Robustness of Risk Maps and Survey Networks to Knowledge Gaps About a New Invasive Pest

In pest risk assessment it is frequently necessary to make management decisions regarding emerging threats under severe uncertainty. Although risk maps provide useful decision support for invasive alien species, they rarely address knowledge gaps associated with the underlying risk model or how they may change the risk estimates. Failure to recognize uncertainty leads to risk‐ignorant decisions and miscalculation of expected impacts as well as the costs required to minimize these impacts. Here we use the information gap concept to evaluate the robustness of risk maps to uncertainties in key assumptions about an invading organism. We generate risk maps with a spatial model of invasion that simulates potential entries of an invasive pest via international marine shipments, their spread through a landscape, and establishment on a susceptible host. In particular, we focus on the question of how much uncertainty in risk model assumptions can be tolerated before the risk map loses its value. We outline this approach with an example of a forest pest recently detected in North America, Sirex noctilio Fabricius. The results provide a spatial representation of the robustness of predictions of S. noctilio invasion risk to uncertainty and show major geographic hotspots where the consideration of uncertainty in model parameters may change management decisions about a new invasive pest. We then illustrate how the dependency between the extent of uncertainties and the degree of robustness of a risk map can be used to select a surveillance network design that is most robust to knowledge gaps about the pest.     

Measurement error in the generalised linear model

This paper considers the problem of estimating the linear parameters of a Generalised Linear Model (GLM) when the explanatory variable is subject to measurement error. In this situation the induced model for dependence on the approximate explanatory variable is not usually of GLM form. However, when the distribution of measurement error is known or estimated from replicated measurements, application of the GLIM iteratively reweighted least squares algorithm with transformed data and weighting is shown to produce maximum quasi likelihood estimates in many cases. Details of this approach are given for two particular generalized linear models; simulation results illustrate the usefulness of the theory for these models.     

失业与就业:一个世界性的难题

在世界经济日益一体化的今天，综观全球，人们会惊奇地发现，失业———这一伴随资本主义生产方式和市场经济的产生而出现的社会现象，已经成为一个困扰许多国家经济和社会发展的严重问题。从西欧到东欧，从北美到南美，从发达国家到发展中国家，失业与就业成为人们关注的焦点，“创造就业机会”、“制定反失业对策”成为各国经济政策的首要目标。可以毫不夸张地说，当今世界几乎所有的国家，都不得不面对失业与就业这一世界性的难题。本文试图从宏观的角度，对世界各国不同类型的失业，以及主要资本主义国家治理失业与贫困问题的社会政策，进行分析与考察，从中总结出一些带有普遍性规律性的问题，为我国实施再就业工程提供决策思路和有益借鉴     

民主化的基础性条件之分析

今天,民主已成为普适的价值,但并不意味着民主化的过程已经终结,很多非民主国家仍然面临着转型。民主化只有在某些条件成熟的情况下才有可能发生,通过对经济发展、政治文化、外部力量、反对运动、精英互动、领袖推动等民主化的基础性条件的分析,可以更好地理解它们与民主化之间的关系。     

工程师职业视角下的工程技术人才培养改革探索——以重庆文理学院为例

工科院校是工程师的摇篮,高等工程教育重在为社会培养优秀工程技术人才。通过分析当前我国高等工程教育改革的背景、存在的主要问题与不足、国际高等工程教育的发展历程与经验等,探索基于工程师职业视角的以工程能力和工程师职业素养为导向的工程技术人才培养模式与路径,从而培养学生具备基础扎实、思想朴实、为人诚实、工作踏实等品行,培养学生具备面向未来的思考能力、面向需求的学习能力、面向实际的动手能力、面向问题的分析能力、面向工程的设计能力、面向工作的交流能力、面向社会的适应能力等工程素质。     

中国资本外逃的测算与防范

资本外逃是金融危机产生的催化剂与蔓延的助动器 ,对一国经济安全构成极大威胁。通过介绍资本外逃及其测算模型 ,运用间接法对我国资本外逃进行估算 ,结果显示中国存在严重的资本外逃现象。在详细分析中国资本外逃的产生原因之后 ,具体提出了一些相关防范对策     

再论同义词

一、现在对同义词的界定是不恰当的 ,应该把意义相同和相近的词分开 ,并给同义词以应有的地位 ;二、词的意义内容 ,即词的词汇意义及其概念对应性 ,以及语法意义和色彩意义是确定同义词的标准和理论根据 ;三、同义词有完全同义词、不完全同义词、义项交叉同义词、言语同义词四个类型 ,并各具不同的性质特点 ;四、古今词和词素也可形成同义关系 ,在这种情况下 ,色彩意义起着不可或缺的作用。     

简析政治学中的研究方法

政治学中的研究方法制约着研究者的观察视野，规定着研究者的思维活动，影响着研究者对研究对象把握的深度和广度，最终决定着研究者解决实际问题的正确程度，所以对研究方法的分析可以帮助我们更好地进行政治学研究。     

A Range-Based Multivariate Stochastic Volatility Model for Exchange Rates

In this paper we present a parsimonious multivariate model for exchange rate volatilities based on logarithmic high-low ranges of daily exchange rates. The multivariate stochastic volatility model decomposes the log range of each exchange rate into two independent latent factors, which could be interpreted as the underlying currency specific components. Owing to the empirical normality of the logarithmic range measure the model can be estimated conveniently with the standard Kalman filter methodology. Our results show that our model fits the exchange rate data quite well. Exchange rate news seems to be currency specific and allows identification of currency contributions to both exchange rate levels and exchange rate volatilities.