BiPO4 film on ITO substrates for photoelectrocatalytic degradation

BiPO₄ film was fabricated on indium-tin oxide glass substrate via dip-coating method for photoelectrocatalytic (PEC) activity. BiPO₄ film has performed a superior PEC degradation ability with synergetic effect of electro-oxidation and photocatalysis. The degradation rate of Methyl Blue (MB) increased greatly as bias potential increased and the highest activity was achieved at the bias potential of 3.0 V (vs. SCE in 0.1 mol/L Na₂SO₄, pH = 7). The PEC activity of BiPO₄ film is 5 times and 15 times higher than that of photocatalytic degradation and electrochemical oxidation, respectively. The acid condition plays an important role in achieving effective photoelectrocatalysis. The PEC degradation rate was also affected by the adsorption and the oxidation reaction of the ions of electrolytes. This BiPO₄ film could open up new opportunities to develop high-performance photoanode for PEC degradation.     

3D polymeric microfluidic device fabrication via contact liquid photolithographic polymerization (CLiPP)

In this contribution, a new method for the fabrication of complex polymeric microfluidic devices is presented. The technology, contact liquid photolithographic polymerization (CLiPP), overcomes many of the drawbacks associated with other rapid prototyping schemes, such as limited materials choices and time-consuming microassembly protocols. CLiPP shares many traits with other photolithographic methods, but three distinct features: (i) liquid photoresists in contact with the photomask, (ii) readily removed sacrificial materials, and (iii) living radical processes, enable multiple polymeric chemistries and mechanical properties while simultaneously enabling facile fabrication of 3D geometries and surface chemistry control. This contribution details fabrication techniques and methods for the fabrication of high aspect ratio posts covalently bonded to a polymeric substrate, an array of independently stacked bars on top of perpendicular bars, multiple undercut structures fabricated simultaneously, and a complex 3D geometry with intertwined channels.     

Deformation behaviour of iron-doped alumina

Compressive creep tests in air were carried out on 1 cat.% Fe-doped alumina at a temperature T=1400 °C. Iron doping affected the plastic deformation by different ways in relation with Fe²⁺ cations population. Fe²⁺ cations sped up the deformation rates. FeAl₂O₄ spinel precipitates were identified and they were found (i) to interact with alumina grain boundaries (ii) to limit the grain growth within a range of strain. The Fe²⁺ cations underwent oxidation and this resulted in the dissolution of the some precipitates and in the decrease of deformation rates. It was suggested that deformation sped up this evolution through mass transport and that time was not a dominating parameter.     

重油纳米化助燃效果研究与表征

将复配的分散剂加入重油中制备得到重油纳米颗粒，采用氧弹热值对比法对所研制的纳米化重油进行实验室评价。研究结果表明，纳米化后的重油燃烧性能得到了改善，在掺水量为3％～12％时，重油的燃烧效率提高了2．5％～6．1％。通过TEM观察，纳米化后的重油呈水包油（O／W）型乳液结构，油水界面清晰，界面膜较厚，乳化油粒径约为20～50nm，油水分散均匀，并且分散后的重油粘度增幅小，掺水量在15％以内，粘度增幅不超过20％，并且随着掺水量的增加，乳化重油的粘度逐渐减少。另外，乳化重油稳定性好，室温下至少可保存6个月，在80℃下存放3天未发生破乳现象。     

Machine-learning paradigms for selecting ecologically significant input variables

Harmful algal blooms, which are considered a serious environmental problem nowadays, occur in coastal waters in many parts of the world. They cause acute ecological damage and ensuing economic losses, due to fish kills and shellfish poisoning as well as public health threats posed by toxic blooms. Recently, data-driven models including machine-learning (ML) techniques have been employed to mimic dynamics of algal blooms. One of the most important steps in the application of a ML technique is the selection of significant model input variables. In the present paper, we use two extensively used ML techniques, artificial neural networks (ANN) and genetic programming (GP) for selecting the significant input variables. The efficacy of these techniques is first demonstrated on a test problem with known dependence and then they are applied to a real-world case study of water quality data from Tolo Harbour, Hong Kong. These ML techniques overcome some of the limitations of the currently used techniques for input variable selection, a review of which is also presented. The interpretation of the weights of the trained ANN and the GP evolved equations demonstrate their ability to identify the ecologically significant variables precisely. The significant variables suggested by the ML techniques also indicate chlorophyll-a (Chl-a) itself to be the most significant input in predicting the algal blooms, suggesting an auto-regressive nature or persistence in the algal bloom dynamics, which may be related to the long flushing time in the semi-enclosed coastal waters. The study also confirms the previous understanding that the algal blooms in coastal waters of Hong Kong often occur with a life cycle of the order of 1–2 weeks.     

