Preliminary study on Late Triassic to Early Jurassic strata and floral variation in Hechuan region of Chongqing,southern Sichuan Basin

The end-Triassic mass extinction event is extensively known, however, the terrestrial response of this event is still poorly understood. Here we briefly report our preliminary results on the variation of floral diversity through the Triassic/Jurassic boundary deposits in the Tanba section of Hechuan region, Chongqing, southern China. It is recognized that the floral biodiversity of the Hechuan region shows a distinct change through the Triassic and Jurassic transition; and the floral diversity loss reaches up to 92.5% at species level. Meanwhile, in northeastern region of the Sichuan Basin, the floral diversity declines by about 50% across the T/J boundary at species level with a remarkable turnover of genera and species. The potential reasons and mechanisms that cause the floral diversity differentiation of the T/J boundary in the Sichuan Basin are briefly discussed in this note.

Rolling Bearing Fault Diagnosis Based On Convolutional Capsule Network

Fault diagnosis technology has been widely applied and is an important part of ensuring the safe operation of mechanical equipment.In response to the problem of frequent faults in rolling bearings,this paper designs a rolling bearing fault diagnosis method based on convolutional capsule network(CCN).More specifically,the original vibration signal is converted into a two-dimensional time–frequency image using continuous wavelet transform(CWT),and the feature extraction is performed on the two-dimensional time–frequency image using the convolution layer at the front end of the network,and the extracted features are input into the capsule network.The capsule network converts the extracted features into vector neurons,and the dynamic routing algorithm is used to achieve feature transfer and output the results of fault diagnosis.Two different datasets are used to compare with other traditional deep learning models to verify the fault diagnosis capability of the method.The results show that the CCN has good diagnostic capability under different working conditions,even in the presence of noise and insufficient samples,compared to other models.This method contributes to the safe and reliable operation of mechanical equipment and is suitable for other rotating scenarios.

Plasmonic light trapping for enhanced light absorption in film-coupled ultrathin metamaterial thermophotovoltaic cells

Ultrathin cells have gained increasing attention due to their potential for reduced weight, reduced cost and increased flexibility. However, the light absorption in ultrathin cells is usually very weak compared to the corresponding bulk cells. To achieve enhanced photon absorption in ultrathin thermophotovoltaic （TPV） cells, this work proposed a film-coupled metamaterial structure made of nanometer-thick gallium antimonide （GaSh） layer sandwiched by a top one-dimensional （1D） metallic grating and a bottom metal film. The spectral normal absorptance of the proposed structure was calculated using the rigorous coupled-wave algorithm （RCWA） and the absorption enhancement was elucidated to be attributed to the excitations of magnetic polariton （MP）, surface plasmon polariton （SPP）, and Fabry-Perot （FP） resonance. The mechanisms of MP, SPP, and FP were further confirmed by an inductor-capacitor circuit model, disper- sion relation, and phase shift, respectively. Effects of grating period, width, spacer thickness, as well as incidence angle were discussed. Moreover, short-circuit current density, open-circuit voltage, output electric power,and conversion efficiency were evaluated for the ultrathin GaSb TPV cell with a film-coupled metamaterial structure. This work will facilitate the development of next- generation low-cost ultrathin infrared TPV cells.