纳米聚N-异丙基丙烯酰胺微凝胶的光引发聚合

选择具有温敏性的高分子单体N－异丙基丙烯酰胺（N－isopropylacrylamide，NIPAM）为主单体，N，N′－亚甲基双丙烯酰胺（methylenebisacrylamide，MBA）为交联剂，运用光引发无皂乳液聚合的方法合成出粒径小于100nm的高分子微凝胶，并研究了在改变体系组成和条件时微凝胶粒径的变化。结果显示，在乳化剂临界胶束浓度以下，随着乳化剂浓度的提高，微凝胶粒子的粒径不断关小且趋向稳定；相比于热引发，产生的微凝胶具有较高的单分散性而且粒径较小。     

Design consideration of photocatalytic oxidation reactors using TiO2-coated foam nickels for degrading indoor gaseous formaldehyde

In the design process of the photocatalytic oxidation (PCO) reactor using TiO₂-coated foam nickels, the optimum of catalyst film thickness, light intensity and flow velocity were considered. A model was developed to study the effect of catalyst film thickness on photocatalytic degradation of formaldehyde by a TiO₂-coated foam nickel at continuous flow mode. In this model, external mass transfer and internal molecule diffusion-reaction were considered. A first-order kinetics equation was used to account for the photocatalytic reaction. Two exponential equations were employed to describe the distribution of light intensities in foam nickels and catalyst films, respectively. Validated with experimental data, the model can be used to predict the optimal thickness of catalyst films. A method for determining appropriate light intensities was proposed and discussed. The appropriate light intensity can be obtained by giving a margin, regarded as an excess coefficient, to the light intensity calculated based on the assumption of complete use of excited electron–hole pairs. The excess coefficient needs to be determined experimentally. In addition, the optimal flow velocity of PCO reactors could be consistent with the required one by changing the windward area of foam nickels. Based on the theoretical analyses, a novel PCO reactor containing 15 parallel-connected cells was designed. Each reaction cell was composed of an UV lamp and a TiO₂-coated tubular foam nickel. The performance of the reactor was tested by degrading gaseous formaldehyde at an indoor concentration level. The results showed that the reactor had low pressure loss and good degradation capability.     

油-气管道检测机器人技术现状及展望

为提高油-气管道检测的效果,结合国内外典型管道机器人的特点,综合分析了管道机器人运动控制技术、定位技术和实时检测技术3个方面的现状,并指出了核心技术的不足;针对石油化工行业高温带压管道环境,提出管道检测机器人的研究重点为分层模糊神经网络运动控制技术、CCD视觉定位技术、低频电磁定位技术和分层图像分割的优化方法等。为进一步提高化工油-气管道内检测机器人的检测效果提供了理论依据。     

La0．8Ca0．2CrO3钙钛矿复合氧化物的GNP法合成与表征

采用GNP（Glycine-Nitrate Process）法合成La0.8Ca0.2CrO3初级粉料，研究甘氨酸用量对产物的晶体结构和显微形貌的影响，并测试烧结体的相对密度和电导率。研究结果表明，甘氨酸与金属离子的摩尔比（G／M^n＋）控制在2．0～2．5时可得到颗粒尺寸细小、均匀（100nm～200nm）的单相钙钛矿粉体，烧结温度为1350℃时样品的相对密度达到91．0％，测试温度为800℃时样品的电导率达到30．5S.cm^-1。与常规固相法相比，GNP法制备的样品具有更好的烧结活性和导电性能。     

Si及变质处理对Mg2Si/Mg复合材料的影响

分析了Mg-Si二元合金直接原位形成Mg2Si/Mg复合材料的过程,研究了Si含量以及变质处理对复合材料组织和性能的影响。试验结果表明,随着合金中Si含量的增加,合金的流动性降低,复合材料中原位Mg2Si的数量增多,树枝晶形态更为发达;对优化的Mg-8Si合金,进行混合稀土(MM)和Sb变质处理,可明显改善Mg2Si的形态和分布,但Sb变质的效果要好于MM。合金经质量分数为1.2%的Sb变质处理后,Mg2Si以颗粒状均匀分布在Mg基体中,从而使复合材料具有较好的耐磨性。     

兰香草挥发油化学成分的研究

采用常压水蒸气蒸馏法提取了兰香草挥发油,得油率为 0.35 ~ 0.52%。其相对密度(20℃/4℃)0.9980 ~0.9900,折射率(20℃)1.4608,比旋光度+0.51°;酸值1.5。并用毛细管气相色谱、红外光谱、核磁共振谱和色-质联机等对该挥发油进行了系统的成分分析。在分出的112个色谱峰中,共鉴定出 71 个化合物,占挥发油总量的 94.6%。其主要成分为芳樟醇、紫苏醇、香芹酮、荠苎烯、4-甲基-6-庚烯-3-酮、葎草烯、马鞭草烯酮、左旋松香芹酮、2-壬烯-4-炔等。     

双马来酰亚胺/二烯丙基双酚A共聚树脂及其玻璃布层压板的制备和性能

用溶液法合成了双马来酰亚胺(BMI)/二烯丙基双酚A(DABPA)共聚树脂。用FTIR、~1H-NMR等方法表征了树脂的结构。DSC曲线显示该树脂的固化能与熔融法得到的基体树脂有所不同。该树脂固化后有良好的热稳定性。以该树脂为基体制备了玻璃布层压板,测试结果表明层压板具有较好的力学性能和电气性能可以作为耐高温结构材料或电绝缘材料在180～200℃长期使用。     

基于分层的改进A＊算法在路径规划中的应用

智能交通中的路径诱导系统能够极大地提高人们的出行效率与出行体验。经典A＊算法只注重搜索精度而忽略了搜索效率,在城市道路网络分层的基础上,对高层道路使用的A＊算法进行了改进,对于道路网络中的不同节点,设置估价函数具有不同的权值,同时给定权值的一个上下限阈值,以平衡算法的搜索效率与搜索精度。实验表明,得到的最短路径虽然不是常规的距离最短却是实际行驶时间最优的。     

基于高频臭氧发生器介质阻挡放电特性研究

为了实现高频臭氧电源与臭氧发生器阻抗匹配问题,采用Q-V Lissajous图形法研究了电源电压幅值和频率对介质阻挡放电(DBD)的放电功率、等效电容等放电参量的影响.试验结果表明,增大外加电源电压幅值和激励频率,放电强度增强,放电功率增大;随着电源电压和频率增大,放电管总等效电容C在1.350～1.356 nF内变化,电介质等效电容Cd增大,放电间隙等效电容Cg减小.     

Person re-identification based on multi-appearance model

Person re-identification plays important roles in many practical applications. Due to various human poses, complex backgrounds and similarity of person clothes, person re-identification is still a challenging task. In this paper, we mainly focus on the robust and discriminative appearance feature representation and proposed a novel multi-appearance method for person re-identification. First, we proposed a deep feature fusion method and get the multi-appearance feature by combining two Convolutional Neural Networks. Then, in order to further enhance the representation of the appearance feature, the multi-part model was constructed by combining the whole body and the six body parts. Additionally, we optimized the feature extraction process by adding a pooling layer. Comprehensive and comparative experiments with the state-of-the-art methods over publicly available datasets demonstrated that the proposed method can get promising results.