Results 221 to 230 of about 540,625 (369)
Collaborative optimization of computational offloading and resource allocation based on Stackelberg game. [PDF]
Li L +6 more
europepmc +1 more source
By engineering the PVA/H3PO4 ionic elastomer with optimized viscoelasticity and a height‐graded microstructure, the pressure sensor achieves a broad linear range up to 2000 kPa and a high sensitivity of 2.70 nF/kPa. These advancements underscore its strong potential for wearable electronics, including bio‐signal detection, health monitoring, and ...
Allen J. Cheng +13 more
wiley +1 more source
Investigation of a Lyapunov delta-type inequality with respect to a discrete fractional Green's function. [PDF]
Mohammed PO, Arab M.
europepmc +1 more source
Logical Foundations of Mathematics and Computational Complexity - A Gentle Introduction
P. Pudlák
semanticscholar +1 more source
Beyond Traditional RAFT Polymerization: Emerging Strategies and Future Perspectives; A Third Update
This review explores recent advances in the past five years for non‐traditional RAFT polymerization, focusing on new activation strategies, sustainable depolymerization, and integration with automated and AI‐driven synthesis. Together, these innovations advance polymer chemistry and reveal how the pieces of the non‐traditional RAFT puzzle are steadily ...
Vianna F. Jafari +10 more
wiley +1 more source
More than just slowing: bimodal vigilance dynamics in sleep deprivation. [PDF]
Lee K, Lim D, Kim JK.
europepmc +1 more source
A key challenge in nicotine electroanalysis is the unresolved complexity of its interface process, which directly determines sensor metrics. Herein, the proton‐coupled electron transfer mechanism of nicotine is decoded for multi‐scenario portable electrochemical sensing.
Yi Peng +9 more
wiley +1 more source
Learning structured population models from data with WSINDy. [PDF]
Lyons R, Dukic V, Bortz DM.
europepmc +1 more source
Computational and Mathematical Realization of the Theory of Nothing
JOHN wayni Santos OLIVEIRA
openalex +1 more source
By combining ionic nonvolatile memories and transistors, this work proposes a compact synaptic unit to enable low‐precision neural network training. The design supports in situ weight quantization without extra programming and achieves accuracy comparable to ideal methods. This work obtains energy consumption advantage of 25.51× (ECRAM) and 4.84× (RRAM)
Zhen Yang +9 more
wiley +1 more source

