Objective Macrophage activation syndrome (MAS), a subtype of secondary haemophagocytic lymphohistiocytosis (HLH), is a rare ...

Introduction SLE is a chronic autoimmune disease characterised by multisystem involvement and fluctuating clinical course, ...

Knowledge of the genetic variability and of the variables for evaluating common bean lines for the physiological seed quality trait is important for the selection of promising common bean genotypes ...

The AERCA algorithm performs robust root cause analysis in multivariate time series data by leveraging Granger causal discovery methods. This implementation in PyTorch facilitates experimentation on ...

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 ...

Department of Chemistry, University of Central Florida, Orlando, Florida 32816, United States Renewable Energy and Chemical Transformations Cluster, University of Central Florida, Orlando, Florida ...

Abstract: The existing literature on forecasting time series data is primarily based on univariate analysis and techniques such as Univariate Autoregressive (UAR), Univariate Moving Average (UMA), ...

The joint probability of two or more variables being “extreme” is relevant in Flood and Coastal Risk Management (FCRM) in various contexts, including: Assessing the likelihood of extreme peak flow ...

Abstract: Correlations among process variables and inconsistencies in alarm decision making are quite common in multivariate alarm analysis, resulting in a large number of false alarms and missed ...