基于1D CNN与XGBoost的恶意代码纹理检测

恶意代码数量已经呈现爆炸式增长,对于恶意代码的检测防护显得尤为重要.近几年,基于深度学习的恶意代码检测方法开始出现,基于此,提出一种新的检测方法,将恶意代码二进制文件转化为十进制数组,并利用一维卷积神经网络(1 Dimention Convolutional Neural Networks,1D CNN)对数组进行分类和识别.针对代码家族之间数量不平衡的现象,该算法选择在分类预测上表现良好的XGBoost,并对Vision Research Lab中的25个不同恶意软件家族的9458个恶意软件样本进行了实验.实验结果表明,所提的方法分类预测精度达到了97％.     

Ensemble relation network with multi-level measure

Fine-grained few-shot learning is a difficult task in image classification. The reason is that the discriminative features of fine-grained images are often located in local areas of the image, while most of the existing few-shotlearning image classification methods only use top-level features and adopt a single measure. In that way, the localfeatures of the sample cannot be learned well. In response to this problem, ensemble relation network with multi-level measure (ERN-MM) is proposed in this paper. It adds the relation modules in the shallow feature space tocompare the similarity between the samples in the local features, and finally integrates the similarity scores from thefeature spaces to assign the label of the query samples. So the proposed method ERN-MM can use local details andglobal information of different grains. Experimental results on different fine-grained datasets show that the proposedmethod achieves good classification performance and also proves its rationality.     

药物相互作用研究在新药研发和审评决策中的应用

药物相互作用改变了剂量效应关系，可能会降低疗效或增加毒性，是临床应用中合并用药治疗时重要的考虑因素。预测具有临床意义的药物相互作用是药物研发过程中获益风险评估的重要环节。本文概述了药物研发过程中药物相互作用研究的目的和意义，体内和体外研究的主要内容；梳理分析了2020年国家药品监督管理局（National Medical Products Administration, NMPA）和美国食品药品监督管理局（Food and Drug Administration, FDA）批准上市的新药药物相互作用研究情况，旨在为我国药物研发过程中药物相互作用研究及其监管审评提供参考。     

Effects of non-thermal plasma treating wheat kernel on the physicochemical properties of wheat flour and the quality of fresh wet noodles

The effects of non-thermal plasma (NTP) on the physicochemical properties of wheat flour and the quality of fresh wet noodles ( FWN) were investigated. The results showed that NTP effectively decreased the total plate count (TPC), yeast and mould count (YMC) and Bacillus spp. in wheat flour. Wet gluten contents and the stability time reached the maximum when treated for 20 s. The viscosity of starch increased significantly after treatment due to the increased of damaged starch. The contents of secondary structure were altered to some extent, which was because that the ordered network structure of gluten protein broken. Furthermore, compared with the control, texture properties of FWN were enhanced significantly at 20 s, and the darkening rate of FWN was greatly inhibited due to the low polyphenol oxidase (PPO) activity. Consequently, the most suitable treatment was 500 W for 20 s, providing a basis for the application of NTP in flour products.     

基于ERNIE-BiGRU模型的摘要语步自动识别研究

学术文献的摘要是对文献主要内容的浓缩,摘要不同部分的语步具有不同的信息,语步的自动识别和抽取对于学术摘要的后续研究有着重要的应用价值,而目前语步识别的研究相对较少,并且相关算法的效果还需要提高。针对上述问题,该文提出了一种基于ERNIE-BiGRU模型的语步识别算法。该算法首先结合中文句法分析理论提出基于句法依存关系的多语步结构拆分法,对学术文献摘要多语步结构进行自动拆分,获得多个单语步结构;然后构建用于训练的单语步结构语料库,并利用知识增强语义表示预训练模型,训练出句子级词向量;最后将训练出的单语步结构词向量信息输入双向门限循环单元(BiGRU)进行摘要语步自动化识别,取得了良好的效果。实验结果表明,该算法具有较好的鲁棒性和较高的识别精度,在结构化和非结构化摘要上的识别准确率分别达到了96.57%和93.75%。     

基于图像分割技术的图像数字水印算法研究

针对数字图像水印技术,通过对闭运算得到的图像再进行开运算,使实验得到的图像区域较为完整,采用4×4的正方形结构元素,使得图像区域有更多的白色像素被置为黑色,对图像进行取反操作,能够对图像区域的非连通区域进行填充.希望能够利用精确的图像分割算法,实现对复杂版面的文档图像的有效切割,在一定程度上对图像数字水印的推广起到促进作用.     

Enhanced thermal conductivity and stability of boron nitride/phenyl silicone rubber composites via surface modification and grain alignment

Journal of Materials Science - With the extensive use of high-power electronic appliances, polymer-based thermal insulation composites with excellent thermal properties are utilized in the field of...     

异种铁素体耐热钢接头界面组织及其影响

综述了铁素体与铁素体异种金属焊缝（dissimilar metal welds，DMWs）接头界面组织及其影响。结果表明，在焊后热处理或运行温度下的铁素体钢DMWs接头的不均匀界面组织中，通常会形成脱碳层和增碳层。在铁素体钢DMWs焊接接头界面组织影响因素中，焊缝金属的化学成分有重要影响；焊后热处理规范（温度和时间）、工作温度下运行时间的影响较为突出；焊接工艺参数的影响亦不可忽略。异种钢接头界面处近缝区裂纹的产生，以及接头的蠕变强度随Larson Miller 参数增大而下降等不利影响，均为异种钢界面碳迁移行为所导致。焊缝成分控制法是接头界面组织控制或改善的必要条件，而脱碳层部位转移法能有效防止裂纹发生，亦是接头安全运行的重要工艺措施之一。