Classification of motor imagery using chaotic entropy based on sub-band EEG source localization.

Objective.Electroencephalography (EEG) has been widely used in motor imagery (MI) research by virtue of its high temporal resolution and low cost, but its low spatial resolution is still a major criticism. The EEG source localization (ESL) algorithm effectively improves the spatial resolution of the signal by inverting the scalp EEG to extrapolate the cortical source signal, thus enhancing the classification accuracy.Approach.To address the problem of poor spatial resolution of EEG signals, this paper proposed a sub-band source chaotic entropy feature extraction method based on sub-band ESL. Firstly, the preprocessed EEG signals were filtered into 8 sub-bands. Each sub-band signal was source localized respectively to reveal the activation patterns of specific frequency bands of the EEG signals and the activities of specific brain regions in the MI task. Then, approximate entropy, fuzzy entropy and permutation entropy were extracted from the source signal as features to quantify the complexity and randomness of the signal. Finally, the classification of different MI tasks was achieved using support vector machine.Main result.The proposed method was validated on two MI public datasets (brain-computer interface (BCI) competition III IVa, BCI competition IV 2a) and the results showed that the classification accuracies were higher than the existing methods.Significance.The spatial resolution of the signal was improved by sub-band EEG localization in the paper, which provided a new idea for EEG MI research.

Molybdenum carbide as an efficient catalyst for low-temperature hydrogenation of dimethyl oxalate.

Silica-supported molybdenum carbide (Mo2C/SiO2) is found to be a highly active, selective and stable catalyst for the hydrogenation of dimethyl oxalate to ethanol at low temperatures (473 K). Moreover, the formation of ethanol over the Mo2C catalyst performs via the novel intermediate methyl acetate instead of ethylene glycol forming over the Cu catalyst.

Destruction of representative submarine food waste using supercritical water oxidation.

In this study, 13 types of organic materials were oxidized using H2O2 in a continuous flow reactor under the condition of supercritical water. The effect of the operational parameters on the conversion of total organic carbon (TOC) and total nitrogen (TN) was investigated, and the resulting quality of treated water was analyzed. It was found that these materials were easily oxidized with a TOC conversion achieving 99% at temperature of 460 °C and TN conversion reaching 94% at temperature of 500 °C. Rice decomposition was rapid, with TOC and TN decomposition rates of 99% obtained within residence of 100 s at temperature of 460 °C. At temperature of 460 °C, pressure of 24 MPa, residence time of 100 s, and excess oxygen of 100%, the quality of treated water attained levels commensurate with China's Standards for Drinking Water Quality. Reaction rate equation parameters were obtained by fitting the experimental data to the differential equation obtained using the Runge-Kutta algorithm. The decrease of the TOC in water samples exhibited reaction orders of 0.95 for the TOC concentration and 0.628 for the oxygen concentration. The activation energy was 83.018 kJ/mol.