not suitable for biexciton-exciton photon pairs because biexciton and exciton photons have different energies. We developed a new paradigm to increase the collection efficiency based on suppression of the emission into the outside of cavity mode using the low-quality factor cavity, which contradicts the conventional method relying on the Purcell enhancement.

Published
2024

36. Risk factors for incisional hernia after liver transplantation in the era of mammalian target of rapamycin inhibitors use: a retrospective study of living donor liver transplantation dominant center in Korea

Author

Kim, Jae-Yoon, primary, Hong, Suk Kyun, additional, Kim, Jiyoung, additional, Choi, Hyun Hwa, additional, Lee, Jaewon, additional, Hong, Su young, additional, Lee, Jeong-Moo, additional, Choi, YoungRok, additional, Yi, Nam-Joon, additional, Lee, Kwang-Woong, additional, and Suh, Kyung-Suk, additional

Published
2024
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38. Comparison of numerical codes for coupled thermo-hydro-mechanical simulations of fractured media

Author

Zareidarmiyan, Ahmad, Salarirad, Hossein, Vilarrasa, Victor, Kim, Kwang-Il, Lee, Jaewon, and Min, Ki-Bok

Abstract

Geo-energy and geo-engineering applications, such as improved oil recovery (IOR), geologic carbon storage, and enhanced geothermal systems (EGSs), involve coupled thermo-hydro-mechanical (THM) processes that result from fluid injection and production. In some cases, reservoirs are highly fractured and the geomechanical response is controlled by fractures. Therefore, fractures should explicitly be included into numerical models to realistically simulate the THM responses of the subsurface. In this study, we perform coupled THM numerical simulations of water injection into naturally fractured reservoirs (NFRs) using CODE_BRIGHT and TOUGH-UDEC codes. CODE_BRIGHT is a finite element method (FEM) code that performs fully coupled THM analysis in geological media and TOUGH-UDEC sequentially solves coupled THM processes by combining a finite volume method (FVM) code that solves non-isothermal multiphase flow (TOUGH2) with a distinct element method (DEM) code that solves the mechanical problem (UDEC). First, we validate the two codes against a semi-analytical solution for water injection into a single deformable fracture considering variable permeability based on the cubic law. Then, we compare simulation results of the two codes in an idealized conceptual model that includes one horizontal fracture and in a more realistic model with multiple fractures. Each code models fractures differently. UDEC calculates fracture deformation from the fracture normal and shear stiffnesses, while CODE_BRIGHT treats fractures as equivalent porous media and uses the equivalent Young's modulus and Poisson's ratio of the fracture. Finally, we obtain comparable results of pressure, temperature, stress and displacement distributions and evolutions for the single horizontal fracture model. Despite some similarities, the two codes provide increasingly different results as model complexity increases. These differences highlight the challenging task of accurately modeling coupled THM processes in fractured media given their high nonlinearity.

Published
2024
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39. Lateral Electronic Junction of a Single Ultrathin Silicon Induced by Interfacial Dipole of Self-Assembled Monolayer.

Author

Han J, Lee WH, Park J, Jin H, Cho YH, Yu S, Li L, Lee J, Woo G, Kim T, and Kim YS

Abstract

Interface engineering is pivotal for enhancing the performance and stability of devices with layered structures, including solar cells, electronic devices, and electrochemical systems. Incorporating the interfacial dipole between the bulk layers effectively modulates the energy level difference at the interface and does not significantly influence adjacent layers overall. However, interfaces can drastically affect adjoining layers in ultrathin devices, which are essential for next-generation electronics with high integrity, excellent performance, and low power consumption. In particular, the interfacial effect is pronounced in ultrathin semiconductors, which have a weak electric field screening effect. Herein, the substantial interfacial impact on the ultrathin silicon is shown, the p- to n-type inversion of the semiconductor solely through the deposition of a self-assembled monolayer (SAM) without external bias. The effects of SAMs with different interfacial dipoles are investigated by using Hall measurement and surface analytic techniques, such as UPS, XPS, and KPFM. Furthermore, the lateral electronic junction of the ultrathin silicon is engineered by the regioselective deposition of SAMs with opposite dipoles, and the device exhibits rectification behavior. When the interfacial dipole of SAM is manipulated, the rectification ratio changes sensitively, and thus the fabricated diode shows potential to be developed as a sensing platform., (© 2024 The Author(s). Advanced Science published by Wiley‐VCH GmbH.)

