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In this paper, Au nanoparticles/reduced graphene oxide (AuNPs/rGO) nanocomposites were prepared through a one-pot strategy, carried out by heating the mixture of HAuCl 4 and graphene oxide solution at 90°C under alkaline condition. The resultant AuNPs/rGO nanocomposites were found to exhibit good catalytic performance toward H 2 O 2 reduction and oxidation as well as hydrazine oxidation. The electrochemical sensing application of the nanocomposites for H 2 O 2 , glucose, and hydrazine was also demonstrated successfully.

This paper reviewed the classical principal components analysis methods for multivariate data analysis and feature extraction in pattern classification. A kernel-based extension to the classical PCA models was discussed to cope with nonlinear data dependencies. Kernel PCA was implicitly performing a linear PCA in some high-dimensional kernel feature space that was nonlinearly related to input space by using a suitable nonlinear kernel function mapping. And then, the conjunction of kernel PCA method and RBF neural networks was proposed in practical and algorithmic considerations. Finally, we illustrate the usefulness of kernel PCA algorithms by discussing kernel PCA RBF neural networks application in handwritten digit classification.

In order to study the wind flow field and dust transport law of the comprehensive mining work surface, taking the 21103 comprehensive mining working surface of Hulusu Coal Mine as the research object, SolidWorks was used to establish the comprehensive mining working surface model, and the comprehensive mining working surface under different inlet wind speed conditions was simulated and analyzed by Fluent. The results show that due to the existence of the high-speed wind flow belt, dust is mainly distributed near the downwind side working surface; when the inlet speed is 2.5m/s, the dust mass concentration of the comprehensive mining working surface is low and it is not easy to cause secondary dust, which is the optimal inlet speed; the dust distribution within 10m of the downwind side of the shearer is the most, which is the key area of dust prevention and control.

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