肠靶向海藻酸钙基微胶囊的制备及控释性能研究

利用毛细管共挤出技术结合静电吸附和仿生硅化的方法，制备了海藻酸钙-壳聚糖/精蛋白/二氧化硅(ACPSi)复合微胶囊。ACPSi复合微胶囊的平均粒径约3.18 mm，单分散性好，囊壁最外层的二氧化硅层可抑制其在肠液pH环境中的溶胀，增强囊的机械稳定性。将羟丙甲基纤维素邻苯二甲酸酯(HPMCP)肠溶微球作为释药“微阀门”，嵌入囊壁可以更好地控制微胶囊的释药行为。以吲哚美辛为模型药物，当药物浓度为22.5 mg/ml时，ACPSi载药微胶囊在pH 2.5模拟胃液中3 h时累计释药率仅为0.33%，而转移至pH 6.8模拟肠液中19 h时累计释药率为77.78%；囊壁嵌入HPMCP微球后，22 h时累计释药率可提高约4%。因此，该复合微胶囊具有良好的肠靶向作用和控释特性，作为口服肠靶向缓控释制剂具有良好的应用前景。     

Longitudinal permeability determination of dual-scale fibrous materials

In this work, the longitudinal permeability of squarely packed dual-scale fiber preforms is studied theoretically. These fiber preforms are composed of aligned porous tows and the tows are tightly packed. The effective permeability is calculated as a parallel-like network of intra-tow permeability and inter-tow permeability, which are quantified by Darcy’s law and the inscribed radius between tows, respectively. The jump velocity at the interface between inter-tow fluids and porous tows is considered, as derived by substituting Beavers and Joseph’s correlation into Brinkman’s equation. We further examine the effects of intra-tow permeability on the effective permeability of the fibrous system with three interface conditions: (1) interface velocity = 0, (2) interface velocity = mean intra-tow velocity, and (3) interface velocity = jump velocity. The jump-velocity-based model is found to be closest to numerical data. The influence of the fiber volume fraction of tows on the effective permeability is also analyzed.     

转载溜槽衬板磨损预测的DEM仿真方法

针对EDEM自动划分网格较稀疏问题,采用Hypermesh划分仿真模型网格,利用Herz-Mindlin接触理论的Archard磨损模型对转载溜槽磨损问题进行仿真,在网格单元上提取出漏斗和溜管衬板的接触能量和磨损量,分析了磨损量与接触能量的关系。假设转载溜槽衬板磨损深度为物料与溜槽衬板的使用时间为线性函数,根据现场衬板磨损量的测量值,将衬板的磨损系数关系的看作隐式的单变量方程,应用EDEM软件的仿真结果求解出磨损系数的标定值。分析了漏斗和溜管的磨损机理。该方法可用于转载溜槽的磨损预测。     

少量有机碳对单级自养脱氮工艺性能的影响

采用序批式生物膜反应器(SBBR),经过4个阶段的培养,快速富集好氧氨氧化细菌(AOB)和厌氧氨氧化细菌(AnAOB),并考察不同低碳氮比对工艺脱氮性能的影响。结果表明,NH4^+-N去除率可达到99%以上,TN去除率可达到90%以上。对应C/N=0、1和2时,反应器出水NH4^+-N和TN去除率分别为99.59%、99.5%、98.47%和93.75%、97.22%、98.11%。说明少量COD的存在,可实现同步硝化-厌氧氨氧化-反硝化,且在一定程度上提高脱氮效率。     

高性能有机氟材料制备科学及应用进展

有机氟材料具有优异的热氧稳定性、耐化学腐蚀性、耐老化性、不黏性、电绝缘性以及极小的摩擦系数等特性，因此作为一种不可替代的材料广泛应用于高新技术产业。近年来高新技术产业发展对高性能有机氟材料的需求引发了学术界和工业界对氟材料的研究兴趣。依据本文作者的研究经历及有机氟材料的发展方向，本文介绍了氟树脂（新型含氟聚合物、电活性含氟聚合物、新型全氟磺酸聚合物、聚四氟乙烯3D打印）及氟橡胶（过氧化物硫化氟橡胶、耐低温氟醚橡胶、耐高温全氟醚橡胶、全氟聚醚基类玻璃橡胶）的制备科学及应用进展，特别阐述为了满足航空航天、能源、信息等高新技术产业需求发展的新一代高性能有机氟材料。本文也介绍了近期出现的聚四氟乙烯新成型技术及类玻璃氟橡胶。文章指出发展绿色环保和高效的高性能有机氟材料制备及成型加工方法是今后的发展方向。     

