中国文化的三次转型与中国比较文学源流

本文通过对中国文化史上的三次文化转型期：汉唐时期、近代鸦片战争时期及“五四”新文化运动时期、二十世纪末期的文化形态的考察,剖析了文化发展过程中由单一文化系统造成的自我设限──封闭模式到吸收他种系统之后文化走向解构──沟通──重构的规律,指出文化转型的积极意义与比较文学注重沟通、对话、交流的本质精神是契合的,实质上二者之间是互为前提、互为因果的互动关系。     

Retirement patterns in Hong Kong: a censored regression analysis

This paper provides an overview of retirement patterns in Hong Kong on the basis of limited data. A censored regression model is used to infer the retirement age from people‘s current retirement status and their current age. This model is equivalent to a restricted probit model, and the interpretation of parameters is straightforward. The results clearly show a negative income effect on the retirement decision. The retirement age seems to be positively related to lifetime earnings but negatively related to the rate of decline of earnings with age. JEL classification: C24, J14, J26 Received May 6, 1996 / Accepted February 5, 1997     

Comparative probability for conditional events: A new look through coherence

We study, from the standpoint of coherence, comparative probabilities on an arbitrary familyE of conditional events. Given a binary relation ·, coherence conditions on · are related to de Finetti's coherent betting system: we consider their connections to the usual properties of comparative probability and to the possibility of numerical representations of ·. In this context, the numerical reference frame is that of de Finetti's coherent subjective conditional probability, which is not introduced (as in Kolmogoroff's approach) through a ratio between probability measures.Another relevant feature of our approach is that the family & need not have any particular algebraic structure, so that the ordering can be initially given for a few conditional events of interest and then possibly extended by a step-by-step procedure, preserving coherence.     

Sensitivity of the Optimum to Perturbations of the Profit or Weight of an Item in the Binary Knapsack Problem

In the binary single constraint Knapsack Problem, denoted KP, we are given a knapsack of fixed capacity c and a set of n items. Each item j, j = 1,...,n, has an associated size or weight w_j and a profit p_j. The goal is to determine whether or not item j, j = 1,...,n, should be included in the knapsack. The objective is to maximize the total profit without exceeding the capacity c of the knapsack. In this paper, we study the sensitivity of the optimum of the KP to perturbations of either the profit or the weight of an item. We give approximate and exact interval limits for both cases (profit and weight) and propose several polynomial time algorithms able to reach these interval limits. The performance of the proposed algorithms are evaluated on a large number of problem instances.     

Quantitative Estimates of Risk for Noncancer Endpoints

While quantitative estimates of risk have been a standard practice in cancer risk assessment for many years, no similar practice is evident in noncancer risk assessment. We use two recent examples involving methylmercury and arsenic to illustrate the negative impact of this discrepancy on risk communication and cost-benefit analysis. We argue for a more balanced treatment of cancer and noncancer risks and suggest an approach for reaching this goal.     

Priority Setting for the Distribution of Localized Hazard Protection

We address the problem of distributing safety-enhancing devices across a region, where each identical device provides for only local protection of the population. The devices protect nonidentical sectors of the population. The sectors of population are exposed to nonidentical intensities of hazard. A method for the screening and prioritizing of needs for the protective devices is described. An approach of risk-benefit-cost analysis under uncertainty is recommended as follows. Measures of hazard intensity and population exposure are identified. Exogenous parameters that influence assessments of risks, benefits, and costs are identified. Uncertainties of the exogenous parameters are propagated by interval analysis. Several tiers of the plausibility of need for protection are identified. The tiers are useful in setting priorities for the distribution of the safety devices. The method is demonstrated in an engineering application to roadway lighting, but has implications for disaster preparedness, anti-terrorism, transportation safety, and other arenas of public safety.     

制造业设备维护与管理的相对有效性评估

在设备维护与管理的评估中引入数据包络分析,以此为核心构建了设备维护与管理相对有效性的评估方法。该方法在系统功能建模的基础上,全面分析了设备维护与管理作为服务系统的投入与产出构成,以数据包络分析为计算模型完成了设备维护与管理有效性的评估。该方法满足了设备维护与管理评估全面性和客观性的要求,其有效性和可信度通过在某石化企业的应用得到了验证。     

Risk Modeling, Assessment, and Management of Lahar Flow Threat

The 1991 eruption of Mount Pinatubo in the Philippines is considered one of the most violent and destructive volcanic activities in the 20th century. Lahar is the Indonesian term for volcanic ash, and lahar flows resulting from the massive amount of volcanic materials deposited on the mountain's slope posed continued post-eruption threats to the surrounding areas, destroying lives, homes, agricultural products, and infrastructures. Risks of lahar flows were identified immediately after the eruption, with scientific data provided by the Philippine Institute of Volcanology, the U.S. Geological Survey, and other research institutions. However, competing political, economic, and social agendas subordinated the importance of scientific information to policy making. Using systemic risk analysis and management, this article addresses the issues of multiple objectives and the effective integration of scientific techniques into the decision-making process. It provides a modeling framework for identifying, prioritizing, and evaluating policies for managing risk. The major considerations are: (1) applying a holistic approach to risk analysis through hierarchical holographic modeling, (2) applying statistical methods to gain insight into the problem of uncertainty in risk assessment, (3) using multiobjective trade-off analysis to address the issue of multiple decisionmakers and stakeholders in the decision-making process, (4) using the conditional expected value of extreme events to complement and supplement the expected value in quantifying risk, and (5) assessing the impacts of multistage decisions. Numerical examples based on ex post data are formulated to illustrate applications to various problems. The resulting framework from this study can serve as a general baseline model for assessing and managing risks of natural disasters, which the Philippines' lead agency-the National Disaster Coordinating Council (NDCC)-and other related organizations can use for their decision-making processes.     

On the Effect of Probability Distributions of Input Variables in Public Health Risk Assessment

A central part of probabilistic public health risk assessment is the selection of probability distributions for the uncertain input variables. In this paper, we apply the first-order reliability method (FORM)^(1–3) as a probabilistic tool to assess the effect of probability distributions of the input random variables on the probability that risk exceeds a threshold level (termed the probability of failure) and on the relevant probabilistic sensitivities. The analysis was applied to a case study given by Thompson et al. ⁽⁴⁾ on cancer risk caused by the ingestion of benzene contaminated soil. Normal, lognormal, and uniform distributions were used in the analysis. The results show that the selection of a probability distribution function for the uncertain variables in this case study had a moderate impact on the probability that values would fall above a given threshold risk when the threshold risk is at the 50th percentile of the original distribution given by Thompson et al. ⁽⁴⁾ The impact was much greater when the threshold risk level was at the 95th percentile. The impact on uncertainty sensitivity, however, showed a reversed trend, where the impact was more appreciable for the 50th percentile of the original distribution of risk given by Thompson et al. ⁴ than for the 95th percentile. Nevertheless, the choice of distribution shape did not alter the order of probabilistic sensitivity of the basic uncertain variables.