Water-resonator-based metasurface : an ultrabroadband and near-unity absorption by Song, Qinghua, Zhang, Wu, Wu, Pin Chieh, Zhu, Weiming, Shen, Zhong Xiang, Chong, Peter Han Joo, Liang, Qing Xuan, Yang, Zhen Chuan, Hao, Yi Long, Cai, Hong, Zhou, Hai Feng, Gu, Yuandong, Lo, Guo-Qiang, Tsai, Din Ping, Bourouina, Tarik, Leprince-Wang, Yamin, Liu, Ai-Qun

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Conserved longitudinal alterations of anti-S-protein IgG subclasses in disease progression in initial ancestral Wuhan and vaccine breakthrough Delta infections by Goh, Yun Shan, Fong, Siew-Wai, Hor, Pei Xiang, Siti Naqiah Amrun, Lee, Cheryl Yi-Pin, Young, Barnaby Edward, Chia, Po Ying, Tambyah, Paul A., Kalimuddin, Shirin, Pada, Surinder, Tan, Seow-Yen, Sun, Louisa Jin, Chen, Mark I-Cheng, Leo, Yee-Sin, Lye, David C., Ng, Lisa F. P., Renia, Laurent

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Cross-reactive dengue human monoclonal antibody prevents severe pathologies and death from Zika virus infections by Kam, Yiu-Wing, Lee, Cheryl Yi-Pin, Teo, Teck-Hui, Howland, Shanshan W., Siti Naqiah Amrun, Lum, Fok-Moon, See, Peter, Kng, Nicholas Qing-Rong, Huber, Roland G., Xu, Mei-Hui, Tan, Heng-Liang, Choo, Andre, Maurer-Stroh, Sebastian, Ginhoux, Florent, Fink, Katja, Wang, Cheng-I, Ng, Lisa F.P., Rénia, Laurent

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Clinical course, immunogenicity, and efficacy of BNT162b2 mRNA vaccination against SARS-CoV-2 infection in liver transplant recipients by Tan, Eunice X., Lim, Wen Hui, Thong, Elizabeth, Chavatte, Jean-Marc, Zhang, Jinyan, Lim, Jonathan, Jin, Jocelyn Y., Lim, Daniel R. X., Kang, Jaclyn Y. T., Tang, Ansel Shao Pin, Chan, Kai En, Tan, Caitlyn, Tan, Shi Ni, Nah, Benjamin, Huang, Daniel Q., Wang, Lin-Fa, Tambyah, Paul A., Somani, Jyoti, Young, Barnaby Edward, Muthiah, Mark D.

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Metabolite profiling in identifying metabolic biomarkers in older people with late-onset type 2 diabetes mellitus by Tam, Zhi Yang, Ng, Sean Pin, Tan, Ling Qiao, Lin, Chih-Hsien, Rothenbacher, Dietrich, Klenk, Jochen, Boehm, Bernhard Otto, Goh, Kelvin Kau Kiat, Suwanchaikasem, Pipob, Tipthara, Pornpimol, Koenig, W., Riepe, M., Peter, R., Geiger, H., Ludolph, A., Arnim, C. v., Denkinger, M. D., Yang, Song Yi, Nagel, G., Weinmayr, G., Rapp, K., Dallmeier, D., Steinacker, J. M., Laszlo, R., Becker, T., Stingl, J.

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Phase-controllable growth of ultrathin 2D magnetic FeTe crystals by Kang, Lixing, Ye, Chen, Zhao, Xiaoxu, Zhou, Xieyu, Hu, Junxiong, Li, Qiao, Liu, Dan, Das, Chandreyee Manas, Yang, Jiefu, Hu, Dianyi, Chen, Jieqiong, Cao, Xun, Zhang, Yong, Xu, Manzhang, Di, Jun, Tian, Dan, Song, Pin, Kutty, Govindan, Zeng, Qingsheng, Fu, Qundong, Deng, Ya, Zhou, Jiadong, Ariando, Ariando, Miao, Feng, Hong, Guo, Huang, Yizhong, Pennycook, Stephen J., Yong, Ken-Tye, Ji, Wei, Wang, Renshaw Xiao, Liu, Zheng

