Learn why cytotoxicity test failures are common in medical devices and discover systematic approaches to identify root causes ...

Abstract: In this work, the possibility of applying machine learning (ML) techniques to analyze and predict radio wave propagation losses in urban environments is explored. Thus, from a measurement ...

The movie industry stands at a critical juncture, with traditional mechanisms of distribution challenged including the important theatrical window.

The release of Spiritual Zombie Apocalypse: How Mass Media and Artificial Intelligence Endanger Our Spiritual Lives introduces a philosophical framework addressing human dignity within digitally ...

Abstract: As a widely used method in signal processing, Principal Component Analysis (PCA) performs both the compression and the recovery of high dimensional data by leveraging the linear ...

Background: This study aimed to explore whether a predictive model based on body composition and physical condition could estimate seasonal playing time in professional soccer players. Methods: 24 ...

ABSTRACT: This study investigates the spatio-temporal distribution of copepods (zooplankton) in the Tinguilinta River estuary, in relation to water physicochemical parameters, during the dry and rainy ...

Inside living cells, mitochondria divide, lysosomes travel, and synaptic vesicles pulse—all in three dimensions (3Ds) and constant motion. Capturing these events with clarity is vital not just for ...

In every corner of the SEO world, llms.txt is popping up in conversations, but it is frequently misunderstood and sometimes poorly explained. If you’ve heard someone call it “the new robots.txt,” or ...

Principal component analysis (PCA) is one of the most common exploratory data analysis techniques with applications in outlier detection, dimensionality reduction, graphical clustering, and ...