Individual Differences in Women's Salivary Testosterone and Estradiol Following Sexual Activity in a Nonlaboratory Setting

Objectives: The current study evaluated women's salivary testosterone and estradiol levels before and after exposure to sexual stimuli in a U.S. sex club. Methods: Behavioral data and salivary samples were collected from 19 women during semistructured interviews. Results: Findings demonstrate substantial individual differences in the magnitude and direction of women's hormonal changes following sexual activity. Conclusions: In an age of individualized medicine, these findings highlight the need to better understand factors shaping variation in physiological responses to sexual activity. Findings contribute to a relatively small and contradictory literature on women's hormonal responses to sexual stimuli.     

To adjust or not to adjust for baseline when analyzing repeated binary responses? The case of complete data when treatment comparison at study end is of interest

The benefits of adjusting for baseline covariates are not as straightforward with repeated binary responses as with continuous response variables. Therefore, in this study, we compared different methods for analyzing repeated binary data through simulations when the outcome at the study endpoint is of interest. Methods compared included chi‐square, Fisher's exact test, covariate adjusted/unadjusted logistic regression (Adj.logit/Unadj.logit), covariate adjusted/unadjusted generalized estimating equations (Adj.GEE/Unadj.GEE), covariate adjusted/unadjusted generalized linear mixed model (Adj.GLMM/Unadj.GLMM). All these methods preserved the type I error close to the nominal level. Covariate adjusted methods improved power compared with the unadjusted methods because of the increased treatment effect estimates, especially when the correlation between the baseline and outcome was strong, even though there was an apparent increase in standard errors. Results of the Chi‐squared test were identical to those for the unadjusted logistic regression. Fisher's exact test was the most conservative test regarding the type I error rate and also with the lowest power. Without missing data, there was no gain in using a repeated measures approach over a simple logistic regression at the final time point. Analysis of results from five phase III diabetes trials of the same compound was consistent with the simulation findings. Therefore, covariate adjusted analysis is recommended for repeated binary data when the study endpoint is of interest. Copyright © 2015 John Wiley & Sons, Ltd.     

核事故早期应急群决策模型研究

有效快速的核事故早期应急决策,是核电站发生核事故后最后一道必要的屏障,因此决策的快速性与有效性至关重要。文章先构造效用函数,求出决策者的乐观系数,将决策判断矩阵中的区间值与模糊值精确化;在此基础上建立了个体与群体的决策模型,以提高决策的有效性。同时根据排序结果,构造群体与个体之间一致性判断矩阵,并根据判断矩阵进行交互与修改,使专家内部快速达成一致。最后通过算例说明方法的可行性。     

脉冲响应函数下的我国货币需求变动与决定

基于V A R模型的脉冲响应函数法和预期方差分解法,分析了我国2000年至2013年期间的货币需求与相关经济因素之间的动态影响特征。研究表明狭义货币、广义货币分别与相关的经济变量存在长期的均衡关系。狭义货币、广义货币对GDP的冲击分别呈现抑制效应、对SV的随机冲击主要呈现正效应、对R的随机冲击主要呈现抑制效应、对CPI的冲击呈现正效应和抑制效应交叉出现的现象。狭义货币、广义货币新息冲击对其自身预测均方误差的贡献度最大。新息冲击对狭义货币预测均方误差的贡献依次为：一年期定期存款名义利率（R）、沪深两市A股总市值（SV）、国内生产总值（GDP）、消费者物价指数（CPI）。新息冲击对广义货币预测均方误差的贡献依次为：国内生产总值（GDP ）、消费者物价指数（CPI ）、一年期定期存款名义利率（R ）、沪深两市A股总市值（S V ）。根据实证结论,得出相关经济变量对货币需求的影响,并据此提出有利于完善货币政策的建议。     

Realized GAS-GARCH及其在VaR预测中的应用

论文提出了新的波动率模型Realized GAS-GARCH,并推导了该模型的QMLE参数估计.该模型结合了Generalized Autoregressive Score (GAS)模型的基本思路,把Realized GARCH 模型扩展到包含厚尾分布的情形,并采用了与厚尾分布参数相依的冲击响应函数.与简单的厚尾分布扩展模型相比,这种设定对于回报率中的极端值更加稳健.在基于沪深300指数高频数据的实证结果中,使用GAS冲击响应函数的模型对“在险价值”VaR的预测能力显著的超过了传统的厚尾Realized GARCH模型.     

大股东资产注入的股东财富效应——来自我国上市公司的经验证据

大股东的资产注入行为理论上存在掏空和支持两种动机。文章通过运用事件分析法和回归分析法实证研究了大股东资产注入对上市公司股东财富的影响。研究发现,大股东资产注入的股东财富效应取决于资产注入的具体代理变量:资产注入的短期宣告效应与注入资产规模和注入模式显著正相关,而与注入资产类型和所有权性质关系不显著;资产注入的长期股价表现与注入资产的类型和规模呈显著的正向关系,而与所有权性质和注入模式呈负向关系。     

关于直销人员人性变异的若干思考

根据直销人员人性变异的现状，分别从宏观、微观环境及个人内在原因三方面进行分析，认为要想从根本上改变这种现象，政府不应该仅仅是简单的管控，更重要是的疏导，才可以有效防范直销人员人性变异的事情继续蔓延，最终引领中国直销业逐步走向健康发展之路。     

Building a Human Health Risk Assessment Ontology (RsO): A Proposed Framework

Over the last decade the health and environmental research communities have made significant progress in collecting and improving access to genomic, toxicology, exposure, health, and disease data useful to health risk assessment. One of the barriers to applying these growing volumes of information in fields such as risk assessment is the lack of informatics tools to organize, curate, and evaluate thousands of journal publications and hundreds of databases to provide new insights on relationships among exposure, hazard, and disease burden. Many fields are developing ontologies as a way of organizing and analyzing large amounts of complex information from multiple scientific disciplines. Ontologies include a vocabulary of terms and concepts with defined logical relationships to each other. Building from the recently published exposure ontology and other relevant health and environmental ontologies, this article proposes an ontology for health risk assessment (RsO) that provides a structural framework for organizing risk assessment information and methods. The RsO is anchored by eight major concepts that were either identified by exploratory curations of the risk literature or the exposure‐ontology working group as key for describing the risk assessment domain. These concepts are: (1) stressor, (2) receptor, (3) outcome, (4) exposure event, (5) dose‐response approach, (6) dose‐response metric, (7) uncertainty, and (8) measure of risk. We illustrate the utility of these concepts for the RsO with example curations of published risk assessments for ionizing radiation, arsenic in drinking water, and persistent pollutants in salmon.     

Optional randomized response techniques for quantitative characteristics

Gupta et al. and Huang considered optional randomized response techniques where the probability of choosing the randomized (or direct) response is fixed for all the respondents. In this paper the assumption of the constant probability of choosing the option has been relaxed by dividing respondents into two groups: one group provides direct response and the second a randomized response. The method of estimation of the population mean and variances under the modified assumption are obtained. Relative efficiencies of the proposed techniques are compared theoretically and empirically.