Exploration of sleep function connection and classification strategies based on sub-period sleep stages

BackgroundAs a medium for developing brain-computer interface systems, EEG signals are complex and difficult to identify due to their complexity, weakness, and differences between subjects. At present, most of the current research on sleep EEG signals are single-channel and dual-channel, ignoring the research on the relationship between different brain regions. Brain functional connectivity is considered to be closely related to brain activity and can be used to study the interaction relationship between brain areas.MethodsPhase-locked value (PLV) is used to construct a functional connection network. The connection network is used to analyze the connection mechanism and brain interaction in different sleep stages. Firstly, the entire EEG signal is divided into multiple sub-periods. Secondly, Phase-locked value is used for feature extraction on the sub-periods. Thirdly, the PLV of multiple sub-periods is used for feature fusion. Fourthly, the classification performance optimization strategy is used to discuss the impact of different frequency bands on sleep stage classification performance and to find the optimal frequency band. Finally, the brain function network is constructed by using the average value of the fusion features to analyze the interaction of brain regions in different frequency bands during sleep stages.ResultsThe experimental results have shown that when the number of sub-periods is 30, the α (8–13 Hz) frequency band has the best classification effect, The classification result after 10-fold cross-validation reaches 92.59%.ConclusionThe proposed algorithm has good sleep staging performance, which can effectively promote the development and application of an EEG sleep staging system

Complete chloroplast genome of a high-quality forage in north China, Medicago ruthenica (Fabaceae：Trifolieae)

Medicago ruthenica is a well-known high-quality forage due to its good palatability and strong tolerance to drought, cold and saline-alkali stress. Here, the complete chloroplast genome sequence of M. ruthenica was reported. The chloroplast genome is 126,939 bp in length. This chloroplast genome has no inverted repeat (IR) regions, which is very common in the family Fabaceae. The M. ruthenica chloroplast genome encodes 107 genes, including 73 protein-coding genes, 30 tRNA genes, and 4 rRNA genes. Phylogenetic analysis result strongly suggested that M. ruthenica is a distinct lineage in Medicago, being sister to highly supported clade composed of three species (M. hybrida, M. papillosa and M. sativa)

General Strategy for Fabricating Thoroughly Mesoporous Nanofibers

Recently, preparation of mesoporous fibers has attracted extensive attentions because of their unique and broad applications in photocatalysis, optoelectronics, and biomaterials. However, it remains a great challenge to fabricate thoroughly mesoporous nanofibers with high purity and uniformity. Here, we report a general, simple and cost-effective strategy, namely, foaming-assisted electrospinning, for producing mesoporous nanofibers with high purity and enhanced specific surface areas. As a proof of concept, the as-fabricated mesoporous TiO₂ fibers exhibit much higher photocatalytic activity and stability than both the conventional solid counterparts and the commercially available P25. The abundant vapors released from the introduced foaming agents are responsible for the creation of pores with uniform spatial distribution in the spun precursor fibers. The present work represents a critically important step in advancing the electrospinning technique for generating mesoporous fibers in a facile and universal manner

Electrospinning 3<i>C</i>-SiC Mesoporous Fibers with High Purities and Well-Controlled Structures

The purity and uniformity issues with tunable structures are significant challenges for the fabrication of porous fibers. In the present work, we reported the fabrication of mesoporous SiC fibers via electrospinning of polyureasilazane and polyvinylpyrrolidone combined with subsequent high-temperature pyrolysis treatment. The resultant mesoporous fibers were systematically characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), and high-resolution transmission electron microscopy (HRTEM). The contents of polyureasilazane within the solutions played a critically important role in the formation of mesoporous SiC fibers, enabling the well-controlled growth of the mesoporous SiC fibers. As compared to the reported works, the as-fabricated mesoporous fibers exhibit very uniform microstructures, very high purities, and highly defined fiber shapes with well-controlled structures, which could inspire and activate their potential applications in photocatalysts and catalyst supports

Performances of a prototype point-contact germanium detector immersed in liquid nitrogen for light dark matter search

The CDEX-10 experiment searches for light weakly interacting massive particles, a form of dark matter, at the China Jinping Underground Laboratory, where approximately 10 kg of germanium detectors are arranged in an array and immersed in liquid nitrogen. Herein, we report on the experimental apparatus, detector characterization, and spectrum analysis of one prototype detector. Owing to the higher rise-time resolution of the CDEX-10 prototype detector as compared with CDEX-1B, we identified the origin of an observed category of extremely fast events. For data analysis of the CDEX-10 prototype detector, we introduced and applied an improved bulk/surface event discrimination method. The results of the new method were compared to those of the CDEX-1B spectrum. Both sets of results showed good consistency in the 0-12 keVee energy range, except for the 8.0 keV K-shell X-ray peak from the external copper