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XXVI IUPAP Conference on Computational Physics (CCP2014) [PDF]
, 2015 The 26th IUPAP Conference on Computational Physics, CCP2014, was held in Boston, Massachusetts, during August 11-14, 2014. Almost 400 participants from 38 countries convened at the George Sherman Union at Boston University for four days of plenary and ...
Campbell, D.K. +3 more
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iScience, 2023 Summary: With pre-trained large models and their associated fine-tuning paradigms being constantly applied in deep learning, the performance of large models achieves a dramatic boost, mostly owing to the improvements on both data quantity and quality ...
Xinyu Pan +9 more
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Applied Sciences, 2022 Prevention of type-1 human immunodeficiency virus (HIV) infections has primarily been through condom usage, abstinence, and behavioral and risk awareness programs.
Jeramy Lewis, Robert E. Camley
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Jurnal Neutrino: Jurnal Fisika dan Aplikasinya, 2021 Neutrino can carry information from places that cannot be reached by the usual detection mechanism because it has a very weak interaction with matter. This can be utilized to study the heat flow process inside the earth by using information carried by ...
Akmal Ferdiyan +1 more
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Transverse confinement of electron beams in a 2D optical lattice for compact coherent x-ray sources
New Journal of Physics, 2021 Compact coherent x-ray sources have been the focus of extensive research efforts over the past decades. As a result, several novel schemes like optical and nano-undulators for generating x-ray emissions in ‘table-top’ setups are proposed, developed, and ...
Arya Fallahi +2 more
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Equivariant neural networks for spin dynamics simulations of itinerant magnets
Machine Learning: Science and Technology, 2023 I present a novel equivariant neural network architecture for the large-scale spin dynamics simulation of the Kondo lattice model. This neural network mainly consists of tensor-product-based convolution layers and ensures two equivariances: translations ...
Yu Miyazaki
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Physics-Informed Deep Learning for Traffic State Estimation: A Survey and the Outlook
Algorithms, 2023 For its robust predictive power (compared to pure physics-based models) and sample-efficient training (compared to pure deep learning models), physics-informed deep learning (PIDL), a paradigm hybridizing physics-based models and deep neural networks ...
Xuan Di +3 more
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Matter and Radiation at Extremes, 2021 We report significant differences in high-pressure properties of vanadium at zero temperature and finite temperature when different projector augmented wave (PAW) potentials are used in simulations based on density functional theory. When a PAW potential
Tingting Zhang +8 more
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The Influence of Clamping, Structure Geometry, and Material on Seismic Metamaterial Performance
Frontiers in Materials, 2021 Diverting and controlling the impact of elastic vibrations upon an infrastructure is a major challenge for seismic hazard mitigation and for the reduction of machine noise and vehicle vibration in the urban environment.
T. Venkatesh Varma +7 more
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Finite Element Analysis of Microwave Tumor Ablation Based on Open-Source Software Components
Mathematics, 2023 Microwave ablation is a procedure for treating various types of cancers during which a small needle-like probe is inserted inside the tumor, which delivers microwave energy, causes tissue heating, and effectively produces necrosis of the tumor tissue ...
Nikola Bošković +2 more
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