关于构建多元化的民营企业激励机制的思考

有效激励机制的建立是保证民营企业保值、增值,实现健康发展的必要条件。推进企业体制、技术以及管理创新,是我国加入WTO后对民营企业改革与发展提出的新要求,也是民营企业克服自身存在的弊端、发挥高素质人才作用、提高市场竞争力的重要保障。相信通过建立多元化的激励机制加之以完善的经营管理,我国的民营企业一定会健康发展并在激烈的市场竞争中取胜。     

Individual differences in numerical representations of risk in health decision making: A fuzzy-trace theory approach

Fuzzy-trace theory predicts that decisionmakers process numerical information about risk at multiple levels in parallel: the simplest level, nominal (categorical some-none) gist, and at more fine-grained levels, involving relative comparison (ordinal less-more gist) and exact quantities (verbatim representations). However, little is known about how individual differences in these numerical representations relate to judgments and decisions, especially involving health tradeoffs and relative risks. To investigate these differences, we administered measures of categorical and ordinal gist representations of number, objective numeracy, and intelligence in two studies (Ns = 978 and 956). In both studies, categorical and ordinal gist representations of number predicted risk judgments and decisions beyond objective numeracy and intelligence. Participants with higher scores in categorical gist were more likely to choose options to avoid cancer recurrence risks; those who were higher in ordinal gist of numbers were more likely to discriminate relative risk of skin cancer; and those with higher scores in objective numeracy were more likely to choose options that were numerically superior overall in terms of relative risk of skin cancer and of genetic risks of breast cancer (e.g., lower numerical probability of cancer). Results support parallel-processing models that assume multiple representations of numerical information about risk, which vary in precision, and illustrate how individual differences in numerical representations are relevant to tradeoffs and risk comparisons in health decisions. These representations cannot be reduced to one another and explain psychological variations in risk processing that go beyond low versus high levels of objective numeracy.     

Some applications of nonlinear and non-Gaussian state–space modelling by means of hidden Markov models

Nonlinear and non-Gaussian state–space models (SSMs) are fitted to different types of time series. The applications include homogeneous and seasonal time series, in particular earthquake counts, polio counts, rainfall occurrence data, glacial varve data and daily returns on a share. The considered SSMs comprise Poisson, Bernoulli, gamma and Student-t distributions at the observation level. Parameter estimations for the SSMs are carried out using a likelihood approximation that is obtained after discretization of the state space. The approximation can be made arbitrarily accurate, and the approximated likelihood is precisely that of a finite-state hidden Markov model (HMM). The proposed method enables us to apply standard HMM techniques. It is easy to implement and can be extended to all kinds of SSMs in a straightforward manner.     

重尾索赔条件下现代风险模型的破产概率估计:多险种混合情形

破产概率是非寿险保险风险理论的核心问题。与经典的Cramér-Lundberg模型相比, 由Li Zehui等建立的现代风险模型更为准确地描述了非寿险保险运营的主要特征, 对现实保险业务具有较好的解释力。本文基于现代风险模型, 考虑保险公司多个险种混合经营这一更为现实的情形, 在索赔额服从正则尾分布条件下获得了破产概率的渐近等价估计。我们发现, 在具有大额索赔特征的多个险种混合的条件下, 公司面临的极端索赔风险将由索赔额分布尾部最厚的那些险种决定, 而索赔额分布尾部相对较薄的那些险种的影响作用将被淹没。该结论的有效性可用MATLAB数值模拟得到理想的验证。本文结果是对风险模型研究的重要推广, 也为多险种混合情形下保险公司的风险控制与初始保证金界定提供了依据。     

Volume estimation by monte carlo methods *

In estimating a multiple integral, it is known that Monte Carlo methods are more efficient than analytical techniques when the number of dimensions is beyond seven. In general, the sample-mean method is better than the hit-or-miss Monte Carlo method. However, when the volume of a domain in a high-dimensional space is of interest, the hit-or-miss method is usually preferred. It is because of the difficulty in generalizing the sample-mean method for the computation of the volume of a domain. This paper develops a technique to make such a generalization possible. The technique can be interpreted as a volume-preserving transformation procedure. A volume-preserving transformation is first performed to transform the concerned domain into a hypersphere. The volume of the domain is then evaluated by computing the volume of the hypersphere.     

大气边界层中天线风载特性的数值分析

基于Reynolds时均N-S方程和RSM湍流模型,以大气边界层中具体地貌的风速剖面为入口边界条件,对某一车载雷达天线的风载进行数值模拟,得到天线的阻力系数;并与目前天线设计采用的均一风速为边界条件的计算结果进行比较,研究了工作高度、风速、地貌等因素对大气边界层中天线风载特性的影响。计算结果表明,大气边界层中天线的阻力系数随工作高度及风速的增加而增大;而地面粗糙度对天线阻力系数的影响则由天线相对于标准参考高度的位置决定。     

最优层界确定方法综述

回顾了分层抽样中层界最优解确定的解析方法和迭代方法,对比并评析了不同方法在计算繁杂程度、有效性等方面的优劣,针对偏态总体分层界限最优解的确定,对几何分层法提出了一种改进思路的变异系数法,并提出了进一步研究最优层界最优解确定方法的思路。     

用数值模拟方法研究气井产量递减

运用数值模拟软件的单井模拟器,建立了异常高压气藏气井和正常压力气藏气井产量递减的单井模型,得到了异常高压气藏气井和正常压力气藏气井的产量递减数据。根据这些产量递减数据,由两种产量递减自动拟合模型分别计算了异常高压气藏气井和正常压力气藏气井的产量递减参数、地层物性参数(k_gh、k_g/Φ)及地质储量。为了提高计算精度,采用根据拟稳态的产量递减数据(去掉不稳定的递减数据)来反求地层参数和地质储量,并根据自动拟合模型的检验标准对计算结果进行了检验。结果表明,由两种产量递减自动拟合模型计算的产量递减参数和地质储量与数值模拟的计算结果非常吻合,再次证明了这两种产量递减模型的适用性。     

强吹除雪气固两相流流场数值模拟分析

为研究和分析机场强吹除雪气固两相流流场的压力、速度和雪粒运移规律,依据离散粒子模型建立了强吹除雪气固两相流方程,并采用计算流体力学数值分析方法,对机场强吹除雪的气固两相流流场进行数值模拟分析,得到了气固两相流流场的压力、速度分布曲线和不同时刻下的雪粒分布规律．数值分析结果表明,气固两相流场发展过程迅速,速度分布符合射流理论,湍流强度变化剧烈．数值模拟得到强风强吹除雪的吹雪时间为2．5s．     

Multimedia Biographies: A Reminiscence and Social Stimulus Tool for Persons with Cognitive Impairment

The multimedia biography tells the story of the life of an elderly person with a cognitive impairment in motion picture format. The multimedia biography combines family photographs, film clips, audio narration, and music. It is intended to be screened on an ongoing basis to provide spaces for reminiscence and communication between cognitively impaired persons and their families. Using a production process in which we collaborated with family caregivers, we created 12 multimedia biographies for persons having Alzheimer's disease or mild cognitive impairment. This article describes our production and screening processes. We also share lessons learned from the multimedia biography research to assist practitioners, families, or researchers who wish to use similar technologies and processes for eliciting and sharing life stories.