Results 151 to 160 of about 3,284,626 (292)
Q‐LEAP: Millisecond Hyperdimensional Optimization for Full‐Spectrum Optical Metamaterials
Q‐LEAP integrates physics‐informed residual machine learning with factorization‐machine‐encoded quantum annealing to design full‐spectrum optical metamaterials. It explores a 2108 design space and, in a single 2.56 ms annealing step, reaches 85.83% of the theoretical FoM limit, enabling selective 5‐8 µm emission with 3–5 and 8–14 µm suppression and ∼40×
Zikang Guo +3 more
wiley +1 more source
Learning a bayesian network from ordinal data [PDF]
Bayesian networks are graphical models that represent the joint distributionof a set of variables using directed acyclic graphs. When the dependence structure is unknown (or partially known) the network can be learnt from data.
Flaminia Musella
core
This study employs a spouse‐pair cohort design and an idopNetwork model that integrates evolutionary game theory, predator‐prey dynamics, and developmental modularity theory to reconstruct maximally informative microbial interaction networks. This approach reveals how interspecies interactions drive the phenotypic plasticity of the gut microbiota in ...
Huizhen Li +15 more
wiley +1 more source
An MTJ‐based probabilistic processing‐in‐memory architecture unites nonvolatile storage, local entropy generation, and stochastic computation within each memory cell. Stored multi‐bit weights are converted directly into programmable stochastic bitstreams, enabling neural‐network inference, adaptive Ising optimization, and uncertainty‐aware Bayesian ...
Qiuyuan Wang +6 more
wiley +1 more source
An Integrated Artificial Intelligence Framework for Nanomedicine Engineering
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
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
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
Bayesian networks to estimate prognosis in vascular cognitive impairment and small vessel disease: Integrated analyses of interdependent contributors to multiple outcomes. [PDF]
Overmars M +10 more
europepmc +2 more sources
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
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

