一种轻量级文本蕴含模型

现有主流文本蕴含模型大多采用循环神经网络编码,并采用各种注意力推理机制或辅以手工提取的特征来提升蕴含关系识别准确率,由于复杂的网络结构和RNNs网络串行机制导致这些模型训练和推理速度较慢.本文提出轻量级文本蕴含模型,采用自注意力编码器编码文本向量,点积注意力交互两段文本,再采用卷积神经网络对交互特征推理,整个结构可根据不同数据的推理难度叠加不同模块数量.在多个文本蕴含数据集实验表明,本文模型在保持较高识别准确率情况下仅用一个块参数仅为665K,模型推理速度相比其他主流文本蕴含模型至少提升一倍.     

Activation of Stimulation of Interferon Genes (STING) Signal and Cancer Immunotherapy

Stimulator of interferon gene (STING), an intracellular receptor in the endoplasmic reticulum, could induce the production of cytokines such as type I interferon (IFN) by activating the cGAS-STING signal pathway. In recent years, activation of STING has shown great potential to enhance anti-tumor immunity and reshape the tumor microenvironment, which is expected to be used in tumor immunotherapy. A number of STING agonists have demonstrated promising biological activity and showed excellent synergistic anti-tumor effects in combination with other cancer therapies in preclinical studies and some clinical trials. The combination of STING agonists and ICI also showed a potent effect in improving anti-tumor immunity. In this review, we introduce the cGAS-STING signaling pathway and its effect in tumor immunity and discuss the recent strategies of activation of the STING signaling pathway and its research progress in tumor immunotherapy.     

Model evolvement and reuse technology of injection molding machine based on performance knowledge

To illuminate the necessity of model evolvement and reuse, dynamics of injection molding machine＇s product models are analyzed. The performance knowledge is used to support the model evolvement and reuse. The driven factors of mechanical product model are concluded. The dynamic characteristics of reuse. Finally, HT1800X1N series injection molding machines are taken as examples to illuminate that the arithmetic is correct and practical.     

Electrochemical Immunoassay for Tumor Marker CA19-9 Detection Based on Self-Assembled Monolayer

A CA19-9 electrochemical immunosensor was constructed using a hybrid self-assembled membrane modified with a gold electrode and applied to detect real samples. Hybrid self-assembled membranes were selected for electrode modification and used to detect antigens. First, the pretreated working electrodes were placed in a 3-mercaptopropionic acid (MPA)/β-mercaptoethanol (ME) mixture for 24 h for self-assembly. The electrodes were then placed in an EDC/NHS mixture for 1 h. Layer modification was performed by stepwise dropwise addition of CA19-9 antibody, BSA, and antigen. Differential pulse voltammetry was used to characterize this immunosensor preparation process. The assembled electrochemical immunosensor enables linear detection in the concentration range of 0.05–500 U/mL of CA19-9, and the detection limit was calculated as 0.01 U/mL. The results of the specificity measurement test showed that the signal change of the interfering substance was much lower than the response value of the detected antigen, indicating that the sensor has good specificity and strong anti-interference ability. The repeatability test results showed that the relative standard deviations were less than 5%, showing good accuracy and precision. The CA19-9 electrochemical immunosensor was used for the actual sample detection, and the experimental results of the standard serum addition method showed that the RSD values of the test concentrations were all less than 10%. The recoveries were 102.4–115.0%, indicating that the assay has high precision, good accuracy, and high potential application value.     

Deep Multilabel Multilingual Document Learning for Cross-Lingual Document Retrieval

Cross-lingual document retrieval, which aims to take a query in one language to retrieve relevant documents in another, has attracted strong research interest in the last decades. Most studies on this task start with cross-lingual comparisons at the word level and then represent documents via word embeddings, which leads to insufficient structure information. In this work, the cross-lingual comparison at the document level is achieved through the cross-lingual semantic space. Our method, MDL (deep multilabel multilingual document learning), leverages a six-layer fully connected network to project cross-lingual documents into a shared semantic space. The semantic distances can be calculated when the cross-lingual documents are transformed into embeddings in semantic space. The supervision signals are automatically extracted from the data and then used to construct the semantic space via a linear classifier. The ambiguity of manual labels could be avoided and the multilabel supervision signals can be acquired instead of a single label. The representation of the semantic space is enriched by multilabel supervision signals, which improves the discriminative ability of the embeddings. The MDL is easy to extend to other fields since it does not depend on specific data. Furthermore, MDL is more efficient than the models training all languages jointly, since each language is trained individually. Experiments on Wikipedia data showed that the proposed method outperforms the state-of-the-art cross-lingual document retrieval methods.     

