从传统文化的角度解读安乐死

“安乐死”问题已经越来越引起世人的关注,由于涉及到种种道德问题,安乐死在我国难以取得合法地位。我国儒、道两家代表的传统生死观对死亡价值的肯定和重视,为安乐死的合法性提供了有说服力的理论依据。     

铸理论丰碑 展实践风采——评《中国共产党三代领导集体的民族理论与实践》

文章从学术研究水平、体系的完整性和创新性、研究方法的科学性和严谨性等方面论述了<中国共产党三代领导集体的民族理论与实践>一书的理论价值和实践意义.     

论审美理念系统的价值阶位

审美理念系统,以其特有的知识形式反映着人类审美价值的阶位需求。文中论述了人类最有代表性的五种阶位需求,认为虽然它们都反映一定的审美本质,但从生命与价值超越角度考虑,它们的内在思想特色和精神追求,还存在着很大的区别。     

美国价值观在英语谚语中的体现

文章分析了英语常用谚语的来源,并且通过大量的例证说明了英语常用谚语反映了美国不同时代的价值观及其变化,指出英语常用谚语不仅是美国文化的一部分,而且是了解美国文化的一面镜子.     

论社会事实与三种价值的内在关系

社会事实是人类的经验可以把握的一类基本事实。社会事实与自然事实的基本区别在于它的价值蕴含。因此,价值包容于社会事实之中,并且不同的价值决定了社会事实的不同特性。具体来说,依据与社会事实的不同关系,价值可以区分为这样三种类型:价值Ⅰ蕴含于精神性社会事物之中;价值Ⅱ是相应精神性社会事实的行为价值(应当);价值Ⅲ是存在于具有物质载体的社会事实中的价值。     

略论清官文学的成因及其价值评判

清官文学的成因是现实苦难的显影、民众诉说苦难心理以及文人拯救苦难情怀三者的合一。通过清官文 学的成因分析表明,清官文学的产生完全是文学自身生态机制作用下的结果。清官文学的合理价值集中表现为 它的现实品格。     

论诚实信用原则——以安全为价值取向的新分析

诚实信用原则是民法和合同法的基本原则。它要求民事主体诚信行使权利和履行义务,在民事活动中友好待人,从而维持当事人之间的利益以及当事人利益和社会利益之间的平衡。中国新的合同法已经把诚实信用原则作为基本的原则并规定了一系列适用规则。这表明我国的合同法已经向现代法律理念靠拢。本文讨论了诚实信用原则的概念和特征,相信这个原则可以根本改善现行司法,并扩大法官权利使他们更独立和自由地行为。“诚信和正义”是这一原则的升华和最高理想,它应该被运用到民事司法实践中。“安全”是诚实信用的一个重要价值,本文拟以安全为价值对诚实信用原则进行新的分析。     

Discrete time modelling of disease incidence time series by using Markov chain Monte Carlo methods

Summary.  A stochastic discrete time version of the susceptible–infected–recovered model for infectious diseases is developed. Disease is transmitted within and between communities when infected and susceptible individuals interact. Markov chain Monte Carlo methods are used to make inference about these unobserved populations and the unknown parameters of interest. The algorithm is designed specifically for modelling time series of reported measles cases although it can be adapted for other infectious diseases with permanent immunity. The application to observed measles incidence series motivates extensions to incorporate age structure as well as spatial epidemic coupling between communities.     

Towards Enhancement of the Economy of a Thermal Power Generating System through Prediction of Plant Efficiency

The plant ‘Heat Rate’ (HR) is a measure of overall efficiency of a thermal power generating system. It depends on a large number of factors, some of which are non-measurable, while data relating to others are seldom available and recorded. However, coal quality (expressed in terms of ‘effective heat value’ (EHV) as kcal/kg) transpires to be one of the important factors that influences HR values and data on EHV are available in any thermal power generating system. In the present work, we propose a prediction interval of the HR values on the basis of only EHV, keeping in mind that coal quality is one of the important (but not the only) factors that have a pronounced effect on the combustion process and hence on HR. The underlying theory borrows the idea of providing simultaneous confidence interval (SCI) to the coefficients of a p-th p(≥1) order autoregressive model (AR(p)). The theory has been substantiated with the help of real life data from a power utility (after suitable base and scale transformation of the data to maintain the confidentiality of the classified document). Scope for formulating strategies to enhance the economy of a thermal power generating system has also been explored.     

HEAVY-TAILED-DISTRIBUTED THRESHOLD STOCHASTIC VOLATILITY MODELS IN FINANCIAL TIME SERIES

To capture mean and variance asymmetries and time‐varying volatility in financial time series, we generalize the threshold stochastic volatility (THSV) model and incorporate a heavy‐tailed error distribution. Unlike existing stochastic volatility models, this model simultaneously accounts for uncertainty in the unobserved threshold value and in the time‐delay parameter. Self‐exciting and exogenous threshold variables are considered to investigate the impact of a number of market news variables on volatility changes. Adopting a Bayesian approach, we use Markov chain Monte Carlo methods to estimate all unknown parameters and latent variables. A simulation experiment demonstrates good estimation performance for reasonable sample sizes. In a study of two international financial market indices, we consider two variants of the generalized THSV model, with US market news as the threshold variable. Finally, we compare models using Bayesian forecasting in a value‐at‐risk (VaR) study. The results show that our proposed model can generate more accurate VaR forecasts than can standard models.