Matching IOL design to near/intermediate requirements, glare tolerance, and travel/night-driving needs can outweigh default reliance on multifocal platforms. Preoperative optimization of astigmatism ...

A "CBS Evening News" producer abruptly resigned on Wednesday, accusing the network of a "shifting set of ideological expectations" in a message that went viral on social media. Alicia Hastey, who ...

We’ve all heard the cliché, “defense wins championships.” In the modern era of the NFL, I’d argue there’s a new MVP that never takes a snap, never makes a tackle, and is completely invisible to the 70 ...

As expected, Browns defensive coordinator Jim Schwartz is moving on. NFL Network reports that Schwartz is resigning. But here’s the kicker. Per the report, he’s exiting with the expectation that he ...

1 Department of Computer Science, Rochester Institute of Technology, Rochester, USA. 2 Department of Computer Science, Rutgers University, New Brunswick, USA. Language identification is a fundamental ...

Networks are systems comprised of two or more connected devices, biological organisms or other components, which typically share information with each other. Understanding how information moves ...

ABSTRACT: Visual Sensor Networks (VSNs) focus on capturing data, extracting relevant information, and enabling communication. However, the presence of obstacles affects network efficiency, linking ...

Cross-sectional network analysis was employed to explore the complex relationships between depression, anxiety, insomnia, somatic symptoms, childhood trauma, self-esteem, social support, and emotional ...

Journal of Nuclear Medicine Technology August 2025, jnmt.125.269869; DOI: https://doi.org/10.2967/jnmt.125.269869 ...

Submodular maximization is a significant area of interest in combinatorial optimization, with numerous real-world applications. A research team led by Xiaoming SUN from the State Key Lab of Processors ...

The expectation-maximization (EM) algorithm is a cornerstone technique for parameter estimation in statistical models that incorporate latent variables or incomplete data. By iteratively alternating ...

Graph Neural Networks (GNNs) have become a central tool for learning from network-structured data, excelling in tasks such as node classification, link prediction and representation learning. In ...