阴阳五行学说与汉代骚体赋的空间建构

阴阳五行学说及其象征思维框架对汉代骚体赋的空间建构影响很大。它不仅为骚体赋提供了一种建构想象空间的可能性,而且还提供了一系列与阴阳五行学说相关联的具体可感的物象和场面,这就使得利用阴阳五行学说来建构空间世界的骚体作品如司马相如《大人赋》和张衡《思玄赋》等具有一种可与散体大赋并驾齐驱的特质。     

元大都休闲文化景观研究

本文归纳了元代大都城市居民公共休闲活动地的类型,总结了当时北京休闲文化景观的特点。作者认为元代大都休闲空间格局的形成经历了两个阶段,城市休闲功能较前代明显增强。     

菲利普·罗斯大屠杀书写的语境与特征

当代美国犹太作家菲利普·罗斯的大屠杀书写揭示了大屠杀事件从边缘逐步进入到美国犹太人身份认知核心的过程。文章从罗斯大屠杀书写的美国语境、大屠杀书写的悖谬性和大屠杀书写的空间化三个方面,探讨罗斯大屠杀书写的外围语境和内在特征,旨在说明罗斯的大屠杀书写一方面拓展了当代美国犹太作家大屠杀书写的可能性,另一方面展现了当代犹太人身份的复杂化和多元化的特点。     

原型理论对介词空间意义的多义性研究--以介词in为例

传统的“任意观”认为,介词的不同义项之间毫无联系,介词的多个义项是一堆分散的语义项集合。通过对介词in的原型意义确定,到各义项的派生形成过程,再到各义项之间的关系的逐一解释,发现：介词in的多个义项是有联系的,其多个义项由原型意义派生形成,相互之间以原型意义为中心呈辐射分布。认知语言学原型理论分析介词多义现象更具理据性。     

Likelihood Inference for Unions of Interacting Discs

Abstract. This is probably the first paper which discusses likelihood inference for a random set using a germ‐grain model, where the individual grains are unobservable, edge effects occur and other complications appear. We consider the case where the grains form a disc process modelled by a marked point process, where the germs are the centres and the marks are the associated radii of the discs. We propose to use a recent parametric class of interacting disc process models, where the minimal sufficient statistic depends on various geometric properties of the random set, and the density is specified with respect to a given marked Poisson model (i.e. a Boolean model). We show how edge effects and other complications can be handled by considering a certain conditional likelihood. Our methodology is illustrated by analysing Peter Diggle's heather data set, where we discuss the results of simulation‐based maximum likelihood inference and the effect of specifying different reference Poisson models.     

约瑟夫·康拉德小说地理空间研究述评

地理空间作为人类生存的最基本条件之一,是包含着人类社会种种权力关系、利益关系以及层级差别的一个集合体。而表现人类价值判断的文学作品自然也附带了这种集合体的特质。波兰裔英国作家康拉德生平的地理空间跨度注定了其小说中的地理空间叙述不只是故事发生与存在的先在条件,更是一种价值取向。以分析与借鉴以往康拉德小说研究成果为契机,尝试着从空间批评与文学地理学批评来重新审视康拉德小说的内涵意义,探讨康拉德作品如何通过地理空间叙述系统来表达意识形态、权力机制以及身份特征等多维层面。     

Target detection from a classical and a Bayesian viewpoint

Two approaches have been used for designing spatial surveys to detect a target. The classical approach controls the probability of missing a target that exists; a Bayesian approach controls the probability that a target exists given that none was seen. In both cases, information about the likely size of the target can reduce sampling requirements. In this paper, previous results are summarized and then used to assess the risk that Roman remains could be present at sites scheduled for development in Greater London.     

The changing spatial distribution and concentration of Australias chinese and Vietnamese communities: An analysis of 1986–2006 Australian population census data

This paper describes the changing spatial distribution and concentration of Chinese and Vietnamese communities in Australia over the two past decades. The research analyses data of individuals (i) born in the People’s Republic of China or Vietnam, (ii) of Chinese or Vietnamese ancestry, and (iii) who spoke Chinese or Vietnamese languages at home. Basic demographic and economic factors at the SLA level are considered to provide an initial discussion of meso-level factors which may have contributed to changes in Chinese-and Vietnamese-Australian distributions and concentrations since 1986. As expected, from field observations, the data reveal a contrasting picture of the spatial distribution and concentration of the Chinese- and Vietnamese-Australian communities, and indicate that although a few areas of high Vietnamese spatial concentration have persisted into 2006, and a few areas of high’ Chinese spatial concentration have developed since 1986, overall there is an increasing dispersion of both communities into the broader Australian community.     

全局主成分法在土地集约利用评价中应用——以中部地区为例

在构建评价指标体系基础上,运用基于三维立体时序全局表的全局主成分法对1997￣2005年东部、中部、西部、东北地区原始数据进行分析,对比分析得出中国中部地区的土地集约利用水平变化规律。结果表明:全局主成分法的适用性广;近9年来中部地区土地集约利用水平在不断提高;中部地区土地集约利用水平与东部和西部、东北地区比较呈现两极变化趋势。     

Bayesian inference for pairwise interacting point processes

Pairwise interacting point processes are commonly used to model spatial point patterns. To perform inference, the established frequentist methods can produce good point estimates when the interaction in the data is moderate, but some methods may produce severely biased estimates when the interaction in strong. Furthermore, because the sampling distributions of the estimates are unclear, interval estimates are typically obtained by parametric bootstrap methods. In the current setting however, the behavior of such estimates is not well understood. In this article we propose Bayesian methods for obtaining inferences in pairwise interacting point processes. The requisite application of Markov chain Monte Carlo (MCMC) techniques is complicated by an intractable function of the parameters in the likelihood. The acceptance probability in a Metropolis-Hastings algorithm involves the ratio of two likelihoods evaluated at differing parameter values. The intractable functions do not cancel, and hence an intractable ratio r must be estimated within each iteration of a Metropolis-Hastings sampler. We propose the use of importance sampling techniques within MCMC to address this problem. While r may be estimated by other methods, these, in general, are not readily applied in a Bayesian setting. We demonstrate the validity of our importance sampling approach with a small simulation study. Finally, we analyze the Swedish pine sapling dataset (Strand 1972) and contrast the results with those in the literature.