Analysis of the Teaching Strategy of English Continuation Task in Senior High School from the Perspective of Metacognitive Theory

With the emergence of new question type in the English reform of college Entrance examination, the academia has set off a research craze of "continuation task".This paper uses questionnaires and interviews with teachers to investigate and study the implementation, effect and existing problems of continuation task in senior high school English reading.Based on the teaching status and existing problems, this paper puts forward three strategies to improve the teaching effect of continuation task from the perspective of metacognitive theory, in order to help front-line English teachers in senior high schools effectively implement continuation task teaching, improve students' ability and level of continuation task, and thus improve students' English learning effect

Nonconforming finite element approximations of the Steklov eigenvalue problem and its lower bound approximations

summary:The paper deals with error estimates and lower bound approximations of the Steklov eigenvalue problems on convex or concave domains by nonconforming finite element methods. We consider four types of nonconforming finite elements: Crouzeix-Raviart, $Q_{1}^{\rm rot}$, $EQ_{1}^{\rm rot}$ and enriched Crouzeix-Raviart. We first derive error estimates for the nonconforming finite element approximations of the Steklov eigenvalue problem and then give the analysis of lower bound approximations. Some numerical results are presented to validate our theoretical results

Task-Oriented Multi-User Semantic Communications for VQA

Semantic communications focus on the transmission of semantic features. In this letter, we consider a task-oriented multi-user semantic communication system for multimodal data transmission. Particularly, partial users transmit images while the others transmit texts to inquiry the information about the images. To exploit the correlation among the multimodal data from multiple users, we propose a deep neural network enabled semantic communication system, named MU-DeepSC, to execute the visual question answering (VQA) task as an example. Specifically, the transceiver for MU-DeepSC is designed and optimized jointly to capture the features from the correlated multimodal data for task-oriented transmission. Simulation results demonstrate that the proposed MU-DeepSC is more robust to channel variations than the traditional communication systems, especially in the low signal-to-noise (SNR) regime

Deep Learning Enabled Semantic Communication Systems

Recently, deep learned enabled end-to-end (E2E) communication systems have been developed to merge all physical layer blocks in the traditional communication systems, which make joint transceiver optimization possible. Powered by deep learning, natural language processing (NLP) has achieved great success in analyzing and understanding large amounts of language texts. Inspired by research results in both areas, we aim to providing a new view on communication systems from the semantic level. Particularly, we propose a deep learning based semantic communication system, named DeepSC, for text transmission. Based on the Transformer, the DeepSC aims at maximizing the system capacity and minimizing the semantic errors by recovering the meaning of sentences, rather than bit- or symbol-errors in traditional communications. Moreover, transfer learning is used to ensure the DeepSC applicable to different communication environments and to accelerate the model training process. To justify the performance of semantic communications accurately, we also initialize a new metric, named sentence similarity. Compared with the traditional communication system without considering semantic information exchange, the proposed DeepSC is more robust to channel variation and is able to achieve better performance, especially in the low signal-to-noise (SNR) regime, as demonstrated by the extensive simulation results.Comment: 13 pages, Journal, accepted by IEEE TS

Association between Tumor necrosis factor-alpha gene polymorphisms and prostate cancer risk: a meta-analysis

BACKGROUND: Tumor necrosis factor-alpha (TNF-α) is an important inflammatory cytokine that may play a role in controlling the progression of prostate cancer. Two common polymorphisms in the TNF-α gene, −308G/A and −238C/T, have been suggested to alter the risk for prostate cancer, but the results have been inconclusive so far. In order to obtain a better understanding of the effects of these two polymorphisms on prostate cancer risk, all available studies were considered in a meta-analysis. METHODS: We conducted a comprehensive literature search in the Cochrane Library, PubMed, EMBASE, Chinese Biomedical Literature database (CBM), and the China National Knowledge Infrastructure (CNKI). The associations were evaluated by calculating the pooled odds ratio (OR) with 95% confidence interval (95% CI). RESULTS: In this meta-analysis, we included 14 studies with 5,757 patients and 6,137 control subjects for the TNF-α-308G/A polymorphism and 1,967 patients and 2,004 control subjects for the TNF-α-238C/T polymorphism. A significantly increased prostate cancer risk was found to be associated with the TNF-α-308C/T polymorphism in studies with healthy volunteers (AA + AG vs. GG: OR = 1.531, 95% CI = 1.093–2.145; P = 0.013; AG vs. GG: OR = 1.477, 95% CI = 1.047–2.085; P = 0.026). No significant association was found between the TNF-α-238G/A polymorphism and prostate cancer risk in the overall or subgroup analyses. There was no risk of publication bias in this meta-analysis. CONCLUSIONS: Our results suggest that while the TNF-α-238G/A polymorphism may not be associated with prostate cancer the TNF-α-308C/T polymorphism may significantly contribute to prostate cancer susceptibility in healthy volunteers. VIRTUAL SLIDES: The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/162928812011630

Tissue factor pathway inhibitor-2 induced hepatocellular carcinoma cell differentiation

AbstractTo investigate the effect of over-expression of tissue factor pathway inhibitor-2 (TFPI-2) on the differentiation of hepatocellular carcinoma (HCC) cells (Hep3B and HepG2). The TFPI-2 recombinant adenovirus (pAd-TFPI-2) was constructed using the pAdeasy-1 vector system. Transfected by pAd-TFPI-2, the cell proliferation of HCC cells was evaluated by CCK-8 assay, flow cytometry was used to detect cell apoptosis and CD133 expression. Real-time PCR and Western blot were used to detect the expression levels of markers of hepatocellular cancer stem cells (CSC) and hepatocytes. The over-expression of TFPI-2 significantly suppressed cell proliferation, induced apoptosis, and dramatically decreased the percentage of CD133 cells, which was considered as CSC in HCC. Real-time PCR and Western blot showed that the expression of markers of CSC in Hep3BcellsandHepG2 cells infected with pAd-TFPI-2 was markedly lower than those of the control group (P<0.05), while the expression of markers of hepatocytes was significantly increased (P<0.05). Hence, TFPI-2 could induce the differentiation of hepatocellular carcinoma cells into hepatocytes, and is expected to serve as a novel way for the treatment of HCC