Results 201 to 210 of about 157,845 (305)

Room‐Temperature Skyrmionic Synapse in 2D Ferromagnet Fe3GaTe2 Operating via Collective Spin Texture Transformation

Advanced Materials, EarlyView.
We demonstrate a neuromorphic synapse in 2D Fe3GaTe2 flakes. The device operates via a current‐driven transformation from a skyrmion‐lattice to a stripe‐domain state, yielding a linear anomalous Hall resistance response with a tunable slope to enable multiply‐accumulate operations. Simulations confirm its viability in artificial neural networks.
Jixiang Huang, Tongji Zhu, PeiYu Cai, Xiaoming Ma, Zhen Wang, Ruifu Zhang, Yi Hao, Jingdi Lu, Liubing He, Jun Xu, Yuejie Zhang, Wanjun Jiang, Jing Tao, Shiming Lei, Pavel Parchinskiy, Jing Teng, Lingfei Wang, Wei Niu, Elton J.G. Santos, Xiaoqian Zhang, Peng Li   +20 more
wiley   +1 more source

Network design for bypass roads using interval valued fuzzy outerplanar graphs. [PDF]

Sci Rep
Jaisankar D, Ramalingam S, Deivanayagampillai N, Walelign T.   +3 more
europepmc   +1 more source

Viral Infection‐Inspired Autonomous Detection of Fusion‐Competent Viruses for Screening and Environmental Surveillance

Advanced Materials, EarlyView.
Inspired by viral entry mechanisms, the FUSION assay enables autonomous detection of respiratory viruses via membrane fusion–triggered CRISPR‐Cas13a activation. VEACON selectively fuses with fusion‐competent viruses, triggering fluorescence within confined vesicles.
Jae Chul Park, Yidam Song, Hyun‐Woo Choi, Jaeuk Sung, Harin Jin, WonSeok Gwak, Kirim Yoo, Soohwang Lee, Jongeon Park, Jeongmin Kim, Hye‐Jun Jo, Jahyun Koo, Youngdo Jeong, Kwan Hyi Lee, Seung‐Jung Kee, Hojun Kim   +15 more
wiley   +1 more source

Interval Throwing Programs of Various Duration for Baseball Players Based on Biomechanical Workload Data. [PDF]

Int J Sports Phys Ther
Reinold MM, Dowling B, Fleisig GS, Macrina LC, Wilk KE, Alexander FJ, Ahmad CS, Dugas J, Andrews JR.   +8 more
europepmc   +1 more source

Inverse Design of Amorphous Materials With Targeted Properties

Advanced Materials, EarlyView.
AMDEN is a diffusion model framework for the inverse design of amorphous materials with targeted properties. By incorporating Hamiltonian Monte Carlo refinement into the denoising process, the framework overcomes the challenge of generating thermally relaxed disordered structures.
Jonas A. Finkler, Yan Lin, Tao Du, Jilin Hu, Morten M. Smedskjaer   +4 more
wiley   +1 more source

Construction and validation of a prognostic model for seroma after breast cancer surgery: a dual-center retrospective cohort study. [PDF]

Front Oncol
Chen Z, Zhou Q, Zhang X, Li C, Li S, Yang G, Xue X, Zhao B.   +7 more
europepmc   +1 more source

A selection of maximal elements under non-transitive indifferences

In this work we are concerned with maximality issues under intransitivity of the indifference. Our approach relies on the analysis of "undominated maximals" (cf., Peris and Subiza, J Math Psychology 2002).
Alcantud, José Carlos R., Bosi, Gianni, Zuanon, Magalì   +2 more
core  

Advancing Lithium–Oxygen Batteries: Pioneering Cathode Catalyst Innovation and Artificial Intelligence‐Driven Design Paradigms

Advanced Materials, EarlyView.
This review summarizes the principles and challenges of nonaqueous lithium‐oxygen batteries and recent advances in cathode catalysts, including carbon‐based materials, metals, oxides, sulfides, nitrides, carbides, and redox mediators. It highlights emerging design strategies and artificial intelligence‐driven approaches, emphasizing data‐assisted ...
Yuqing Yao, Chongyang Hao, Karol Viviana Mejia‐Centeno, Malik Dilshad Khan, Shang Wang, Longqiu Li, Yanhong Tian, Andreu Cabot, Qing Sun   +8 more
wiley   +1 more source

The Median Effective Dose of Phenylephrine Infusion for Prevention of Spinal-Induced Hypotension During Cesarean Delivery in the 15° Left-Tilt vs. Supine Positions: A Randomised Control Study. [PDF]

Drug Des Devel Ther
Yu XQ, Drzymalski DM, Qian J, Hu HJ, Xiao F, Yu L.   +5 more
europepmc   +1 more source

Machine Learning Accelerated Computational Design of Bio‐Inspired Catalysts in the Nitrogen Reduction Reaction

Advanced Materials, EarlyView.
We introduce a computational workflow that combines quantum chemical calculations and machine learning techniques to predict the catalytic performance of a wide range of catalysts in the nitrogen reduction reaction (NRR). The analysis of the trained models provides insights into the complex structure–activity relationship in experimental catalytic ...
Leonardo Di Ciano, Zihan You, Haoran Chen, Qifan Zhong, Rong‐Zhen Liao, Shaoqi Zhan   +5 more
wiley   +1 more source