注重语文能力教学法及其在美国汉语教学中的应用

注重语文能力教学法（Ｐｒｄｉｄｅｎｃ－ｔｒｉｅｎｔｅｄＩｎｓｔｒｕｃｔｉｏｎ）是８０年代在欧美国家出现的新型外语教学方法，已为这些国家欧美语系外语教学广泛采用．其特点是以增强学生外语之语言及文字能力为主，使学生全面掌握所修习的外语。本文介绍此法的形成、发展、特点及其在美国汉语教学中的应用。     

论大学生素质教育

本文论述了素质和大学生素质教育的基本内涵和本质,并论述了当前我国大学生素质的现状以及影响和制约当前我国大学生素质教育的因素,提出了加强和改进大学生素质教育的途径和方法。     

一人公司的法律规制

一人公司法律地位在新公司法上的确立,并不是说在此之前不存在这种公司,事实上一人公司尤其是形式上的普通公司实质上的一人公司是广泛存在的。一人公司与传统公司法人制度的冲突,使它在传统公司法框架体系下很难得以规范,而公司法人人格否认法理作为一种判例法上的重要原则,可以有效弥补成文法上的不足,从而在有效规制一人公司方面具有极为广泛的运用价值。一人公司需要信用的土壤,发挥政府和监管部门的信息披露职能是十分重要的。     

简谈领导干部形象

良好的领导形象,不仅有利于领导威信的建立,而且有利于领导者的决策、指示、领导方法为群众所接受,并将愉快地执行与创造性地完成。否则,则会影响领导效能。因此,作为一名领导干部应从多方面加强自身修养,塑造良好的领导形象。     

The current state of the labor queue: National and regional Evidence

We employ vector autoregressive techniques to determine the current state of the labor queue. Unemployment rate differentials have narrowed in recent years, potentially due to a change in the queue ordering, though a tight labor market and a stable queue would yield similar results. We find no evidence that the queue ordering has changed, which brings into question the resiliency of gains made by minority groups. We employ the same techniques to reveal the state of the queue across geographic regions and find that substantial differences exist across regions, implying variation in the relative labor force status of demographic groups.     

产业集群核心竞争力分析

在经济全球化的今天,产业集群逐渐成为地区、国家之间经济竞争的主要模式。本文探讨了产业集群核心竞争力的框架及其根本所在,最终将它归结为集群内所独有的合作的、信任的、宽容的、激励的、创新的网络经济关系,并由此提出了提升我国产业集群核心竞争力的几点对策建议。     

生物学中的相异构想及转变探讨

研究表明，学生学习科学的过程是一种由前概念向科学概念转变的过程。学生头脑中形成的与科学概念不一致的相异构想是造成学生学习困难的重要原因。本文分析了学生在生物学学习中相异构想的成因及来源，并在此基础上提出了生物学教学中相异构想的转变模式及策略。     

Factor analysis for ranked data with application to a job selection attitude survey

Summary.  Factor analysis is a powerful tool to identify the common characteristics among a set of variables that are measured on a continuous scale. In the context of factor analysis for non-continuous-type data, most applications are restricted to item response data only. We extend the factor model to accommodate ranked data. The Monte Carlo expectation–maximization algorithm is used for parameter estimation at which the E-step is implemented via the Gibbs sampler. An analysis based on both complete and incomplete ranked data (e.g. rank the top q out of k items) is considered. Estimation of the factor scores is also discussed. The method proposed is applied to analyse a set of incomplete ranked data that were obtained from a survey that was carried out in GuangZhou, a major city in mainland China, to investigate the factors affecting people's attitude towards choosing jobs.     

从冲突到秩序:政治冲突调控机制分析

冲突是不可避免的政治现象,是政治的内在属性.政治冲突具有不同的功能和强度,这为政治冲突调控机制的选择提供了路径依赖.政治冲突的调控是内力和外力共同作用的结果.所以,政治冲突的调控机制也就包括了自我调控和政府调控两大机制,它们共同推动和维持政治系统的动态稳定,实现从冲突到秩序的转换.     

Bayesian analysis of a marked point process: Application in seismic hazard assessment

Point processes are the stochastic models most suitable for describing physical phenomena that appear at irregularly spaced times, such as the earthquakes. These processes are uniquely characterized by their conditional intensity, that is, by the probability that an event will occur in the infinitesimal interval (t, t+Δt), given the history of the process up tot. The seismic phenomenon displays different behaviours on different time and size scales; in particular, the occurrence of destructive shocks over some centuries in a seismogenic region may be explained by the elastic rebound theory. This theory has inspired the so-called stress release models: their conditional intensity translates the idea that an earthquake produces a sudden decrease in the amount of strain accumulated gradually over time along a fault, and the subsequent event occurs when the stress exceeds the strength of the medium. This study has a double objective: the formulation of these models in the Bayesian framework, and the assignment to each event of a mark, that is its magnitude, modelled through a distribution that depends at timet on the stress level accumulated up to that instant. The resulting parameter space is constrained and dependent on the data, complicating Bayesian computation and analysis. We have resorted to Monte Carlo methods to solve these problems.