Published
2024
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40. Synergistic Enhancement of Electron Dynamics and Optical Properties in Zeolitic Imidazolate Framework-8-Derived Zinc Oxide via Surface Plasmon Resonance Effects of Silver Nanoparticles under UV Irradiation.

Author

Lee J and Park BN

Abstract

This study investigates the surface plasmon resonance (SPR)-induced UV photoresponse of zinc oxide (ZnO) derived from zeolitic imidazolate framework-8 (ZIF-8) to assess the influence of silver nanoparticles (Ag NPs) on the photoresponse behavior of metal-organic framework (MOF)-derived ZnO. The initial synthesis involved a thermal treatment in air to convert ZIF-8 into ZnO. We noted enhanced optical absorption both in the UV and visible spectra with the deposition of Ag NPs onto the ZIF-8-derived ZnO. Additionally, the presence of Ag NPs in the ZnO resulted in a substantial increase in current, even without any light exposure. This increase is attributed to the transfer of electrons from the Ag NPs to the ZnO. Photocurrent measurements under UV illumination revealed that the photocurrent with Ag NPs was significantly higher-by two orders of magnitude-compared with that without Ag NPs. This demonstrates that SPR-induced absorption markedly boosted the photocurrent, although the current rise and decay time constants remained comparable to those observed with ZnO alone. Although Ag NPs contribute electrons to ZnO, creating a "pre-doping" effect that heightens baseline conductivity (even in the absence of light), this does not necessarily alter the recombination dynamics of the photogenerated carriers, as indicated by the similar rise and decay time constants. The electron transfer from Ag to ZnO increases the density of charge carriers but does not significantly influence their recombination.

Published
2024
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41. Resistin Regulates Inflammation and Insulin Resistance in Humans via the Endocannabinoid System.

Author

Yang HM, Kim J, Kim BK, Seo HJ, Kim JY, Lee JE, Lee J, You J, Jin S, Kwon YW, Jang HD, and Kim HS

Abstract

Resistin plays an important role in the pathophysiology of obesity-mediated insulin resistance in mice. However, the biology of resistin in humans is quite different from that in rodents. Therefore, the association between resistin and insulin resistance remains unclear in humans. Here, we tested whether and how the endocannabinoid system (ECS) control circulating peripheral blood mononuclear cells (PBMCs) that produce resistin and infiltrate into the adipose tissue, heart, skeletal muscle, and liver, resulting in inflammation and insulin resistance. Using human PBMCs, we investigate whether the ECS is connected to human resistin. To test whether the ECS regulates inflammation and insulin resistance in vivo, we used 2 animal models such as "humanized" nonobese diabetic/Shi-severe combined immunodeficient interleukin-2Rγ (null) (NOG) mice and "humanized" resistin mouse models, which mimic human body. In human atheromatous plaques, cannabinoid 1 receptor (CB1R)-positive macrophage was colocalized with the resistin expression. In addition, resistin was exclusively expressed in the sorted CB1R-positive cells from human PBMCs. In CB1R-positive cells, endocannabinoid ligands induced resistin expression via the p38-Sp1 pathway. In both mouse models, a high-fat diet increased the accumulation of endocannabinoid ligands in adipose tissue, which recruited the CB1R-positive cells that secrete resistin, leading to adipose tissue inflammation and insulin resistance. This phenomenon was suppressed by CB1R blockade or in resistin knockout mice. Interestingly, this process was accompanied by mitochondrial change that was induced by resistin treatment. These results provide important insights into the ECS-resistin axis, leading to the development of metabolic diseases. Therefore, the regulation of resistin via the CB1R could be a potential therapeutic strategy for cardiometabolic diseases., Competing Interests: Competing interests: The authors declare that they have no competing interests., (Copyright © 2024 Han-Mo Yang et al.)

Published
2024
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