圆柱绕流复杂尾迹的实验研究

本实验研究由两个或三个并排圆柱体所产生的复杂尾迹。其中一个圆柱被加热,流体尾迹中最高温度比环境温度高１℃左右,对湍流场影响很小。用Ｘ热线和一根冷线相结合的三线探头分别测量速度和温度的脉动。以一个圆柱尾迹的实验数据为基础,用位置叠加假设来计算复杂尾迹,并与实际测量结果比较,用以检查该假设在圆柱绕流复杂尾迹的适用情况。结果表明,利用位置叠加假设,可以根据该假设的实验结果来对复杂尾迹的平均速度进行描述     

Stochastic Multivariate Mixture Covariance Model

Stochastic covariance models have been explored in recent research to model the interdependence of assets in financial time series. The approach uses a single stochastic model to capture such interdependence. However, it may be inappropriate to assume a single coherence structure at all time t. In this paper, we propose the use of a mixture of stochastic covariance models to generalize the approach and offer greater flexibility in real data applications. Parameter estimation is performed by Bayesian analysis with Markov chain Monte Carlo sampling schemes. We conduct a simulation study on three different model setups and evaluate the performance of estimation and model selection. We also apply our modeling methods to high‐frequency stock data from Hong Kong. Model selection favors a mixture rather than non‐mixture model. In a real data study, we demonstrate that the mixture model is able to identify structural changes in market risk, as evidenced by a drastic change in mixture proportions over time. Copyright © 2016 John Wiley & Sons, Ltd.     

Variants in KCNQ1 are associated with susceptibility to type 2 diabetes mellitus

We carried out a multistage genome-wide association study of type 2 diabetes mellitus in Japanese individuals, with a total of 1,612 cases and 1,424 controls and 100,000 SNPs. The most significant association was obtained with SNPs in KCNQ1, and dense mapping within the gene revealed that rs2237892 in intron 15 showed the lowest Pvalue (6.7 x 10(-13), odds ratio (OR) = 1.49). The association of KCNQ1 with type 2 diabetes was replicated in populations of Korean, Chinese and European ancestry as well as in two independent Japanese populations, and meta-analysis with a total of 19,930 individuals (9,569 cases and 10,361 controls) yielded a P value of 1.7 x 10(-42) (OR = 1.40; 95% CI = 1.34-1.47) for rs2237892. Among control subjects, the risk allele of this polymorphism was associated with impairment of insulin secretion according to the homeostasis model assessment of beta-cell function or the corrected insulin response. Our data thus implicate KCNQ1 as a diabetes susceptibility gene in groups of different ancestries.     

用伪谱方法计算强激光场中一维原子的高次谐波和电离几率

引入非线性空间变换,用伪谱方法求解了一维原子在强激光场中的薛定谔方程,计算了一维原子在强激光场中的高次谐波和电离几率,其结果与分裂算符法得到的结果符合得很好.     

自由振动圆柱绕流近尾迹湍流普朗特数

对自由振动圆柱后尾迹中的湍流普朗特数进行了实验研究 ,并与刚性柱体尾迹的结果作了比较 .加热圆柱后的流场温度比环境温度高 1℃左右 ,对流场影响很小 .用自制的X热线和一根冷线相结合的三线探头测量速度和温度的脉动 ,并用激光测振仪测量了该柱体的振动情况 .结果表明 ,在自由振动后的尾迹中 ,湍流脉动引起的能量输运能力比动量输运能力强 ,湍流的梯度输运假设与实验结果符合较好     

寄生于细尾异齿(鱼旻)的新施分虫一新种

报道寄生于细尾异齿鱼日女 Oreoglanisdelacouri(Pellegrin)鳃丝上的一种异齿 鱼日女 新施分虫新种     

A threshold factor multivariate stochastic volatility model

A new multivariate stochastic volatility model is developed in this paper. The main feature of this model is to allow threshold asymmetry in a factor covariance structure. The new model provides a parsimonious characterization of volatility and correlation asymmetry in response to market news. Statistical inferences are drawn from Markov chain Monte Carlo methods. We introduce news impact analysis to analyze volatility asymmetry with a factor structure. This analysis helps us to study different responses of volatility to historical market information in a multivariate volatility framework. Our model is successful when applied to an extensive empirical study of twenty stocks. Copyright © 2009 John Wiley & Sons, Ltd.     

Multivariate GARCH Models with Correlation Clustering

A new clustered correlation multivariate generalized autoregressive conditional heteroskedasticity (CC‐MGARCH) model that allows conditional correlations to form clusters is proposed. This model generalizes the time‐varying correlation structure of Tse and Tsui (2002, Journal of Business and Economic Statistics 20 : 351–361) by classifying the correlations among the series into groups. To estimate the proposed model, Markov chain Monte Carlo methods are adopted. Two efficient sampling schemes for drawing discrete indicators are also developed. Simulations show that these efficient sampling schemes can lead to substantial savings in computation time in Monte Carlo procedures involving discrete indicators. Empirical examples using stock market and exchange rate data are presented in which two‐cluster and three‐cluster models are selected using posterior probabilities. This implies that the conditional correlation equation is likely to be governed by more than one set of decaying parameters. Copyright © 2011 John Wiley & Sons, Ltd.