Results 241 to 250 of about 259,006 (285)

Generalized non-Hermitian Hamiltonian for guided resonances in photonic crystal slabs. [PDF]

open access: yesNanophotonics
Nguyen VA   +8 more
europepmc   +1 more source

Navigating Supply Shocks: Sector Resilience and Production Prices Through Stochastic Input–Output Modeling

open access: yesMathematical Finance, EarlyView.
ABSTRACT This study develops a novel multivariate stochastic framework for assessing systemic risks, such as climate and nature‐related shocks, within production or financial networks. By embedding a linear stochastic fluid network, interpretable as a generalized vector Ornstein–Uhlenbeck process, into the production network of interdependent ...
Giovanni Amici   +3 more
wiley   +1 more source

Topological data analysis and topological deep learning beyond persistent homology: a review. [PDF]

open access: yesArtif Intell Rev
Su Z   +7 more
europepmc   +1 more source

Spatial depth for data in metric spaces

open access: yesScandinavian Journal of Statistics, EarlyView.
Abstract We propose a novel measure of statistical depth, the metric spatial depth, for data residing in an arbitrary metric space. The measure assigns high (low) values for points located near (far away from) the bulk of the data distribution, allowing quantifying their centrality/outlyingness.
Joni Virta
wiley   +1 more source

Spinal motor neuron pools may be partly driven by impulsive common inputs

open access: yesThe Journal of Physiology, EarlyView.
Abstract figure legend A schematic overview of the proposed motor neuron drive framework. Unlike the traditionally assumed continuous common input (cCI), we propose that impulsive common inputs (iCI) constitute a key driver of motor neuron (MN) pool activity.
Javier Yanguas Mayo   +5 more
wiley   +1 more source

Ultrahigh mobility and Rashba spin splitting in Sb-substituted bismuth telluride and bismuth selenide. [PDF]

open access: yesNanoscale
Kavkhani R   +5 more
europepmc   +1 more source

scMOG: A graph neural network method for regulatory relationship‐preserving single‐cell multi‐omics integration

open access: yesQuantitative Biology, Volume 14, Issue 3, September 2026.
Abstract Single‐cell multi‐omics sequencing technology provides a powerful tool for studying cellular heterogeneity. However, beyond the challenges of sparsity, heterogeneity, and dimensionality differences, a critical challenge in multi‐omics data integration lies in preserving the true regulatory relationships among molecular features.
Yucheng Lu, Xun Zhang, Hongwei Li
wiley   +1 more source

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