岚山10万m3罐SPV490Q钢板埋弧横焊焊接裂纹的预防

SPV490Q钢板是具有较强裂纹倾向的低合金高强钢,现场施焊时可通过采取优化焊接参数、改善焊缝成型系数等措施控制扩散氢含量、淬硬组织和拘束应力三个致裂要素,实现预防或减少焊接裂纹产生,提高焊接质量的目的.     

Specificity of Systemically Released Cotton Volatiles as Attractants for Specialist and Generalist Parasitic Wasps

Cotton plants under herbivore attack release volatile semiochemicals that attract natural enemies of the herbivores to the damaged plant. The volatiles released in response to herbivory are not only released from the damaged leaves but from the entire cotton plant. We found that cotton plants that released myrcene, (Z)-3-hexenyl acetate, (E)--ocimene, linalool, (E)-4,8-dimethyl-1,3,7-nonatriene, (E)--farnesene, and (E, E)-4,8,12-trimethyl-1,3,7,11-tridecatetraene systemically from undamaged leaves of caterpillar damaged plants were attractive to the generalist parasitoid Cotesia marginiventris and the specialist parasitoid Microplitis croceipes. Plants from which the caterpillar damaged leaves were removed and that released those compounds systemically were significantly preferred over undamaged control plants in two-choice experiments in a flight tunnel. Artificially damaged cotton plants that released green leafy volatiles and constitutive terpenoids were less attractive for M. croceipes and C. marginiventris. Only C. marginiventris preferred artificially damaged plants over undamaged control plants, whereas M. croceipes showed no preference. The apparent lack of specificity of systemically released compounds in response to different herbivores feeding on the lower leaves is discussed.     

关于木素生物降解酶类活力测定问题的讨论

由于木素结构和生物降解过程复杂多样，全面测定一个菌株的木素降解活力也比较困难，目前已发现三类主要参与木素降解的酶类（LIP、MnP、漆酶），但至今很少有国际上公认的酶活力测定方法，也未见到能把某一菌株木素降解酶类的活力与其在木质纤维材料中降解木素的能力定量关联的报导。本文综合评述了几类主要的木素降解酶类活力测定方法的作用机制和存在的问题，指出一个菌株的木素降解活力是由它的生理特性和总体代谢能力共同决定的，仅由一类或几类酶活力的表现水平难以对其作出确切的评价，从这个角度出发进行研究才能更客现他认识菌株的木素降解活力．     

我国平板玻璃需求预测优选方法的探讨

阐述了需求预测的重要性,介绍了在平板玻璃需求预测中应用较多的移动平均、指数平滑、趋势外推等时间序列外推法,以及多元线性回归等方法,通过寻找适用的最优预测模型,对不同预测模型进行试算,对预测结果进行分析,得出在平板玻璃短期需求预测时,使用二元线性回归模型的结果更接近最优解这一结论.     

Miscibility in poly-p-phenylene terephthalamide/nylon 6 and nylon 66 molecular composites

Miscibility and crystallization of poly-p-phenylene terephthalamide (PPTA)/nylon 6 and nylon 66 composites prepared by coagulation of isotropic ternary sulfuric acid solutions were studied. The apparent crystallinity of nylon 6 and nylon 66 in molecular composites was investigated by differential scanning calorimetry and Fourier transform infrared spectroscopy. The solvation of nylon 6 crystals in PPTA matrix was observed when the PPTA content exceeds 70 wt%. Cross-hydrogen bonding seems to be responsible for the virtual disappearance of nylon 6 crystals. Specific interaction between PPTA and nylon 6 macromolecules and phase separation during thermal treatment has been discussed.     

