一种5 重real-time PCR筛查转基因水稻方法的建立

以转基因水稻中最常用的CaMV35S启动子、NOS终止子、Cry1Ab/Ac基因、HPT基因及SPS水稻内标基因为研究对象，利用5 种不同的荧光信号（FAM、HEX、Taxas Red、Cy5、Cy5.5）进行多重实时聚合酶链式反应（real-time polymerase chain reaction，real-time PCR）检测方法的研究。通过引物组合筛选、反应体系优化、特异性测试、灵敏度测试、适用性测试等一系列实验，建立了5 重real-time PCR方法，灵敏度可达0.032%。此方法具有灵敏度高、结果准确、通量大等优点，可实现水稻中转基因成分的快速、高效检测。     

某矿快速掘进最优炮孔间距的选择

山西某矿5308底抽巷在掘进过程中速度慢、效率低，直接影响工作面的瓦斯抽采，为了改善上述情形，对炮孔间距进行研究。通过使用ANSYS软件对不同炮孔间距下快速掘进效果的模拟分析，并经现场验证，得出了适应该矿的最佳炮孔间距。结果表明：炮孔间距为500 mm时，爆破产生裂隙发育范围和岩石损伤区域都最大，快速掘进的效果最好。     

应用膨胀算法提取目标的直接定位算法

为了解决被动雷达系统中的多发射源定位问题，提出了一种基于多重信号分类(MUSIC)算法和图像膨胀(IE)算法的直接定位方法。该方法结合了谱分析中的MUSIC思想，通过对接收量测协方差矩阵进行特征分析求解目标的位置。首先，在目标个数未知的前提下，利用Akaike信息准则(AIC)来确定模型阶数；然后，推导了基于MUSIC的定位代价函数；之后，利用图像膨胀算法处理得到的代价函数平面；最后，膨胀处理后的输出为目标个数及目标位置的估计值。提出的算法有效地解决了目标检测及提取的问题，能够确定多个目标的位置坐标，为后续的定位性能分析提供可能性，也保证了算法的完整性。进一步地分析了多个临近目标情况下影响目标提取性能的主要因素。     

结合优化支持向量机与K-means++的工控系统入侵检测方法

针对工业控制系统传统单一检测算法模型对不同攻击类型检测率和检测速度不佳的问题，提出一种优化支持向量机和K-means++算法结合的入侵检测模型。首先利用主成分分析法（PCA）对原始数据集进行预处理，消除其相关性；其次在粒子群优化（PSO）算法的基础上加入自适应变异过程避免在训练的过程中陷入局部最优解；然后利用自适应变异粒子群优化（AMPSO）算法优化支持向量机的核函数和惩罚参数；最后利用密度中心法改进K-means算法与优化后的支持向量机组合成入侵检测模型，从而实现工业控制系统的异常检测。实验结果表明，所提方法在检测速度和对各类攻击的检测率上得到明显提升。     

水提法提取—电感耦合等离子体质谱法测定婴幼儿配方奶粉中的碘

用水提取婴幼儿奶粉中的碘,亚铁氰化钾和乙酸锌盐析法沉淀蛋白,过滤后可以得到澄清处理液。用电感耦合等离子体质谱对提取样液进行测定,130Te作为内标物进行定量分析。该方法简便快捷,检出限为0.10 mg/kg加标回收率为90.8%~109%,相关系数0.999,精密度试验RSD2%。     

电磁精细探测法在隐伏型导水地质裂缝勘探中的应用

针对传统隐伏型导水地质裂缝勘探方法存在勘测精度较差的问题,提出电磁精细探测法探析隐伏型导水地质裂缝。依照屏蔽系数、实测场强和理论场强数据绘制综合曲线图,通过该图获取隐伏型导水地质裂缝所处位置几何阴影范围,采用层析成像法得到网格化的工作面,获取隐伏型导水地质图像。通过图像直接观测隐伏型导水地质工作面裂缝所处位置,在此基础上,观测四个电磁场分量,采用正交电磁场分量计算介质视电阻率,依据计算视电阻率数值和视电阻率分布状态研究裂缝发育情况和裂缝富水程度。结果表明:采用该方法能较为精准地获取隐伏型导水地质裂缝位置。通过裂缝位置进一步检测出隐伏型导水地质裂缝最大发育高度为63.5 m。当视电阻数值不断增加时,隐伏型导水地质裂缝和裂缝富水性逐渐减小,与实际情况较为相符,说明该种方法探析效果较好。     

