锂电池用SnO基复合氧化物负极材料的研究

将SnCl2、FeCl2及CuCl2按一定比例进行混合并水解，得到Sn基氧化物与其他惰性材料（FeO,CuO）的混合物，将其在还原性气氛（Ar96% H24%）中进行热处理，以获得具有高容量及更好的循环性能的负极材料。研究结果表明：热处理温度对首次循环的库仑效率影响不大，但对循环稳定性有明显影响。复合材料电极的可逆容量起过381mAh/g。Sn-Fe体系在400℃热处理2h，获得的材料具有优异的循环稳定性，但首次循环的库仑效率仅24．91％。     

A Composite Likelihood Approach to Multivariate Survival Data

This paper is about the statistical analysis of multivariate survival data. We discuss the additive and multiplicative frailty models which have been the most popular models for multivariate survival data. As an alternative to the additive and multiplicative frailty models, we propose basing inference on a composite likelihood function that only requires modelling of the marginal distribution of pairs of failure times. Each marginal distribution of a pair of failure times is here assumed to follow a shared frailty model. The method is illustrated with a real-life example.     

频带分析方法在我国景气周期波动中的应用

摘　　要:本文介绍了国外最近提出的基于频带分析的景气指标选择方法。本文首先利用带通滤波分离出我国实际GDP增长率的循环要素并把它作为基准指标,然后利用文中介绍的频带分析方法选择一致指标。在选择一致指标时发现,利用频带分析方法选择的固定资产投资指标,在时域上却未被入选。这表明选择指标时频带选择方法比时域选择方法选择范围更广。本文还分别基于频带方法和时域方法构造一致合成指数,这两者都能够较好地拟合GDP增长率的波动情况,但使用频带方法得到的结果略好一些     

Technology selection in the absence of standardised materials and processes: a survey in the UK composite materials supply chain

Composite materials is an industry where technology selection has major consequences as there is not a standard manufacturing process, nor are there standardised materials with defined or proscribed properties for companies to select as multiple solutions are technically viable. This research aims to identify key factors for manufacturing technology selection in the UK composite materials supply chain. Literature review and managers’ opinions were used to identify 18 factors affecting manufacturing technology selection. This was followed by a survey comprising the multi-tier supply chain of the composite materials industry. The results of the survey show ‘on time deliveries/service level to customers’, ‘improve quality’ and ‘reduce cycle time’ received the highest average ratings. In this study a correlation analysis was performed to identify the underlying dependencies between the factors investigated. The identification and use of underlying dependencies rather than highest average provided a more comprehensive picture of the factors that affect technology selection in the composite materials industry. For this study, experts in composite materials were asked to comment on the findings of the survey and their value to the industry. The results presented may assist companies in the composite materials industry with technology selection decision-making processes.     

Integrative Analysis of Cancer Diagnosis Studies with Composite Penalization

In cancer diagnosis studies, high‐throughput gene profiling has been extensively conducted, searching for genes whose expressions may serve as markers. Data generated from such studies have the ‘large d, small n’ feature, with the number of genes profiled much larger than the sample size. Penalization has been extensively adopted for simultaneous estimation and marker selection. Because of small sample sizes, markers identified from the analysis of single data sets can be unsatisfactory. A cost‐effective remedy is to conduct integrative analysis of multiple heterogeneous data sets. In this article, we investigate composite penalization methods for estimation and marker selection in integrative analysis. The proposed methods use the minimax concave penalty (MCP) as the outer penalty. Under the homogeneity model, the ridge penalty is adopted as the inner penalty. Under the heterogeneity model, the Lasso penalty and MCP are adopted as the inner penalty. Effective computational algorithms based on coordinate descent are developed. Numerical studies, including simulation and analysis of practical cancer data sets, show satisfactory performance of the proposed methods.     

Empirical likelihood weighted composite quantile regression with partially missing covariates

This paper develops a novel weighted composite quantile regression (CQR) method for estimation of a linear model when some covariates are missing at random and the probability for missingness mechanism can be modelled parametrically. By incorporating the unbiased estimating equations of incomplete data into empirical likelihood (EL), we obtain the EL-based weights, and then re-adjust the inverse probability weighted CQR for estimating the vector of regression coefficients. Theoretical results show that the proposed method can achieve semiparametric efficiency if the selection probability function is correctly specified, therefore the EL weighted CQR is more efficient than the inverse probability weighted CQR. Besides, our algorithm is computationally simple and easy to implement. Simulation studies are conducted to examine the finite sample performance of the proposed procedures. Finally, we apply the new method to analyse the US news College data.     

The Stability of Rankings Derived From Composite Indicators: Analysis of the “IL Sole 24 Ore” Quality of Life Report

The calculation of composite indicators and the derivation of respective rankings is a common method used to benchmark countries or regions. However, although the statistical robustness of these rankings is often criticised, they often still spark off heated political debate. Here, we assess the sensitivity of the province ranking published by the Italian economics newspaper “Il Sole 24 Ore”. For this purpose, various weighting, normalising and aggregation schemes were compared. Furthermore, to assess the accuracy of the underlying model, confidence intervals were calculated for the indicator values. The dynamic properties of the rankings were also analysed by evaluating the short- and long-term forecast properties of the rankings.     

Hamacher算子在模糊评价中的应用方法

模糊合成算子是模糊评价中数据处理的核心技术。目前模糊合成算子在模糊评价中应用时比较混乱,没有一般方法。原因之一是Zadeh的模糊集理论存在缺陷,另一方面是对算子性质研究挖掘不够。需要研究不同的模糊算子在模糊评价中的使用方法。Hamacher算子是参数算子,含参γ在[1,+∞)时有对参数变量和数据变量的多重单调性,它的清晰域不随参数变化而改变,并且清晰域最小。模糊评价中的数据起到至关重要作用,分析模糊与算子的清晰域,确定数据点与清晰域的从属关系,提出基于清晰域与数据分布的Hamacher算子的应用方法,通过实例验证其合理、有效性。     

考虑剪滞剪切效应的复合材料薄壁箱型连续梁理论分析

以含三次项的四次抛物线作为箱梁翼缘板的纵向位移函数,推导出了考虑横向剪切变形及剪力滞后效应时的双轴对称铺设的复合材料层合箱梁在对称弯曲条件下的控制微分方程,并推导出了两等跨连续梁分别在跨中受一集中力P的位移差函数,最后结合具体的复合材料箱型连续梁实例,将本文理论推导的结果与ANSYS结果以及实验结果进行了对比,结果表明,理论推导的结果与ANSYS结果和实验结果吻合较好,其结果是正确可靠的。     

纤维增强复合材料弹性常数测定的平面声波相速法研究

本文把纤维增强复合材料视为宏观均匀正交各向异性物体,应用平面声波的Christoffel方程求出平面声波的相速度与各弹性常数之间的关系式,若以实验方法测得平面声波的相速度,则可用这些关系式求出各弹性常数。作者根据这个原理,用实验方法测定了钢、玻璃钢、玻璃纤维——环氧、碳纤维——环氧四种材料的弹性常数,并与共振法进行比较。文末提出了此方法的某些特点,以及改进实验的设想。