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.     

Learning shape and texture progression for young child face aging

Face aging (FA) for young faces refers to rendering the aging faces at target age for an individual, generally under 20s, which is an important topic of facial age analysis. Unlike traditional FA for adults, it is challenging to age children with one deep learning-based FA network, since there are deformations of facial shapes and variations of textural details. To alleviate the deficiency, a unified FA framework for young faces is proposed, which consists of two decoupled networks to apply aging image translation. It explicitly models transformations of geometry and appearance using two components: GD-GAN, which simulates the Geometric Deformation using Generative Adversarial Network; TV-GAN, which simulates the Textural Variations guided by the age-related saliency map. Extensive experiments demonstrate that our method has advantages over the state-of-the-art methods in terms of synthesizing visually plausible images for young faces, as well as preserving the personalized features.     

Effect of Bimodal Grain Size Distribution on the Strain Hardening Behavior of a Medium-Entropy Alloy

The evolution of strain hardening behavior of the Fe_(50)(CoCrMnNi)_(50) medium-entropy alloy as a function of the fraction of recrystallized microstructure and the grain size was studied using the Hollomon and Ludwigson equations.The specimens under study were partially recrystallized,fully recrystallized with ultrafine-grained microstructure,and fully recrystallized with coarse grains.The yield strength decreases steadily as the fraction of recry stallized micro structure and grain size increases due to the recovery process and the Hall-Petch effect.Interestingly,the bimodal grain distribution was found to have a significant impact on strain hardening during plastic deformation.For instance,the highest ultimate tensile strength was exhibited by a 0.97 μm specimen,which was observed to contain a bimodal grain distribution.Furthermore,using the Ludwigson equation,the effect of the bimodal grain distribution was established from the behavior of K_2 and n1 curves.These curves tend to show very high values in the specimens with a bimodal grain distribution compared to those that show a homogenous grain distribution.Additionally,the bimodal grain distribution contributes to the extensive L(u|")ders strain observed in the 0.97 μm specimen,which induces a significant deviation of the Hollomon equation at lower strains.     

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.     

Dynamic energy and mass balance model for an industrial alkaline water electrolyzer plant process

This paper proposes a parameter adjustable dynamic mass and energy balance simulation model for an industrial alkaline water electrolyzer plant that enables cost and energy efficiency optimization by means of system dimensioning and control. Thus, the simulation model is based on mathematical models and white box coding, and it uses a practicable number of fixed parameters. Zero-dimensional energy and mass balances of each unit operation of a 3 MW, and 16 bar plant process were solved in MATLAB functions connected via a Simulink environment. Verification of the model was accomplished using an analogous industrial plant of the same power and pressure range having the same operational systems design. The electrochemical, mass flow and thermal behavior of the simulation and the industrial plant were compared to ascertain the accuracy of the model and to enable modification and detailed representation of real case scenarios so that the model is suitable for use in future plant optimization studies. The thermal model dynamically predicted the real case with 98.7 % accuracy. Shunt currents were the main contributor to relative low Faraday efficiency of 86 % at nominal load and steady-state operation and heat loss to ambient from stack was only 2.6 % of the total power loss.