冷低压分离器油相系统铵盐垢下腐蚀风险的模拟预测

为探究某加氢装置高压换热器管束腐蚀泄漏原因，利用Aspen Plus工艺模拟软件计算了冷低压分离器油相（简称冷低分油）中水质量分数分别为1%,2%,3%时，冷低分油系统的露点温度、氯化铵结晶温度、氯化铵潮解点温度和相对湿度。结果表明：相较于经验的露点温度预测方法，通过引入潮解点、划分系统“湿环境”温度范围判断氯化铵垢下腐蚀风险区域的方法与实际腐蚀案例更为切合；在3种油相含水条件下，换热器管束存在氯化铵垢下腐蚀的“湿环境”温度范围分别为：50~103 ℃,50~161 ℃,50~176 ℃；随着油相中含水量的提高，“湿环境”腐蚀区域逐渐向高温部位迁移，预计铵盐导致的垢下腐蚀将会愈加严重。     

Prelabeling Expansion Single-Molecule Localization Microscopy with Minimal Linkage Error

Expansion microscopy combined with single-molecule localization microscopy (ExSMLM) has a potential for approaching molecular resolution. However, ExSMLM faces multiple challenges such as loss of fluorophores and proteins during polymerization, digestion or denaturation, and an increase in linkage error arising from the distance between the fluorophore and the target molecule. Here, we introduce a trifunctional streptavidin to link the target, fluorophore and gel matrix via a biotinylizable peptide tag. The resultant ExSMLM images of vimentin filaments demonstrated high labeling efficiency and a minimal linkage error of ∼5 nm. Our ExSMLM provides a simple and practical means for fluorescence imaging with molecular resolution.     

SRS: Spatial-tagged radio-mapping system combining LiDAR and mobile-phone data for indoor location-based services

One of the most challenging issues in radio received signal strength (RSS)-based localization systems is the generation and distribution of a radio map with a coordinate system linked with spatial information in a large indoor space. This study proposes a novel spatial-tagged radio-mapping system (SRS) that effectively combines the heterogeneous properties of LiDAR and mobile phones to simultaneously perform both spatial and radio mappings. The SRS consists of synchronization, localization, and map building processes, and enables real-time spatial and radio mapping. In the synchronization process, the distance range, motion data, and radio signals obtained through the LiDAR and mobile phone are collected in nodal units according to the sensing time. In the localization process, a feature variance filter is used to control the number of features generated from LiDAR and estimate the positions at which the nodes are generated in real time according to the motion data and radio signals. In map building, the estimated positions of the nodes are used to extract spatial and radio maps by using a unified location coordinate system. To ensure mobility, the SRS is manufactured in the form of a backpack supporting LiDAR and a mobile phone; the usefulness of the system is experimentally verified. The experiments are performed in a large indoor shopping mall with a complex structure. The experimental results demonstrated that a common coordinate system could be used to build spatial and radio maps with high accuracy and efficiency in real time. In addition, the field applicability of the SRS to location-based services is experimentally verified by applying the constructed radio map to well-known fingerprinting algorithms using the heterogeneous mobile phones.     

Designing amorphous formulations of polyphenols with naringin by spray-drying for enhanced solubility and permeability

Naringin (NAR), a major flavanone (FVA) glycoside, is a component of food mainly obtained from grapefruit. We used NAR as a food additive to improve the solubility and permeability of hydrophobic polyphenols used as supplements in the food industry. The spray-dried particles (SDPs) of NAR alone show an amorphous state with a glass transition temperature (T_g) at 93.2 °C. SDPs of hydrophobic polyphenols, such as flavone (FVO), quercetin (QCT), naringenin (NRG), and resveratrol (RVT) were prepared by adding varying amounts of NAR. All SDPs of hydrophobic polyphenols with added NAR were in an amorphous state with a single T_g, but SDPs of hydrophobic polyphenols without added NAR showed diffraction peaks derived from each crystal. The SDPs with NAR could keep an amorphous state after storage at a high humidity condition for one month, except for SDPs of RVT/NAR. SDPs with NAR enhanced the solubility of hydrophobic polyphenols, especially NRG solubility, which was enhanced more than 9 times compared to NRG crystal. The enhanced solubility resulted in the increased membrane permeability of NRG. The antioxidant effect of the hydrophobic NRG was also enhanced by the synergetic effect of NAR. The findings demonstrated that NAR could be used as a food additive to enhance the solubility and membrane permeability of hydrophobic polyphenols.     

