Tough salami-inspired Cf/ZrB2 UHTCMCs produced by electrophoretic deposition

One of the biggest challenges of the materials science is the mutual exclusion of strength and toughness. This issue was minimized by mimicking the natural structural materials. To date, few efforts were done regarding materials that should be used in harsh environments. In this work we present novel continuous carbon fiber reinforced ultra-high-temperature ceramic matrix composites (UHTCMCs) for aerospace featuring optimized fiber/matrix interfaces and fibers distribution. The microstructures – produced by electrophoretic deposition of ZrB₂ on unidirectional carbon fibers followed by ZrB₂ infiltration and hot pressing – show a maximum flexural strength and fracture toughness of 330 MPa and 14 MPa m^1/2, respectively. Fracture surfaces are investigated to understand the mechanisms that affect strength and toughness. The EPD technique allows the achievement of a peculiar salami-inspired architecture alternating strong and weak interfaces.     

Pt–Ru nanoparticles anchored on poly(brilliant cresyl blue) as a new polymeric support: Application as an efficient electrocatalyst in methanol oxidation reaction

The glassy carbon electrode is modified by poly(brilliant cresyl blue) (PBCB) to be applied as a new green and efficient platform for Pt and Pt–Ru alloy nanoparticles deposition. Surface composition, morphology and catalytic activity of these modified electrodes towards methanol oxidation are assessed by applying X-ray diffraction, field emission scanning electron microscopy, cyclic voltammetry and electrochemical impedance spectroscopy techniques. The X-ray diffraction patterns reveal that the highly crystalline Pt and Pt–Ru alloy and RuO₂ nanoparticles with low crystallinity are deposited on the PBCB modified glassy carbon electrodes. The microscopic images indicate smaller size and better distribution of deposited nanoparticles on the surface of PBCB modified electrodes. Cyclic voltammetry and electrochemical impedance spectroscopy results reveal that PBCB supported Pt and Pt–Ru nanoparticles have better electrocatalytic performance and durability towards methanol oxidation rather than the unsupported nanoparticles. From the obtained results it can be concluded that the presence of PBCB not only improves the stability of nanoparticles on the surface, but also leads to the formation of smaller size and more uniform distribution of nanoparticles on the surface, which, in turn, cause the nanoparticles to provide a higher accessible surface area and more active centers for the oxidation of methanol. The results will be valuable in extending the applications of this polymer in surface modification steps and in developing promising catalyst supports to be applied in direct methanol fuel cells.     

基于MF-R和AWS密钥管理机制的物联网健康监测大数据分析系统

带有传感器的可穿戴式医疗设备不断生成大量数据，由于数据的复杂性，难以通过处理和分析大数据来找到有价值的决策信息。为了解决这个问题，提出了一种新的物联网体系结构，用于存储和处理医疗应用的可扩展传感器数据（大数据）。所提出的架构主要由两个子架构组成：Meta Fog重定向（MF-R）架构和AWS密钥管理机制。MF-R架构使用Apache Pig和Apache HBase等大数据技术来收集和存储不同传感器设备生成的传感器数据，并利用卡尔曼滤波消除噪声。AWS密钥管理机制使用密钥管理方案，目的是保护云中的数据，防止未经授权的访问。当数据存储在云中时，所提出的系统能够使用随机梯度下降算法和逻辑回归来开发心脏病的预测模型。仿真实验表明，和其他几种算法相比，提出的算法具有更小的误差，且在吞吐量、准确度等方面具有一定的优越性。     

Robust Control of Permanent Magnet Synchronous Motors

In this paper, permanent magnet synchronous motors (PMSMs) are investigated. According to the feature of PMSMs, a novel state equation of PMSMs is obtained by choosing suitable state variables. Based on the state equation, robust controllers are designed via interval matrix and PI control idea. In terms of bilinear matrix inequations, sufficient conditions for the existence of the robust controller are derived. In order to reduce the conservation and the dependence on parameter, the control inputs of PMSMs are divided into two parts, a feedforward control input and a feedback control input, and relevant sufficient conditions for the existence of the controller are obtained. Because of the suitable choice of state variables, the proposed control strategies can cope with the load uncertainty and have robustness for disturbance. Finally, simulations are carried out via Matlab/Simulink soft to verify the effectiveness of the proposed control strategies. The performance of the proposed control strategies are demonstrated by the simulation results.      

