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。     

基于量子线路逻辑运算的单光子量子态测量方案

在量子探测领域,关键任务之一就是要对未知量子态进行测量以获取量子态信息。通过将量子计算中的量子门所组成的量子线路应用于量子探测领域,提出实现单光子未知量子态的测量方案。利用量子计算的叠加性、纠缠性、可纠错性以及量子线路的可集成性,可以使得探测更具高效性并简化探测的实验系统。利用本文提出的探测新方案,通过仿真计算对该方案进行了模拟。在该方案的理论计算与仿真模拟结果的基础上,得到了以下的结论:通过在不同信噪比等参数的条件下选择适当的测量次数,基于量子线路的方案可以得到较为精确的测量结果。     

Proton-Detected Solid-State NMR of the Cell-Free Synthesized α-Helical Transmembrane Protein NS4B from Hepatitis C Virus

Proton-detected 100 kHz magic-angle-spinning (MAS) solid-state NMR is an emerging analysis method for proteins with only hundreds of microgram quantities, and thus allows structural investigation of eukaryotic membrane proteins. This is the case for the cell-free synthesized hepatitis C virus (HCV) nonstructural membrane protein 4B (NS4B). We demonstrate NS4B sample optimization using fast reconstitution schemes that enable lipid-environment screening directly by NMR. 2D spectra and relaxation properties guide the choice of the best sample preparation to record 2D ¹H-detected ¹H,¹⁵N and 3D ¹H,¹³C,¹⁵N correlation experiments with linewidths and sensitivity suitable to initiate sequential assignments. Amino-acid-selectively labeled NS4B can be readily obtained using cell-free synthesis, opening the door to combinatorial labeling approaches which should enable structural studies.     

浅谈城市废水水质检测方法与应用

国家与地区的经济发展水平一定离不开工业的发展,我国作为工业大国,工业发展对于国家整体经济有着不可取代的作用。然而随着工业的发展,全球性的环境污染和生态破坏越来越严重。特别是我国经济正处于快速发展阶段,城市化进程不断推进,城市污染情况日益严重,城市污水治理工作逐渐被大众所关注,逐渐开始进入公众可能给事业。我国二十世纪七十年代开始逐渐开始现代城市污水的治理工作。因此,对城市污水的水质监测工作成为了极为重要的一个环节。从城市污水检测方式这一角度进行研究,分析当前城市污水水质检验方法提升实际效果的应用模式,希望能够更好的处理我国城市日益严峻废水处理问题。     

Moderate lameness leads to marked behavioral changes in dairy cows

Lameness is one of the most prevalent diseases affecting the welfare of cows in modern dairy production. Lameness leads to behavioral changes in severely lame cows, which have been investigated in much detail. For early detection of lameness, knowledge of the effects of moderate lameness on cow behavior is crucial. Therefore, the behavior of nonlame and moderately lame cows was compared on 17 Swiss dairy farms. On each farm, 5 to 11 nonlame (locomotion score 1 of 5) and 2 to 7 moderately lame (locomotion score 3 of 5) cows were selected for data collection in two 48-h periods (A, B) separated by an interval of 6 to 10 wk. Based on visual locomotion scoring, 142 nonlame and 66 moderately lame cows were examined in period A and 128 nonlame and 53 moderately lame cows in period B. Between these 2 periods, the cows underwent corrective hoof trimming. Lying behavior, locomotor activity, and neck activity were recorded by accelerometers (MSR145 data logger, MSR Electronics GmbH, Seuzach, Switzerland), and feeding and rumination behaviors by noseband sensors (RumiWatch halter, ITIN + HOCH GmbH, Liestal, Switzerland). Furthermore, visits to the brush and the concentrate feeder, and the milking order position were recorded. In comparison with nonlame cows, moderately lame cows had a longer lying duration, a longer average lying bout duration, and a greater lateral asymmetry in lying duration. Average locomotor activity, locomotor activity during 1 h after feed delivery or push-ups, and average neck activity were lower in moderately lame cows. Eating time and the number of eating chews (jaw movements) were reduced in moderately lame compared with nonlame cows, whereas no effect of moderate lameness was evident for ruminating time, number of ruminating chews and boluses, and average number of ruminating chews per bolus. Moderately lame cows visited the concentrate feeder and the brush less frequently, and they were further back in the milking order compared with nonlame cows. In conclusion, nonlame and moderately lame cows differed in a biologically relevant way in many of the behavioral variables investigated in this study. Therefore, the use of these behavioral changes seems to be promising to develop a tool for early lameness detection.     

建筑工程地基检测技术要点分析及优化对策

针对建筑工程的地基检测技术进行重点分析,并且相应的提出了检测技术的优化对策,以此来促进建筑工程得以顺利发展。     

基于局部放电法的矿用高压电缆信号去噪算法研究

干扰噪声直接影响局部放电法有效检测矿用高压电缆故障。基于局部放电法，综合采用理论计算、仿真实验、现场试验的方法，对比分析了短时傅里叶变换和傅里叶分析去噪法的原理和优缺点，提出了一种矿用高压电缆的局部放电去噪算法——小波阈值去噪法，同时，选择了合理的阈值函数和去噪流程。基于此，采用白噪声和连续周期信号作为高压电缆的干扰噪声，进行了模拟仿真实验。结果表明，小波阈值去噪法可有效抑制白噪声，其中，Db2小波性能和去噪效果最好；同时，现场试验结果显示，去噪后信噪比得到了显著增加，验证了小波阈值去噪法的合理性和可靠性。     

Image and Feature Space Based Domain Adaptation for Vehicle Detection

The application of deep learning in the field of object detection has experienced much progress. However, due to the domain shift problem, applying an off-the-shelf detector to another domain leads to a significant performance drop. A large number of ground truth labels are required when using another domain to train models, demanding a large amount of human and financial resources. In order to avoid excessive resource requirements and performance drop caused by domain shift, this paper proposes a new domain adaptive approach to cross-domain vehicle detection. Our approach improves the cross-domain vehicle detection model from image space and feature space. We employ objectives of the generative adversarial network and cycle consistency loss for image style transfer in image space. For feature space, we align feature distributions between the source domain and the target domain to improve the detection accuracy. Experiments are carried out using the method with two different datasets, proving that this technique effectively improves the accuracy of vehicle detection in the target domain.     

基于机器视觉的手机电池表面缺陷检测

针对手机电池表面质量人工检测情况,开发了电池表面缺陷无损检测系统软件。首先电池表面经过倾斜矫正、感兴趣区域提取和字符灰度值修改等预处理操作,通过基于灰度密度分布和灰度差的自适应阈值亮度法对感兴趣区域进行子图像遍历,融合有重合区域的缺陷子图像并滤除没有明显缺陷的区域;然后采用支持向量机多种类分类法,提取二值图像像素分布规律作为训练特征,识别电池表面缺陷种类;最后设计了人机交互界面,确定最佳的可变参数,实验测试缺陷识别率达95%以上。