Results 221 to 230 of about 12,151,236 (300)

An Integrated Artificial Intelligence Framework for Nanomedicine Engineering

open access: yesAdvanced Science, EarlyView.
This review outlines a closed‐loop AI ecosystem for nanomedicine engineering. By synergizing multimodal data harmonization, objective‐driven AI architectures, and automated high‐throughput validation, this “Design‐Make‐Test‐Analyze” (DMTA) workflow transforms traditional heuristic formulation into a predictive, self‐optimizing paradigm, accelerating ...
Meichen Dong   +10 more
wiley   +1 more source

Enhancing Specific Stiffness of Nano‐Architected Materials Through Generative AI and Active Learning

open access: yesAdvanced Science, EarlyView.
A structure‐centric generative framework searches voxelated design space directly, coupling a variational autoencoder with multi‐objective optimization and active learning to progressively expand the validated design domain. The discovered nano‐architectures, realized as pyrolytic carbon by two‐photon lithography, deliver 18–23% higher stiffness and 26–
Jinwook Yeo   +4 more
wiley   +1 more source

LLM‐Assisted Design of Ultralow‐κ$\kappa$ Chalcogenides

open access: yesAdvanced Science, EarlyView.
An AI assisted, physics guided workflow accelerates the discovery of ultralow thermal conductivity materials by combining Bayesian optimization, evidence conditioned LLM reasoning, and automated physics‐based validation. The framework uncovers dynamically stable Ag based chalcogenides with ultralow thermal conductivity and promising thermoelectric ...
Yujie Liu   +9 more
wiley   +1 more source

A Living Multi‐Omics PDX Biobank of High‐Risk Sarcomas Reveals ecDNA‐Driven Oncogene Amplification in Osteosarcoma and Enables Preclinical Precision Oncology

open access: yesAdvanced Science, EarlyView.
A living multi‐omics sarcoma PDX biobank is enriched for high‐risk disease and preserves key patient tumor features at histopathological and molecular levels. Integrated profiling reveals ecDNA‐driven oncogene amplification in osteosarcoma and preferential retention of ecDNA during PDX evolution.
Weisong Zhao   +34 more
wiley   +1 more source

Predictive Accuracy of COVID-19 World Health Organization (WHO) Severity Classification and Comparison with a Bayesian-Method-Based Severity Score (EPI-SCORE). [PDF]

open access: yesPathogens, 2020
de Terwangne C   +11 more
europepmc   +1 more source

Temporally Correlated Stochastic Spiking Neural Networks Enabled by 2D Ferroelectric Synapse‐Neuron Integration

open access: yesAdvanced Science, EarlyView.
We demonstrate a stochastic spiking neural network by integrating an α‐ln2Se3/h‐BN/CIPS FeFET synapse with an Au/CIPS/Au neuron. Unlike conventional memoryless stochastic neurons, the proposed neuron generates stochastic spikes through the evolution of internal ferroelectric polarization states, giving rise to intrinsic temporal correlations and ...
Hanseo Jeon   +7 more
wiley   +1 more source

Precision Nanomedicine for Traumatic Neural Injury: Functional Paradigms and Translational Frameworks

open access: yesAdvanced Science, EarlyView.
This review presents a pathology‐driven framework unifying nanomedicine across TBI, SCI, and PNI. Epidemiological evidence and comparative single‐cell transcriptomic reanalysis define shared pathological modules, injury‐specific effectors, and therapeutic bottlenecks. Six functional paradigms connect nanomaterial structure and biological fate to injury‐
Mouyuan Sun   +12 more
wiley   +1 more source

Data‐Driven and Physics‐Informed Modeling Perspectives for Soft Manipulators: From SINDy to Hybrid Intelligence

open access: yesAdvanced Science, EarlyView.
This Perspective charts the modeling landscape for soft manipulators, spanning sparse system identification, neural dynamics, physics‐informed models and hybrid intelligence. We examine how physics, data, sensing, adaptation and control can assume complementary roles within this landscape, and provide a framework for selecting modeling approaches ...
Wenbo Hui   +4 more
wiley   +1 more source

Multiscale Regulation of Ru‐Based Catalysts for Upgrading Biomass‐Derived Levulinic Acid and Levulinates to γ‐Valerolactone: Mechanisms, Advances, and Challenges

open access: yesAdvanced Science, EarlyView.
This review summarizes recent advances in the mechanistic, thermodynamic, and kinetic studies of biomass‐derived levulinic acid/levulinates conversion to γ‐valerolactone, along with the corresponding multiscale regulation strategies of Ru‐based catalysts.
Xin Ni   +3 more
wiley   +1 more source

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