大规模多状态计算系统的容错性能分析

针对异构计算节点组成的大规模多状态计算系统的容错性能分析问题，提出了一种计算系统容错性能的评估方法。该方法采用自定义的两级容错性能形式化描述框架进行系统描述，通过构造多值决策图（Multi-value Decision Diagram，MDD）模型对系统进行容错性能建模，并基于构造的模型高效地计算出部件故障的条件下计算系统在特定性能水平上运行的概率，减少了计算的冗余性。实验结果表明，该方法在模型的大小和构建时间上均优于传统方法。该方法的提出将对系统操作员或程序设计者具有重要意义，使其确保系统适合预期应用。     

A self-adaptive synthetic over-sampling technique for imbalanced classification

Traditionally, in supervised machine learning, (a significant) part of the available data (usually 50%-80%) is used for training and the rest—for validation. In many problems, however, the data are highly imbalanced in regard to different classes or does not have good coverage of the feasible data space which, in turn, creates problems in validation and usage phase. In this paper, we propose a technique for synthesizing feasible and likely data to help balance the classes as well as to boost the performance in terms of confusion matrix as well as overall. The idea, in a nutshell, is to synthesize data samples in close vicinity to the actual data samples specifically for the less represented (minority) classes. This has also implications to the so-called fairness of machine learning. In this paper, we propose a specific method for synthesizing data in a way to balance the classes and boost the performance, especially of the minority classes. It is generic and can be applied to different base algorithms, for example, support vector machines, k-nearest neighbour classifiers deep neural, rule-based classifiers, decision trees, and so forth. The results demonstrated that (a) a significantly more balanced (and fair) classification results can be achieved and (b) that the overall performance as well as the performance per class measured by confusion matrix can be boosted. In addition, this approach can be very valuable for the cases when the number of actual available labelled data is small which itself is one of the problems of the contemporary machine learning.     

A novel fast distance relay for series compensated transmission lines

This paper presents a fast distance relay for series compensated transmission lines based on the R–L differential-equation algorithm using the theory of equal transfer process of transmission lines. The measuring distances based on the proposed algorithm can fast approach the actual value of fault distance when a fault occurs in front of the series capacitor. When a fault occurs behind of the series capacitor, the fault loop, including the series capacitor, does not match the R–L transmission line model, so the measuring distances fluctuate severely. Based on this, the relative position of the fault with respect to the series capacitor can be judged effectively according to the fluctuation range of the measuring distances, and the accurate fault location can be obtained fast. A variety of PSCAD/EMTDC simulation tests show that the new relay has fast operating speed and high accuracy when applied to the long series compensated transmission lines.     

Platinum nanoparticles decorated on graphitic carbon nitride-ZIF-67 composite support: An electrocatalyst for the oxidation of butanol in fuel cell applications

In the present study, we report an eco-friendly and simple route to design and synthesize novel nanocomposite catalyst based on platinum nanoparticles anchored on binary support of graphitic carbon nitride (g-C₃N₄) and cobalt-metal-organic framework (ZIF-67). For this purpose, ZIF-67 was prepared by precipitation method and g-C₃N₄ was prepared through thermal polymerization method. Later, ZIF-67 and g-C₃N₄ were hybridized through sonication to get homogeneous g–C₃N₄–ZIF-67 nanocomposite support material. Platinum nanoparticles (PtNPs) were uniformly deposited on g–C₃N₄–ZIF-67 by an electrochemical method. The as-developed nanocatalyst was characterized by morphological, structural and electrochemical techniques. The electrocatalytic activity of PtNPs@g–C₃N₄–ZIF-67 nanocatalyst towards butanol oxidation was evaluated via CV, CA, LSV and EIS in an alkaline medium. Results revealed that the proposed catalyst showed greatly enhanced electrooxidation of butanol in terms of high magnificent current density, lower oxidation potential, excellent long-term stability, large surface area, low charge transfer resistance and less toxic ability. Enhanced catalytic performance of the proposed catalyst could be ascribed to the synergistic effect of g–C₃N₄–ZIF-67 nanocomposite and PtNPs. The PtNPs@g–C₃N₄–ZIF-67 catalyst holds promising potential applications to be used as an anodic electrocatalyst for the development of high-performance alkaline fuel cells.