Analysis of Controlling Genes for Tiller Growth of \u3cem\u3ePsathyrostachys juncea\u3c/em\u3e Based on Transcriptome Sequencing Technology

Tillering is an important trait of bunch grass that affects biomass and seed yield. Psathyrostachys juncea is a typical perennial bunch grass, and unraveling the regulatory mechanisms of tillering in P. juncea could be helpful to improve the yield of perennial gramineous forages. Hence, we selected the tiller node of P. juncea for transcriptome sequencing to determine the differentially expressed genes (DEG) between high and low tillering materials. The metabolic pathway was studied，candidate genes were screened, and reference genes stability were evaluated. The results showed that approximately 5466 DEGs were identified between two P. juncea genotypes that significantly differed in tiller number. Pathway enrichment analysis indicated that DEGs related to the biosynthesis of three classes of phytohormones, i.e., strigolactones (SLs), auxin (IAA), and cytokinin (CTK), as well as “nitrogen metabolism” and “biosynthesis of lignin” dominated the differences between the dense and sparse tillering genotypes. Meanwhile, the reference gene Actin1, having with the best stability, was screened from twelve highest expression level genes and was used in verification of ten tillering candidate genes. The candidate genes revealed in our research are involved in the regulation of tillering in perennial grasses and are available for new breeding resources establishment for high-yield perennial grasses

Anti-tumor activity of triterpenoid-rich extract from bamboo shavings (Caulis bamfusae in Taeniam)

Bamboo shavings are a kind of Chinese traditional medicine, which have been certificated as a material of functional food by the Ministry of Health in China. The anti-tumor activities of a triterpenoid-rich extract of bamboo shavings (EBS) and its main component, friedelin were evaluated in the present study. It was proved that EBS could inhibit the growth of P388 and A549 cancer cell lines effectively by SRB and MTT assay. Meanwhile, EBS had notable inhibitory effect on the sarcoma-loaded mice S180 model, which led to a depressed trend of tumor weight, compared to cyclophosphamide. Furthermore, the anti-tumor activity of friedelin monomer, a main triterpenoid separated from EBS, was tested by MTT assay and results showed that friedelin displayed rather strong anti-tumor activities on the proliferation of four cancer lines, A375, L929, Hela and THP-1, with a time-dose relationship compared to de-methylcantharidin, respectively. Therefore, it is suggested that EBS has a great potential to be applied in functional food for its anti-tumor activity, in which friedelin was one of the most important active factors.Key words: Extract of bamboo shavings, anti-tumor, friedelin, triterpenoid (Caulis bamfusae in Taeniam)

Research on automatic grinding platform for rare earth ingot casting

Aiming at the problems of low grinding efficiency and difficulty in ensuring grinding uniformity of rare earth metal ingots, a rare earth metal ingot grinding system was designed. Based on Creo software and ANSYS/Workbench software, the kinematics analysis, modal analysis and transient dynamics analysis were carried out on the walking mechanism and flipping mechanism of automatic displacement platform of grinding system. The results show that the rare earth metal ingot grinding system has good stability and is beneficial to improving the grinding quality

Variational Multi-Task Learning with Gumbel-Softmax Priors

Multi-task learning aims to explore task relatedness to improve individual tasks, which is of particular significance in the challenging scenario that only limited data is available for each task. To tackle this challenge, we propose variational multi-task learning (VMTL), a general probabilistic inference framework for learning multiple related tasks. We cast multi-task learning as a variational Bayesian inference problem, in which task relatedness is explored in a unified manner by specifying priors. To incorporate shared knowledge into each task, we design the prior of a task to be a learnable mixture of the variational posteriors of other related tasks, which is learned by the Gumbel-Softmax technique. In contrast to previous methods, our VMTL can exploit task relatedness for both representations and classifiers in a principled way by jointly inferring their posteriors. This enables individual tasks to fully leverage inductive biases provided by related tasks, therefore improving the overall performance of all tasks. Experimental results demonstrate that the proposed VMTL is able to effectively tackle a variety of challenging multi-task learning settings with limited training data for both classification and regression. Our method consistently surpasses previous methods, including strong Bayesian approaches, and achieves state-of-the-art performance on five benchmark datasets.Comment: 19 pages, 6 figures, accepted by NeurIPS 202

Neural Univariate Activity and Multivariate Pattern in the Posterior Superior Temporal Sulcus Differentially Encode Facial Expression and Identity

Faces contain a variety of information such as one’s identity and expression. One prevailing model suggests a functional division of labor in processing faces that different aspects of facial information are processed in anatomically separated and functionally encapsulated brain regions. Here, we demonstrate that facial identity and expression can be processed in the same region, yet with different neural coding strategies. To this end, we employed functional magnetic resonance imaging to examine two types of coding schemes, namely univariate activity and multivariate pattern, in the posterior superior temporal cortex (pSTS) - a face-selective region that is traditionally viewed as being specialized for processing facial expression. With the individual difference approach, we found that participants with higher overall face selectivity in the right pSTS were better at differentiating facial expressions measured outside of the scanner. In contrast, individuals whose spatial pattern for faces in the right pSTS was less similar to that for objects were more accurate in identifying previously presented faces. The double dissociation of behavioral relevance between overall neural activity and spatial neural pattern suggests that the functional-division-of-labor model on face processing is over-simplified, and that coding strategies shall be incorporated in a revised model

Probing the lightest new gauge boson BHB_H in the littlest Higgs model via the processes γγ→ffˉBH\gamma\gamma \to f\bar{f}B_H at the ILC

The neutral gauge boson $B_H$ with the mass of hundreds GeV, is the lightest particle predicted by the littlest Higgs(LH) model, and such particle should be the first signal of the LH model at the planed ILC if it exists indeed. In this paper, we study some processes of the $B_H$ production associated with the fermion pair at the ILC, i.e., $\gamma\gamma\to f\bar{f}B_{H}$. The studies show that the most promising processes to detect $B_H$ among $\gamma\gamma\to f\bar{f}B_{H}$ are $\gamma\gamma\to l'^+l'^-B_{H}(l'=e,\mu)$, and they can produce the sufficient signals in most parameter space preferred by the electroweak precision data at the ILC. On the other hand, the signal produced via the certain $B_H$ decay modes is typical and such signal can be easily identified from the SM background. Therefore, $B_H$, the lightest gauge boson in the LH model would be detectable at the photon collider realized at the ILC.Comment: 12 pages, 4 figure

Relative entropy of entanglement of a kind of two qubit entangled states

We in this paper strictly prove that some block diagonalizable two qubit entangled state with six none zero elements reaches its quantum relative entropy entanglement by the a separable state having the same matrix structure. The entangled state comprises local filtering result state as a special case.Comment: 5 page