Results 91 to 100 of about 5,021 (265)
Neural Fields for Highly Accelerated 2D Cine Phase Contrast MRI
ABSTRACT 2D cine phase contrast (CPC) MRI provides quantitative information on blood velocity and flow within the human vasculature. However, data acquisition is time‐consuming, motivating the reconstruction of the velocity field from undersampled measurements to reduce scan times. In this work, neural fields are proposed as a continuous spatiotemporal
Pablo Arratia +7 more
wiley +1 more source
In this manuscript we investigate electrodynamic flow. For several values of the intimate parameters we proved that the approximate solution depends on a reproducing kernel model.
Akgül Ali +3 more
doaj +1 more source
Multimodal Cross‐Attentive Graph‐Based Framework for Predicting In Vivo Endocrine Disruptors
A multimodal cross‐attentive graph neural network integrates molecular graphs with androgen and estrogen adverse outcome pathway (AOP)–anchored in vitro assay signals to predict in vivo endocrine disruption. By fusing information on Tier‐1 AOP logits with chemical structures, the framework achieves high accuracy and provides assay‐traceable ...
Eder Soares de Almeida Santos +6 more
wiley +1 more source
This study develops a 3D co‐culture and co‐differentiation system for porcine muscle stem cells (pMuSCs) and mesenchymal stem cells (pMSCs) on edible starch‐based scaffolds. The system simultaneously generates myotubes and adipocytes without using serum or chemical inducers.
Xin Guan +9 more
wiley +1 more source
This study firstly presents a comprehensive and high‐resolution pan‐3D genome resource in chicken. Our findings reveal the role of structural variations in 3D genome architectures, and how they influence the domestication process and production traits at the 3D genome level.
Zhen Zhou +19 more
wiley +1 more source
Reproducing kernel method for PDE constrained optimization
This paper presents reproducing kernel Hilbert spaces method to obtain the numerical solution for partial differential equation constrained optimization problem.
openaire +2 more sources
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
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
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
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

