Atom transfer radical polymerization (ATRP): A versatile and forceful tool for functional membranes

The progress in atom transfer radical polymerization (ATRP) provides an effective means for the design and preparation of functional membranes. Polymeric membranes with different macromolecular architectures applied in fuel cells, including block and graft copolymers are conveniently prepared via ATRP. Moreover, ATRP has also been widely used to introduce functionality onto the membrane surface to enhance its use in specific applications, such as antifouling, stimuli-responsive, adsorption function and pervaporation. In this review, the recent design and synthesis of advanced functional membranes via the ATRP technique are discussed in detail and their especial advantages are highlighted by selected examples extract the principles for preparation or modification of membranes using the ATRP methodology.     

透气性陶瓷复合材料的相变强韧化及其机制

制备了用Ca-PSZ进行相变强韧化FMA的复合陶瓷材料,发现在Ca—PSZ加入量为9％时其宏观力学性能达到峰值;从SEM微观形貌和EDS能谱分析结果出发研究了FMA基体材料的强度形成因素、Ca—PSZ补强的机理;通过XRD衍射分析及相成分的近似定量分析阐明了半稳定化ZrO_2相交增韧作用的材料学本质;从微观角度提出ZrO_2相变增韧和割裂作用综合影响的结果是复合材料的宏观性能存在峰值的原因。     

FMEA简介

介绍了一种新的对产品设计及工艺设计进行预测和评估的方法。它对完善设计，预防和纠正可能发生 的错误将起到非常有效的作用。     

柔性气动执行器的研究现状和趋势

介绍了当前各种柔性气动执行器的研究背景、结构原理和最新研究进展，并对其发展趋势作了进一步的展望。     

Practices @ Home: Assimilating the Past and the Present for a Visionary Architecture

Guest-Editor Mehran Gharleghi describes the work of four Iranian practices - Fluid Motion Architects (FMA), Pouya Khazaeli Parsa, Arsh Design Studio and Kourosh Rafiey/Asar Consultant Engineers' Co) - that are worthy of international attention. Over the last decade, all have distinguished themselves by developing a body of work ‘that is not only globally informed but also conscious and proud of its local, regional and national identity’.     

锡层厚度无模型自适应控制系统

武钢冷轧厂电镀锡线锡层厚度无模型自适应（FMA）控制系统是专门为了解决大滞后时变的非线性复杂系统控制难题而研制设计的。该控制系统采用了当今最先进的无模型自适应控制技术（FMA）来对镀锡板锡层厚度进行闭环控制。其突出特点是无需数学模型、鲁棒性强、抗滞后。系统投运以来,取得了良好的控制效果,也代表了电镀锡生产线锡层控制的最新发展方向,可广泛应用于各种行业的镀层或涂层生产线上。     

浮点乘加部件延迟对浮点性能影响的研究

浮点融合乘加部件会增加独立浮点加减法、乘法等运算延迟.为克服该缺陷,研究将乘加部件独立乘法、加减法等运算延迟由6拍减为4拍时对浮点性能的影响.以某支持乘加运算的国产处理器为基础,修改相关的RTL级设计代码,利用硬件仿真加速器平台,对SPEC CPU2000浮点测试课题进行评估.实验结果表明,该延迟优化有利于提高浮点性能,最大提高5.25％,平均提高1.61％.     

Music Genre Classification Using DenseNet and Data Augmentation

It can be said that the automatic classification of musical genres plays a very important role in the current digital technology world in which the creation, distribution, and enjoyment of musical works have undergone huge changes. As the number of music products increases daily and the music genres are extremely rich, storing, classifying, and searching these works manually becomes difficult, if not impossible. Automatic classification of musical genres will contribute to making this possible. The research presented in this paper proposes an appropriate deep learning model along with an effective data augmentation method to achieve high classification accuracy for music genre classification using Small Free Music Archive (FMA) data set. For Small FMA, it is more efficient to augment the data by generating an echo rather than pitch shifting. The research results show that the DenseNet121 model and data augmentation methods, such as noise addition and echo generation, have a classification accuracy of 98.97% for the Small FMA data set, while this data set lowered the sampling frequency to 16000 Hz. The classification accuracy of this study outperforms that of the majority of the previous results on the same Small FMA data set.