Learning text representation using recurrent convolutional neural network with highway layers

Recently, the rapid development of word embedding and neural networks has brought new inspiration to various NLP and IR tasks. In this paper, we describe a staged hybrid model combining Recurrent Convolutional Neural Networks (RCNN) with highway layers. The highway network module is incorporated in the middle takes the output of the bi-directional Recurrent Neural Network (Bi-RNN) module in the first stage and provides the Convolutional Neural Network (CNN) module in the last stage with the input. The experiment shows that our model outperforms common neural network models (CNN, RNN, Bi-RNN) on a sentiment analysis task. Besides, the analysis of how sequence length influences the RCNN with highway layers shows that our model could learn good representation for the long text.Comment: Neu-IR '16 SIGIR Workshop on Neural Information Retrieva

Short-time critical dynamics and universality on a two-dimensional Triangular Lattice

Critical scaling and universality in short-time dynamics for spin models on a two-dimensional triangular lattice are investigated by using Monte Carlo simulation. Emphasis is placed on the dynamic evolution from fully ordered initialstates to show that universal scaling exists already in the short-time regime in form of power-law behavior of the magnetization and Binder cumulant. The results measured for the dynamic and static critical exponents, $\theta$, $z$, $\beta$ and $\nu$, confirm explicitly that the Potts models on the triangular lattice and square lattice belong to the same universality class. Our critical scaling analysis strongly suggests that the simulation for the dynamic relaxation can be used to determine numerically the universality.Comment: LaTex, 11 pages and 10 figures, to be published in Physica

A Dataset of Open-Domain Question Answering with Multiple-Span Answers

Multi-span answer extraction, also known as the task of multi-span question answering (MSQA), is critical for real-world applications, as it requires extracting multiple pieces of information from a text to answer complex questions. Despite the active studies and rapid progress in English MSQA research, there is a notable lack of publicly available MSQA benchmark in Chinese. Previous efforts for constructing MSQA datasets predominantly emphasized entity-centric contextualization, resulting in a bias towards collecting factoid questions and potentially overlooking questions requiring more detailed descriptive responses. To overcome these limitations, we present CLEAN, a comprehensive Chinese multi-span question answering dataset that involves a wide range of open-domain subjects with a substantial number of instances requiring descriptive answers. Additionally, we provide established models from relevant literature as baselines for CLEAN. Experimental results and analysis show the characteristics and challenge of the newly proposed CLEAN dataset for the community. Our dataset, CLEAN, will be publicly released at zhiyiluo.site/misc/clean_v1.0_ sample.json

Constructions of Binary Optimal Locally Repairable Codes via Intersection Subspaces

Locally repairable codes (LRCs), which can recover any symbol of a codeword by reading only a small number of other symbols, have been widely used in real-world distributed storage systems, such as Microsoft Azure Storage and Ceph Storage Cluster. Since binary linear LRCs can significantly reduce coding and decoding complexity, constructions of binary LRCs are of particular interest. The aim of this paper is to construct dimensional optimal binary locally repairable codes with disjoint local repair groups. We introduce how to connect intersection subspaces with binary locally repairable codes and construct dimensional optimal binary linear LRCs with locality $2^b$ ($b\geq 3$) and minimum distance $d\geq 6$ by employing intersection subspaces deduced from the direct sum. This method will sufficiently increase the number of possible repair groups of dimensional optimal LRCs, and thus efficiently expanding the range of the construction parameters while keeping the largest code rates compared with all known binary linear LRCs with minimum distance $d\geq 6$ and locality $2^b$ ($b\geq 3$).Comment: Accepted for publication in the SCIENCE CHINA Information Science

PO-205 Effect of AMPK agonist / inhibitor on Nrf2 expression in C2C12 cells

Objective In the past few decades, the study of skeletal muscle oxidative stress has been concerned about the increase of free radicals induced by muscle contraction. In recent years, the activation of antioxidant stress signaling pathway has gradually become one of the hot topics in the field of sports medicine. Although current research has confirmed that long-term aerobic training can bring health benefits to the body, the molecular mechanism of its role is still not very clear.Traditionally, AMPK has been regarded as the energy receptor of cells. During exercise, the energy consumption of skeletal muscle doubled, ATP decreased, AMP increased, and the ratio of AMP/ATP increased, thus inducing the activation of AMPK and regulating cell energy metabolism. Recent studies have found that AMPK not only plays an important role in the regulation of energy metabolism, but also plays a role in the body's antioxidant stress response. However, the relationship between AMPK and oxidative stress has been studied only in a small number of cells in non skeletal muscle cells. The results of this few studies show that oxidative stress in AMPK can not depend on the increase of intracellular AMP/ATP ratio, and the independent activation of AMPK, thus reducing the level of intracellular ROS, but the molecular mechanism of its action is not clear. Nrf2 is an important nuclear transcription factor in the body and plays an important role in the body's antioxidant stress response. Whether AMPK can participate in the regulation of Nrf2 mediated antioxidant activity in skeletal muscle has not been reported.In this study, the mouse skeletal muscle C2C12 cells were used in vitro cell experiments. The AMPK pharmacologic activator AICAR and the pharmacological inhibitor Compound C were used to treat the cells respectively. The role of AMPK in the regulation of Nrf2 expression in C2C12 cells and its mechanism were observed.  Methods Cell experiments were performed on C2C12 cells of skeletal muscle of mice, and AMPK activator AICAR and AMPK inhibitor Compound C were used to intervene. The fluorescence intensity of C2C12 cells in each group was qualitatively detected by fluorescence inverted microscope, and the ROS level of C2C12 cells in each group was detected by fluorescence colorimetry. Results the ROS level of each group was significantly higher than that of the control group. RT-PCR assay was used to detect the antioxidant enzyme mRNA level of C2C12 cells in each group. Western Blot assay was used to detect the expression of AMPK alpha, pAMPK alpha, Nrf2, pNrf2 and antioxidant enzyme protein in C2C12 cells of each group.  Results (1) compared with the control group, the pAMPK alpha /AMPK alpha ratio of C2C12 cells in the agonist group increased significantly, the expression of pNrf2 protein in the cells increased significantly, and the expression of NQO1mRNA, HO-1mRNA and GSR mRNA increased significantly, and the cells SOD1, GCLM, NQO1, HO-1, pNrf2, and protein were significantly increased. Low. (2) compared with the control group, the levels of NQO1mRNA, HO-1mRNA, CATmRNA, SOD1mRNA, Gpx-1mRNA and GCLc mRNA in the C2C12 cells of the inhibitor group decreased significantly, and the expression of NQO1 and GCLM proteins in the cells decreased significantly, and the ROS level of the cells increased significantly.  Conclusions  (1) the activation of AMPK by AICAR activates the increase of Nrf2 activation in skeletal muscle C2C12 cells, and then increases the expression of mRNA and protein (SOD1, GCLM, NQO1, NQO1, GSR) in the downstream of Nrf2 (NQO1, HO-1, GSR), and significantly reduces the intracellular level.(2) the inhibition of AMPK by Compound C significantly decreased the mRNA expression of C2C12 cells (NQO1, HO-1, CAT, SOD1, Gpx-1, GCLc) in skeletal muscle, and significantly decreased the expression of protein (NQO1 and GCLc