Comparison of γ-aminobutyric acid accumulation capability in different mung bean (Vigna radiata L.) varieties under heat and relative humidity treatment,and its correlation with endogenous amino acids and polyamines

In this study, the accumulation of GABA and its inherent factors across different varieties of mung bean (Vigna radiata L.) in response to heat and relative humidity (HRH) were investigated. Results showed the average GABA content in mung bean varieties was increased 7.52 times following HRH treatment, and the black mung bean variety (A8) exhibited the highest GABA accumulation capability (1.76–84.57 mg per 100 g DW). From the perspective of GABA shunt metabolites, the free glutamic acid content of mung beans significantly decreased (P < 0.05) after HRH treatment and presented a significant correlation (P < 0.05) with GABA content. In polyamine degradation pathway, although the average levels of spermine and spermidine of mung bean varieties significantly decreased (P < 0.05) after HRH treatment, no significant correlation with GABA content was identified. Hence, the GABA accumulation was predominantly attributed to GABA shunt. Besides, free amino acids including glutamic acid, serine, ornithine, arginine and glycine in mung beans showed a significant positive correlation (P < 0.05) with GABA content and increment following HRH treatment, which suggested that mung beans enriched in these free amino acids might accumulate higher amounts of GABA after HRH treatment and be useful for industrial applications.     

基于多边限定的室内定位方法设计与系统实现

随着基于位置服务（Location Based Services，LBS）的发展与智能移动设备的普及，室内定位算法与系统受到了广泛研究与关注。为提高室内定位精度、增强系统鲁棒性，提出了基于多边限定的fingerprint定位方法。基于Wi-Fi RSSI（Received Signal Strength Indication）信号处理建立离线fingerprint数据库；通过对拟合距离-RSSI函数分析，提出了多边限定的方法确定一个最佳参考点（Reference Point，RP）集合，缩小在线定位阶段的搜索范围。在此基础上，再利用fingerprint定位方法进行定位。此外，实现了基于提出方法的室内定位系统原型用于算法性能评估。通过大量真实场景实验分析、验证了相较于传统fingerprint方法，基于多边限定的fingerprint定位方法能有效提高室内定位精度，增强系统鲁棒性。     

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.     

翅片结构对单向开缝翅片管换热器传热与阻力性能的影响

通过对不同开缝数量、不同相对开缝高度的单向开缝翅片管换热器进行模拟,分析开缝数量、相对开缝高度对单向开缝翅片管换热器传热与阻力性能的影响规律。结果表明:在开缝数量为3～7片时,翅片侧Nu和f因子随着开缝数量的增加而增大,但Nu增幅逐渐减小;将开缝的数量取为5片能得到最好的综合性能;在相对开缝高度为0.3～0.7时,翅片侧Nu和f因子随着相对开缝高度的增加而增大,但当相对开缝高度在0.5～0.7范围内,翅片侧Nu的增幅减小;将相对开缝高度取为0.5能得到最好的综合性能。     

A volume element model (VEM) for energy systems engineering

This work presents a simplified modeling and simulation approach for energy systems engineering that is capable of providing quick and accurate responses during system design. For that, the laws of conservation are combined with available empirical and theoretical correlations to quantify the diverse types of flows that cross the system and produce a simplified tridimensional mathematical model, namely a volume element model (VEM). The physical domain of interest is discretized in space, thus producing a system of algebraic and ODEs with respect to time, whose solution delivers the project variables spatial distribution and dynamic response. In order to illustrate the application of the VEM in energy systems engineering, three example problems are considered: (i) a regenerative heat exchanger; (ii) a power electronic building block (PEBB); and (iii) a notional all‐electric ship. The same mathematical model was used to analyze problems (ii) and (iii), that is, the thermal management of heat‐generating equipment packaging. In the examples, the converged mesh had a total of 20, 2000, and 7725 volume elements. The third problem led to the largest simulation, which for steady‐state cases took between 5 and 10 min of computational time to reach convergence and for the ship dynamic response 50 min (i.e., 80,000 s of real time). The regenerative heat exchanger model demonstrated how VEM allowed for the coexistence of different phases (subsystems) within the same volume element. The thermal management model was adjusted and experimentally validated for the PEBB system, and it was possible to perform a parametric and dynamic analysis of the PEBB and of the notional all‐electric ship. Therefore, because of the observed combination of accuracy and low computational time, it is expected that the model could be used as an efficient tool for design, control, and optimization in energy systems engineering. Copyright © 2014 John Wiley & Sons, Ltd.     

基于人工智能算法的投诉用户质差小区定位及预测的方法研究

目前LTE及GSM的质差小区投诉定位主要是依靠用户投诉的地址回放分析附近小区是否存在性能、告警上的裂变,如无则安排人员现场测试信号强度、干扰等。为了解决自动定位投诉质差小区,创新性提出以数据驱动来实现业务规则自动化,充分考虑用户投诉的时间和问题、网络交互信令、无线性能指标和告警等海量数据,运用人工智能技术中的逻辑回归及决策树算法训练出“2G语音、VoLTE语音及数据业务的投诉质差小区定界模型、质差小区预测模型及问题网元”,更快速,更智能,更准确输出语音及数据业务投诉原因、质差小区及质差原因,并对潜在质差小区进行预测,对无线规划、基站建设、故障处理、网络改造等方面的工作也具有积极指导意义。