Multi-turn Inference Matching Network for Natural Language Inference

Natural Language Inference (NLI) is a fundamental and challenging task in Natural Language Processing (NLP). Most existing methods only apply one-pass inference process on a mixed matching feature, which is a concatenation of different matching features between a premise and a hypothesis. In this paper, we propose a new model called Multi-turn Inference Matching Network (MIMN) to perform multi-turn inference on different matching features. In each turn, the model focuses on one particular matching feature instead of the mixed matching feature. To enhance the interaction between different matching features, a memory component is employed to store the history inference information. The inference of each turn is performed on the current matching feature and the memory. We conduct experiments on three different NLI datasets. The experimental results show that our model outperforms or achieves the state-of-the-art performance on all the three datasets

A pathway analysis of genome-wide association study highlights novel type 2 diabetes risk pathways.

Genome-wide association studies (GWAS) have been widely used to identify common type 2 diabetes (T2D) variants. However, the known variants just explain less than 20% of the overall estimated genetic contribution to T2D. Pathway-based methods have been applied into T2D GWAS datasets to investigate the biological mechanisms and reported some novel T2D risk pathways. However, few pathways were shared in these studies. Here, we performed a pathway analysis using the summary results from a large-scale meta-analysis of T2D GWAS to investigate more genetic signals in T2D. Here, we selected PLNK and VEGAS to perform the gene-based test and WebGestalt to perform the pathway-based test. We identified 8 shared KEGG pathways after correction for multiple tests in both methods. We confirm previous findings, and highlight some new T2D risk pathways. We believe that our results may be helpful to study the genetic mechanisms of T2D

Circular photogalvanic effect induced by near-infrared radiation in InAs quantum wires patterned quasi two-dimensional electron system

In this work we investigated the InAs/InAlAs quantum wires (QWRs) superlattice by optically exciting the structure with near-infrared radiation. By varying the helicity of the radiation at room temperature we observed the circular photogalvanic effect related to the $C_{2v}$ symmetry of the structure, which could be attributed to the formation of a quasi two-dimensional system underlying in the vicinity of the QWRs pattern. The ratio of Rashba and Dresselhaus terms shows an evolution of the spin-orbit interaction in quasi two-dimensional structure with the QWR layer deposition thickness.Comment: 9 pages, 3 figure