抗几何失真的视频Hashing算法研究

文中提出了一种基于视频灰度直方图形状的Hashing算法,能有效抵抗各种常见的几何失真和视频处理操作.算法的鲁棒性原理如下:1)由于直方图的形状与像素位置无关,故基于直方图的视频Hashing算法能有效抵抗各种常见的几何攻击;2)由于在计算Hashing前对视频帧进行了平滑预处理,故算法对加噪攻击、模糊滤波、有损压缩等处理操作有很好的鲁棒性;3)由于计算Hashing前在时间轴上进行了低通滤波预处理,故算法能抵抗帧率变化、帧丢失等时域同步攻击.实验结果表明,所提出的Hashing算法有良好的唯一性和鲁棒性能.     

New Paradigm of Data-Driven Smart Customisation through Digital Twin

Big data is one of the most important resources for the promotion of smart customisation. With access to data from multiple sources, manufacturers can provide on-demand and customised products. However, existing research of smart customisation has focused on data generated from the physical world, not virtual models. As physical data is constrained by what has already occurred, it is limited in the identification of new areas to improve customer satisfaction. A new technology called digital twin aims to achieve this integration of physical and virtual entities. Incorporation of digital twin into the paradigm of existing data-driven smart customisation will make the process more responsive, adaptable and predictive. This paper presents a new framework of data-driven smart customisation augmented by digital twin. The new framework aims to facilitate improved collaboration of all stakeholders in the customisation process. A case study of the elevator industry illustrates the efficacy of the proposed framework.     

即时定向新闻采集技术研究

互联网的迅速发展带动了信息量的爆炸性增加。如何更快地采集所需信息一直是国内外研究和开发的热点。近年来,不断增长的对特定信息(例如特定领域的新闻)的需求要求有针对性地从指定的网站即时采集相关信息。这些新闻一般具有不可预见性、更新频率较快、时效性强等特点。这要求我们必须能针对这些特点实现即时定向的采集。本文提出了一种有效抓取网页并进行分析的方法,实践表明取得了满意的效果。     

Membrane bioreactor with nonwoven fabrics as solid–liquid separation media for wastewater treatment

A nonwoven fabric module was utilized as a solid–liquid separation medium in a membrane bioreactor (MBR) for treating wastewater. The experimental results indicated that nonwoven fabrics had lower filtration resistance than microporous membranes in MBR applications. The optimal aeration intensity was approximately 0.01m³/m² s. The effect of mixed liquor suspended solid concentration on filtration resistance was not significant at an operating flux of under 0.8m³/m² d in the study range. The performance of nonwoven fabrics in a MBR application was further demonstrated in a pilot test. Chemical oxygen demand (COD) and suspended solids (SS) in the effluent were maintained under 60 and 10 mg/L, respectively, whereas influent COD varied from 800 to 1800mg/L. The transmembrane pressure was maintained below 5 kPa at a permeation flux of 0.18m³/m² d. The experimental results demonstrated that nonwoven fabrics maintained stable operation in MBR applications under appropriate operating conditions.     

基于Bayes特征判别的选煤建模与识别

研究了煤块的Harr小波变换和幅度投影分析,在对原始图像进行特征判别分析的基础上,建立了煤块和煤矸石的统计模型,提出了用Bayes判别函数分选煤块和煤矸石的算法,实现了用计算机视觉系统对样本进行了识别检验.并运用神经网络BP算法进行训练识别,检验其正确性,最后通过实验验证了算法有效性.