森林可持续经营的政策支持体系——亚太区域示范林项目中国临安示范林实践

运用参与性诊断(即PRRA)方法对临安示范林地区的森林经营主要政策进行了诊断分析,找出了现行政策存在的问题,如:政策环境欠佳,产权政策不到位,税费政策不合理,林业产品生产、加工和销售脱节,森林生态效益补偿政策欠规范、不合理等.同时,运用参与性设计的方法对若干主要政策进行专项设计,并在此基础上,从优化森林可持续经营的政策环境和规范政策系统运行两方面入手,提出一套科学、合理和有效的适合当地水平的森林可持续经营综合设计方案,以促进示范林网络的发展.     

Dairy Farm Survival in a Metropolitan Area: Dutchess County,New York, 1984–19901

Abstract The effect of nonfarm development on dairy farm survival in New York's highly developed lower Hudson Valley is analyzed. The major hypothesis is that significant losses of dairy farms during this period are the result of urban development pressures. Contrary to this hypothesis, however, the bivariate and multivariate analyses of data from a mail survey of all commercial dairy operators in Dutchess County as of 1984 and industry survivors, exiters, and new entrants through 1990 demonstrate that nonfarm development has a negligible effect on dairy farm survival; rather, survival is significantly affected by age of operator and by family disruption. Thus, demographic and family process factors are found to be more powerful determinants of dairy farm survival in this particular metropolitan context.     

A NOTE ON EVANESCENT PROCESSES

This note examines the connection between μ-invariant measures for the transition function of a continuous-time Markov chain and those of its q-matrix, Q. The major result establishes a necessary and aufficient condition for a convergent μ-invariant measure for Q to be μ-inhant for the minimal transition function, P, under the assumption that P is honest. This corrects Theorem 6 of Vere-Jones (1969) and the first part of Corollary 1 of Pollett (1986), both of which assert that the above conclusion holds in the absence of this condition. The error was pointed out by E.A. van Doom (1991) and the counterexample which be presented provides the basis for the present arguments. In determining where the error occurred in the original proof, we are able to identify a simple sufficient condition for μ-invariance.     

对林业税费的经济学分析

该文运用经济学的基本工具———供给和需求曲线 ,以商品林为研究对象 ,探讨了林业税费的作用机理和内涵。该文认为商品林生产具有正的外部性 ,市场失灵使生产者将不能提供社会真正所需要的商品林数量。在封闭的市场条件下 ,林业税费会直接成为价格的一部分 ,商品林生产者应当能够获得正常利润 ,与税费高低无关 ,但会使一部分林地退出生产。林业补贴是一种负的林业税收。在开放市场经济条件下 ,国内商品林供应量低于没有林业税收时的商品林供应量 ,更低于考虑社会生态需求时的商品林供应量 ,造成巨大的社会福利损失 ,应减免林业税费、增加林业扶持、取消价格管制。该文进一步研究了与林业税费密切相关的森林采伐限额政策 ,认为对商品林应该完全取消采伐限额政策     

浅谈外语学院教学管理工作

教学管理是教学工作运转的支柱,教学管理的优劣影响着教学质量。该文介绍了外语学院教学管理工作的基本内容,包括教学任务的布置落实、教学检查、教学文件的建设、学籍管理,以及结合学院的实际情况完善考试制度、制定成绩管理细则和考试结果奖励办法等。     

Design optimization using ANOVA

This paper describes the design optimization of a robot sensor used for locating 3-D objects employing the Taguchi method in a computer simulation scenario. The location information from the sensor is to be utilized to control the movements of an industrial robot in a 'pick-and-place' or assembly operation. The Taguchi method, which is based on the Analysis-of-Variance (ANOVA) approach, is utilized to improve the performance of the sensor over a wider operating range. A review of the Taguchi method is presented along with step-by-step implementation details to identify and optimize the design parameters of the sensor. The method allows us to gauge the impact of various interactions present in the sensor system exclusively and permits us to single out those factors that have a dominant influence on the overall performance of the sensor. The investigation suggests that the Taguchi method is a more structured and efficient approach for achieving a robust design compared with the classical full factorial design approach.     

Empirical likelihood confidence intervals for the mean of a population containing many zero values

If a population contains many zero values and the sample size is not very large, the traditional normal approximation‐based confidence intervals for the population mean may have poor coverage probabilities. This problem is substantially reduced by constructing parametric likelihood ratio intervals when an appropriate mixture model can be found. In the context of survey sampling, however, there is a general preference for making minimal assumptions about the population under study. The authors have therefore investigated the coverage properties of nonparametric empirical likelihood confidence intervals for the population mean. They show that under a variety of hypothetical populations, these intervals often outperformed parametric likelihood intervals by having more balanced coverage rates and larger lower bounds. The authors illustrate their methodology using data from the Canadian Labour Force Survey for the year 2000.     

Implied Preference for Seismic Design Level and Earthquake Insurance

Seismic risk can be reduced by implementing newly developed seismic provisions in design codes. Furthermore, financial protection or enhanced utility and happiness for stakeholders could be gained through the purchase of earthquake insurance. If this is not so, there would be no market for such insurance. However, perceived benefit associated with insurance is not universally shared by stakeholders partly due to their diverse risk attitudes. This study investigates the implied seismic design preference with insurance options for decisionmakers of bounded rationality whose preferences could be adequately represented by the cumulative prospect theory (CPT). The investigation is focused on assessing the sensitivity of the implied seismic design preference with insurance options to model parameters of the CPT and to fair and unfair insurance arrangements. Numerical results suggest that human cognitive limitation and risk perception can affect the implied seismic design preference by the CPT significantly. The mandatory purchase of fair insurance will lead the implied seismic design preference to the optimum design level that is dictated by the minimum expected lifecycle cost rule. Unfair insurance decreases the expected gain as well as its associated variability, which is preferred by risk-averse decisionmakers. The obtained results of the implied preference for the combination of the seismic design level and insurance option suggest that property owners, financial institutions, and municipalities can take advantage of affordable insurance to establish successful seismic risk management strategies.     

Social Antecedents of Medical Fraud and Over-Servicing: What Makes A Doctor Criminal?

Medical fraud and overservicing are estimated to cost the Australian community between $130 and $200 million per annum, a figure far greater than the national cost of burglary and almost the same as the total property loss from all conventional crime. An examination of the social antecedents of medical fraud and overservicing suggests that the predisposition of some doctors to engage in these practices occurs because of the following: (1) medical training and professional socialization that orientate student doctors away from altruistic health issues towards narrower self-interested professional concerns; (2) career expectations of a high pattern of material consumption that are often frustrated by an increasingly competitive medical market place; and (3) professional medical organizations that lobby for national health policies which reflect the mercenary self-interest of doctors rather than the health interest of the nation.     

Non-ignorable missing covariate data in survival analysis: a case-study of an International Breast Cancer Study Group trial

Summary.  Non-ignorable missing data, a serious problem in both clinical trials and observational studies, can lead to biased inferences. Quality-of-life measures have become increasingly popular in clinical trials. However, these measures are often incompletely observed, and investigators may suspect that missing quality-of-life data are likely to be non-ignorable. Although several recent references have addressed missing covariates in survival analysis, they all required the assumption that missingness is at random or that all covariates are discrete. We present a method for estimating the parameters in the Cox proportional hazards model when missing covariates may be non-ignorable and continuous or discrete. Our method is useful in reducing the bias and improving efficiency in the presence of missing data. The methodology clearly specifies assumptions about the missing data mechanism and, through sensitivity analysis, helps investigators to understand the potential effect of missing data on study results.