Results 201 to 210 of about 2,020,572 (302)

Towards a Compositional Framework for Describing Human Phenotypes

open access: yesAdvanced Science, EarlyView.
The Phenotype Assembly Method (PhenoAM) decomposes phenotype variables into measurable Features and typed Qualifiers, enabling standardized, machine‐readable Phenome Data Elements (PhenoDEs) that preserve measurement context. Applied in the International Human Phenome Project (IHPP), the framework yields 58 371 PhenoDEs and supports component‐level ...
Wanting Hu   +11 more
wiley   +1 more source

Beyond Conventional: A Review of Phytochemical‐Hydrogel Systems Enhanced by AI and 3D Printing for Chronic Wound Management

open access: yesAdvanced Science, EarlyView.
This review systematically bridges chronic wound pathology with natural phytochemical hydrogel therapeutics. A pathology‐to‐phytochemical mechanistic mapping framework is established, linking specific wound hallmarks to targeted phytochemical interventions.
Yitao Zhou   +8 more
wiley   +1 more source

Hierarchical Bayesian estimation of motor-evoked potential recruitment curves yields accurate and robust estimates. [PDF]

open access: yesBrain Stimul
Tyagi V   +7 more
europepmc   +1 more source

Terahertz Channel Modeling, Estimation and Localization in RIS‐Assisted Systems

open access: yesAdvanced Electronic Materials, EarlyView.
Reconfigurable intelligent surfaces have become a recent intensive research focus. Based on practical applications, channel strategies for RIS‐assisted terahertz wireless communication systems are categorized into three different types: channel modeling, channel estimation, and channel localization.
Hongjing Wang   +9 more
wiley   +1 more source

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

open access: yesAdvanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho   +6 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

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