网络安全威胁因素及其常见网络安全技术分析

社会经济的快速发展促进了科学技术水平的显著提升，社会生产生活各个领域当中对计算机网络的应用程度不断提升，当前，网络已经成为了人们日常生活与工作的重要组成部分。为此，加强对网络安全等因素影响研究就显得格外重要。网络环境关系着用户的使用质量，更加影响人们的工作效率，加强对网络安全技术的研究时解决相关问题的核心内容。本文针对网络安全威胁因素以及常见的网络安全技术进行了简要分析。     

Superior foetal electrocardiogram signal elicitation using a novel artificial intelligent Bayesian methodology

Innumerable casualties due to intrauterine hypoxia are a major worry during prenatal phase besides advanced patient monitoring with latest science and technology. Hence, the analysis of foetal electrocardiogram (fECG) signals is very vital in order to evaluate the foetal heart status for timely recognition of cardiac abnormalities. Regrettably, the latest technology in the cutting edge field of biomedical signal processing does not seem to yield the desired quality of fECG signals required by physicians, which is the major cause for the pathetic condition. The focus of this work is to extort non-invasive fECG signal with highest possible quality with a motive to support physicians in utilizing the methodology for the latest intrapartum monitoring technique called STAN (ST analysis) for forecasting intrapartum foetal hypoxia. However, the critical quandary is that the non-invasive fECG signals recorded from the maternal abdomen are affected by several interferences like power line interference, baseline drift interference, electrode motion interference, muscle movement interference and the maternal electrocardiogram (mECG) being the dominant interference. A novel hybrid methodology called BANFIS (Bayesian adaptive neuro fuzzy inference system) is proposed. The BANFIS includes a Bayesian filter and an adaptive neuro fuzzy filter for mECG elimination and non-linear artefacts removal to yield high quality fECG signal. Kalman filtering frame work has been utilized to estimate the nonlinear transformed mECG component in the abdominal electrocardiogram (aECG). The adaptive neuro fuzzy filter is employed to discover the nonlinearity of the nonlinear transformed version of mECG and to align the estimated mECG signal with the maternal component in the aECG signal for annulment. The outcomes of the investigation by the proposed BANFIS system proved valuable for STAN system for efficient prediction of foetal hypoxia.     

Restructuring bank networks after mergers and acquisitions: A capacitated delocation model for closing and resizing branches

During restructuring processes, due to mergers and acquisitions, banks frequently face the problem of having redundant branches competing in the same market. In this work, we introduce a new Capacitated Branch Restructuring Model which extends the available literature in delocation models. It considers both closing down and long term operations׳ costs, and addresses the problem of resizing open branches in order to maintain a constant service level. We consider, as well, the presence of competitors and allow for ceding market share whenever the restructuring costs are prohibitively expensive.We test our model in a real life scenario, obtaining a reduction of about 40% of the network size, and annual savings over 45% in operation costs from the second year on. We finally perform a sensitivity analysis on critical parameters. This analysis shows that the final design of the network depends on certain strategic decisions concerning the redundancy of the branches, as well as their proximity to the demand nodes and to the competitor׳s branches. At the same time, this design is quite robust to changes in the parameters associated with the adjustments on service capacity and with the market reaction.     

增效过磷酸钙的增效机制及其对玉米生长的影响

利用猪毛、风化煤和腐植酸钠的水解液为增效剂制备了一种增效过磷酸钙,探讨了增效过磷酸钙的增效机制及其对玉米生长的影响。结果表明,蒸馏水浸提条件下,增效过磷酸钙能减缓水溶磷的释放,具备较高的pH值缓冲性。与普通过磷酸钙相比,增效过磷酸钙处理的玉米生物量平均增加了41.9%,吸磷量和吸钙量分别增加了61.7%和27.8%,根系活力增加了24.3%。该研究结果对过磷酸钙生产的技术改进具有指导意义。     

Combination of nuclear magnetic resonance spectroscopy and nonlinear methods to analyze the copolymerization of phosphonic acid derivatives

We demonstrate in this study that the combination of modern inline monitoring methods [here: inline nuclear magnetic resonance (NMR)] with simulations gains more exact and profound kinetic results than previously used methods like linearization without that combination. The ¹H-NMR spectroscopic data (more than 100 data points) are used to construct the copolymerization diagram. The reactivity ratios are obtained applying the van Herks nonlinear least square method. The examination of the radical copolymerization of 2-hydroxyethyl methacrylate (HEMA) with (2-{[2-(ethoxycarbonyl)prop-2-en-1-yl]oxy}ethyl) phosphonic acid (ECPPA) as important adhesive monomer used in dentistry yields reactivity ratios of r_HEMA = 1.83; r_ECPPA = 0.42. The copolymerization diagram reflects nonideal, non-azeotropic copolymerization. The sequence distribution of the obtained by Monte Carlo simulation indicates the generation of statistical copolymers. As an important finding, it is demonstrated that the repeating units responsible for etching and adhesion are arranged over the whole polymer chain, which is necessary to achieve proper functionality. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 48256.