It is important to understand moulting behaviours in trilobites through different growth stages. Most studies have focused on patterns of moulting in trilobites based on a few exuviae. The present study is based on 177 disarticulated specimens of Arthricocephalites xinzhaiheensis from the Balang Formation (Cambrian Series 2, Stage 4, Guizhou Province, South China). The abundance of disarticulated assemblages allows the distinction between carcasses and exuviae to be made with confidence and enables a detailed exploration of moulting behaviours. About 96.6% of exuviae of both meraspides and holaspides of Ar. xinzhaiheensis show a disarticulated cranidium characterizing Henningsmoen's configuration. The trilobites commonly used the cephalic sutures and cephalothoracic joint for moulting, involving lateral rotation or inversion of the cranidium to create a wide exuvial gape. Only one specimen displays the Somersault configuration characterized by an overturned lower cephalic unit and the data also show that trilobites employing the cephalic sutures to create an anterior exuvial gape are rare in holaspides. Though some specimens are similar to Salter's configuration with an inverted cephalon with respect to the thoracopygon, the specimens show closed cephalic sutures and thus dissociated or inverted cephala are likely to represent disturbed carcasses. Several other species of oryctocephalid trilobites display Henningsmoen's configuration indicating that exuviation by disarticulated cranidium to enlarge the exuvial gape was prevalent in the family from Cambrian Series 2 Stage 4 to the succeeding Wuliuan Stage of the Miaolingian Series.

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The complete chloroplast genome of Andrographis paniculata, an important medicinal plant with great economic value, has been studied in this article. The genome size is 150,249 bp in length, with 38.3% GC content. A pair of inverted repeats (IRs, 25,300 bp) are separated by a large single copy region (LSC, 82,459 bp) and a small single-copy region (SSC, 17,190 bp). The chloroplast genome contains 114 unique genes, 80 protein-coding genes, 30 tRNA genes and 4 rRNA genes. In these genes, 15 genes contained 1 intron and 3 genes comprised of 2 introns.

The precise evaluation of camera position and orientation is a momentous procedure of most machine vision tasks, especially visual localization. Aiming at the shortcomings of local features of dealing with changing scenes and the problem of realizing a robust end-to-end network that worked from feature detection to matching, an invariant local feature matching method for changing scene image pairs is proposed, which is a network that integrates feature detection, descriptor constitution, and feature matching. In the feature point detection and descriptor construction stage, joint training is carried out based on a neural network. In the feature point extraction and descriptor construction stage, joint training is carried out based on a neural network. To obtain local features with solid robustness to viewpoint and illumination changes, the Vector of Locally Aggregated Descriptors based on Neural Network (NetVLAD) module is introduced to compute the degree of correlation of description vectors from one image to another counterpart. Then, to enhance the relationship between relevant local features of image pairs, the attentional graph neural network (AGNN) is introduced, and the Sinkhorn algorithm is used to match them; finally, the local feature matching results between image pairs are output. The experimental results show that, compared with the existed algorithms, the proposed method enhances the robustness of local features of varying sights, performs better in terms of homography estimation, matching precision, and recall, and when meeting the requirements of the visual localization system to the environment, the end-to-end network tasks can be realized.