As a novel category of biometric features, research on brain fingerprints has become a hot
topic in neuroscience, not only for its reliable performance on individual identification but also …

Cross-site datasets expand the data size and could improve the disease diagnosis capabilities
of machine learning models. However, differences in data distribution between different …

Brain fingerprint with electroencephalogram (EEG) is widely employed in identification.
However, the security of brain fingerprint and the identification system is greatly reduced due to …

One of the central goals of neuroscience is to understand the group commonality and
individual variability in functional connectome. However, the entangled nature of the group and …

Considering the self‐healing phenomenon of lithium batteries during intermittent discharge,
a self‐healing characteristic‐based equivalent circuit model of lithium batteries is proposed. …

… Ting Li and Zhaodi Pei contributed equally to the current work. … by Chunliang Feng and
Zhaodi Pei. The first draft of the manuscript was written by Ting Li and Zhaodi Pei, and all authors …

Accurately predicting the remaining useful life (RUL) of lithium-ion batteries is very
important to battery management systems (BMS). Recently, Extreme Learning Machine (ELM) …

Background: The non-steroidal mineralocorticoid receptor antagonist finerenone (BAY 94–8862)
has been used to treat chronic heart failure (CHF) with reduced ejection fraction (HFrEF…

The cross-subject variability poses a great challenge to the practical application of the brain
state decoding model. Although many transfer learning methods have been used to solve …

Electroencephalography (EEG) plays a pivotal role in brain-computer interface (BCI). Among
the various paradigms, motor imagery (MI) stands out as a spontaneous and valuable …