Impacts of layout,surface condition and alloying elements on diffusion welding of micro process devices

The formation of a monolithic part during diffusion bonding is accompanied by the diffusion of atoms across the bonding planes. At sufficient low roughness, it mainly depends on the temperature and dwell time. At the same time, the diffusion process competes against grain growth. By adjusting an appropriate level of bearing pressure, it is possible to control deformation taking into account additional parameters resulting from mechanical microstructures and the design and aspect ratio of the part. Furthermore, material properties, such as the content of alloying elements, the degree of cold work hardening and the grain size, have an impact on diffusion and deformation behavior. Also the surface condition of mating surfaces is important to diffusion kinetics and the quality of the joint. Especially passivation layers of corrosion‐resistant alloys, such as stainless steels and nickel‐based alloys, impair diffusion. In contrast to this, cold work hardening at low depth below the surface, e. g. by means of a blasting processes, may facilitate formation of a good bond and help to limit grain size. For oxide dispersion‐strengthened materials, additional impacts on diffusion bonding behavior applies.     

Poly(L-lysine)-poly(ethylene glycol) layers with different structure and their influence on silica suspension stability

The effects of the structure of di- and triblock copolymers of poly(L-lysine) – LYS with poly(ethylene glycol) – PEG as well as the length of nonionic fragment in the LYS-PEG macromolecule on the copolymer chains conformation in the adsorption layer formed on the colloidal silica (SiO2) surface were examined. Spectrophotometry and turbidimetry were applied for the determination of copolymer adsorbed amounts and stability coefficients of silica aqueous suspensions. The electrokinetic parameters such as solid surface charge density and zeta potential were also estimated. The adsorption of LYS-PEG was proved to be the highest at pH 10 whereas the lowest adsorption on the solid surface was found for the triblock copolymer with long fragments of LYS at the same pH value.     

New version of continuous–discrete cubature Kalman filtering for nonlinear continuous–discrete systems

For nonlinear continuous–discrete systems, this paper elaborates a new accurate implementation of continuous–discrete cubature Kalman filter (CD-CKF). As the main contribution of this work, the new Kalman prediction stage begins by integrating the nonlinear continuous model for all the cubature sample vectors; the prior estimate state and covariance prediction are based on the weighted statistics of these integrated cubature sample vectors and the Gauss–Legendre approximation scheme. The new square root form CD-CKF is also derived and accurately implemented by combining with the modified variable stepsize NIRK. As the advantages of proposed approach, the complicated and error-prone processes of solving covariance differential equation or calculating derivatives are avoided, while the positive semi-definiteness of prior error covariance are numerically guaranteed. Simulations of traffic control scenarios further confirm the new approach’s superior filtering performance in both reliability and accuracy.     

Individual-based multi-objective optimal structured treatment interruption for HIV infection

In this paper, based on the measurable quantities from an individual patient that has infection to human immunodeficiency virus (HIV) and his/her condition is near to acquired immune deficiency syndrome (AIDS), individual-based multi-objective optimal treatments have been proposed. Firstly, the most effective parameters of the patient in computing Long-term non-progressor (LTNP) equilibrium are derived using global sensitivity analysis (GSA). To accomplish GSA effectively, Latin hypercube sampling (LHS) and partial rank correlation coefficients (PRCC) are utilized to rank each of the parameters based on each state of the 5-dimensional model. Then, these results are used by Dempster–Shafer (D–S) evidence theory (DSET) to rank the most effective parameters comprehensively. Now, these effective identified parameters are estimated using extended Kalman filter (EKF), which its covariance matrices are optimized based on particle swarm optimization (PSO) algorithm. Thus, the proposed methodology gives a calibrated model corresponding to the individual patient. Based on this calibrated model, the LTNP equilibrium related to the individual patient is derived. Using the derived individual-based LTNP equilibrium optimal structured treatment interruption (STI) strategies are extracted by defining suitable multi-objective optimization problem and solving it through using non-dominated sorting genetic algorithm-II (NSGA-II). The results demonstrate that the proposed optimal treatments are able to effectively reach LTNP equilibrium with using the minimum and maximum drug usage of 3.6% and 35.1% of full drug usage treatment. Meanwhile, the different optimal treatments give the decision-makers enough flexibility to choose the suitable treatment based on existing facilities and necessities.     

Indoor boundary layer chemistry modeling

Ozone (O₃) chemistry is thought to dominate the oxidation of indoor surfaces. We consider the hypothesis that reactions taking place within indoor boundary layers result in greater than anticipated hydroxyl radical (OH) deposition rates. We develop models that account for boundary layer mass‐transfer phenomena, O₃‐terpene chemistry and OH formation, removal, and deposition; we solve these analytically and by applying numerical methods. For an O₃‐limonene system, we find that OH flux to a surface with an O₃ reaction probability of 10^?8 is 4.3 × 10^?5 molec/(cm² s) which is about 10 times greater than predicted by a traditional boundary layer theory. At very low air exchange rates the OH surface flux can be as much as 10% of that for O₃. This effect becomes less pronounced for more O₃‐reactive surfaces. Turbulence intensity does not strongly influence the OH concentration gradient except for surfaces with an O₃ reaction probability >10^?4. Although the O₃ flux dominates OH flux under most conditions, OH flux can be responsible for as much as 10% of total oxidant uptake to otherwise low‐reactivity surfaces. Further, OH chemistry differs from that for ozone; therefore, its deposition is important in understanding the chemical evolution of some indoor surfaces and surface films.     

