Box-Behnken Design a Key Tool to Achieve Optimized PCL/Gelatin Electrospun Mesh

Hybrid electrospun nanofibers of polycaprolactone (PCL)/gelatin are considered as drug-delivery systems for increasing the treatment efficacy in superficial (skin) wounds. Continuous delivery of therapeutic agents, skin extracellular matrix similarity, management of wound exudate, and antimicrobial barrier effect are the major advantages of electrospun nanofibers in skin applications. Additionally, combining the favorable properties of PCL and gelatin, regarding their biocompatibility, biodegradability and mechanical performance have been revealed promising parameters to be considered for blend in hybrid structures. However, the usual optimization protocol of nanofibers’ production in electrospinning is based on the observation of one-variable-at-time being this methodology expensive and time-consuming. Therefore, in this research work, a statistical model based on four input variables namely, the flow rate, the needle-working distance, the applied voltage, and the ratio of PCL in the solution, is developed to predict the behavior of nanofibers. The performance of nanofibers is monitored by measurements of fiber's diameter, mesh's thickness, and mesh's permeability. Overall, the model showed to be statistically significant (p-value < 0.05) and an independent analysis validated the predicted response for optimal condition. Finally, a delivery study is performed to evaluate the electrospun mesh performance as a drug carrier.     

Hydrodynamics study of a fast liquid–liquid oxidation process with in situ gas production in microreactors

Hydrodynamics characteristics of a fast and highly exothermic liquid–liquid oxidation process with in situ gas production in microreactors were studied using a newly developed experimental method. In the adipic acid synthesis through the K/A oil (the mixture of cyclohexanol and cyclohexanone) oxidation with nitric acid, bubble generation modes were divided into four categories. The gas production became more intensive, unstable, even explosive with increasing the oil phase feed rate and the temperature. A novel automatic image processing method was developed to monitor the instantaneous velocity online by tracking the gas–liquid interface. The axial velocity at the same location was unstable due to the changing gas production rate. Furthermore, the actual residence time was obtained easily with being only 36% of the space–time minimally, beneficial for establishing accurate kinetics and mass transfer models with time participation. Finally, an empirical correlation was developed to predict the actual residence time under different conditions.     

基于现代审美下的赣傩艺术元素分析与设计应用

目的 赣傩艺术元素内容丰富并保存完整,是研究我国古代赣傩地区文化与艺术的珍贵史料.研究赣傩艺术元素的提取及衍生图案的设计方法,在设计应用中表达赣傩傩面具、选取傩舞形和构筑傩庙魂,能给当代赣傩艺术元素的产品设计以指引.方法 通过直接引用、形意结合和局部强化的设计方法,增厚其丰富内涵、设计个性和主题意蕴.通过现代化审美中"绿色化、感性化、地域化"的要求,遵循"以退为进,化繁为简""多元并存,个性体现"的原则,强化赣傩艺术元素的独特风格.结论 用现代的手法,将特色的赣傩艺术元素植入到理性的产品设计中去,使赣傩艺术元素与现代设计思想有机结合.在继承传统文化与现代流行中找到契合点,深入挖掘赣傩艺术元素蕴含的文化精神、文化胸怀和文化自信,使中华传统文化在现代审美下进行创新再现.     

Microbial susceptibility of various polymers and evaluation of thermoplastic elastomers with antimicrobial additives

The incursion of microbial growth on polymeric products can deteriorate their performance and lead to the development of undesirable staining and odors. A growing trend in the industry has aimed to reduce microbial populations on high-touch surfaces via the use of antimicrobials to protect material aesthetics and durability or to prevent the spread of pathogenic microorganisms. In this study, a variety of plastic substrates (30 unique polymer compounds), including poly(acrylonitrile-co-butadiene-co-styrene), poly(butylene terephthalate), poly(etherimide), various thermoplastic elastomers (TPEs), poly(carbonates), and poly(amides), were screened for susceptibility to microbial attack using American Society for Testing and Materials (ASTM) G21 (fungi susceptibility), Japanese Industrial Standard (JIS) Z2801, and modified ASTM E1428-15a (bacterial susceptibility) test standards. TPEs were determined to be most susceptible to microbial attack under the appropriate environmental conditions. Subsequent studies assessed the use of an antimicrobial additive, zinc pyrithione (ZPT), for potential efficacy in a variety of TPE blends for diverse target market applications. ZPT proved to be very effective in protecting TPEs, reducing Staphylococcus aureus and Escherichia coli populations by 99.9% or more in JIS Z2801 testing and inhibiting fungal growth (rating = 0) according to the ASTM G21 standard.     

