Results 181 to 190 of about 3,361,542 (356)

Multimodal Locomotion: Next Generation Aerial–Terrestrial Mobile Robotics

open access: yesAdvanced Intelligent Systems, EarlyView., 2023
Aerial–terrestrial robots can achieve efficient energy consumption and robust environmental interaction by adding morphological features, adapting forms for locomotion transitions, and integrating multiple platforms. This next generation of mobile robots advances real‐world robotic deployment for operations with complex tasks and tackle environments ...
Jane Pauline Ramirez, Salua Hamaza
wiley   +1 more source

"A mathematical theory of evolution": phylogenetic models dating back 100 years. [PDF]

open access: yesPhilos Trans R Soc Lond B Biol Sci
Rosenberg NA, Stadler T, Steel M.
europepmc   +1 more source

Integrative Multi‐Omics and Routine Blood Analysis Using Deep Learning: Cost‐Effective Early Prediction of Chronic Disease Risks

open access: yesAdvanced Science, EarlyView.
Omicsformer, a deep learning model, integrates multi‐omics and routine blood data to accurately predict risks for nine chronic diseases, including cancer and cardiovascular conditions. Validated using large scale clinical data, it reveals early risk trajectories, advancing personalized medicine and offering a cost‐effective, community‐based solution ...
Zhibin Dong   +20 more
wiley   +1 more source

FREQ‐NESS Reveals the Dynamic Reconfiguration of Frequency‐Resolved Brain Networks During Auditory Stimulation

open access: yesAdvanced Science, EarlyView.
A new analytical pipeline, FREQuency‐resolved Network Estimation via Source Separation (FREQ‐NESS), reveals how the brain at rest is organized in frequency‐specific networks and dynamically rearranges during auditory stimulation. By analyzing source‐reconstructed magnetoencephalography (MEG) data, FREQ‐NESS uncovers the networks' prominence, spatial ...
Mattia Rosso   +6 more
wiley   +1 more source

Exploring the Latent Information in Spatial Transcriptomics Data via Multi‐View Graph Convolutional Network Based on Implicit Contrastive Learning

open access: yesAdvanced Science, EarlyView.
STMIGCL is an implicit contrastive learning‐based multi‐view graph convolutional network framework designed for downstream tasks such as spatial domain recognition, trajectory inference, and spatially variable gene identification. By combining multi‐view learning with contrastive learning and employing contrastive learning methods that enhance contrast
Sheng Ren   +5 more
wiley   +1 more source

A Ca<sup>2+</sup> puff model based on integrodifferential equations. [PDF]

open access: yesJ Math Biol
Hawker M   +4 more
europepmc   +1 more source

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