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。     

基于多Agent的模糊粗交流

提出了变异模糊粗集的概念及其相应的性质和定理;建立了模糊粗交流最优传递序列的数学模型,并给出了解决此模型的算法思想,算例证明了算法思想的有效性。     

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。     

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。     

东海西湖凹陷平湖油气田花港组高分辨率层序地层特征

通过岩心观察、测井与录井资料,对平湖油气田花港组河流相地层进行了高分辨层序地层分析,识别出2个中期旋回(MSC1与MSC2)与20个短期旋回,建立了研究区的层序地层格架。短期旋回分4种类型并以非对称旋回为主。两个中期旋回为非对称旋回,但MSC2对称性更大,反映了可容纳空间的持续增加。在基准面旋回的控制下,沉积相呈现有规律的辫状河曲流河辫状河曲流河交替演化,在每个中期旋回均以辫状河开端,以曲河流结束,由于中期旋回在长期旋回中的位置不同,曲流河的特征也有所不同。位于中期旋回上升半旋回中部的曲流河及底部的辫状河是研究区的有利砂体,尤其是前者最为有利。