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The impact of death and dying on the personhood of medical students : a systematic scoping review by Ho, Chong Yao, Kow, Cheryl Shumin, Chia, Joshua Chin Howe, Low, Jia Ying, Lai, Melvin Yong Hao, Lauw, Sarah-Kei, How, Ashley Ern Hui, Tan, Lorraine Hui En, Ngiam, Lisa Xin Ling, Chan, Natalie Pei Xin, Kuek, Joshua Tze Yin, Nur Haidah Ahmad Kamal, Chia, Jeng Long, Ahmad Hanifah Marican Abdurrahman, Chiam, Min, Ong, Yun Ting, Chin, Annelissa Mien Chew, Toh, Ying Pin, Mason, Stephen, Krishna, Lalit Kumar Radha

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16.100 Aerodynamics, Fall 2002 by Darmofal, David L.

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16.07 Dynamics, Fall 2004 by Peraire, Jaume

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Artificial neural networks solutions for solving differential equations: A focus and example for flow of viscoelastic fluid with microrotation by Abdullah, null, Faye, Ibrahima, Laila Amera, Aziz

“…PINN offers an alternative to classical numerical methods. …”
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Data-driven forward and inverse analysis of two-dimensional soil consolidation using physics-informed neural network by Wang, Yu, Shi, Chao, Shi, Jiangwei, Lu, Hu

“…Different random seeds are used to test the robustness of the PINN developed and quantify the associated model uncertainty. …”
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Physics-informed neural network for fast prediction of temperature distributions in cancerous breasts as a potential efficient portable AI-based diagnostic tool by Mukhmetov, Olzhas, Zhao, Yong, Mashekova, Aigerim, Zarikas, Vasilios, Ng, Eddie Yin Kwee, Aidossov, Nurduman

“…This work presents the development of a novel Physics-Informed Neural Network (PINN) method for fast forward simulation of heat transfer through cancerous breast models. …”
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Population of Merging Compact Binaries Inferred Using Gravitational Waves through GWTC-3 by Sudhir, Vivishek

“…While the majority of spins are preferentially aligned with the orbital angular momentum, we infer evidence of antialigned spins among the binary population. …”
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Design and investigation of air-cooled heat sinks using 3D printing technology by Lim, Ming Chong

“…This study presents the heat transfer performance of five pin fin heat sinks that have been fabricated using Selective Laser Melting. …”
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Learning stock market dynamics using the kinetic ising model by Nguyen, Ai Linh

“…In this approach, the states in the time series data are represented by configurations of N spins, and the time evolution of these states in the time series data by an update rule that depends on the spin configuration {σ_i (t)}_(i=1,…,N), and the connection weights {W_ij }_(i,j=1,…N) between the spins. …”
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Physics-Informed Deep Learning for Plasma Etch Optimization by Dighamber, Mohit

“…Future work includes utilizing the PINN model in a Bayesian framework to facilitate recipe optimization for the desired etch profile.…”
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Domain wall dynamics in engineered multilayer magnetic nanostructures by Lin, Eddy Junxiang

“…This is attributed to the spins of the domain wall in Co60Fe20B20 aligning along the magnetic moment of the permalloy strip above it. …”
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Stress faced by executives in Singapore. by Par, Hwee Fong., Tan, Chin Ying., Thong, Hwei Ling.

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Challenges faced by women in the corporate world by Ang, Hui Jia, Sim, Jasmine Mei Yao, Yeo, Siew Hong

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The theory of complex network sensing. by Wang, Yidan.

“…The objective of this project is to explore this interaction between internal dynamics and extrinsic information by simulating Ising spins on a scale-free network. As a first step to understand how complex networks sense and react to environmental signals, we studied how to achieve a global change of the system through the control of local nodes.…”
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