Elucidation of colour development and microstructural characteristics of Allium sativum fumigated with acetic acid

It has been well known that the greening of Allium sativum cloves could be formed after immersed in acetic acid solution. Nonetheless, no investigation was reported on colour development of A. sativum in response to acetic acid vapour until now. In this study, the brief exposure of A. sativum to acetic acid vapour (200–400 ppm) was combined with controlled atmosphere (5%, 20% and 80% CO₂) packaging storage to break cell membrane and green garlic. The garlic bulbs were fumigated with acetic acid before controlled CO₂ atmosphere packaging for 25 days at 4 °C. Fumigation with 200 ppm acetic acid followed by high CO₂ atmosphere packaging (80% CO₂) facilitated the garlic greening. It was also verified that γ‐glutamyl transpeptidase was involved in garlic greening in present study, and the compromise of glacial acetic acid vapour fumigation and CO₂ gas atmosphere in package stored at low temperature could result in garlic greening as well.     

离子液体水热法辅助合成稀土Ce掺杂ZnO纳米材料的制备及其应用研究

以1-甲基咪唑和氯代正丁烷为原料,合成1-丁基-3-甲基咪唑氯盐离子液体;以醋酸锌[Zn(Ac)2]、硫酸锌(ZnSO4)和氯化锌(ZnCl2)为锌源,在1-丁基-3-甲基咪唑氯盐离子液体和丙氨酸体系中与硝酸铈反应,经水热合成法制备得到Ce掺杂的纳米ZnO。采用扫描电子显微镜(SEM)、紫外-可见光吸收光谱(UV-Vis)、X射线衍射仪(XRD)、X射线光电子能谱分析(XPS)和红外光谱(FT-IR)对产品进行表征。以亚甲基蓝(MB)为目标降解物,采用UV-Vis检测,考察了Ce掺杂的纳米ZnO的光催化活性。研究表明,焙烧温度对光催化的晶体结构和光催化活性产生较大的影响;2%Ce/ZnO、焙烧温度为500℃、催化时间为30 min、亚甲基蓝用量0.05 g、pH值为10时降解率可达99.5%以上。     

郭庄煤业选煤厂振动筛筛选形式的优化研究

针对郭庄煤业选煤厂振动筛振动筛分方式可靠性差、筛分效率低下、物料筛分率低的难题,本文提出了三种新的振动筛分方案,对不同筛分方案的实际应用效果进行了分析。结果表明三移动一摆动的振动筛分方式对物料的综合分散度最高,稳定性好,该筛分方案已在郭庄煤业选煤厂煤炭筛分过程中得到了全面的应用。     

Research on hydrophobicity of electrospun Fe3O4/PVDF nanofiber membranes under different preparation conditions

Abstract

Preparation condition can affect the structure and the properties of nanofiber membrane. In order to explore suitable conditions to prepare the Fe₃O₄/PVDF nanofiber membrane with good hydrophobicity, the hydrophobicity of Fe₃O₄/PVDF nanofiber membranes obtained by electrospinning was investigated by changing preparation conditions like weight percentage of Fe₃O₄ nanoparticles, blending quality concentration of poly (vinylidene fluoride) (PVDF) and Fe₃O₄ nanoparticles, and positive voltage. And the variations of hydrophobicity of Fe₃O₄/PVDF nanofiber membranes modified by 1H, 1H, 2H, 2H-perfluorodecyl trimethoxysilane were studied. The results show that the hydrophobicity of Fe₃O₄/PVDF nanofiber membranes has changed under different preparation conditions. The contact angles of samples increased after a modification by 1H, 1H, 2H, 2H-perfluorodecyl trimethoxysilane, which indicates that the hydrophobicity of Fe₃O₄/PVDF nanofiber membranes has been enhanced.     

铝碳质长水口用低铝抗氧化涂层的研制

为抑制铝碳质长水口使用过程中石墨的氧化，其表面会涂覆含 20%~30%Al₂O₃的抗氧化涂层，但切割丝钢等特种钢冶炼过程必须严格控制钢液中夹杂的 Al₂O₃的含量，因此需要制备低氧化铝含量的抗氧化涂层。本文通过调节涂料组成、加水量和水玻璃加入量制备了低铝抗氧化涂层，并利用扫描电镜分析了抗氧化实验后试样断口的显微结构。结果表明：以粘土粉、钾长石粉和硅砂为主要原料，添加 10%硼砂的涂料可在 800 ℃形成良好的釉层，此时涂料中 A12O3的含量可降至 12%，得到了低铝涂料；当加入占涂料质量 80%的水和 40%的水玻璃时，涂层具有最佳的涂覆性能和抗氧化性能，涂层和长水口基体结合致密，保护了长水口中的石墨不被氧化。     

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.