By reducing fossil fuel use, renewable energy improves the economy, quality of life, and
environment. These impacts make renewable energy forecasting crucial for lowering fossil …

The complexity of hydrological data requires an understanding of its spatiotemporal
evolution for effective modeling and prediction. In this study, the underlying spatiotemporal …

Motivated by the One Health paradigm, we found the expected changes in temperature and
UV radiation (UVR) to be a common trigger for enhancing the risk that viruses, vectors, and …

This study presents a data-driven approach to identifying anomaly-sensitive parameters
through a multiscale, multifaceted analysis of simulated respiratory flows. The anomalies …

When conducting an analysis of nature's time series, such as meteorological ones, an
important matter is a long-range dependence to quantify the global behavior of the series …

The final destination country for refugees heading to Europe may be a changing one
depending on various factors, such as the relocation program at the EU level, their ability to …

Understanding and measuring complexity is one of the emerging fields in physics and
science more generally. The original impetus was given by Shannon's information theory …

A streamflow time series contains a large quantity of information and finding the instruments
that are capable of accessing this information remains an important task. Using the …

This paper deals with the first analysis of the neutron and gamma time series measured with
organic scintillators from plutonium samples by using information measures. Fast neutron …

The rating curve is a fit to concurrent hydrometric measurements of stage and discharge
(spot-gauging data) which is commonly referred to as the 'stage-discharge relationship'. It is …