刑事审判程序拒绝预断的两条路径

各国刑事审判程序对预断的“拒绝”，可分为事前防止和事后排除两种途径。正因如此，认为“大陆法系职权主义刑事诉讼没有预断排除规则”的观点值得商榷。显而易见的是，对事前防止与事后排除的不同侧重，正是两种审判模式对待预断的区别之处。预断的作用机制，在心理学上可用“首因效应”来解释，从预断的发生、防止和排除三个方面入手进行分析十分必要，由此得以阐明两种审判模式拒绝预断的不同进路。并且从法制国家的程序设置来看，拒绝预断只是保障公正审判的诸多手段之一。     

国家资源安全体系下资源再生产业贡献因子研究

借鉴发达国家资源再生产业的实践经验，提出基于国家矿产资源安全的资源再生产业发展模式研究的基本内容与方法，建立资源再生产业对国家资源安全体系的贡献因子理论模型，确定了由产业发展的关键性要素到制订资源再生产业市场化发展战略的研究框架。     

OPTIMAL SOFTWARE RELEASE POLICY BASED ON MARKOVIAN PERFECT DEBUGGING MODEL

In this paper we consider a Markovian perfect debugging model for which the software failure is caused by two types of faults, one which is easily detected and the other which is difficult to detect. When a failure occurs, a perfect debugging is immediately performed and consequently one fault is reduced from fault contents. We also treat the debugging time as a variable to develop a new debugging model. Based on the perfect debugging model, we propose an optimal software release policy that satisfies the requirements for both software reliability and expected number of faults which are required to achieve before releasing the software. Several measures, including the distribution of first passage time to the specified number of removed faults, are also obtained using the proposed debugging model.     

Social Activity,School-related Activity,and Anti–substance Use: Media Messages on Adolescent Tobacco and Alcohol Use

In this article, we present the effects of three hypothesized protective factors—social activities, school-related activities, and anti–substance use media messages—on adolescent tobacco and alcohol use. Data were drawn from the “Monitoring the Future” research project, which was conducted by the Institute for Social Research at the University of Michigan. The sample included 2,551 twelfth-grade students. The results of the structural equation model showed that exposure to media anti-drug messages had an indirect negative effect on tobacco and alcohol use through school-related activity and social activity. The results suggest that comprehensive ecological interventions encompassing media, family, and school can increase the preventive effects of adolescent's substance use.     

The Social Ecology of Child Development in the Mexican American Population

Abstract

This article explores the influence of contextual factors on the developmental outcomes of Mexican American children. The contextual structure of child development is conceptualized as a complex system of environments, including the socio-demographic, social service, academic, and parental home environments. Based on an extensive review of the current theoretical and empirical literature, we find that the disadvantaged social position of Mexican American children has detrimental implications for all other aspects of their environment, thus hindering their development. In addition, although Mexican American parents are highly competent in providing a nurturing and culturally-rich environment, there is a often a discontinuity between the home environment and both the academic and the social service environments.     

Estimability and Linear Hypotheses

A proposition is given which provides an easily justified reason as to why attention should be confined to estimable parametric vectors when formulating linear hypotheses. The possibility of justifying one's linear estimation effort on the estimable parametric functions via an identifiability condition is also mentioned.     

A Mechanical Interpretation of the Coefficient of Rank Correlation and other Analogies

Periodically, the pyramid or “chain letter” scheme is offered to Americans under the guise of a business dealership. Recently, the FTC ordered Glen Turner's “Dare to be Great” firm to repay 44 million dollars to participants. In order to demonstrate that the potential gains are misrepresented by promoters, a probability model of the pyramid scheme is developed. The major implications are that the vast majority of participants have less than a ten percent chance of recouping their initial investment when a small profit is achieved as soon as they recruit three people and that, on the average, half of the participants will recruit no one else and lose all their money.     

New difference-based estimator of parameters in semiparametric regression models

The paper introduces a new difference-based Liu estimator β?_Ldiff=([Xtilde]′[Xtilde]+I)^?1([Xtilde]′[ytilde]+η β?_diff) of the regression parameters β in the semiparametric regression model, y=Xβ+f+?. Difference-based estimator, β?_diff=([Xtilde]′[Xtilde])^?1[Xtilde]′[ytilde] and difference-based Liu estimator are analysed and compared with respect to mean-squared error (mse) criterion. Finally, the performance of the new estimator is evaluated for a real data set. Monte Carlo simulation is given to show the improvement in the scalar mse of the estimator.     

Case–control genome-wide joint association study using semiparametric empirical model and approximate Bayes factor

We propose a semiparametric approach for the analysis of case–control genome-wide association study. Parametric components are used to model both the conditional distribution of the case status given the covariates and the distribution of genotype counts, whereas the distribution of the covariates are modelled nonparametrically. This yields a direct and joint modelling of the case status, covariates and genotype counts, and gives a better understanding of the disease mechanism and results in more reliable conclusions. Side information, such as the disease prevalence, can be conveniently incorporated into the model by an empirical likelihood approach and leads to more efficient estimates and a powerful test in the detection of disease-associated SNPs. Profiling is used to eliminate a nuisance nonparametric component, and the resulting profile empirical likelihood estimates are shown to be consistent and asymptotically normal. For the hypothesis test on disease association, we apply the approximate Bayes factor (ABF) which is computationally simple and most desirable in genome-wide association studies where hundreds of thousands to a million genetic markers are tested. We treat the approximate Bayes factor as a hybrid Bayes factor which replaces the full data by the maximum likelihood estimates of the parameters of interest in the full model and derive it under a general setting. The deviation from Hardy–Weinberg Equilibrium (HWE) is also taken into account and the ABF for HWE using cases is shown to provide evidence of association between a disease and a genetic marker. Simulation studies and an application are further provided to illustrate the utility of the proposed methodology.