警察人权面临困境的行政法解析

袭警案件的多发凸显了警察人权面临的困境。警察人权处于警察与国家、警察与公民双重关系之中,结合行政法学上“特别权力关系”和“反射利益”两个基本概念研究警察的多重身份和警察权对警察人权的影响,有利于在理论和实践上对警察权益保护的研究能在一个更广阔的平台上进行。     

构建以审美为中介的文学价值系统——兼论文学理论批评怎样应对多元化的文学格局

以人与对象性世界关系为逻辑起点 ,通过对文学活动过程的静态与动态分析 ,揭示文学价值是自我价值与社会价值双向互动的系统构成 ,并在此基础上形成以审美为中介的多重性价值构建的阐释座标 :既不应把维护文学的审美价值的基点简单地理解或置换成为闭锁于作家———文本自身的完全自洽的概念 ,也不能摒弃以审美价值为基点去直接考察和分析包括政治、伦理及其它精神文化在内的多重性价值内涵和形态。同时 ,不仅要重视文学两个基本价值取向 (满足人的基本的情感要求与注重人性深度的开掘和形而上意义的承诺 )的差异和冲突 ;更要体认它们之间的“共在”关系及隐含制衡的张力结构。这样 ,文学理论批评才能在保持文学的审美特性的同时 ,形成开放、多元良性发展的崭新局面。     

二元多元和谐

把事物"一分为二",通过矛盾双方的斗争,使一方战胜另一方,实现矛盾统一,这是"二元归一"的思维方式。"一分为二"是对复杂事物矛盾结构的抽象。但现代社会是多元的社会,而且多元各方要求更多的合作,因此,必须以更为具体的"多元协同"思维方式观察社会。从"二元归一"到"多元协同",是思维方式从抽象上升到具体的运动。在"多元协同"思维方式指导下,"和为贵"、"和而不同"是构建和谐社会的最佳选择。     

A novel approach based on multiple correspondence analysis for monitoring social networks with categorical attributed data

In in most cases, the distribution of communications is unknown and one may summarize social network communications with categorical attributes in a contingency table. Due to the categorical nature of the data and a large number of features, there are many parameters to be considered and estimated in the model. Hence, the accuracy of estimators decreases. To overcome the problem of high dimensionality and unknown communications distribution, multiple correspondence analysis is used to reduce the number of parameters. Then the rescaled data are studied in a Dirichlet model in which the parameters should be estimated. Moreover, two control charts, Hotelling’s T² and multivariate exponentially weighted moving average (MEWMA), are developed to monitor the parameters of the Dirichlet distribution. The performance of the proposed method is evaluated through simulation studies in terms of average run length criterion. Finally, the proposed method is applied to a real case.     

Understanding parental leave experiences: connecting the dots with a multiple-methods approach

ABSTRACT

This research note draws selected findings from a multiple-methods study conducted in partnership with a large public-sector employer in Portland, OR to describe the added value of this approach for research translation. We focus on how our study of a newly implemented paid parental leave policy can translate to actionable steps for two important end-users: employers and policymakers. Using administrative records (N?=?579), a countywide employee survey (N?=?137 leave-takers) and focus groups (N?=?35), we describe how each data source contributes important and unique information about how the policy’s implementation affected diverse employees. We find gender differences in how employees changed leave-taking in response to the policy, and describe the critical but nuanced role that supervisors play. Working with employers and policymakers to develop and implement thoughtful policies will help to ensure equitable distribution of the benefits of paid leave policies.     

Bayesian MARS

A Bayesian approach to multivariate adaptive regression spline (MARS) fitting (Friedman, 1991) is proposed. This takes the form of a probability distribution over the space of possible MARS models which is explored using reversible jump Markov chain Monte Carlo methods (Green, 1995). The generated sample of MARS models produced is shown to have good predictive power when averaged and allows easy interpretation of the relative importance of predictors to the overall fit.     

Multiple roots of estimating functions

Estimating functions can have multiple roots. In such cases, the statistician must choose among the roots to estimate the parameter. Standard asymptotic theory shows that in a wide variety of cases, there exists a unique consistent root, and that this root will lie asymptotically close to other consistent (possibly inefficient) estimators for the parameter. For this reason, attention has largely focused on the problem of selecting this root and determining its approximate asymptotic distribution. In this paper, however, we concentrate on the exact distribution of the roots as a random set. In particular, we propose the use of higher-order root intensity functions as a tool for examining the properties of the roots and determining their most problematic features. The use of root intensity functions of first and second order is illustrated by application to the score function for the Cauchy location model.     

Evaluating surrogate variables for improving microarray multiple testing inference

The use of surrogate variables has been proposed as a means to capture, for a given observed set of data, sources driving the dependency structure among high-dimensional sets of features and remove the effects of those sources and their potential negative impact on simultaneous inference. In this article we illustrate the potential effects of latent variables on testing dependence and the resulting impact on multiple inference, we briefly review the method of surrogate variable analysis proposed by Leek and Storey (PNAS 2008; 105:18718-18723), and assess that method via simulations intended to mimic the complexity of feature dependence observed in real-world microarray data. The method is also assessed via application to a recent Merck microarray data set. Both simulation and case study results indicate that surrogate variable analysis can offer a viable strategy for tackling the multiple testing dependence problem when the features follow a potentially complex correlation structure, yielding improvements in the variability of false positive rates and increases in power.     

通胀市场下多设备租赁的在线策略分析

现实租赁市场中,企业同时租赁多台设备的现象大量存在,但经营者面临的最大难题是如何对这多台设备进行在线租赁的组合优化,从而降低决策成本,而通货膨胀又进一步增加了决策难度。本文运用在线算法和竞争分析法建立多设备投资的风险控制策略,并分析通胀对决策的影响。首先在Karp经典模型上给出通胀因素下多设备投资的最优在线和离线策略;接着建立设备租赁在连续可分情形下的最优风险控制模型,进一步结合实际投资中设备必须以离散整数租赁的特点,对CR策略进行调整和优化,得到近似的CRJ策略,使得策略更符合实际投资活动。最后给出具体实例分析,结果显示,当物价指数逐渐增大时,最优决策日期相应提前,对应最优策略的竞争比也逐渐增大,进一步说明物价指数因素和多设备投资因素的引入对投资者的决策有着重要的影响,为多设备在线租赁问题的研究提供了新的解决思路。