PMMA／PBA乳胶IPN阻尼材料的研究

用乳液聚合方法合成了一系列的互穿聚合物网络，其中包括：ＰＭＭＡ／ＰＢＡ和Ｐ（ＭＭＡ－ｃｏ－ＰＭＡ）／ＰＢＡ乳胶互穿聚合物网络（ＬＩＰＮ），ＰＭＭＡ／ＰＢＡ乳胶双向互穿聚合物网络（ＬＢＩＰＮ）以及ＰＭＭＡ／ＰＢＡ界面交联互穿聚合物网络（ＩＣＬＩＰＮ）。动态力学谱和拉伸试验结果表明：（１）ＰＭＭＡ／ＰＢＡ互穿聚合物网络的两组分相容性和阻尼性能可通过ＭＭＡ和ＰＭＡ共聚来改善；（２）双向互穿技术是一种行之     

Activities of MFI-Supported Rhenium Catalysts for the Aromatization of Methane: Effect of Cationic Form of the Inorganic Carrier

MFI type inorganic carrier was used in two different cationic forms, hydrogen and calcium respectively. MFI-supported molybdenum and rhenium catalysts were prepared. The activities of the catalysts were compared for the aromatization reaction of methane. Higher activity values were attained with the catalysts supported on HZSM-5. Aromatics were also observed with the catalysts supported on CaZSM-5, despite their deficiency in acid sites. Highly dispersed rhenium is expected to be formed with the use of the inorganic carrier in calcium form. On the other hand, lower reaction rates were observed with rhenium supported on CaZSM-5, in spite of the improved dispersion of the active rhenium species on this catalyst. This was interpreted in terms of the critical role of the acid sites in the conversion of methane to aromatics, compared to the improved dispersion of the active metal.     

LoVis: Local Pattern Visualization for Model Refinement

Linear models are commonly used to identify trends in data. While it is an easy task to build linear models using pre‐selected variables, it is challenging to select the best variables from a large number of alternatives. Most metrics for selecting variables are global in nature, and thus not useful for identifying local patterns. In this work, we present an integrated framework with visual representations that allows the user to incrementally build and verify models in three model spaces that support local pattern discovery and summarization: model complementarity, model diversity, and model representivity. Visual representations are designed and implemented for each of the model spaces. Our visualizations enable the discovery of complementary variables, i.e., those that perform well in modeling different subsets of data points. They also support the isolation of local models based on a diversity measure. Furthermore, the system integrates a hierarchical representation to identify the outlier local trends and the local trends that share similar directions in the model space. A case study on financial risk analysis is discussed, followed by a user study.     

Efficacy of iron fortification compared to iron supplementation among Vietnamese schoolchildren

Background  

Parents of six children are facing a trial on charges of aggravated manslaughter in the care a 5 1/2 month old infant who died suddenly and neglect of their four older children for causing them to be malnourished by feeding them all an exclusively raw foods vegan diet. Both parents declined plea bargains and plan to defend themselves in court.     

Interleaving Guidance in Evolutionary Multi-Objective Optimization

In this paper, we propose a framework that uses localization for multi-objective optimization to simultaneously guide an evolutionary algorithm in both the decision and objective spaces. The localization is built using a limited number of adaptive spheres （local models） in the decision space. These spheres axe usually guided, using some direction information, in the decision space towards the areas with non-dominated solutions. We use a second mechanism to adjust the spheres to specialize on different parts of the Paxeto front by using a guided dominance technique in the objective space. Through this interleaved guidance in both spaces, the spheres will be guided towards different parts of the Paxeto front while also exploring the decision space efficiently. The experimental results showed good performance for the local models using this dual guidance, in comparison with their original version.     

