Results 221 to 230 of about 83,564 (303)

EZpred: Improving Deep Learning‐Based Enzyme Function Prediction Using Unlabeled Sequence Homologs

open access: yesAdvanced Science, EarlyView.
Schematic of the EZpred pipeline, which provides high‐confidence predictions of enzyme function using a combination of sequence alignments, structural alignments, and deep learning. EZpred can be used to provide substantial increases in the richness of protein function annotations at genomic scales.
Chengxin Zhang   +2 more
wiley   +1 more source

People Counting and Positioning Using Low‐Resolution Infrared Images for FeFET‐Based In‐Memory Computing

open access: yesAdvanced Electronic Materials, EarlyView.
In this work, low‐resolution infrared imaging is combined with a 28 nm FeFET IMC architecture to enable compact, energy‐efficient edge inference. MLC FeFET devices are experimentally characterized, and controlled multi‐level current accumulation is validated at crossbar array level.
Alptekin Vardar   +9 more
wiley   +1 more source

Experimental Demonstration of Temporally Aware Fault‐Tolerant Sensor Fusion Using Memristive Associative Learning

open access: yesAdvanced Electronic Materials, EarlyView.
In dynamic driving scenarios, the proposed approach ensures only temporally aligned sensor inputs to make driving decisions, preventing false activations. By enabling selective hardware‐level learning, it achieves fast, reliable responses under noisy conditions.
Kapil Bhardwaj   +4 more
wiley   +1 more source

Stochastic‐MTJ Sampler Arrays for In‐Array Monte–Carlo Estimation

open access: yesAdvanced Electronic Materials, EarlyView.
A low‐energy‐barrier magnetic tunnel junction array is operated as a probability‐domain sampler: each cell's random switching, programmed through a shared digital‐to‐analog converter, makes the per‐column multiply–accumulate an unbiased Monte–Carlo expectation estimator that returns both a mean and a calibrated uncertainty.
Ran Zhang   +6 more
wiley   +1 more source

Amorphous Tungsten Driving Extraordinary Long‐Range Interlayer Exchange Coupling and Large Spin‐Orbit Torque

open access: yesAdvanced Electronic Materials, EarlyView.
The amorphous tungsten (W) is found to be a promising non‐magnetic interlayer simultaneously driving the long‐range interlayer exchange coupling and the large spin Hall effect in a synthetic antiferromagnet (SyAF). Thanks to these characteristics, efficient spin‐orbit torque switching is achieved in the SyAF.
Xueyao Hou   +9 more
wiley   +1 more source

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