供应链风险产生根源的理论分析

根据现有文献研究成果,结合实际调研分析,将供应链风险因素整理归纳为系统风险、供应风险、物流风险、信息风险、财务风险、管理风险、需求风险和环境风险。每种风险因素并非独立存在,而是相互影响、互为根源。其非线性叠加结果将会放大供应链整体风险水平。因此,必须认识到其存在的风险,只有在明确各种风险产生根源的基础上,才能恰当地制定、选择和采取有效措施,规避风险,确保供应链整体绩效稳步提高。     

中日城市供水系统静态效率的对比研究

文章运用DEA方法，评价了北京、东京、上海以及横滨等城市2003年-2005年间供水系统的静态效率，发现日本三个城市供水系统的效率要高于中国三个城市的效率，造成这种状况的原因主要在于中国的水价体系还不够完善，供水企业收益不能完全回收其成本。     

Markov chain Monte Carlo methods for high dimensional inversion in remote sensing

Summary.  We discuss the inversion of the gas profiles (ozone, NO₃, NO₂, aerosols and neutral density) in the upper atmosphere from the spectral occultation measurements. The data are produced by the 'Global ozone monitoring of occultation of stars' instrument on board the Envisat satellite that was launched in March 2002. The instrument measures the attenuation of light spectra at various horizontal paths from about 100 km down to 10–20 km. The new feature is that these data allow the inversion of the gas concentration height profiles. A short introduction is given to the present operational data management procedure with examples of the first real data inversion. Several solution options for a more comprehensive statistical inversion are presented. A direct inversion leads to a non-linear model with hundreds of parameters to be estimated. The problem is solved with an adaptive single-step Markov chain Monte Carlo algorithm. Another approach is to divide the problem into several non-linear smaller dimensional problems, to run parallel adaptive Markov chain Monte Carlo chains for them and to solve the gas profiles in repetitive linear steps. The effect of grid size is discussed, and we present how the prior regularization takes the grid size into account in a way that effectively leads to a grid-independent inversion.     

协同运输管理运行机制研究

协同运输管理是在CPFR基础上发展起来的一种供应链管理方法。它通过降低供应链中的运输成本、缩短商品交付时间和提高准时交货率,实现供应链价值的最大化。协同运输管理的有效实施,需要建立完善的运行机制,包括动力机制、约束机制、实际行为和惩罚机制,并配备相应的软硬件条件。     

进化的精神和生活的道德——鲁迅与契诃夫人生哲学比较论

面对着现实困境的鲁迅与契诃夫都珍视人生的价值,强调人的自我意识与主体力量,但是由于文化传统与历史背景的不同,他们的人生哲学各具特色。鲁迅的人生哲学体现了战斗的进化精神,契诃夫的人生哲学探讨了超脱的生活道德。     

BAYESIAN SUBSET SELECTION AND MODEL AVERAGING USING A CENTRED AND DISPERSED PRIOR FOR THE ERROR VARIANCE

This article proposes a new data‐based prior distribution for the error variance in a Gaussian linear regression model, when the model is used for Bayesian variable selection and model averaging. For a given subset of variables in the model, this prior has a mode that is an unbiased estimator of the error variance but is suitably dispersed to make it uninformative relative to the marginal likelihood. The advantage of this empirical Bayes prior for the error variance is that it is centred and dispersed sensibly and avoids the arbitrary specification of hyperparameters. The performance of the new prior is compared to that of a prior proposed previously in the literature using several simulated examples and two loss functions. For each example our paper also reports results for the model that orthogonalizes the predictor variables before performing subset selection. A real example is also investigated. The empirical results suggest that for both the simulated and real data, the performance of the estimators based on the prior proposed in our article compares favourably with that of a prior used previously in the literature.     

优化我国能源结构的基本对策

我国能源结构存在着以煤炭能源为主、能源效率低、地区性能源短缺以及结构性污染等问题,严重制约着国民经济的发展和产业结构的提升.强化煤炭能源的基础地位、充分利用天然气、石油资源、发展可再生能源、充分利用国内外两种资源两个市场、调整区域能源结构等是优化我国能源结构的基本对策.     

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.     

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.     

论新文学思潮与新文学流派的动态关系

新文学思潮与新文学流派之间因果莫辨、源流纠缠的动态关系 ,充分证明了近百年来新文学思潮与新文学流派本身非线性、非对称的生存状态。所谓非线性与非对称 ,其实质就是不稳定性和不成熟性 ,它们直接制约着新文学近百年发展进程 ,使之在历时态和共时态上始终呈现出某种程度的不良生存状态和发展趋势。