Results 111 to 120 of about 63,273 (275)
By integrating single‐nuclei and spatial transcriptomics, this study presents a stereoscopic landscape of maize leaf to Puccinia polysora infection. Epidermal and mesophyll cells initiate primary defenses via RLPs/RLKs and jasmonic acid signaling. Cell‐cell communication analyses further reveal the underlying the dynamics of the underlying immune ...
Qiongqiong Wang +16 more
wiley +1 more source
A Novel Method for Solutions of Fourth-Order Fractional Boundary Value Problems
In this paper, we find the solutions of fourth order fractional boundary value problems by using the reproducing kernel Hilbert space method. Firstly, the reproducing kernel Hilbert space method is introduced and then the method is applied to this kind ...
Ali Akgül, Esra Karatas Akgül
doaj +1 more source
Climate Change Threatens Micronutrient Density of European Winter Wheat
Micronutrients are vital for human health. Wheat is a major staple crop and a significant source of minerals and B‐vitamins. The impact of climate change on their content remains largely unknown. We evaluated micronutrient levels in European winter wheat grown under historical and projected climate conditions. Our findings indicate that future climates
Da Cao +17 more
wiley +1 more source
Causal Prediction of TP53 Variant Pathogenicity Using a Perturbation‐Informed Protein Language Model
A TP53‐specific predictor, CaVepP53, is developed by fine‐tuning ESMC on experimentally validated variants, quantifying pathogenicity via Euclidean distances. It outperforms general‐purpose models and extends to five cancer genes, enabling interpretable variant classification for precision medicine.
Huiying Chen +15 more
wiley +1 more source
This report is concerned with the theory of reproducing kernels. First, a background of elementary facts about Hilbert spaces is given. The most important theorems are the projection and Riesz theorems. Some examples are provided to show how the theory of Hilbert spaces can be applied to mathematical problems.
openaire +1 more source
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
Some Notes on Error Analysis for Kernel Based Regularized Interpolation
Kernel based regularized interpolation is one of the most important methods for approximating functions. The theory behind the kernel based regularized interpolation is the well-known Representer Theorem, which shows the form of approximation function in
Qing Zou
doaj
This study performs pan‐viromic profiling of 14,529 samples from 5,710 domestic herbivores across five Chinese provinces, establishing the DhCN‐Virome (1,085,360 viral metagenomes). It reveals species/sample‐specific viromic signatures and cross‐species transmission dynamics, aiding unified disease control.
Yue Sun +19 more
wiley +1 more source
Skeleton‐oriented object segmentation (SKOOTS) introduces a new strategy for 3D mitochondrial instance segmentation by predicting explicit skeletons rather than relying on boundary cues. This approach enables robust analysis of densely packed organelles in large FIB‐SEM datasets.
Christopher J. Buswinka +3 more
wiley +1 more source
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

