Zobrazeno 1 - 10
of 6 866
pro vyhledávání: '"Tran, P. T."'
We investigate the dependence of the yield of positive secondary ions created upon impact of primary He, B and Ne ions on geometry and electronic and nuclear energy deposition by the projectiles. We employ pulsed beams in the medium energy regime and
Externí odkaz:
http://arxiv.org/abs/2411.05525
Autor:
Wei, Chao-Chun, Li, Xiaoyin, Hatt, Sabrina, Huai, Xudong, Liu, Jue, Singh, Birender, Kim, Kyung-Mo, Fernandes, Rafael M., Cardon, Paul, Zhao, Liuyan, Tran, Thao T., Frandsen, Benjamin M., Burch, Kenneth S., Liu, Feng, Ji, Huiwen
Altermagnets represent a new class of magnetic phases without net magnetization that are invariant under a combination of rotation and time reversal. Unlike conventional collinear antiferromagnets (AFM), altermagnets could lead to new correlated stat
Externí odkaz:
http://arxiv.org/abs/2410.14542
Autor:
Vantaraki, Christina, Ström, Petter, Tran, Tuan T., Grassi, Matías P., Fevola, Giovanni, Foerster, Michael, Sadowski, Jerzy T., Primetzhofer, Daniel, Kapaklis, Vassilios
Publikováno v:
Appl. Phys. Lett. 125, 202403 (2024)
We present a method for the additive fabrication of planar magnetic nanoarrays with minimal surface roughness. Synthesis is accomplished by combining electron-beam lithography, used to generate nanometric patterned masks, with ion implantation in thi
Externí odkaz:
http://arxiv.org/abs/2409.10433
Autor:
Ta, Lien T. P., Tran, Huong T. T.
Most Mahonian statistics can be expressed as a linear combination of vincular patterns. This is not only true with statistics on the permutation set, but it can also be applied for statistics on the permutation with repetition set. By following the m
Externí odkaz:
http://arxiv.org/abs/2405.10983
Autor:
Potiriadis, C., Karafasoulis, K., Papadimitropoulos, C., Papadomanolaki, E., Papangelis, A., Kazas, I., Vourvoulakis, J., Theodoratos, G., Kok, A., Tran, L. T., Povoli, M., Vohradsky, J., Dimitropoulos, G., Rosenfeld, A., Lambropoulos, C. P.
Publikováno v:
Advances in Space Research Volume 74, Issue 3, 1 August 2024, Pages 1352-1365
Moon is an auspicious environment for the study of Galactic cosmic rays (GCR) and Solar particle events (SEP) due to the absence of magnetic field and atmosphere. The same characteristics raise the radiation risk for human presence in orbit around it
Externí odkaz:
http://arxiv.org/abs/2405.03187
Autor:
Meouchi, Cynthia, Barna, Sandra, Rosenfeld, Anatoly, Tran, Linh T., Palmans, Hugo, Magrin, Giulio
This paper characterizes the microdosimetric spectra of a single-energy carbon-ion pencil beam at MedAustron using a miniature solid-state silicon microdosimeter to estimate the impact of the lateral distribution of the different fragments on the mic
Externí odkaz:
http://arxiv.org/abs/2403.08561
Autor:
Huai, Xudong, Acheampong, Emmanuel, Delles, Erich, Winiarski, Michał J., Sorolla II, Maurice, Nassar, Lila, Liang, Mingli, Ramette, Caleb, Ji, Huiwen, Scheie, Allen, Calder, Stuart, Mourigal, Martin, Tran, Thao T.
Noncentrosymmetric triangular magnets offer a unique platform for realizing strong quantum fluctuations. However, designing these quantum materials remains an open challenge attributable to a knowledge gap in the tunability of competing exchange inte
Externí odkaz:
http://arxiv.org/abs/2403.08069
Histologic examination plays a crucial role in oncology research and diagnostics. The adoption of digital scanning of whole slide images (WSI) has created an opportunity to leverage deep learning-based image classification methods to enhance diagnosi
Externí odkaz:
http://arxiv.org/abs/2401.11062
Autor:
Nguyen, Cuong N., Tran, Phong, Ho, Lam Si Tung, Dinh, Vu, Tran, Anh T., Hassner, Tal, Nguyen, Cuong V.
We consider transferability estimation, the problem of estimating how well deep learning models transfer from a source to a target task. We focus on regression tasks, which received little previous attention, and propose two simple and computationall
Externí odkaz:
http://arxiv.org/abs/2312.00656
Autor:
Tran, Huynh T. T., Nguyen, Hieu T.
Publikováno v:
The 2024 Conference on Innovative Smart Grid Technologies, North America (ISGT NA 2024)
In recent years, scientific machine learning, particularly physic-informed neural networks (PINNs), has introduced new innovative methods to understanding the differential equations that describe power system dynamics, providing a more efficient alte
Externí odkaz:
http://arxiv.org/abs/2311.06580