Fast reconstruction of EEG signal compression sensing based on deep learning.

When traditional EEG signals are collected based on the Nyquist theorem, long-time recordings of EEG signals will produce a large amount of data. At the same time, limited bandwidth, end-to-end delay, and memory space will bring great pressure on the effective transmission of data. The birth of compressed sensing alleviates this transmission pressure.

Identification of medicinal plants within the Apocynaceae family using ITS2 and psbA-trnH barcodes.

To ensure the safety of medications, it is vital to accurately authenticate species of the Apocynaceae family, which is rich in poisonous medicinal plants. We identified Apocynaceae species by using nuclear internal transcribed spacer 2 (ITS2) and psbA-trnH based on experimental data. The identification ability of ITS2 and psbA-trnH was assessed using specific genetic divergence, BLAST1, and neighbor-joining trees.