Results 211 to 220 of about 246,254 (290)

Sustainable Fabrication of Tailored Bone Substitutes: From High‐Throughput Scaffold Manufacturing, Scaled‐Up HMSC Expansion to Dynamic Cultivation in a Perfusion Bioreactor

open access: yesAdvanced Science, EarlyView.
ABSTRACT The demand for off‐the‐shelf biocompatible bone substitutes has driven the development of numerous independent in vitro technologies to generate products resembling physiological tissues. Due to technical challenges and overly simplified cultivation approaches/niches, the end‐products are often uniformly shaped and inferior to native bone ...
Franziska Braun   +10 more
wiley   +1 more source

Explainable machine learning prediction of functional independence measure scores and gain in subacute stroke survivors. [PDF]

open access: yesJ Neuroeng Rehabil
Miyazaki Y   +10 more
europepmc   +1 more source

Ethical Precision in Nanoscale Brain Interfacing

open access: yesAdvanced Science, EarlyView.
As brain interfaces approach the nanoscale, precision no longer only measures—it knows, predicts, and potentially reshapes the mind. This work argues that traditional ethics fails under such conditions and proposes a shift toward continuous, operation‐based governance using the recovery–discovery framework to track, constrain, and responsibly steer ...
Guilherme Wood
wiley   +1 more source

Strain-level transmission inference across multi-kingdom metagenomic data using TRACS. [PDF]

open access: yesNat Microbiol
Tonkin-Hill G   +10 more
europepmc   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

open access: yesAdvanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu   +8 more
wiley   +1 more source

Integrating Machine Learning With Constant‐Potential Simulation to Unravel Charge‐Transfer Mechanisms in Electrochemical Nitrogen Fixation

open access: yesAdvanced Science, EarlyView.
Integrating interpretable machine learning with the fixed‐potential method reveals a novel mechanism: the catalytic activity of the electrochemical nitrogen reduction reaction is governed by partial charge transfer, induced by variations in the intermediate potential of zero charge under constant potential.
Yufei Xue   +6 more
wiley   +1 more source

High‐Throughput Screening and Interpretable Machine Learning for Rational Design of Bimetallic Catalysts for Methane Activation

open access: yesAdvanced Science, EarlyView.
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan   +8 more
wiley   +1 more source

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