Geochronological and geochemical constraints on Late Cryogenian to Early Ediacaran magmatic rocks on the northern Tarim Craton:implications for tectonic setting and affinity with Gondwana

The Tarim Craton provides a geologic record of both the fragmentation of the Rodinian supercontinent and the subsequent assembly of Gondwana. However, the timing and interactions of these radically different tectonic processes remain contested. A critical part of this debate revolves around the Late Cryogenian-Ediacaran igneous rocks along the Craton’s northern margin, specifically, whether they record super-plume related Rodinian breakup or Gondwanan orogeny. To address this issue, we present zircon U-Pb-Hf isotopic data and whole rock geochemistry from Late Cryogenian to Early Ediacaran granitoids of the northern Tarim Craton. U-Pb zircon ages reveal three magmatic periods along the northern Tarim margin: ca. 660–640 Ma, 635–625 Ma and 620–600 Ma, associated with small scale felsic and mafic magmas. These granitoids have an A2-type affinity and are enriched in alkalines, but are depleted in Nb, Ta, Sr, P and Ti. Elemental data and generally negative εHf(t) values (−13.96 to 1.65) suggest that they were mainly derived from partial melting of enriched, subduction-modified lithospheric mantle triggered by upwelling of the asthenospheric mantle along the active continental margin of northern Tarim. We suggest that the Tarim Craton travelled as an isolated plate for much of the Late Neoproterozoic, near the outer part of Rodinia and subsequently Gondwana. During this time it was affected by localized and periodic subduction-related intrusion and eruption. However, within the samples of this study, there is no U-Pb-Hf isotopic and whole-rock geochemical evidence to support either super-plume-related rifting (i.e. Rodinian breakup) or Pan-African orogeny (i.e. Gondwanan assembly).</p

Spontaneous facial expression database for academic emotion inference in online learning

Academic emotions can produce a great impact on the learning effect. Normally, emotions are expressed externally in the students' facial expressions, speech and behaviour. In this paper, the focus is on automatic academic emotion inference based on facial expressions in online learning. Considering the lack of training samples for the inference algorithm, a spontaneous facial expression database is established. It includes the facial expressions of five common academic emotions and consists of two subsets: a video clip database and an image database. A total of 1,274 video clips and 30,184 images from 82 students are included in the database. The samples are labelled by both the participants and external coders. An extensive analysis is carried out on the image database using a convolutional neural network (CNN)‐based algorithm to infer self‐annotation. Some data augmentation algorithms are applied to improve the algorithm performance. Additionally, an adaptive data augmentation algorithm based on spatial transformer network is introduced, which can remove some confounding factors in the original images. The algorithm can obviously improve the inference performance, which has been proven by comparing some evaluation indicators before and after adoption. Such a database will certainly accelerate the application of affective computing in the educational field

Association of the Asporin D14 Allele with Lumbar-Disc Degeneration in Asians

Lumbar-disc degeneration (LDD) is a polygenic disease. Susceptibility genes reported so far are mainly extracellular matrix proteins. D14 allele of asporin (ASPN) is associated with osteoarthritis (OA). Candidate-gene association studies showed that the D14 allele is also significantly associated with LDD in Chinese and Japanese individuals. Meta-analysis showed that individuals harboring a D14 allele had higher risk with a summary odds ratio of 1.70 (p = 0.000013). ASPN expression in vertebral discs increased with age and degeneration. Our results indicate ASPN is a LDD gene in Asians, and common risk factors may be considered for OA and LDD