Co-precipitation of nano Mg–Y/ZrO2 ternary oxide eutectic system: Effects of calcination temperature

In the family of inorganic nanomaterials, zirconia is a highly promising functional ceramic with a high refractive index, hardness, and dielectric constant, as well as excellent chemical inertness and thermal stability. These properties are enhanced in nano-zirconia ceramics, because nanopowders have a small particle size, good morphology, and uniform and dispersive distribution. In this study, a co-precipitation process was proposed to synthesise highly dispersed MgO–Y₂O₃ co-stabilized ZrO₂ nanopowders. The effects of different calcination temperatures on the crystallisation degree and particle dispersion of zirconia nanopowders were characterised by X-ray diffraction (XRD), thermogravimetry-differential scanning calorimetry (TG-DSC), Raman spectroscopy, Fourier transform infrared spectroscopy (FTIR), nitrogen adsorption using the Brunauer–Emmett–Teller (BET) theory, transmission electron microscopy (TEM), and field emission scanning electron microscopy (FESEM). The optimum synthesis conditions were obtained as follows: 6 h of high-energy planetary grinding and calcination at 800 °C in an electric furnace. Under these optimum conditions, the average particle size of the prepared powder was 28.7 nm. This process enriches the literature on the controllable preparation of Mg–Y/ZrO₂ nanopowders obtained by the co-precipitation method.     

Numerical Investigation of the Capture of Polydisperse Particles by Charged Droplets

The capture of particles by charged droplets was simulated by considering the electrostatic interactions of droplet-droplet and droplet-particle. The results indicate that the electrostatic repulsion between droplets leads to a dynamic accumulation mode of particles. However, the droplet spacing has an insignificant effect on the capture efficiency when the electrostatic deposition predominates. The increase of droplet charge remarkably improves the capture efficiency, in which the capture of fine particles accounts for the largest proportion. Compared to the droplet charge, the droplet size shows a limited improvement in the capture efficiency. Reducing the droplet velocity prolongs the capture time instead of enhancing the capture capacity per unit time, thereby improving capture efficiency.     

Practical Application of the Probabilistic‐Statistical Model of the Suspension Separation in Hydrocyclones

An effective practical approach that allows not only a significant reduction in the scope of practical experiments in the course of studying suspension separation processes in hydrocyclones, but also makes it possible to assess the intensity of random components of the processes and define the interrelation between such components and hydrodynamics of flows in a hydrocyclone is presented. Within the frames of the developed probabilistic‐statistical model of suspension separation in hydrocyclones on the basis of statistical self‐similarity properties, a relationship was found between determined and random components of the processes. This allowed transitioning from three‐parameter probability density functions for suspension particles in hydrocyclones to two‐parameter functions; thus significantly improving the efficiency of practical application of the developed model.     

基于粒子群优化和支持向量机的花粉浓度预测模型

为了提高花粉浓度预报的准确率，解决现有花粉浓度预报准确率不高的问题，提出了一种基于粒子群优化（PSO）算法和支持向量机（SVM）的花粉浓度预报模型。首先，综合考虑气温、气温日较差、相对湿度、降水量、风力、日照时数等多种气象要素，选择与花粉浓度相关性较强的气象要素构成特征向量；其次，利用特征向量与花粉浓度数据建立SVM预测模型，并使用PSO算法找出最优参数；然后利用最优参数优化花粉浓度预测模型；最后，使用优化后的模型对花粉未来24 h浓度进行预测，并与未优化的SVM、多元线性回归法（MLR）、反向神经网络（BPNN）作对比。此外使用优化后的模型对某市南郊观象台和密云两个站点进行逐日花粉浓度预测。实验结果表明，相比其他预报方法，所提方法能有效提高花粉浓度未来24 h预测精度，并具有较高的泛化能力。     

PSO优化多核RVM的模拟电路故障预测

针对模拟电路健康管理的特点，提出了一种基于PSO优化多核RVM的模拟电路故障预测方法。利用参数分析得到电路的输出频域响应作为特征，计算其与电路无故障标准响应的欧氏距离来表征电路元件健康值，将多个核函数线性组合，并用PSO优化多核RVM参数后的模型实现对各个时间点元件的健康值变化轨迹进行预测。仿真结果表明，该方法在小样本情况下，预测效果优于单一核函数的RVM模型，适用于健康管理中实时预测，具有较好的实用性。     

结合优化支持向量机与K-means++的工控系统入侵检测方法

针对工业控制系统传统单一检测算法模型对不同攻击类型检测率和检测速度不佳的问题，提出一种优化支持向量机和K-means++算法结合的入侵检测模型。首先利用主成分分析法（PCA）对原始数据集进行预处理，消除其相关性；其次在粒子群优化（PSO）算法的基础上加入自适应变异过程避免在训练的过程中陷入局部最优解；然后利用自适应变异粒子群优化（AMPSO）算法优化支持向量机的核函数和惩罚参数；最后利用密度中心法改进K-means算法与优化后的支持向量机组合成入侵检测模型，从而实现工业控制系统的异常检测。实验结果表明，所提方法在检测速度和对各类攻击的检测率上得到明显提升。     

Additively manufactured respirators: quantifying particle transmission and identifying system-level challenges for improving filtration efficiency

