Results 161 to 170 of about 1,679,013 (321)

Numerical analysis, spectral graph theory, orthogonal polynomials and quantum algorithms. [PDF]

Philos Trans A Math Phys Eng Sci
Minenkova A, Mograby G, Zhan H.
europepmc   +1 more source

Strategic Mobility Engineering in 2D Semiconductor‐based FETs for Enhanced Electronic Devices

Advanced Science, EarlyView.
This review highlights device‐level strategies to optimize carrier transport in 2D‐FETs, focusing on channel engineering and contact interface design. Techniques such as doping, strain tuning, and contact resistance reduction are discussed to improve mobility and drive current.
Sheila Sim, Sichao Li, Weifan Cai, Baiyu Yu, Xin Ju, Jing Cao, Zhaogang Dong, Xinmao Yin, Sunmi Shin, Yue Luo, Dongzhi Chi, Ady Suwardi, Hong Kuan Ng, Jing Wu   +13 more
wiley   +1 more source

R-annihilated and independent perfect neighborhood sets in chordal graphs

, 2000
Joël Puech
openalex   +1 more source

Circular perfect graphs [PDF]

, 2005
Xuding Zhu
openalex   +1 more source

Orthology and near-cographs in the context of phylogenetic networks. [PDF]

Algorithms Mol Biol
Lindeberg A, Scholz GE, Wieseke N, Hellmuth M.   +3 more
europepmc   +1 more source

High‐Speed Design of Multiplexed Meta‐Optics Enabled by Physics‐Driven Self‐Supervised Network

Advanced Science, EarlyView.
A physics‐driven self‐supervised network (PDSS‐Net) is proposed for high‐speed, iteration‐free design of multiplexed meta‐optics. By learning a direct mapping from holographic targets to all meta‐atom structures, PDSS‐Net achieves a 1000× speedup over traditional optimization methods in designing 2K RGB meta‐holograms.
Yuqing He, Sheng Ye, Yue Han, Mingna Xun, Qiang Li, Ruiqi Wang, Qihuang Gong, Yan Li   +7 more
wiley   +1 more source

Some conjectures on perfect graphs

, 2000
Van Bang Lê
openalex   +2 more sources

Solving perfect matchings by frequency-grouped multi-photon events using a silicon chip. [PDF]

Nat Commun
Zhu P, Zheng Q, Wang K, Yu M, Xia G, Liu J, Liu Y, Zhu Z, Xu P.   +8 more
europepmc   +1 more source

Transfer Learning and Permutation‐Invariance Improving Predicting Genome‐Wide, Cell‐Specific and Directional Interventions Effects of Complex Systems

Advanced Science, EarlyView.
SETComp, a transfer learning model based on permutation‐invariance, is pre‐trained on single‐compound intervention data and fine‐tuned on complex system (e.g., natural products) data. The model achieves up to 93.86% accuracy on complex system‐cell‐gene association predictions, outperforming the baseline by up to 27.59%.
Boyang Wang, Boyu Pan, Tingyu Zhang, Qingyuan Liu, Shao Li   +4 more
wiley   +1 more source

On graphs all of whose {C_3, T_3}-free arc colorations are kernel-perfect

, 2001
Hortensia Galeana‐Sánchez, José de Jesús García-Ruvalcaba   +1 more
openalex   +2 more sources