Simple Sequence Repeat Markers in Genetic Divergence and Marker-Assisted Selection of Rice Cultivars: A Review

Sequencing of rice genome has facilitated the understanding of rice evolution and has been utilized extensively for mining of DNA markers to facilitate marker-assisted breeding. Simple sequence repeat (SSR) markers that are tandemly repeated nucleotide sequence motifs flanked by unique sequences are presently the maker of choice in rice improvement due to their abundance, co-dominant inheritance, high levels of allelic diversity, and simple reproducible assay. The current level of genome coverage by SSR markers in rice is sufficient to employ them for genotype identification and marker-assisted selection in breeding for mapping of genes and quantitative trait loci analysis. This review provides comprehensive information on the mapping and applications of SSR markers in investigation of rice cultivars to study their genetic divergence and marker-assisted selection of important agronomic traits.     

Facial expression recognition of intercepted video sequences based on feature point movement trend and feature block texture variation

Facial Expression Recognition (FER) is an important subject of human–computer interaction and has long been a research area of great interest. Accurate Facial Expression Sequence Interception (FESI) and discriminative expression feature extraction are two enormous challenges for the video-based FER. This paper proposes a framework of FER for the intercepted video sequences by using feature point movement trend and feature block texture variation. Firstly, the feature points are marked by Active Appearance Model (AAM) and the most representative 24 of them are selected. Secondly, facial expression sequence is intercepted from the face video by determining two key frames whose emotional intensities are minimum and maximum, respectively. Thirdly, the trend curve which represents the Euclidean distance variations between any two selected feature points is fitted, and the slopes of specific points on the trend curve are calculated. Finally, combining Slope Set which is composed by the calculated slopes with the proposed Feature Block Texture Difference (FBTD) which refers to the texture variation of facial patch, the final expressional feature are formed and inputted to One-dimensional Convolution Neural Network (1DCNN) for FER. Five experiments are conducted in this research, and three average FER rates 95.2%, 96.5%, and 97% for Beihang University (BHU) facial expression database, MMI facial expression database, and the combination of two databases, respectively, have shown the significant advantages of the proposed method over the existing ones.     

Combination of nuclear magnetic resonance spectroscopy and nonlinear methods to analyze the copolymerization of phosphonic acid derivatives

We demonstrate in this study that the combination of modern inline monitoring methods [here: inline nuclear magnetic resonance (NMR)] with simulations gains more exact and profound kinetic results than previously used methods like linearization without that combination. The ¹H-NMR spectroscopic data (more than 100 data points) are used to construct the copolymerization diagram. The reactivity ratios are obtained applying the van Herks nonlinear least square method. The examination of the radical copolymerization of 2-hydroxyethyl methacrylate (HEMA) with (2-{[2-(ethoxycarbonyl)prop-2-en-1-yl]oxy}ethyl) phosphonic acid (ECPPA) as important adhesive monomer used in dentistry yields reactivity ratios of r_HEMA = 1.83; r_ECPPA = 0.42. The copolymerization diagram reflects nonideal, non-azeotropic copolymerization. The sequence distribution of the obtained by Monte Carlo simulation indicates the generation of statistical copolymers. As an important finding, it is demonstrated that the repeating units responsible for etching and adhesion are arranged over the whole polymer chain, which is necessary to achieve proper functionality. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 48256.     

苏6井区下石盒子组高分辨率层序地层学特征

以高分辨率层序地层学理论和技术方法为指导，在苏里格气田苏6井区地表露头、钻井岩心、测井、地震资料综合研究的基础上，通过基准面旋回结构、叠加样式的沉积动力学分析，将该井区下石盒子组划分为2个长期、5个中期和14个短期旋回层序；并较为详细地讨论了各期旋回层序特征；建立了以长期旋回层序界面和最大洪泛面为等时年代地层框架，以中期旋回层序为等时地层单元的高分辨率层序地层格架；通过分析，认为下石盒子组盒₈下段天然气储、盖条件最为有利；有利于储层发育的河道砂体主要出现在长、中期上升半旋回的中、下部，层序界面上相当短期旋回级别的单河道砂体是下石盒子组天然气勘探开发的主要目标。     

FZ-870绕线机排线机构电控系统分析

文章分析了FZ-870绕线机排线机构电控系统，并就存在的问题提出了对策。     

吐哈盆地丘东洼陷层序基准面旋回与储集性能关系

通过对吐哈盆地台北凹陷丘东洼陷中侏罗统层序基准面旋回与储集层储集性能的对比分析认为，丘东洼陷短期基准面的升降对储集性能具有明显的控制作用，短期基准面上升，储集层储集性能变差；短期基准面下降，储集层储集性能则变好。将中侏罗统短期基准面旋回测井响应模型分为退积-退积型、退积-进积型、进积-退积型和进积-进积型等4种。同时认为，储集层物性随着中期基准面的上升，辫状河道沉积砂体变厚、粒级变粗、砂泥比增大；中期基准面下降、旋回，储集层物性明显变差。指出了相对优质储集层发育的层段对应于基准面较低部位的储集层，丘东洼陷纵向上J2X^4早期和J2s^2是岩性油气藏勘探的有利目标层位；平面上弧形带两翼为有利的岩性油气藏发育区。     

农业灌溉的负效应

农业灌溉在提高农业抗灾能力、促进农业发展、改善人民生活中都发挥了十分重要的作用。但同时,灌溉打破了原有水量平衡、水土平衡、水沙平衡和水盐平衡。造成的负面效应有:水污染加剧对物理系统、生物系统(动植物和人类健康等)产生负面影响;水资源短缺降低了历史文化景观价值,对社会系统产生负面影响。应加强流域和区域灌溉水源统一调度,协调灌溉用水和生态环境用水的关系,大力发展节水灌溉,加强灌溉工程运行管理,减小农业灌溉负效应。     

差分跳频通信系统的特点及性能

文章介绍了一种新型的短波跳频通信技术——差分跳频,分析了差分跳频技术区别于常规跳频技术的主要特点。针对按序列检测的信号接收方法,对差分跳频通信系统在AWGN信道下的性能进行了理论分析,同时做出相应的计算机仿真,证实了差分跳频通信技术和按序列检测方法的结合,使通信系统在AWGN信道下的性能得到了比较显著的提升。     

博兴洼陷沙四上亚段高精度层序格架研究

博兴洼陷下第三系沙四上亚段滩坝砂体十分发育，主要是一套砂泥岩的薄互层，横向变化快，在地震剖面上难以识别和描述，用常规的地质研究方法难以预测砂体的分布趋势。本文应用高精度层序地层学的原理和方法，通过测井、岩心资料的综合分析，重点对沙四上亚段进行了高精度层序地层划分，共识别出了5个具有等时意义的水进面（四级层序界面），建立了洼陷内沙四上亚段的四级层序格架，在四级层序格架基础上进行了沉积体系分析，并对层序发育的控制因素进行了探讨。本研究对洼陷内隐蔽油气藏的进一步勘探具有重要的指导意义。     

人工免疫原理在网络入侵检测系统中的研究

文章分析了人工免疫系统的原理,简单建立了一种基于否定选择算法的网络入侵检测系统,引入了一种用于异常事件识别的r-字符块匹配规则,并对规则存在的漏洞进行了分析。