Wearing prediction of stellite alloys based on opposite degree algorithm

In order to predict the wearing of stellite alloys,the related methods of rare metals data processing were discussed. The method of opposite degree(OD) algorithm was put forward to predict the wearing of stellite alloys.OD algorithm is based on prior numerical data, posterior numerical data and the opposite degree between numerical forecast data. To compare the performance of predicted results based on different algorithms, the back propagation(BP) and radial basis function(RBF) neural network methods were introduced. Predicted results show that the relative error of OD algorithm is smaller than those of BP and RBF neural network methods. OD algorithm is an effective method to predict the wearing of stellite alloys and it can be applied in practice.     

Lead-free sodium niobate nanowires with strong piezo-catalysis for dye wastewater degradation

In this work, the hydrothermally-synthesized sodium niobate nanowires were used to decompose Rhodamine B dye solution through the piezo-catalytic effect. With the sodium niobate catalyst, a high piezo-catalytic degradation ratio of ～80% was achieved under the excitation of vibration for the Rhodamine B dye solution (～5?mg/l). These active species in the catalytic process, hydroxyl radicals and superoxide radicals with the strong oxidation ability, were also observed, which confirmed the key role of piezoelectric effect for piezo-catalysis. The piezo-catalysis of sodium niobate nanowires provides a high-efficiency and reusable tool in application in depredating the dye wastewater.     

Oxide-Scale Evolution on a New Ni–Fe-Based Superalloy at High Temperature

Oxidation of Metals - The isothermal oxidation behavior and oxide-scale evolution on a newly developed Ni–Fe-based superalloy were investigated. Three oxidation stages were generally...     

A Dual Inhibitor of DYRK1A and GSK3β for β-Cell Proliferation: Aminopyrazine Derivative GNF4877

Loss of β-cell mass and function can lead to insufficient insulin levels and ultimately to hyperglycemia and diabetes mellitus. The mainstream treatment approach involves regulation of insulin levels; however, approaches intended to increase β-cell mass are less developed. Promoting β-cell proliferation with low-molecular-weight inhibitors of dual-specificity tyrosine-regulated kinase 1A (DYRK1A) offers the potential to treat diabetes with oral therapies by restoring β-cell mass, insulin content and glycemic control. GNF4877, a potent dual inhibitor of DYRK1A and glycogen synthase kinase 3β (GSK3β) was previously reported to induce primary human β-cell proliferation in vitro and in vivo. Herein, we describe the lead optimization that lead to the identification of GNF4877 from an aminopyrazine hit identified in a phenotypic high-throughput screening campaign measuring β-cell proliferation.     

Thermoplastic and low dielectric constants polyimides based on BPADA-BAPP

ABSTRACT

The thermoplastic and low dielectric constants polyimides were introduced. The polyimides were prepared by pyromellitic dianhydride (PMDA) or 4,4?-(4,4?-Isopropylidenediphenoxy)diphthalic anhydride (BPADA) as anhydride monomer and 4,4?-oxydianiline (ODA) or 2,2-bis(4-(4-aminephenoxy)phenyl)propane (BAPP) as amine monomer. The polyimides were well characterized by FT-IR, thermogravimetric analysis, dynamic thermomechanical analysis, dielectric measurement, and tensile test. The dielectric constants were 2.32–2.95 compared with 3.10 of ODA-PMDA polyimide, while partly polyimides were thermoplastic. The results indicated anhydride monomers, containing lateral methyl groups, made polyimides become thermoplastic. The results of molecular simulations via Materials Studio also proved this conclusion.     

Study on Wettability and Corrosion Behavior of Al2O3 Doped Polyurea Coatings

Protection of Metals and Physical Chemistry of Surfaces - The Al2O3 powder was added as a filler to polyurea and the effect of doping amount on Shore hardness and wetting property were...     

Synergistic flame retardant effects of activated carbon and molybdenum oxide in poly(vinyl chloride)

The synergistic effects of activated carbon (AC) and molybdenum oxide (MoO₃) in improving the flame retardancy of poly(vinyl chloride) (PVC) were investigated. The effects of AC, MoO₃ and their mixture with a mass ratio of 1:1 on the flame retardancy and smoke suppression properties of PVC were studied using the limiting oxygen index and cone calorimeter tests. It was found that the flame retardancy of the relatively cheaper AC was slightly weaker than that of MoO₃. In addition, the incorporation of AC and MoO₃ greatly reduced the total heat release and improved smoke suppressant property of PVC composites. When the total content of AC and MoO₃ was 10 phr, PVC/AC/MoO₃ had the lowest peak heat release rate and peak smoke production rate values of 173.80 kW m^?2 and 0.1472 m² s^?1, which represented reductions of 47.3 and 59.9%, respectively, compared with those of PVC. Furthermore, thermogravimetric analysis and gel content tests were used to analyze the flame retardant mechanism of AC and MoO₃, with results showing that AC could promote early crosslinking in PVC. Char residue left after heating at 500 °C was analyzed using scanning electron microscopy and Raman spectroscopy, and the results showed that MoO₃ produced the most compact char, with the smallest and most organized carbonaceous microstructures. © 2017 Society of Chemical Industry     

Using electroencephalogram to continuously discriminate feelings of personal thermal comfort between uncomfortably hot and comfortable environments

Thermal comfort is an important factor for the design of buildings. Although it has been well recognized that many physiological parameters are linked to the state of thermal comfort or discomfort of humans, how to use physiological signal to judge the state of thermal comfort has not been well studied. In this paper, the feasibility of continuously determining feelings of personal thermal comfort was discussed by using electroencephalogram (EEG) signals in private space. In the study, 22 subjects were exposed to thermally comfortable and uncomfortably hot environments, and their EEG signals were recorded. Spectral power features of the EEG signals were extracted, and an ensemble learning method using linear discriminant analysis or support vector machine as a sub-classifier was used to build the discriminant model. The results show that an average discriminate accuracy of 87.9% can be obtained within a detection window of 60 seconds. This study indicates that it is feasible to distinguish whether a person feels comfortable or too hot in their private space by multi-channel EEG signals without interruption and suggests possibility for further applications in neuroergonomics.     

畜禽骨蛋白质材料化利用的研究现状与发展趋势分析

作为畜禽屠宰的副产物,动物骨因其丰富的蛋白质和广阔的深加工利用的发展前景而成为当今环境、农业和能源等领域的研究热点.受自身骨骼结构和综合利用技术的制约,骨骼的深加工利用率不足2％,造成了严重的资源浪费与环境污染.蛋白水解作为蛋白质资源深加工领域最有效的技术手段,可实现大宗蛋白质资源的高效回收利用;而蛋白水解物优异的溶解性、可降解性、生物相容性和独特的生物功能活性使其具有开发高值材料的潜力.随着石化资源的短缺和人们健康环保意识的增强,人们对环保型可再生型新材料的需求逐渐迫切,而畜禽骨蛋白质材料的开发利用紧密结合国家新型战略产业——生物制造业,将促进农副产品加工业的持续健康发展.针对畜禽骨蛋白质材料化开发利用的发展历程及当前的研究热点,本文阐述了絮凝剂、粘结剂、可降解塑料、表面活性剂、医用材料等近年来研究较广的畜禽骨蛋白质材料化利用途径,并总结了各种利用途径的应用效果和局限性;同时,总结分析了现今利用蛋白水解物开发新型材料的相关理论及研究成果,为开发畜禽骨蛋白质材料提供了理论支持;最后,基于目前生物基材料的发展趋势及畜禽骨深加工技术的难点问题,客观展望了畜禽骨蛋白质材料的制备及应用发展方向.