Results 181 to 190 of about 132,524 (284)

Automated Alignment Powered by Computer Vision Streamlines the Two‐Photon Polymerization‐Based Micro 3D Printing of Multiscale and Multimaterial Structures

open access: yesAdvanced Intelligent Discovery, EarlyView.
Two‐photon polymerization enables high‐resolution microfabrication, but performing alignment when printing multiple structures is difficult. Here, we present a fast, robust, and open‐source protocol for automated alignment on Nanoscribe systems. Achieving ≈0.4 μm accuracy in under 5 s, our protocol reduces time and error in multimaterial printing. This
Daniel Maher   +4 more
wiley   +1 more source

A High‐Precision Dynamic Movement Recognition Algorithm Using Multimodal Biological Signals for Human–Machine Interaction

open access: yesAdvanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This article describes a multimodal fusion data acquisition and processing system about electromyography for dynamic movement recognition and bioelectrical impedance for key posture recognition. In addition, a new dynamic–static fusion algorithm strategy is designed.
Chenhao Cao   +5 more
wiley   +1 more source

Melatonin for chronic back pain (the MOCHA trial): study protocol for a randomized, double-blind, placebo-controlled trial. [PDF]

open access: yesTrials
Kilic K   +8 more
europepmc   +1 more source

A Generalizable Transformer Framework for Gene Regulatory Network Inference from Single‐Cell Transcriptomes

open access: yesAdvanced Intelligent Systems, EarlyView.
FTGRN introduces an LLM‐enhanced framework for gene regulatory network inference through a two‐stage workflow. It combines a Transformer‐based model, pretrained on GPT‐4 derived gene embeddings and regulatory knowledge, with a fine‐tuning stage utilizing single‐cell RNA‐seq data.
Guangzheng Weng   +7 more
wiley   +1 more source

Comparing the Latent Features of Universal Machine‐Learning Interatomic Potentials

open access: yesAdvanced Intelligent Systems, EarlyView.
This study quantitatively assesses how universal machine‐learning interatomic potentials encode the chemical space into latent features, showing unique model‐specific representations with high cross‐model reconstruction errors. It explores how training datasets, protocols, and targets affect these encodings.
Sofiia Chorna   +5 more
wiley   +1 more source

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