Theoretical investigations of the structural,electronic and optical properties of Hg1−xCdxTe alloys

The structural, electronic and optical properties of mercury cadmium telluride (Hg_1?xCd_xTe; x = 0.0, 0.25, 0.5, 0.75) alloys are studied using density functional theory within full-potential linearized augmented plane wave method. We used the local density approximation (LDA), generalized gradient approximation (GGA), hybrid potentials, the modified Becke–Johnson (LDA/GGA)-mjb and Hubbard-corrected functionals (GGA/LDA + U), for the exchange-correlation potential (E_ex). We found that LDA functional predicts better lattice constants than GGA functional, whereas, both functionals fail to predict the correct electronic structure. However, the hybrid functionals were more successful. For the case of HgTe binary alloy, the GGA + U functional predicted a semi-metallic behaviour with an inverted band gap of ?0.539 eV, which is closest to the experimental value (?0.30 eV). Ternary alloys, however, are found to be semiconductors with direct band gaps. For the x = 0.25 and 0.50, the best band gaps are found to be 0.39 and 0.81 eV using LDA-mbj functional, whereas, the GGA-mbj functional predicted the best band gap of 1.09 eV for Hg_0.25Cd_0.75Te alloy, which is in a very good agreement with the experimental value (1.061 eV). The optical properties of the alloys are obtained by calculating the dielectric function ?(ω). The peaks of the optical dielectric functions are consistent with the electronic gap energies of the alloys.     

基于用户主题模型的微博用户兴趣挖掘(英文)

Microblogs have become an important platform for people to publish,transform information and acquire knowledge.This paper focuses on the problem of discovering user interest in microblogs.In this paper,we propose a topic mining model based on Latent Dirichlet Allocation(LDA) named user-topic model.For each user,the interests are divided into two parts by different ways to generate the microblogs:original interest and retweet interest.We represent a Gibbs sampling implementation for inference the parameters of our model,and discover not only user's original interest,but also retweet interest.Then we combine original interest and retweet interest to compute interest words for users.Experiments on a dataset of Sina microblogs demonstrate that our model is able to discover user interest effectively and outperforms existing topic models in this task.And we find that original interest and retweet interest are similar and the topics of interest contain user labels.The interest words discovered by our model reflect user labels,but range is much broader.     

改进LDA在模拟电路故障预测中的应用

针对模拟电路早期故障识别难度大的问题,提出一种改进线性辨别分析法和隐马尔科夫相结合的故障预测方法。首先设置元件的参数,提取幅频特征;然后采用改进的线性辨别分析（LDA）对电压特征进行提取消除特征的冗余性和高维性;最后将提取的特征用于训练和测试HMM,以实现模拟电路的状态监测。通过实验验证了其具有良好的模拟电路早期故障监测能力。     

基于特征项分布的信息熵及特征动态加权概念漂移检测模型

现有的概念漂移算法大多建立在数据流的分类模型上,忽略了特征空间与样本空间的分布特点,以及特征选择和加权的重要性.针对此问题提出了一种基于特征项分布的信息熵及特征动态加权算法,从概念漂移的动态演化性出发,根据样本和特征空间的拟合程度,运用特征信息熵理论对数据流中的概念漂移现象进行捕捉,以实现新旧概念的过渡.利用改进的隐含Dirichlet模型特征动态加权算法,以解决当前特征与历史特征的权重确定和无效特征的裁剪问题.在公开的语料库CCERT和Trec06上的测试实验证明了所提出算法的有效性.     

Merits of random forests emerge in evaluation of chemometric classifiers by external validation

Real-world applications will inevitably entail divergence between samples on which chemometric classifiers are trained and the unknowns requiring classification. This has long been recognized, but there is a shortage of empirical studies on which classifiers perform best in ‘external validation’ (EV), where the unknown samples are subject to sources of variation relative to the population used to train the classifier. Survey of 286 classification studies in analytical chemistry found only 6.6% that stated elements of variance between training and test samples. Instead, most tested classifiers using hold-outs or resampling (usually cross-validation) from the same population used in training. The present study evaluated a wide range of classifiers on NMR and mass spectra of plant and food materials, from four projects with different data properties (e.g., different numbers and prevalence of classes) and classification objectives. Use of cross-validation was found to be optimistic relative to EV on samples of different provenance to the training set (e.g., different genotypes, different growth conditions, different seasons of crop harvest). For classifier evaluations across the diverse tasks, we used ranks-based non-parametric comparisons, and permutation-based significance tests. Although latent variable methods (e.g., PLSDA) were used in 64% of the surveyed papers, they were among the less successful classifiers in EV, and orthogonal signal correction was counterproductive. Instead, the best EV performances were obtained with machine learning schemes that coped with the high dimensionality (914–1898 features). Random forests confirmed their resilience to high dimensionality, as best overall performers on the full data, despite being used in only 4.5% of the surveyed papers. Most other machine learning classifiers were improved by a feature selection filter (ReliefF), but still did not out-perform random forests.     

A Convenient Route to (E)-α,β-Unsaturated Methyl Ketones

Aldehydes are converted into (E)-α,β-unsaturated methyl ketones in good yield and with a high E stereoselectivity using α,α-bis(trimethylsilyl) N-tert-butyl acetimine 3. The reaction was mediated by a catalytic amount of tetrabutylammonium fluoride (TBAF) under mild conditions. The disilylated reagent 3 is easily generated from N-tert-butylacetimine, lithium diisopropylamide (LDA), and chlorotrimethylsilane. The mechanism of the reaction is discussed.     

LD纵向抽运固体激光器中的耦合系统

介绍了目前在LD纵向抽运的固体激光器中可以采用的各种耦合系统，分析了它们的优缺点及适用范围，重点研究了排球面柱透镜系统和透镜导管耦合系统。     

声光扫描激光测速研究

针对机械式扫描激光多普勒测速技术(LDA)存在的缺陷.利用声光互作用中衍射光束的偏转效应来实现激光束扫描.构成的声光扫描LDA系统不存在任何运动的光学元件.克服了机械扫描LDA存在惯性影响带来的局限性.应用于人工心瓣返流瞬态流速分布的测定.所获得的实验结果为评定二尖瓣替代物返流特性提供了可信的依据.     

First principles investigation of optical properties of zinc-blende AlxGa1−xAs1−yNy materials

We have performed a first-principle Full Potential Linearized Augmented Plane Waves calculation within the local density approximation (LDA) to the zinc-blende Al_xGa_1−xAs_1−yN_y to predict its optical properties as a function of N and Al mole fractions. The accurate calculations of electronic properties such as band structures and optical properties like refractive index, reflectivity and absorption coefficient of Al_xGa_1−xAs and Al_xGa_1−xAs_1−yN_y with x≤0.375 and y up to 4% are presented. Al_xGa_1−xAs on GaAs have a lattice mismatch less than 0.16% and the lattice constant of Al_xGa_1−xAs has a derivation parameter of 0.0113±0.0024. The band gap energies are calculated by LDA and the band anticrossing model using a matrix element of C_MN=2.32 and a N level of E_N=(1.625+0.069x) eV. The results show that Al_xGa_1−xAs can be very useful as a barrier layer in separate confinement heterostructure lasers and indicate that the best choice of x and y Al_xGa_1−xAs_1−yN_y could be an alternative to Al_xGa_1−xAs when utilized as active layers in quantum well lasers and high-efficiency solar cell structures.