试论苏轼认同陶渊明却终未归隐之原因

苏轼一生无论居庙堂之高 ,或处江湖之远 ,皆追求心灵自由 ,达到了物我同一、高凡绝尘的理想境界。该文认为苏轼慕陶、学陶 ,作《和陶诗》12 0余首以明志 ,却始终未能像陶渊明那样挂冠而去 ,归隐田园。究其原因 ,不外乎生活时代、出身背景、思想体系、入仕经历等方面的差异     

Nonparametric estimation of the conditional distribution function in a semiparametric censorship model

In this paper we propose a new nonparametric estimator of the conditional distribution function under a semiparametric censorship model. We establish an asymptotic representation of the estimator as a sum of iid random variables, balanced by some kernel weights. This representation is used for obtaining large sample results such as the rate of uniform convergence of the estimator, or its limit distributional law. We prove that the new estimator outperforms the conditional Kaplan–Meier estimator for censored data, in the sense that it exhibits lower asymptotic variance. Illustration through real data analysis is provided.     

Beggars can be choosers: Resource scarcity,dynamism, search activities,and their joint impact on performance

Research on firm search stresses the need for firms to adapt and align concurrently with their environment to optimize the ability to sense and seize opportunities for sustained performance. We postulate resource scarcity as an important contingency factor for the search-performance relationship, and assess its joint influence with high and low dynamism. Using a dataset spanning 23 years, we examine the performance implications of combinations of internal and external exploratory and exploitative search in resource-scarce environments, under conditions of high and low dynamism. We find that resource scarcity is an important condition for performance stemming from exploratory and exploitative search: even under conditions that involve low dynamism, but joined with resource scarcity, firms may benefit from pursuing exploratory and exploitative knowledge simultaneously.     

Patterns and Drivers of Emigration of the Turkish Second Generation in the Netherlands

European Journal of Population - Using unique longitudinal data from the Dutch population registers, this study investigates the patterns and drivers of emigration of the Turkish second generation...     

Institutional Fleecing: The Slow Death of Dutch Provinces

Many theories on organizational change depart from the assumption of change for the better, that is, change in order to gain a stronger position in relation to its competitors, to become more effective or efficient, or at least to improve the organization. It is our idea that the theories developed on this basis are biased. Contrasting to this dominant approach, this article gives a longitudinal analysis of the development in an organization in decline. It is directed at explaining the downfall of a Dutch province. In the medieval empire of Charlemagne it was one of the most powerful duchies of Europe. Later it became one of the seven provinces in the powerful Dutch Republic, and nowadays it has lost nearly all its tasks and functions. Departing from neo-institutional theory this paper seeks the major causes for this downfall and specifies some of the relations in the theoretical model of punctuated equilibrium. It concludes that the historical institutional dynamics can be seen as a self-enforcing process in which punctuations can be explained by the increasing distance between individual preferences within the organization, and the pressures originating from developments in the environment.Dr. M.S. de Vries is professor in Public Administration at the Radboud University Nijmegen. Address: Thomas van Aquinostraat 5 (room 5.1.56). P.O. Box 9108, 6500 HK Nijmegen, The Netherlands, tel;++31 24 3615691.     

民族精神决定汉语的价值取向--洪堡特语言学评介

本文根据洪堡特的《论人类语言结构的差异性及其对人类精神发展的影响》,从语言的界定与民族精神、语言的认识与世界观、语言的系统性与思维方式、语言的分类与创新等方面对汉语的形成和发展进行了剖析,并由此阐明了汉语在今后发展以及创新的见解。     

Improved Transferability of Data‐Driven Damage Models Through Sample Selection Bias Correction

Damage models for natural hazards are used for decision making on reducing and transferring risk. The damage estimates from these models depend on many variables and their complex sometimes nonlinear relationships with the damage. In recent years, data‐driven modeling techniques have been used to capture those relationships. The available data to build such models are often limited. Therefore, in practice it is usually necessary to transfer models to a different context. In this article, we show that this implies the samples used to build the model are often not fully representative for the situation where they need to be applied on, which leads to a “sample selection bias.” In this article, we enhance data‐driven damage models by applying methods, not previously applied to damage modeling, to correct for this bias before the machine learning (ML) models are trained. We demonstrate this with case studies on flooding in Europe, and typhoon wind damage in the Philippines. Two sample selection bias correction methods from the ML literature are applied and one of these methods is also adjusted to our problem. These three methods are combined with stochastic generation of synthetic damage data. We demonstrate that for both case studies, the sample selection bias correction techniques reduce model errors, especially for the mean bias error this reduction can be larger than 30%. The novel combination with stochastic data generation seems to enhance these techniques. This shows that sample selection bias correction methods are beneficial for damage model transfer.     

Flood Catastrophe Model for Designing Optimal Flood Insurance Program: Estimating Location‐Specific Premiums in the Netherlands

As flood risks grow worldwide, a well‐designed insurance program engaging various stakeholders becomes a vital instrument in flood risk management. The main challenge concerns the applicability of standard approaches for calculating insurance premiums of rare catastrophic losses. This article focuses on the design of a flood‐loss‐sharing program involving private insurance based on location‐specific exposures. The analysis is guided by a developed integrated catastrophe risk management (ICRM) model consisting of a GIS‐based flood model and a stochastic optimization procedure with respect to location‐specific risk exposures. To achieve the stability and robustness of the program towards floods with various recurrences, the ICRM uses stochastic optimization procedure, which relies on quantile‐related risk functions of a systemic insolvency involving overpayments and underpayments of the stakeholders. Two alternative ways of calculating insurance premiums are compared: the robust derived with the ICRM and the traditional average annual loss approach. The applicability of the proposed model is illustrated in a case study of a Rotterdam area outside the main flood protection system in the Netherlands. Our numerical experiments demonstrate essential advantages of the robust premiums, namely, that they: (1) guarantee the program's solvency under all relevant flood scenarios rather than one average event; (2) establish a tradeoff between the security of the program and the welfare of locations; and (3) decrease the need for other risk transfer and risk reduction measures.     

A Stochastic Model to Assess the Effect of Meat Inspection Practices on the Contamination of the Pig Carcasses

The objective of meat inspection is to promote animal and public health by preventing, detecting, and controlling hazards originating from animals. With the improvements of sanitary level in pig herds, the hazards profile has shifted and the inspection procedures no longer target major foodborne pathogens (i.e., not risk based). Additionally, carcass manipulations performed when searching for macroscopic lesions can lead to cross‐contamination. We therefore developed a stochastic model to quantitatively describe cross‐contamination when consecutive carcasses are submitted to classic inspection procedures. The microbial hazard used to illustrate the model was Salmonella, the data set was obtained from Brazilian slaughterhouses, and some simplifying assumptions were made. The model predicted that due to cross‐contamination during inspection, the prevalence of contaminated carcass surfaces increased from 1.2% to 95.7%, whereas the mean contamination on contaminated surfaces decreased from 1 logCFU/cm² to ?0.87 logCFU/cm², and the standard deviations decreased from 0.65 to 0.19. These results are explained by the fact that, due to carcass manipulations with hands, knives, and hooks, including the cutting of contaminated lymph nodes, Salmonella is transferred to previously uncontaminated carcasses, but in small quantities. These small quantities can easily go undetected during sampling. Sensitivity analyses gave insight into the model performance and showed that the touching and cutting of lymph nodes during inspection can be an important source of carcass contamination. The model can serve as a tool to support discussions on the modernization of pig carcass inspection.