Results 161 to 170 of about 2,848,958 (338)
Singular wavelets on a finite interval
Nonparametric methods are used in complex cases where model information is insufficient. A new method of nonparametric approximation, the singular wavelet method, is developed.
V. M. Romanchak
doaj
Linearizing and Forecasting: A Reservoir Computing Route to Digital Twins of the Brain
A new approach uses simple neural networks to create digital twins of brain activity, capturing how different patterns unfold over time. The method generates and recovers key dynamics even from noisy data. When applied to fMRI, it predicts brain signals and reveals distinctive activity patterns across regions and individuals, opening possibilities for ...
Gabriele Di Antonio +3 more
wiley +1 more source
AI‐Enhanced Vibrational Capsule for Minimally Invasive Detection of Abnormal Bowel Tissue
A fully integrated vibration‐assisted capsule is presented for the minimally invasive detection of bowel lesions. The capsule incorporates a wireless sensor and an eccentric motor to probe tissue mechanics in situ. By coupling triaxial vibration signals with AI‐based classification and analytical modeling, the system enables early, non‐visual ...
Xizheng Fang +6 more
wiley +1 more source
vEMRec is a frequency‐adaptive computational framework for three‐dimensional alignment in volume electron microscopy. It integrates feature‐based rigid alignment with Gaussian filter‐guided elastic registration to correct rigid misalignments and nonlinear distortions while preserving structural fidelity.
Zhenbang Zhang +7 more
wiley +1 more source
Volterra Kernel Estimation of White Light LEDs in the Time Domain. [PDF]
Stepniak G, Kowalczyk M, Siuzdak J.
europepmc +1 more source
This study highlights that radioimmunotherapy drives crosstalk between fibroblasts and immune cells (especially macrophages) in the cardiac microenvironment, with IL‐6 as the key mediator, and tocilizumab alleviates cardiac fibrosis by targeting this interplay.
Yuxi Luo +10 more
wiley +1 more source
We consider the learning problem of finding a dependency between a general class of objects and another, possibly different, general class of objects. The objects can be for example: vectors, images, strings, trees or graphs. Such a task is made possible by employing similarity measures in both input and output spaces using kernel functions, thus ...
Weston, J. +4 more
openaire +2 more sources
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
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 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

