Results 211 to 220 of about 499,314 (280)

Analysis of Multiscale Condensation Phenomena Using a Zero‐Shot Computer Vision Framework

open access: yesAdvanced Science, EarlyView.
A zero‐shot computer vision framework quantifies multiscale condensation dynamics by automatically segmenting droplets and extracting physical parameters without labeled data. The workflow integrates data mining and statistical analysis to reveal droplet growth, coalescence statistics, and sweeping behaviors, enabling label‐free measurement of heat ...
Donghyeong Lee   +5 more
wiley   +1 more source

Cation‐Driven Valence Change Mechanism in 2D AgCrS2 for Ultralow‐Power and Reliable Memristors

open access: yesAdvanced Science, EarlyView.
A 2D AgCrS2 volatile memristor is shown to switch via a cation‐driven valence change mechanism, where Ag+ reversibly intercalates into tetrahedral vacancies between CrS2 layers to form a conductive Ag2CrS2 pathway without elemental Ag metallization. The device exhibits 0.2 V switching, nA‐compliance power down to 200 pW, and endurance beyond 3 × 105 ...
Yueqi Su   +8 more
wiley   +1 more source

A Scalable Framework for Comprehensive Typing of Polymorphic Immune Genes from Long‐Read Data

open access: yesAdvanced Science, EarlyView.
SpecImmune introduces a unified computational framework optimized for long‐read sequencing to resolve over 400 highly polymorphic immune genes. This scalable approach achieves high‐resolution typing, enabling the discovery of cross‐family co‐evolutionary networks and population‐specific diversity.
Shuai Wang   +5 more
wiley   +1 more source

Optimal bandwidth selection in stochastic regression of Bio-FET measurements. [PDF]

open access: yesJ Math Biol
Melara LA   +4 more
europepmc   +1 more source

In Situ Quantization with Memory‐Transistor Transfer Unit Based on Electrochemical Random‐Access Memory for Edge Applications

open access: yesAdvanced Science, EarlyView.
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

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