In order to detect multiple sclerosis (MS) subjects from healthy controls (HCs) in magnetic
resonance imaging, we developed a new system based on machine learning. The MS …

This paper examined the presence of daily returns coherence and spillover between 30
forex markets over the complete sample and crisis sub-periods. We mainly employed the …

This paper studies the information efficiency of China's carbon markets using the fuzzy
entropy method. The overall and time-varying results show that Hubei market has the …

Measures of predictability in physiological signals using entropy measures have been
widely applied in many areas of research. Multiscale entropy expresses different levels of …

The low-carbon transition of the energy system plays a crucial role in achieving carbon
neutrality. However, the development of new energy heavily relies on rare earth resources …

We investigate regularity and asynchrony in Brazilian energy (ethanol) and agriculture
(sugar) market with focus on 2008 global economic crisis, using multiscale entropy method …

This study aimed to uncover the impact of COVID-19 on the leading cryptocurrency (Bitcoin)
and on sustainable finance with specific attention to their potential long memory properties …

The full-fledging of Chinese national emissions trading system (ETS) still depends on the
experiences of its pilot projects. This paper accesses the interdependence between ETSs …

Nuclear energy is crucial for achieving net-zero carbon emissions. A big challenge in the
nuclear sector is ensuring the safety of radiation workers and the environment, while being …

In recent years, the concept of entropy is widely used to measure the degree of uncertainty
or complexity of dynamics system. In our work, we utilize the composite multiscale entropy …