Theoretical estimation of dielectric loss of oxide glasses using nonequilibrium molecular dynamics simulations

To theoretically explore amorphous materials with a sufficiently low dielectric loss, which are essential for next-generation communication devices, the applicability of a nonequilibrium molecular dynamics simulation employing an external alternating electric field was examined using alkaline silicate glass models. In this method, the dielectric loss is directly evaluated as the phase shift of the dipole moment from the applied electric field. This method enabled us to evaluate the dielectric loss in a wide frequency range from 1 GHz to 10 THz. It was observed that the dielectric loss reaches its maximum at a few THz. The simulation method was found to qualitatively reproduce the effects of alkaline content and alkaline type on the dielectric loss. Furthermore, it reasonably reproduced the effect of mixed alkalines on the dielectric loss, which was observed in our experiments on sodium and/or potassium silicate glasses. Alkaline mixing was thus found to reduce the dielectric loss.     

Preparation of Pt/Ce–Zr–Y mixed oxide/anodized aluminium oxide catalysts for hydrogen passive autocatalytic recombination

The use of a Pt-based catalyst was evaluated for autocatalytic hydrogen recombination. The Pt was supported on a mixture of Ce-, Zr- and Y-oxides (CZY) to yield nanosized Pt particles. The Pt/CZY/AAO catalyst was then prepared by the spray-deposition of the Pt/CZY intermediate onto an anodized aluminium oxide (AAO) layer on a metallic aluminum core. The Pt/CZY/AAO catalyst (3 × 1 cm) was evaluated for hydrogen combustion (1–8 vol% hydrogen in the air) in a recombiner section testing station. The thermal distribution throughout the catalyst surface was investigated using an infrared camera. The maximum temperature gradient (ΔT) for the examined hydrogen concentrations did not exceed 36 °C. The Pt/CZY/AAO catalyst was also evaluated for prolonged hydrogen combustion duration to assess its durability. An average combustion temperature of 239.0 ± 10.0 °C was maintained for 53 days of catalytic hydrogen combustion, suggesting that there was limited, or no, catalyst deactivation. Finally, a Pt/CZY/AAO catalytic plate (14.0 × 4.5 cm) was prepared to investigate the thermal distribution. An average surface temperature of 212.5 °C and a maximum ΔT of 5.4 °C was obtained throughout the catalyst surface at a 3 vol% hydrogen concentration.     

自适应融合层级特征的混合退化图像复原算法

多种退化类型混合的图像比单一类型的退化图像降质更严重,很难建立精确模型对其复原,研究端到端的神经网络算法是复原的关键.现有的基于操作选择注意力网络的算法(operation-wiseattentionnetwork,OWAN)虽然有一定的性能提升,但是其网络过于复杂,运行较慢,复原图像缺乏高频细节,整体效果也有提升的空间.针对这些问题,提出一种基于层级特征融合的自适应复原算法.该算法直接融合不同感受野分支的特征,增强复原图像的结构;用注意力机制对不同层级的特征进行动态融合,增加模型的自适应性,降低了模型冗余;另外,结合L1损失和感知损失,增强了复原图像的视觉感知效果.在DIV2K,BSD500等数据集上的实验结果表明,该算法无论是在峰值信噪比和结构相似性上的定量分析,还是在主观视觉质量方面,均优于OWAN算法,充分证明了该算法的有效性.     

硫磷混合酸溶样重铬酸钾容量法测定全铁

介绍了硫磷混合酸溶样重铬酸钾容量法测定矿石中铁含量的方法和步骤。重点讨论了一线生产中的质量控制。     

Evolutionary collective behavior decomposition model for time series data mining

In this research, we propose a novel framework referred to as collective game behavior decomposition where complex collective behavior is assumed to be generated by aggregation of several groups of agents following different strategies and complexity emerges from collaboration and competition of individuals. The strategy of an agent is modeled by certain simple game theory models with limited information. Genetic algorithms are used to obtain the optimal collective behavior decomposition based on history data. The trained model can be used for collective behavior prediction. For modeling individual behavior, two simple games, the minority game and mixed game are investigated in experiments on the real-world stock prices and foreign-exchange rate. Experimental results are presented to show the effectiveness of the new proposed model.     

