Results 161 to 170 of about 150,269 (267)
Heterosis-Based Identification of Candidate Genes Associated with Lipid Metabolism and Meat Quality in Crossbred Pigs. [PDF]
Suthar TK +7 more
europepmc +1 more source
Learnable Diffusion Framework for Mouse V1 Neural Decoding
We introduce Sensorium‐Viz, a diffusion‐based framework for reconstructing high‐fidelity visual stimuli from mouse primary visual cortex activity. By integrating a novel spatial embedding module with a Diffusion Transformer (DiT) and a synthetic‐response augmentation strategy, our model outperforms state‐of‐the‐art fMRI‐based baselines, enabling robust
Kaiwen Deng +2 more
wiley +1 more source
Effects of ferulic acid on meat quality and fat metabolism in broilers. [PDF]
Zhang X +6 more
europepmc +1 more source
Ultrafast Multilevel Switching and Synaptic Behavior in a Planar Quantum Topological Memristor
Dry‐transferred Bi2Te3 layers enable a planar quantum topological memristor framework. In‐plane topological surface states facilitate ultrafast & low‐power operations. Coexisting analog and digital modes support current‐controlled multilevel states. PQTM exhibits 105 s retention, 103 cycles endurance, and reproducibility across 24 devices.
Mamoon Ur Rashid +12 more
wiley +1 more source
Effects of Age on Slaughter Performance and Meat Quality of Shanbei White Cashmere Goat and Optimization of Slaughter Strategies. [PDF]
He Y +5 more
europepmc +1 more source
This study introduces stVGP, a variational spatial Gaussian process framework for multi‐modal, multi‐slice spatial transcriptomics. By integrating histological and genomic data through hybrid alignment and attention‐based fusion, stVGP reconstructs coherent 3D functional landscapes.
Zedong Wang +3 more
wiley +1 more source
A meta-analysis of broiler chicken meat quality: Comparative evidence of halal slaughter and electrical stunning. [PDF]
Okon UM +5 more
europepmc +1 more source
SpatialESD: Spatial Ensemble Domain Detection in Spatial Transcriptomics
ABSTRACT Spatial transcriptomics (ST) measures gene expression while preserving spatial context within tissues. One of the key tasks in ST analysis is spatial domain detection, which remains challenging due to the complex structure of ST data and the varying performance of individual clustering methods. To address this, we propose SpatialESD, a Spatial
Hongyan Cao +11 more
wiley +1 more source

