By modeling the single-trial electroencephalogram of participants performing perceptual decisions, and building on predictions from two century-old psychological laws, we estimate the times of ...

Objective Patients with atrial fibrillation (AF) frequently have multiple comorbidities that increase the risk of hospitalisation and contribute to higher mortality. However, studies examining the ...

Delayed consultation represents a major barrier to effective stroke management in Pointe-Noire. It is associated with geographic, temporal, and behavioral factors. Awareness measures, better ...

Discover how multivariate models use multiple variables for investment forecasting, risk analysis, and decision-making in finance. Ideal for portfolio management.

Abstract: Multivariate time series forecasting has wide applications such as traffic flow prediction, supermarket commodity demand forecasting and etc., and a large number of forecasting models have ...

President Donald Trump’s 2024 victory rested on support from voters who are less engaged with politics, an assessment of the election based on newly available voter file data confirms, as Democratic ...

Recent advances in green chemistry have made multivariate experimental design popular in sample preparation development. This approach helps reduce the number of measurements and data for evaluation ...

The research methodology started with plowing and tilling the land to create a muddy environment. After that, the field was organized with a plot system measuring 3.5 m x 3.5 m and 1 m between plots.

Fundamental analysis is a method used to evaluate the intrinsic value of a financial asset, such as a stock, bond, or currency. This analysis involves examining various economic, financial, and ...

Learn what analysis of variance (ANOVA) is, how it works, and when to use it. See how it helps compare means across multiple data groups in statistics and research.