基于双策略协同进化的QPSO算法及其应用

为更好地提升量子粒子群优化算法（QPSO）的局部挖掘和全局搜索能力,提出了一种改进的QPSO算法（DSQPSO）。在改进算法中引入了双策略协同进化的思路调整粒子的位置更新公式。为充分体现个体粒子挖掘的优势和群体共同引导的特点,提出了两种吸引点构造的思路,做到个体和种群更好地融合以及信息的互通;分别考虑了最优平均位置与全局最优和粒子的历史最优之间的联系,对粒子搜索范围作出了重新定义;此外,在迭代过程中,借助随机扰动机制对全局最优位置进行调整,以保持种群的多样性。通过18个测试函数将DSQPSO算法与PSO、QPSO、RQPSO和LQPSO四种算法在收敛精度和鲁棒性方面进行对比;进而在两个具体的工程优化问题上,应用改进算法与八个智能算法进行了寻优结果比较。实验表明DSQPSO算法无论在基准测试中还是在工程应用上,其计算精度和收敛效果均有明显优势。     

LFSCA-UNet：基于空间与通道注意力机制的肝纤维化区域分割网络

目的 肝纤维化是众多慢性肝脏疾病的常见表现,如不及时治疗可发展为肝硬化甚至引发肝癌。肝纤维化的准确评估对临床治疗和预后评估等至关重要。目前,肝纤维化的诊断通过肝穿活检判断,有创且有并发症危险。为此,基于影像学的无创诊断方法越来越受到关注。本文提出一种基于通道注意力与空间注意力机制改进的用于肝纤维化区域的自动化分割U-Net （liver fibrosis region segmentation network based on spatial and channel attention mechanisms,LFSCA-UNet）。方法 依据Attention U-Net的改进方式,围绕U-Net的跳跃连接结构进行基于注意力的改进,在AG （attention gate）的基础上,加入以ECA （efficient channel attention）模块为实现方式的通道注意力机制,依据加入ECA的位置,LFSCA-UNet分为A、B、C共3个子型。结果 在肝数据集上与其他实验网络进行评估对比,本文提出的LFSCA-UNet网络结构平均Dice系数达到了93.33%,相比原始U-Net的Dice系数提高了0.539 6%。结论 本文方法将空间注意力机制与通道注意力机制进行结合,有效提高了肝纤维化区域的分割精度,对空间注意力模块使用通道注意力模块优化输入和输出,增加了网络的稳定性,提升了网络的整体效果。     

Positivity and stability of mixed fractional‐order systems with unbounded delays: Necessary and sufficient conditions

This article provides a comprehensive study on quantitative properties of linear mixed fractional‐order systems with multiple time‐varying delays. The delays can be bounded or unbounded. We first obtain a result on existence and uniqueness of solutions to these systems. Then, we prove a necessary and sufficient condition for their positivity. Finally, we provide a necessary and sufficient criterion to characterize asymptotic stability of positive linear mixed fractional‐order systems with multiple time‐varying delays.     

A robust video zero-watermarking based on deep convolutional neural network and self-organizing map in polar complex exponential transform domain

In this paper, a robust video zero-watermarking scheme for copyright protection using a combination of convolutional neural network (CNN) and self-organizing map (SOM) in polar complex exponential transform (PCET) space is presented. The scheme is developed not only to remedy the existing problems of lacking in some performance assessments but also to enhance the robustness. It starts with extracting the content feature of each frame by CNN and then some significant frames are selected using SOM clustering and maximum entropy. Secondly, the PCET is applied to all selected frames to abstract invariant moments, and further, is scrambled by a chaotic logistic map and is reduced in dimensions by singular value decomposition (SVD). Next, a binary sequence is generated by comparing adjacent values of the obtained compact PCET moments in the previous step, and further is permuted to produce a binary matrix. Finally, a bitwise exclusive-OR operation is imposed on the binary matrix and the encrypted watermark by the chaotic map to generate a zero-watermark signal. Experimental results demonstrate that the proposed scheme has adequate equalization and distinguishability of zero-watermarks as well as strong robustness against common signal processing, geometric, compression, and inter-frame attacks. Also, compared with existing video zero-watermarking and traditional video watermarking methods, the proposed scheme exhibits superior robustness.

     

电力巡检无人机精准降落方法研究与应用

针对现有电力巡检无人机降落方法定位误差较大、机身稳定性较差、易受外部环境干扰等问题,提出一种电力巡检无人机自适应降落方法.构建基于多级视觉标识图像识别的四维定位降落方法,指引无人机进行垂直方向精确降落.开发基于分段式反馈控制的速度矢量的四维控制方法,稳定无人机水平方向的姿态.设计基于视觉标识阵列的自适应抗干扰降落方法,克服降落平台的阴影对无人机定位的影响.开展无人机精准降落现场实验,结果表明所提方法具有非常高的降落定位精度,简单实用.