从换韵看王令《梦蝗》诗的情绪变化

换韵与情绪宣泄关系十分密切,从王令《梦蝗》诗可以明显看到这一点。从《梦蝗》诗的换韵中人们可以有效地把握王令诗的情绪节奏变化特征,真正理解作为"蓄含悲愤"而又"笔力恣肆"诗人的情绪结构本质。     

Building community: a conceptual framework for child protection

This paper proposes a community-building framework as an innovative strategy to begin to re-claim children and families at risk. It is a strategy that identifies a purpose, a value base, knowledge and theoretical dimensions, and methods of practice that present as an approach for child welfare systems to consider shifts in thinking in order to meet what is considered the most important challenge of the next century: that of rediscovering community. Copyright © 2001 John Wiley & Sons, Ltd.     

班干部轮岗制——一种新的育人机制

对于高校的班干部 ,人们更多的理解为是班主任管理班级的工作助手。我们认为 ,“班干部”这一角色本身还隐含着丰富的促进学生自我教育的功能。这种育人功能以普遍而深刻的社会心理为依据。充分认识、挖掘和利用这一特殊的“教育资源”,对于高校实施素质教育 ,全面提高学生的综合素质 ,有着重要的作用     

评《永别了,武器》的语言运用——从“我”到“你”或到“我们”的人称转变

在《永别了,武器》一文中,这种从"我"到"你"或到"我们"的人称转变,至少隐含以下几种含义:主人公弗雷德里克·亨利(Frederic Henry)对过去思想和感情的回忆;以平民身份对军人身份的描述;对凯瑟琳·芭克莉(Catherine Barkley)的爱;对战争的愤恨。本文从语言学和心理学的角度来解读这部经典小说的隐显叙事手法。     

易代风气下的红楼梦

明清易代是中国历史上最为深刻的变革,它对社会的各个领域都产生了极大的影响。伴随着政权鼎革,士大夫家族的命运也随之发生了巨大变化。文章聚焦于曹家以及《红楼梦》在这样的历史中所呈现出的独特意蕴,在周汝昌先生考证的提示下,进一步揭示《红楼梦》伟大的人本主义精神内涵和启蒙意义。     

On a bayesian approach for the shiftpoint problem

Using a direct resampling process, a Bayesian approach is developed for the analysis of the shiftpoint problem. In many problems it is straight forward to isolate the marginal posterior distribution of the shift-point parameter and the conditional distribution of some of the parameters given the shift point and the other remaining parameters. When this is possible, a direct sampling approach is easily implemented whereby standard random number generators can be used to generate samples from the joint posterior distribution of aii the parameters in the model. This technique is illustrated with examples involving one shift for Poisson processes and regression models.     

女性择偶偏好的周期转换效应：三种解释视角

进化心理学的研究显示,女性更喜欢那些拥有男性化面孔及特定体味、身体对称、外表健康的男性,并且这种偏好会随着女性的月经周期而发生转变。在排卵期表现出明显的男性化偏好,而在其他时段偏好不明显,该效应被称为＂周期转换效应＂。通过梳理三种主流的解释视角,即基因选择假设、激素刺激假设和排卵引起知觉偏差的假设,结合＂周期转换效应＂遇到的挑战,从而指出未来的研究方向。     

Circular First- and Second-Order Balanced Repeated Measurements Designs

Sharma (1977 Sharma , V. K. ( 1977 ). Change-over designs with complete balance for first and second order residual effect . Canad. J. Statist. 5 : 121 – 132 .[Crossref] , [Google Scholar]) and Aggarwal et al. (2006 Aggarwal , M. L. , Deng , L.-Y. , Jha , M. K. ( 2006 ). Balanced residual treatment effects designs of first and second order . Statist. Probab. Lett. 76 : 597 – 600 .[Crossref], [Web of Science ®] , [Google Scholar]) considered non circular construction of first- and second-order balanced repeated measurements designs. Sharma et al. (2002 Sharma , V. K. , Varghese , C. , Jaggi , S. ( 2002 ). On optimality of change-over designs balanced for first and second order residual effects . Metron 60 : 153 – 162 . [Google Scholar]) constructed circular first- and second-order balanced repeated measurements designs only for a class with parameters (v, p = 3n, n = v ²) and also showed its universal optimality. In this article, we consider circular construction of first- and second-order balanced repeated measurements designs and strongly balanced repeated measurements designs by using the method of cyclic shifts. Some new circular designs with parameters (v, p, n) for cases p = v, p < v and p > v are given.     

A Data‐Driven Approach to Assessing Supply Inadequacy Risks Due to Climate‐Induced Shifts in Electricity Demand

The U.S. electric power system is increasingly vulnerable to the adverse impacts of extreme climate events. Supply inadequacy risk can result from climate‐induced shifts in electricity demand and/or damaged physical assets due to hydro‐meteorological hazards and climate change. In this article, we focus on the risks associated with the unanticipated climate‐induced demand shifts and propose a data‐driven approach to identify risk factors that render the electricity sector vulnerable in the face of future climate variability and change. More specifically, we have leveraged advanced supervised learning theory to identify the key predictors of climate‐sensitive demand in the residential, commercial, and industrial sectors. Our analysis indicates that variations in mean dew point temperature is the common major risk factor across all the three sectors. We have also conducted a statistical sensitivity analysis to assess the variability in the projected demand as a function of the key climate risk factor. We then propose the use of scenario‐based heat maps as a tool to communicate the inadequacy risks to stakeholders and decisionmakers. While we use the state of Ohio as a case study, our proposed approach is equally applicable to all other states.     

Sample Splitting and Threshold Estimation

Threshold models have a wide variety of applications in economics. Direct applications include models of separating and multiple equilibria. Other applications include empirical sample splitting when the sample split is based on a continuously‐distributed variable such as firm size. In addition, threshold models may be used as a parsimonious strategy for nonparametric function estimation. For example, the threshold autoregressive model (TAR) is popular in the nonlinear time series literature. Threshold models also emerge as special cases of more complex statistical frameworks, such as mixture models, switching models, Markov switching models, and smooth transition threshold models. It may be important to understand the statistical properties of threshold models as a preliminary step in the development of statistical tools to handle these more complicated structures. Despite the large number of potential applications, the statistical theory of threshold estimation is undeveloped. It is known that threshold estimates are super‐consistent, but a distribution theory useful for testing and inference has yet to be provided. This paper develops a statistical theory for threshold estimation in the regression context. We allow for either cross‐section or time series observations. Least squares estimation of the regression parameters is considered. An asymptotic distribution theory for the regression estimates (the threshold and the regression slopes) is developed. It is found that the distribution of the threshold estimate is nonstandard. A method to construct asymptotic confidence intervals is developed by inverting the likelihood ratio statistic. It is shown that this yields asymptotically conservative confidence regions. Monte Carlo simulations are presented to assess the accuracy of the asymptotic approximations. The empirical relevance of the theory is illustrated through an application to the multiple equilibria growth model of Durlauf and Johnson (1995).