正电子湮没研究Al、Nb共掺CaCu3Ti4O12陶瓷高介电常数机理

关于CaCu₃Ti₄O₁₂陶瓷的高介电常数机理，目前广泛接受的是非本征的内阻挡层电容模型。该模型认为在多晶中元素变价、缺陷和非化学计量比等导致的半导化晶粒被绝缘晶界层，即内阻挡层所包围。其中内阻挡层的厚度对材料的介电性能影响较大，而扫描电子显微镜（SEM）测试表明样品晶界呈稀烂的果酱状，SEM难以测量晶界区域绝缘内阻挡层厚度。本文采用正电子湮没技术表征其厚度，通过对CaCu₃Ti₄O₁₂陶瓷共掺不同浓度的Al、Nb（CaCu₃Ti_4-xAl_0.5xNb_0.5xO₁₂，x=0.2%、0.5%、5.0%）改变其晶粒和晶界的微观结构，研究CaCu₃Ti₄O₁₂陶瓷高介电常数机理。正电子湮没结果显示，掺杂样品符合多普勒展宽谱S参数的变化趋势与平均寿命的变化趋势一致。x=0.5%掺杂样品的介电常数最高，其平均寿命、S参数和湮没长寿命成分均最小，阻挡层最薄。实验结果验证了描述CaCu₃Ti₄O₁₂陶瓷高介电常数机理的内阻挡层电容模型的预测。     

Hierarchical sampling optimization of particle filter for global robot localization in pervasive network environment

This paper presents a hierarchical framework for managing the sampling distribution of a particle filter (PF) that estimates the global positions of mobile robots in a large‐scale area. The key concept is to gradually improve the accuracy of the global localization by fusing sensor information with different characteristics. The sensor observations are the received signal strength indications (RSSIs) of Wi‐Fi devices as network facilities and the range of a laser scanner. First, the RSSI data used for determining certain global areas within which the robot is located are represented as RSSI bins. In addition, the results of the RSSI bins contain the uncertainty of localization, which is utilized for calculating the optimal sampling size of the PF to cover the regions of the RSSI bins. The range data are then used to estimate the precise position of the robot in the regions of the RSSI bins using the core process of the PF. The experimental results demonstrate superior performance compared with other approaches in terms of the success rate of the global localization and the amount of computation for managing the optimal sampling size.     

Multi-objective iterative optimization algorithm based optimal wavelet filter selection for multi-fault diagnosis of rolling element bearings

Rolling element bearings (REBs) play an essential role in modern machinery and their condition monitoring is significant in predictive maintenance. Due to the harsh operating conditions, multi-fault may co-exist in one bearing and vibration signal always exhibits low signal-to-noise ratio (SNR), which causes difficulties in detecting fault. In the previous studies, maximum correlated kurtosis deconvolution (MCKD) has been validated as an efficient method to extract fault feature in the fault signals. Nonetheless, there are still some challenges when MCKD is applied to fault detection owing to the rigorous requirements of multiple input parameters. To overcome limitation, a multi-objective iterative optimization algorithm (MOIOA) for multi-fault diagnosis is proposed. In this method, correlated kurtosis (CK) is taken as a criterion to select optimal Morlet wavelet filter using the whale optimization algorithm (WOA). Meanwhile, to further eliminate the effect of the inaccurate period on CK, the update process of period is incorporated. After that, the simulated and experimental signals are utilized to testify the validity and superiority of the MOIOA for multiple faults detection by the comparison with MCKD. The results indicate that MOIOA is efficient to extract weak fault features even with heavy noise and harmonic interferences.     

On‐site wastewater treatment using reactive filter media

The aim of this study is to reduce the phosphate concentration in treated wastewater using a small amount of the reactive filter media, Filtralite P. Biologically treated wastewater was passed through a filter with 215 g of Filtralite P. In the laboratory, the phosphate removal efficiency was 51% at a flow speed of 0.87 m/h. Under real conditions, in an experimental stand filled with 0.5 m³ of Filtralite P, the phosphate removal efficiency was 85% and the removal efficiency of total suspended solids was 57% after a 5‐month period. The residual phosphate concentration in the filtrate from the experimental stand was 1 mg/L of PO₄‐P after the 5‐month period. The experimental filtration plant was buried in the ground, and it did not freeze and worked well under winter conditions. The results of this study can be useful in the design and development of tertiary wastewater treatment plants in view of their sustainability potential.     

DCNN深度特征与交替方向乘子的相关滤波跟踪

针对采用相关滤波的判别式目标跟踪遇到的瓶颈问题：由于目标快速移动引起边界效应，使得相关滤波器在学习与更新过程中可能会引入错误，最终错误的累积将导致跟踪失败。在采集深度学习特征与样本相似性度量的基础上，提出一种引入交替方向乘子方法的改进相关滤波目标跟踪算法，选择DCNN深度特征有效地表征待跟踪目标的初始状态，通过在线分类过程中样本相似性比对与半监督学习，辅助解决相关滤波器在学习过程中存在的自学习问题。所提目标跟踪算法特别适合训练样本为持续获得的、同时存储空间较小的机器学习过程，提高目标在快速运动与部分遮挡等复杂情况下的跟踪成功率，针对VOT2016标准测试视频的实验表明：当目标面临快速运动时，对比CN、SAMF、STC算法，所提DA-CFT跟踪算法将跟踪成功率分别由60.4%～73.4%、67.2%～82.9%、80.9%～88.1%提升至85.6%～91.0%。