聚合物气体辅助注射成型制品的形态结构

作为一种由常规注射成型发展起来的聚合物加工技术,气体辅助注射成型具有节约原材料、缩短成型周期以及提高制品性能等优点,已得到广泛的应用.由于气辅成型过程是一个在刚、柔双重约束界面条件下进行的多相复杂体系的多次流动过程,因而其形态结构的形成、发展和演化要远比常规注塑成型复杂.然而在气辅成型的形态结构方面,国内外的研究一直以来开展得较少.近年来,作者在聚合物及其共混物、复合材料气辅成型制品的形态结构方面已开展了广泛的研究工作,本文对这些工作和一些重要结果作了总结,并简要分析了成型过程中剪切场对形态演化的影响,最后对该研究方向的发展趋势作了展望.     

Tailoring Pore Structure and Morphologies in Covalent Organic Frameworks for Xe/Kr Capture and Separation

As a rising star among porous solid materials, covalent organic frameworks(COFs) with excellent properties including but not limit to facilely controllable structure, high porosity, and multi-chemical functionality represent significant potential for efficient ¹²⁷Xe/⁸⁵Kr capture and separation. In this study, through tuning the length of the organic ligands, two-dimensional(2D) COF mate-rials with identical connection group but different pore properties, denoted as ATFG-COF and TpPa-COF with AA-stacking model and TpBD-COF with AB-stacking model were synthesized and tested for Kr and Xe adsorption for the first time. Adsorption measurements indicate that the narrower pore apertures and higher porosity are conducive for COF materials to capture Xe and Kr. Furthermore, the Henry's constant, isosteric heat of adsorption(Q_st), and ideal adsorbed solution theory(IAST) selectivity of ATFG-COF, the pore size of which is closest to the kinetic diameter of the Xe atom(0.41 nm) among 2D COF materials, were carried out based on the single component sorption isotherms. The results illustrate that the high isosteric heat values of Xe/Kr adsorption on ATFG-COF are 25 and 16 kJ/mol at room temperature, respectively. Henry's law predicts that the selectivity factor of Xe to Kr is 6.07, consistent with the adsorption selectivity(ca. 6) calculated based on the IAST.     

Genetically engineered materials: Proteins and beyond

Information-rich molecules provide opportunities for evolution. Genetically engineered materials are superior in that their properties are coded within genetic sequences and could be fine-tuned. In this review, we elaborate the concept of genetically engineered materials(GEMs) using examples ranging from engineered protein materials to engineered living materials. Proteinbased materials are the materials of choice by nature. Recent progress in protein engineering has led to opportunities to tune...     

铁素体不锈钢热轧板材的拉伸行为和断裂特征

用金相显微镜、X射线衍射仪、SEM手段研究2种铁素体不锈钢热轧板材0.04C-16Cr、0.02C-12Cr在室温下的拉伸行为和断裂特征.结果表明,这2种铁素体不锈钢的强度高,但塑性较差;C、Cr含量较低的0.02C-12Cr钢的强度、硬度均较0.04C-16Cr的高,这是由于0.02C-12Cr在空冷过程中产生了大量的马氏体;2种钢室温下都为韧性断裂,其断口微观形貌主要为细小韧窝聚集,沿轧制方向分布的条带组织中存在细小的碳化物颗粒,成为韧窝的发源地;部分断口出现了分层和侧向开裂现象.分析其断口形貌、断裂过程和组织特征,可知沿着轧制方向分布的条带组织致使材料表现出上述力学行为和断裂特征.     

YSI 6600型水质多参数监测仪在太湖藻类监测中的应用

采用YSI 6600型水质多参数监测仪对太湖藻类密度进行监测,发现蓝藻在水中呈垂直分布。选取不同水深对太湖藻类密度进行监测,结果表明,水深0.5m处的藻类密度监测数据较能反映水体中藻类密度的实际情况,以此制定了太湖蓝藻水华状况评价及水源地藻类应急处置级别推荐标准(试行)。最后提出了YSI 6600型水质多参数监测仪在监测中存在的优点与不足。