The COVID-19 pandemic has disrupted the supply chain for personal protective equipment (PPE) for medical professionals, including N95-type respiratory protective masks. To address this shortage, many have looked to the agility and accessibility of additive manufacturing (AM) systems to provide a democratized, decentralized solution to producing respirators with equivalent protection for last-resort measures. However, there are concerns about the viability and safety in deploying this localized download, print, and wear strategy due to a lack of commensurate quality assurance processes. Many open-source respirator designs for AM indicate that they do not provide N95-equivalent protection (filtering 95% of SARS-CoV-2 particles) because they have either not passed aerosol generation tests or not been tested. Few studies have quantified particle transmission through respirator designs outside of the filter medium. This is concerning because several polymer-based AM processes produce porous parts, and inherent process variation between printers and materials also threaten the integrity of tolerances and seals within the printed respirator assembly. No study has isolated these failure mechanisms specifically for respirators. The goal of this paper is to measure particle transmission through printed respirators of different designs, materials, and AM processes. The authors compare the performance of printed respirators to N95 respirators and cloth masks. Respirators in this study printed using desktop- and industrial-scale fused filament fabrication processes and industrial-scale powder bed fusion processes were not sufficiently reliable for widespread distribution and local production of N95-type respiratory protection. Even while assuming a perfect seal between the respirator and the user’s face, although a few respirators provided >90% efficiency at the 100−300 nm particle range, almost all printed respirators provided <60% filtration efficiency. Post-processing procedures including cleaning, sealing surfaces, and reinforcing the filter cap seal generally improved performance, but the printed respirators showed similar performance to various cloth masks. The authors further explore the process-driven aspects leading to low filtration efficiency. Although the design/printer/material combination dictates the AM respirator performance, the identified failure modes originate from system-level constraints and are therefore generalizable across multiple AM processes. Quantifying the limitations of AM in producing N95-type respiratory protective masks advances understanding of AM systems toward the development of better part and machine designs to meet the needs of reliable, functional, end-use parts.     

Cost-minimization analysis of a working vacation queue with N-policy and server breakdowns

This paper investigates the N-policy M/M/1 queueing system with working vacation and server breakdowns. As soon as the system becomes empty, the server begins a working vacation. The server works at a lower service rate rather than completely stopping service during a vacation period. The server may break down with different breakdown rates during the idle, working vacation, and normal busy periods. It is assumed that service times, vacation times, and repair times are all exponentially distributed. We analyze this queueing model as a quasi-birth–death process. Furthermore, the equilibrium condition of the system is derived for the steady state. Using the matrix-geometric method, we find the matrix-form expressions for the stationary probability distribution of the number of customers in the system and system performance measures. The expected cost function per unit time is constructed to determine the optimal values of the system decision variables, including the threshold N and mean service rates. We employ the particle swarm optimization algorithm to solve the optimization problem. Finally, numerical results are provided, and an application example is given to demonstrate the applicability of the queueing model.     

Design and Characterization of a New pVII Combinatorial Phage Display Peptide Library for Protease Substrate Mining Using Factor VII Activating Protease (FSAP) as Model

We describe a novel, easy and efficient combinatorial phage display peptide substrate-mining method to map the substrate specificity of proteases. The peptide library is displayed on the pVII capsid of the M13 bacteriophage, which renders pIII necessary for infectivity and efficient retrieval, in an unmodified state. As capture module, the 3XFLAG was chosen due to its very high binding efficiency to anti-FLAG mAbs and its independency of any post-translational modification. This library was tested with Factor-VII activating protease (WT-FSAP) and its single-nucleotide polymorphism variant Marburg-I (MI)-FSAP. The WT-FSAP results confirmed the previously reported Arg/Lys centered FSAP cleavage site consensus as dominant, as well as reinforcing MI-FSAP as a loss-of-function mutant. Surprisingly, rare substrate clones devoid of basic amino acids were also identified. Indeed one of these peptides was cleaved as free peptide, thus suggesting a broader range of WT-FSAP substrates than previously anticipated.     

High areal capacitance of FeOOH-carbon nanotube negative electrodes for asymmetric supercapacitors

The relatively low capacitance of negative electrodes, as compared to the capacitance of advanced positive electrodes, poses a serious problem, since this limits the development of asymmetric supercapacitor (SC) devices with a large voltage window and enhanced power-energy characteristics. We fabricate negative SC electrodes with a high capacitance that match the capacitance of advanced positive electrodes at similar active mass loadings, as high as 37?mg?cm^?2. Cyclic voltammetry, impedance spectroscopy, galvanostatic charge-discharge data and the power-energy characteristics of the asymmetric SC device exhibit good electrochemical performance for a voltage window of 1.6?V. Our approach involves the development and application of particle extraction through liquid-liquid interface (PELLI) methods, new extraction mechanisms and efficient extractors to synthesize α-FeOOH and β-FeOOH electrode materials. The use of PELLI allows agglomerate-free processing of powders, which facilitates their efficient mixing with multiwalled carbon nanotubes (MWCNT) and allows improved electrolyte access to the particle surface. Experiments to determine the properties of FeOOH-MWCNT composites provided insight into the influence of the electrode material and the structure of extractor molecules on the composite properties. The highest capacitance of 5.86?F?cm^?2 for negative electrodes and low impedance were achieved using α-FeOOH-MWCNT composites and a 16-phosphonohexadecanoic acid (PHDA) extractor. This extractor allows adsorption on particles, not only at the liquid-liquid interface, but also in the bulk aqueous phase and can potentially be used as a capping agent for particle synthesis and as an extractor in the PELLI method.