Applying Wide & Deep Learning Model for Android Malware Classification

Android malware has exploded in popularity in recent years, due to the platform’s dominance of the mobile market. With the advancement of deep learning technology, numerous deep learning-based works have been proposed for the classification of Android malware. Deep learning technology is designed to handle a large amount of raw and continuous data, such as image content data. However, it is incompatible with discrete features, i.e., features gathered from multiple sources. Furthermore, if the feature set is already well-extracted and sparsely distributed, this technology is less effective than traditional machine learning. On the other hand, a wide learning model can expand the feature set to enhance the classification accuracy. To maximize the benefits of both methods, this study proposes combining the components of deep learning based on multi-branch CNNs (Convolutional Network Neural) with wide learning method. The feature set is evaluated and dynamically partitioned according to its meaning and generalizability to subsets when used as input to the model’s wide or deep component. The proposed model, partition, and feature set quality are all evaluated using the K-fold cross validation method on a composite dataset with three types of features: API, permission, and raw image. The accuracy with Wide and Deep CNN (WDCNN) model is 98.64%, improved by 1.38% compared to RNN (Recurrent Neural Network) model.     

数据挖掘在CRM中的应用

本文介绍了数据挖掘技术与CRM,在此基础上提出了数据挖掘在CRM中的一些应用,最后对数据挖掘的发展方向及其在CRM中的应用前景作了展望。     

Vapor- and liquid-phase adsorption of alcohol and water in silicalite-1 synthesized in fluoride media

In this work, batch-adsorption experiments and molecular simulations are employed to probe the adsorption of binary mixtures containing ethanol or a linear alkane-1,n-diol solvated in water or ethanol onto silicalite-1. Since the batch-adsorption experiments require an additional relationship to determine the amount of solute (and solvent) adsorbed, as only the bulk liquid reservoir can be probed directly, molecular simulations are used to provide a relationship between solute and solvent adsorption for input to the experimental bulk measurements. The combination of bulk experimental measurements and simulated solute–solvent relationship yields solvent and solute loadings that are self-consistent with simulation alone, and allow for an assessment of the various assumptions made in the literature. At low solution concentrations, the solute loading calculated is independent of the assumption made. At high concentrations, a negligent choice of assumption can lead to systematic overestimation or underestimation of calculated solute loading.     

The APOA5-rs662799 Polymorphism Is a Determinant of Dyslipidemia in Vietnamese Primary School Children

Apolipoprotein A-V encoded by apolipoprotein 5 (APOA5) gene plays an important role in lipid metabolism, especially in the regulation of plasma triglycerol levels. The study aimed to evaluate the association of the APOA5-rs662799 polymorphism with dyslipidemia in Vietnamese children and the potential modification of obesity-related traits (body mass index, waist circumference, hip circumference, and waist-to-hip ratio) on this association. A case–control study was conducted with a total of 154 dyslipidemia cases and 389 controls at the age of 6 to 10 recruited at 31 primary schools in Hanoi city of Vietnam. Genotype for APOA5-rs662799 polymorphism was determined by the restriction fragment length polymorphism analysis. The association of APOA5-rs662799 polymorphism with dyslipidemia adjusting for age, sex, residence, and obesity-related traits was analyzed by binary logistic regression analysis. The results showed that in comparison with T/T and T/C carriers, the C/C carriers had a higher concentration of serum TAG in cases (p =0.049). Carriers of the C allele (C/C + T/C) had higher risk for developing dyslipidemia and hypertriglyceridemia than subjects with T/T genotype (odds ratio, OR = 1.7, p =0.0062 and OR = 1.6, p = 0.026, respectively). The association remained significant after adjusting for age, gender, residence, and obesity status (OR = 1.75, p = 0.006 and OR = 1.53, p = 0.049, respectively) or other obesity-related traits. The study suggested that the APOA5-rs662799 polymorphism may be a determinant of dyslipidemia and hypertriglyceridemia in Vietnamese children, independent of obesity-related traits.     

Interval functional observers for time-delay systems with additive disturbances

This article considers the design of interval functional observers to estimate a linear function of the state vector of time-delay systems subject to both input and output additive disturbances. Two novel functional observers are proposed and designed such that they bound the set of all admissible values of a linear function of the state vector at each instant of time. By contrast to interval observers currently available in the literature, both observers proposed in this article utilize multiple delayed output measurement and have a more general structure. This trade-off feature overcomes some drawbacks in previous work and enables interval functional observers to be designed for a wider class of time-delay systems. Conditions for the existence of interval functional observers are derived and an effective design algorithm for computing unknown observer matrices is provided. Two illustrative examples are given to show the advantages and effectiveness of our design method.