A case-deletion diagnostic for penalized calibration estimators and BLUP under linear mixed models in survey sampling

The penalized calibration technique in survey sampling combines usual calibration and soft calibration by introducing a penalty term. Certain relevant estimates in survey sampling can be considered as penalized calibration estimates obtained as particular cases from an optimization problem with a common basic structure. In this framework, a case deletion diagnostic is proposed for a class of penalized calibration estimators including both design-based and model-based estimators. The diagnostic compares finite population parameter estimates and can be calculated from quantities related to the full data set. The resulting diagnostic is a function of the residual and leverage, as other diagnostics in regression models, and of the calibration weight, a singular feature in survey sampling. Moreover, a particular case, which includes the basic unit level model for small area estimation, is considered. Both a real and an artificial example are included to illustrate the diagnostic proposed. The results obtained clearly show that the proposed diagnostic depends on the calibration and soft-calibration variables, on the penalization term, as well as on the parameter to estimate.     

管式段塞流捕集器构造及其优化设计

天然气近年来由于技术的进步及其自身多项优势而被广泛利用,油气混输作为一种经济性良好的运输方式也开始服务于各大油气田。然而多相流的运动很复杂,加上一些其他因素而产生的段塞流则是危害较大,其主要危害体现在各项参数不稳,混输管路下游的处理设备会受到较大冲击,因此需要在混输管路末端设置段塞流捕集器来缓解这种冲击,保证下游的稳定供给。     

An engineering method for complex structural optimization involving both size and topology design variables

This work presents an engineering method for optimizing structures made of bars, beams, plates, or a combination of those components. Corresponding problems involve both continuous (size) and discrete (topology) variables. Using a branched multipoint approximate function, which involves such mixed variables, a series of sequential approximate problems are constructed to make the primal problem explicit. To solve the approximate problems, genetic algorithm (GA) is utilized to optimize discrete variables, and when calculating individual fitness values in GA, a second-level approximate problem only involving retained continuous variables is built to optimize continuous variables. The solution to the second-level approximate problem can be easily obtained with dual methods. Structural analyses are only needed before improving the branched approximate functions in the iteration cycles. The method aims at optimal design of discrete structures consisting of bars, beams, plates, or other components. Numerical examples are given to illustrate its effectiveness, including frame topology optimization, layout optimization of stiffeners modeled with beams or shells, concurrent layout optimization of beam and shell components, and an application in a microsatellite structure. Optimization results show that the number of structural analyses is dramatically decreased when compared with pure GA while even comparable to pure sizing optimization.     

Development of mobile miniature natural gas liquefiers

With increasing consumption of natural gas (NG), small NG reservoirs, such as coalbed methane and oil field associated gas, have recently drawn significant attention. Owing to their special characteristics (e.g., scattered distribution and small output), small-scale NG liquefiers are highly required. Similarly, the mixed refrigerant cycle (MRC) is suitable for small-scale liquefaction systems due to its moderate complexity and power consumption. In consideration of the above, this paper reviews the development of mobile miniature NG liquefiers in Technical Institute of Physics and Chemistry (TIPC), China. To effectively liquefy the scattered NG and overcome the drawbacks of existing technologies, three main improvements, i.e., low-pressure MRC process driven by oil-lubricated screw compressor, compact cold box with the new designed heat exchangers, and standardized equipment manufacturing and integrated process technology have been made. The development pattern of “rapid cluster application and flexible liquefaction center” has been eventually proposed. The small-scale NG liquefier developed by TIPC has reached a minimum liquefaction power consumption of about 0.35 kW·h/Nm³. It is suitable to exploit small remote gas reserves which can also be used in boil-off gas reliquefaction and distributed peak-shaving of pipe networks.     

Group sequential crossover trial designs with strong control of the familywise error rate

Crossover designs are an extremely useful tool to investigators, and group sequential methods have proven highly proficient at improving the efficiency of parallel group trials. Yet, group sequential methods and crossover designs have rarely been paired together. One possible explanation for this could be the absence of a formal proof of how to strongly control the familywise error rate in the case when multiple comparisons will be made. Here, we provide this proof, valid for any number of initial experimental treatments and any number of stages, when results are analyzed using a linear mixed model. We then establish formulae for the expected sample size and expected number of observations of such a trial, given any choice of stopping boundaries. Finally, utilizing the four-treatment, four-period TOMADO trial as an example, we demonstrate that group sequential methods in this setting could have reduced the trials expected number of observations under the global null hypothesis by over 33%.