Background Little is known about the association between direct pollen exposure and cognitive performance. The aim of our ...

Background: Online gambling and sports betting have recently been legalized and expanded in North America. We aimed to evaluate long-term changes in the frequency of gambling-related helpline contacts ...

1 School of Aeronautics and Astronautics, Sun Yat-sen University, Guangzhou, China. 2 School of Science and Technology, Hunan University of Technology, Zhuzhou, China. To address the multicoupling ...

ABSTRACT: A hyperbolic model for the diffusion of proteins through the blood-cerebrospinal fluid (CSF) barrier revolutionized clinical neurochemistry thirty years ago. The regression curves were ...

Three Opinion writers break down the former vice president’s book of excuses. By Michelle Cottle Carlos Lozada and Lydia Polgreen Produced by Vishakha Darbha Three Opinion writers weigh in on Kamala ...

In today’s fast-paced, ever-evolving world, the complexity of challenges faced in both business and everyday life requires a shift in how we approach problem solving. Traditional linear thinking, ...

What is linear regression in machine learning ? Understanding Linear Regression in machine learning is considered as the basis or foundation in machine learning. In this video, we will learn what is ...

Derivative-free method to find zeros of analytic (holomorphic) functions / solve nonlinear (polynomial / generalized) eigenvalue problems using contour integration. (Block SS-Hankel method, Block ...

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...

Abstract: The accurate prediction of nonlinear regression problems plays a central role in many practical applications, and the improvement of its prediction accuracy holds significant practical value ...

Abstract: The accurate forecasting of nonlinear regression problems is essential in numerous real-world applications, and enhancing the precision of predictions in such problems is significantly ...