Investigation on the effectiveness of the repair method 8.3 “Corrosion protection by increasing the electrical resistivity” in chloride-containing concrete Part 2: Chloride redistribution in concrete after application of a system sealing surface protective coating

This DFG-funded research project aimed to gain a better understanding of the mechanisms of the W-Cl repair principle within the framework of fundamental investigations, to contribute to the creation of the necessary basis for a broader application of the repair principle in practice. The focus was on the development of a model to describe the chloride redistribution after the application of a system sealing surface protective coating. On the basis of Fick's second law of diffusion, a mathematical model with a self-contained analytical solution was developed, with the help of which the chloride redistribution after application of a system sealing surface protective coating can be calculated under the idealized assumption of complete water saturation of the concrete. Furthermore, the influence of the dehydration of the concrete, expected as a result of the application of the repair principle W-Cl, on the chloride redistribution was investigated. On the basis of laboratory tests and numerical simulations, material-specific reduction functions were developed to quantify the relationship between the chloride diffusion coefficient and the ambient humidity.     

The World robot summit disaster robotics category – achievements of the 2018 preliminary competition

The World Robot Summit is a robot Olympics and aims to be held in a different country every four years from 2020. The concept of the Plant Disaster Prevention challenge is daily inspections, checks, and emergency response in industrial plants, and in this competition, robots must carry out these types of missions in a mock-up plant. The concept of the Tunnel Disaster Response and Recovery challenge is emergency response to tunnel disasters, and is a simulation competition whereby teams compete to show their ability to deal with disasters, by collecting information and removing debris. The Standard Disaster Robotics challenge assesses, in the form of a contest, the standard performance levels of a robot that are necessary for disaster prevention and emergency response. The World Robot Summit Preliminary Competition was held at Tokyo Big Sight in October 2018, and 36 teams participated in the Disaster Robotics Category. UGVs and UAVs contended the merits of new technology for solving complex problems, using core technologies such as mobility, sensing, recognition, performing operations, human interface, autonomous intelligence etc., as well as system integration and implementation of strategies for completing missions, gaining high-level results.     

Retinal Vessel Extraction Framework Using Modified Adaboost Extreme Learning Machine

An explicit extraction of the retinal vessel is a standout amongst the most significant errands in the field of medical imaging to analyze both the ophthalmological infections, for example, Glaucoma, Diabetic Retinopathy (DR), Retinopathy of Prematurity (ROP), Age-Related Macular Degeneration (AMD) as well as non retinal sickness such as stroke, hypertension and cardiovascular diseases. The state of the retinal vasculature is a significant indicative element in the field of ophthalmology. Retinal vessel extraction in fundus imaging is a difficult task because of varying size vessels, moderately low distinction, and presence of pathologies such as hemorrhages, microaneurysms etc. Manual vessel extraction is a challenging task due to the complicated nature of the retinal vessel structure, which also needs strong skill set and training. In this paper, a supervised technique for blood vessel extraction in retinal images using Modified Adaboost Extreme Learning Machine (MAD-ELM) is proposed. Firstly, the fundus image preprocessing is done for contrast enhancement and in-homogeneity correction. Then, a set of core features is extracted, and the best features are selected using “minimal Redundancy-maximum Relevance (mRmR).” Later, using MAD-ELM method vessels and non vessels are classified. DRIVE and DR-HAGIS datasets are used for the evaluation of the proposed method. The algorithm’s performance is assessed based on accuracy, sensitivity and specificity. The proposed technique attains accuracy of 0.9619 on the DRIVE database and 0.9519 on DR-HAGIS database, which contains pathological images. Our results show that, in addition to healthy retinal images, the proposed method performs well in extracting blood vessels from pathological images and is therefore comparable with state of the art methods.     

黄浦江下游吴淞口站低潮位重现期研究

黄浦江为感潮河流,低潮位重现期的确定对黄浦江航道的设计具有重要意义。为了准确估计黄浦江低潮位的重现期,以黄浦江下游吴淞口站年最低潮位序列为例,在对样本进行三性审查的基础上,分别采用传统的数理统计方法和时变矩方法进行水文频率分析。结果表明:吴淞口站年最低潮位序列在1996年发生了变异;还现修正后的序列服从位置参数线性时变的GEV模型,低潮位存在缓慢的上升趋势;一致性条件下百年一遇低潮位约为0.261 m,在非一致性条件下其重现期增大为150 a。非一致性条件下的重现期增大说明黄浦江现有的航道设计标准偏安全,航道通航保证率提高。