This valuable study provides a practical computational framework for inferring latent neural states directly from calcium fluorescence recordings, bypassing the traditional need for a separate spike ...
Organoids are three-dimensional miniature models of organs, grown in a dish. They have become a valuable tool for studying ...
Due to their error-prone hardware, quantum computers have not yet found practical use. One promising solution is quantum error correction: special methods are used to find and correct errors in the ...
Background Although 90% of youth live in low- and middle-income countries, only 10% of child mental health research is ...
Abstract: Deep learning models have significantly addressed the challenges of multivariate time series forecasting. Recently, Transformer-based models which have primarily focused on either temporal ...
Background We investigated the prevalence, temporal trends and associated factors of overweight and obesity among adults in ...
Adapting to the Stream: An Instance-Attention GNN Method for Irregular Multivariate Time Series Data
Managing irregular multivariate time series (IMTS) data is a significant challenge due to inherent irregularities and missing values. Recent advancements have utilized graph neural networks (GNNs) to ...
During last year’s presidential debate between Donald Trump and Kamala Harris, Trump said violent crime was rising. ABC moderator David Muir immediately fact-checked him, claiming, “President Trump, ...
ABSTRACT: This study presents the Dynamic Multi-Objective Uncapacitated Facility Location Problem (DMUFLP) model, a novel and forward-thinking approach designed to enhance facility location decisions ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Quantitative determination of the relative contributions from multiple sources in ...
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