Aldehyde-Sodium Alginate and Amino-Gelatin Preparation as Soft Tissue Adhesive

Sodium alginate and gelatin are both remarkable natural biomaterials; they all have been extensively applied in tissue engineering and other relative fields,due to their low price and good biocompatibility. In this paper,we oxidized sodium alginate with sodium periodate to convert 1,2-hydroxyl groups into aldehyde groups to get aldehyde-sodium alginate（ A-SA）. Gelatin was modified with ethylenediamine（ ED） in the presence of water-soluble1-ethyl-3（ 3-dimethylaminopropyl） carbodiimide（ EDC） to introduce additional amino groups to get amino-gelatin. Upon mixing the A-SA and amino-gelatin aqueous solutions together,a gel rapidly formed based on the Schiff＇s base reaction between the aldehyde groups in A-SA and the amino groups in amino-gelatin.Fourier transform infrared spectroscopy（ FTIR） analysis confirmed the characteristic peak of Schiff＇s base group in the hydrogel. The gelation time measure has confirmed the gelation time is dependent on the aldehyde group content in A-SA and amino group content in amino-gelatin. The fasted hydrogel formation takes place within 30 s. The entire test suggested that this gel could be a promising candidate as soft tissue adhesive.     

Preparation of Electrospun CdSe-Quantum-Dots-Doped Porous Films

Electrospun porous films doped with the green-synthesized CdSe quantum dots were synthesized. Glycerol was chosen to prepare the quantum dots （ QDs）, with the highest quantum yield of 78.28%. Polycaprolactone （PCL） was electrospun with CdSe QDs to avoid the QDs＇ toxicity and improve the QDs＇ cytocompatibility. The electrospun QDs-doped films preserve the original QDs＇ fluorescence. Pores can be detected from the SEM of the films, predicting the possibility of loading drugs in the cancer therapy. The cell proliferation assay shows excellent cytocompatibility of the eletrospun CdSe-QDs-doped films. The present eletrospun CdSe- QDs-doped porous films are cytocompatibale, highly-fluorescent and ootential to load drugs in cancer therapy.     

Settlement Prediction of Dredger Fill with the Optimal Combination Model

Post-construction settlement has gained increasing attention because it frequently causes engineering problems. A combined model is a commonly used prediction model that overcomes the difficulty of a single model（ i. e., cannot reflect various regulations of settlement at some stages or the entire process）. In this study,the correlation coefficient,maximum error values,and other values were obtained according to the fitting and predicted results of a single model. The coefficient of variation was then introduced to determine the weight of each model forming the combination. The proposed model was used to fit and predict for settlement and overcome the issue of utilizing a single model while determining the weight. The fitting predictive effect was also analyzed using the settlement fitting precision results. The fitting precision of optimizing the combination model is high. The predicted data of the post-construction settlement are closer to the calculated value of the settlement monitoring data. Moreover,the proposed model has good practicability,does not require the interval data of settlement,and restricts the model number. Thus,this model can be applied in the engineering field.     

基于Ansoft的开关磁阻平面电机磁场分析

开关磁阻平面电机具有结构简单、运行可靠、控制方便等优点,在生产生活中应用广泛.然而其磁路特有的非线性结构,给电机的结构分析和控制方法带来了很大的困难.本文采用有限元分析方法,对开关磁阻平面电机结构分析,并运用Ansoft Maxwell 3D软件仿真.通过建立有限元模型,分析了开关磁阻平面电机的磁链以及电磁推力与动子位置的关系.研究结果为进一步开展开关磁阻平面电机的研究奠定基础.     

基于正交试验和回归分析的羽绒服装样板缩率研究

为揭示影响羽绒服装缩率各影响因素的重要程度及其和缩率之间的定量关系,采用正交试验方法,选择羽绒填充量、绗线间距、含绒量为因素,结合极差分析法探讨各因素对缩率的重要程度,并建立缩率与各影响因素的多元线性回归方程.结果表明,影响羽绒服装样板缩率各因素的主次顺序为:羽绒填充量绗线间距含绒量;对回归方程的显著性和系数显著性探讨表明,回归方程对垂直绗线方向缩率具有显著性影响;回归方程的建立能够有效提高羽绒服装样板制作的准确性,为其他填充类服装制板提供理论参考.     

黄芪多糖提取工艺及真空膜蒸馏浓缩提取液的研究

以黄芪提取液的多糖得率为考核指标,采用正交实验设计的方法优化并确定了黄芪多糖提取的最佳工艺条件为:提取温度70℃,加水7倍,提取3次,每次提取120min.采用真空膜蒸馏浓缩黄芪提取液,以不同条件下制备的聚丙烯疏水微孔膜作为膜材料,考察了过程通量变化,并分析了在膜蒸馏浓缩过程中膜污染产生的原因.结果表明,提高膜蒸馏过程的进料流量可以减轻膜污染程度.     

框支-斜交密肋复合墙结构影响因素及框支梁内力系数研究

采用正交试验设计方法,考虑框支梁高跨比(hb/l0)、抗震墙截面宽度与高度比(Bw/Hw)、密肋复合墙高跨比(hw/l0),通过对框支-斜交密肋复合墙结构计算结果直观分析和方差分析,对构件关键部位内力和整体结构最大转角影响因素进行显著性分析,得出hb/l0和Bw/Hw对框支梁和框支柱的部分内力具有显著影响,对整体结构最大转角具有一定影响的结论.并在此基础上给出相应框支梁内力系数实用设计计算方法.     

基于改进粒子群算法的分布式电源选址定容优化设计

在分析了分布式电源接入对配电网影响的基础上,针对配电网中的关键问题———分布式电源的选址和定容,进行了优化设计.通过构建包含分布式电源的投资运行费用、环境因素、网损费用的目标函数,并考虑潮流约束、电流约束、电压约束、系统容量约束等条件,搭建了分布式电源的模型,采用一种改进的粒子群算法,设计出了分布式电源所处位置及容量.通过仿真分析计算,验证了该方案的正确性和有效性.     

新型表面活性剂类硫脲高效催化硝基烯烃的不对称Michael加成(英文)

由N-BOC-胺甲基吡咯烷和异硫氰酸盐反应合成了一种新型结构的硫脲分子,将该具有表面活性剂类型的硫脲分子用作有机催化剂来催化硝基烯烃的不对称Michael加成,条件实验探索结果表明,最优的实验条件是,10 mol%催化剂,10 mol%的苯甲酸作为添加剂,用水做溶剂以及在室温反应温度.在该最优条件下,可以非常顺利地实现各种硝基烯烃与各类醛和酮的Michael加成,得到较高的收率(76%~97%),良好的几何选择性(顺∶反=82∶18~99∶1)以及对映选择性(ee值达到97%).     

金矿浮选回收率预测模型

浮选回收率是金矿选矿过程重要的生产指标,目前主要是通过人工化验的方法检测获得,人工检测周期较长,造成金矿厂不能及时把握浮选工艺水平.在大量现场生产数据的基础上,分别采用多元线性回归和BP神经网络的方法,建立了金矿厂浮选回收率的预测模型.预测误差分析表明,BP神经网络预测模型能较好地预测金矿厂的浮选回收率,当预测相对误差在±3%范围内时,模型的预测精度达到91%,对于实际生产具有良好的参考作用.