夹角余弦与欧式距离相结合建立烟用香精HPLC指纹图谱

研究并建立了6批次JT-1烟用香精的HPLC指纹图谱,采用ZORBAX Extend-C18(5μm,4.6×150mm)色谱柱,ZORBAX RX-C18(4.6×12.5mm,5μm)保护柱,乙腈0.1%甲酸为流动相,梯度洗脱,流速1mL/min,柱温40℃,检测波长254nm.进样量15μL,硝基苯为内标,采用欧式距离与夹角余弦相结合的方法计算其相似度,并通过稀释实验进一步验证该指纹图谱对烟用香精质量控制的可行性,实验结果表明夹角余弦方法计算的相似度不能够完全反映香精样品有效成分的含量问题,而欧式距离对于解决样品有效含量检测问题更加有效,夹角余弦与欧式距离相结合使所建立的高效液相指纹图谱能更加快速、方便地检测烟用香精的质量稳定性.     

含纳米ATO聚氨酯弹性抗静电涂料

以脂肪族聚氨酯弹性树脂为基体，透明纳米ATO导电粉为导电介质，添加超分散剂，采用物理与化学相结合的分散方法对纳米ATO进行预处理。主要解决纳米粒子的分散与团聚的难题，制备出可常温固化、颜色可调的含纳米ATO聚氨酯弹性抗静电涂料。讨论了基体树脂、纳米ATO含量、超分散剂种类与加量、研磨时间以及助剂等因素对抗静电涂料的表面电阻、耐候性、弹性、强度以及稳定性等性能的影响。同时对涂料的性能进行了测试与表征。     

冷冻交联制备ZM-CSt-PVA复合凝胶及吸附Cu2+性能

以两性离子单体二甲氨基丙基丙烯酰胺-1-羧酸(ZM)、木薯淀粉(CSt)和聚乙烯醇(PVA)为主要原料,采用"一锅法",通过冷冻交联制备ZM接枝共聚CSt-PVA互穿网络复合凝胶(ZPG2)。使用FTIR、TGA、POM、SEM-EDS对ZPG2进行了表征,评价了ZPG2对Cu~(2+)的静态吸附效果。结果表明:300℃以下,ZPG2的热稳定性良好;ZM的存在可产生反聚电解质效应和化学配位效应,显著提高凝胶吸附能力;在吸附温度25℃、ZPG20.1 g、Cu~(2+)质量浓度2×10~3 mg/L、溶液体积100 mL时,饱和吸附量为199 mg/g;吸附过程符合Langmuir等温吸附模型和准二级动力学模型。     

大单体参与的分散聚合

~~大单体参与的分散聚合@陈永春$湖北大学化学与材料科学学院!武汉,430062 @易昌凤$湖北大学化学与材料科学学院!武汉,430062 @曹红燕$湖北大学化学与材料科学学院!武汉,430062 @冯伟程$湖北大学化学与材料科学学院!武汉,430062 @时远$湖北大学化学与材料科学学院!武汉,430062~~~~~~     

混合纤维制品在制瓶玻璃窑供料道上的应用

叙述了用多晶氧化铝纤维和高铝纤维制成的混合纤维段制品的生产工艺。该制品是一种能在１３５０℃长期使用的隔热新材料，它用在全电加热玻璃窑供料道后，玻璃液温度稳定，料滴温度长期控制精度可达±１℃，成品率上升到９６．６％，能耗降低。     

Precipitation from glassy polymer solutions

Solid solutions of general-purpose polystyrene containing crystalline tetrabromoxylene, tetrachloroxylene, or tetrachlorobenzene were prepared. The effects of the low molecular weight crystalline additive concentration and the thermal history on the thermal properties of the system have been studied. The system solubility, rejection of solute, etc., were characterized by such techniques as rheology, thermal analysis (DSC), and Vicat softening point.     

景德镇青白瓷起源与发展的探讨

景德镇是宋元时期青白瓷的产地代表。本文分析了景德镇早期青白瓷的胎釉化学组成与同时期景德镇青瓷和白瓷化学组成之间的关系，以及与其制瓷原料化学组成之间的联系；探讨了宋元时期青白瓷胎、釉配方的发展及显微结构的差异。结果表明，青白瓷可能起源于五代白瓷的烧制，并在其后的生产过程中不断改进坯釉料配方，成品率和质量不断得以提高。     

Atom transfer radical polymerization of n‐butyl methacrylate in an aqueous dispersed system

Atom transfer radical polymerization of n‐butyl methacrylate (BMA) was conducted in an aqueous dispersed system with different kinds of copper complexes. The partitioning behavior of the copper complexes, including CuCl/4,4′‐di(5‐nonyl)‐2,2′‐bipydine (dNbpy), CuCl₂/dNbpy, CuCl/2,2′‐bipydine (bpy), CuCl₂/bpy, CuCl/bis(N,N′‐dimethylaminoethyl)ether (bde), and CuCl₂/bde between the monomer (BMA), and water was studied in detail with ultraviolet‐visible spectroscopy. The results show that with a less hydrophobic ligand, such as bpy or bde, most of the Cu(I) or the Cu(II) complexes migrated from the BMA phase to the aqueous phase, the atom transfer equilibrium was destroyed, and the polymerization was nearly not controlled; it converted to classical emulsion polymerization. As to the very hydrophobic ligand dNbpy, although the partitioning study of the copper complexes indicated that not all the copper species were restricted to the organic phase, the linear correlation between the molecular weight and the monomer conversion and the narrow polydispersities confirmed that the polymerization was still quite well controlled. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 89: 3175–3179, 2003     

Contrastive Meta-learning on Heterogeneous Information Networks for Cold-start Recommendation

In recommender systems, the cold-start issue is challenging due to the lack of interactions between users or items. Such an issue can be alleviated via data-level and model-level strategies. Traditional data-level methods employ auxiliary information like feature information to enhance the learning of user and item embeddings. Recently, Heterogeneous Information Networks (HINs) have been incorporated into the recommender system as they provide more fruitful auxiliary information and meaningful semantics. However, these models are unable to capture the structural and semantic information comprehensively and neglect the unlabeled information of HINs during training. Model-level methods propose to apply the meta-learning framework which naturally fits into the cold-start issue, as it learns the prior knowledge from similar tasks and adapts to new tasks quickly with few labeled samples. Therefore, we propose a contrastive meta-learning framework on HINs named CM-HIN, which addresses the cold-start issue at both data level and model level. In particular, we explore meta-path and network schema views to describe the higher-order and local structural information of HINs. Within meta-path and network schema views, contrastive learning is adopted to mine the unlabeled information of HINs and incorporate these two views. Extensive experiments on three benchmark datasets demonstrate that CM-HIN outperforms all state-of-the-art baselines in three cold-start scenarios.     

认识隐患预防事故

事故隐患是客观存在的，不论你是否承认，是否意识到，它都存在于企业的生产全过程，而且对员工的人身安全，国家的财产安全和企业的生存、发展都直接构成威胁。正确认识隐患的特征，对熟悉和掌握隐患产生的原因，及时研究并落实防范对策是十分重要的。下面就这方面的问题，谈一点粗浅认识。