一类分数阶微积分的中值定理及应用

Riemann-Liouville分数阶微积分算子是一类带有一个函数的分数阶微积分算子的特殊情形，以Riemann-Liouville分数阶微积分算子的积分中值定理和微分中值定理为基础，我们得到了一类带有一个函数的分数阶微积分算子的积分中值定理和微分中值定理，并给出其在计算方面的一些应用。     

给水管道腐蚀原因及防护措施探讨

给水管道在使用过程中很容易受到人为外力、管道材质、地下水、周围空气、土壤等因素的影响而腐蚀,影响了管道的使用质量和寿命,也带来较大的安全隐患。本文主要是从给水管道腐蚀原因出发,并探讨防护措施。     

Description of the thermodynamic properties and fluid-phase behavior of aqueous solutions of linear,branched, and cyclic amines

The SAFT-γ Mie group-contribution equation of state is used to represent the fluid-phase behavior of aqueous solutions of a variety of linear, branched, and cyclic amines. New group interactions are developed in order to model the mixtures of interest, including the like and unlike interactions between alkyl primary, secondary, and tertiary amine groups (NH₂, NH, N), cyclic secondary and tertiary amine groups (cNH, cN), and cyclic methine-amine groups (cCHNH, cCHN) with water (H₂O). The group-interaction parameters are estimated from appropriate experimental thermodynamic data for pure amines and selected mixtures. By taking advantage of the group-contribution nature of the method, one can describe the fluid-phase behavior of mixtures of molecules comprising those groups over broad ranges of temperature, pressure, and composition. A number of aqueous solutions of amines are studied including linear, branched aliphatic, and cyclic amines. Liquid–liquid equilibria (LLE) bounded by lower critical solution temperatures (LCSTs) have been reported experimentally and are reproduced here with the SAFT-γ Mie approach. The main feature of the approach is the ability not only to represent accurately the experimental data employed in the parameter estimation, but also to predict the vapor–liquid, liquid–liquid, and vapor–liquid–liquid equilibria, and LCSTs with the same set of parameters. Pure compound and binary phase diagrams of diverse types of amines and their aqueous solutions are assessed in order to demonstrate the main features of the thermodynamic and fluid-phase behavior.     

天然气水合物储层泥质细粉砂挡砂介质堵塞规律与微观挡砂机制

中国南海海域部分天然气水合物储层中地层砂为高泥质含量细粉砂，开采防控砂难度较大。针对高泥质细粉砂挡砂机制问题，使用粒度中值为10.13 μm的泥质细粉砂样品，模拟单向气液携砂流动条件，使用绕丝筛板、金属烧结网、金属纤维、预充填陶粒4类挡砂介质在20~80 μm挡砂精度下进行挡砂模拟实验，采用显微成像系统观察挡砂介质内部及表面砂粒沉积与堵塞动态，分析介质流通性能和挡砂性能变化，总结堵塞规律、微观挡砂机制与形态及其控制因素。研究结果表明，不同类型和精度的挡砂介质对泥质细粉砂的堵塞总体呈现堵塞开始、堵塞加剧和堵塞平衡3个阶段。随着驱替进行，挡砂介质渗透率逐渐降低，幅度会高达90%以上；同时过砂速度减缓，最终过砂率为5%~10%。根据堵塞规律和微观图像分析，提出了粗组分分选桥架、局部砂团适度挡砂、整体砂桥阻挡等挡砂介质对泥质细粉砂的3种微观挡砂机制。以粗组分分选桥架挡砂机制为主的挡砂工况下，挡砂介质堵塞渗透率较高，但过砂率超过15%，挡砂效果较差；以整体砂桥挡砂机制为主时，过砂率在10%以下，挡砂性能较好，但各类挡砂介质的堵塞渗透率不足1 D，流通性能较差。局部砂团适度挡砂机制为主时介质挡砂性能及流通性能介于两者之间。挡砂介质对天然气水合物储层泥质细粉砂的微观挡砂机制和形态受挡砂介质类型、精度、地层砂特征以及流动条件等因素控制，其规律对于水合物泥质细粉砂防控砂优化有指导意义。     

煤泥燃烧过程中汞的迁移行为研究

采用在线汞测试方法，以山西省低热值煤电厂中掺烧的煤泥为研究对象，利用实验室小型流化床，研究煤泥中汞的热转化行为差异及共性特征、影响煤泥热转化过程中汞迁移的关键因素，以揭示煤泥热转化过程中汞污染物的迁移机理。结果表明，同一种煤泥，相同气氛，800、900、1 000 ℃下，燃烧温度对煤泥中的汞的释放比例没有变化；相同温度，汞的释放比例为氮气>空气>氧气。3种煤泥在相同燃烧条件下，汞的释放特征相似，元素汞的释放量和释放比例差异较大。释放量与煤泥中的汞含量正相关，释放比例与煤泥中汞的赋存形态有一定关系。     

Micro-expression recognition from local facial regions

MiE is a facial involuntary reaction that reflects the real emotion and thoughts of a human being. It is very difficult for a normal human to detect a Micro-Expression (MiE), since it is a very fast and local face reaction with low intensity. As a consequence, it is a challenging task for researchers to build an automatic system for MiE recognition. Previous works for MiE recognition have attempted to use the whole face, yet a facial MiE appears in a small region of the face, which makes the extraction of relevant features a hard task. In this paper, we propose a novel deep learning approach that leverages the locality aspect of MiEs by learning spatio-temporal features from local facial regions using a composite architecture of Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM). The proposed solution succeeds to extract relevant local features for MiEs recognition. Experimental results on benchmark datasets demonstrate the highest recognition accuracy of our solution with respect to state-of-the-art methods.