追寻先民印迹守护精神家园——长阳土家族非物质文化遗产的保护与利用对策

土家族是一个有着悠久历史和文化魅力的少数民族,历史的涤荡和土家族先民世世代代的创造与传承,孕育出绚丽多彩的民族民间文化。长阳作为土家先民巴人的发祥地,其保留下来的传统建筑艺术、婚丧习俗、饮食文化等无不成为土家民族民间文化中最为亮丽的色彩。     

膏状金霉素流变特性影响因素的试验研究

针对膏状金霉素物料，通过试验研究，在不同温度，不同时间，不同含水率条件下对该膏状物进行了较为广泛的剪切应力与速率之间关系的测试，分析，并由此推出该物料的一般性流变性质，从而为实现其合理输送，最终的喷雾干燥技术奠定一定的理论基础。     

运用表面光电压技术对半导体表面光电特性的研究

对运用表面光电压技术(SPS)对半导体材料光电性质的研究进行了综述,系统阐述了表面光电压谱(SPS)和场诱导表面光电压谱(FISPS)在测定半导体类型、表面态及其能级位置、表面电荷分布、半导体的能带隙等方面所表现出的优越性质.研究了半导体能带隙所表现出的特有性质.     

关注非物质文化遗产保护背景下的民俗文化与民俗学学科的命运

国家非物质文化遗产名录的门类是根据民俗学的范畴列出的,民俗的事象成为非物质文化遗产的主流。但国家非物质文化遗产的名录却出现了逻辑混乱问题:种属相混,如民俗本是一个大的概念,结果列在一个很小的范围里,这使得人们对民俗的概念产生了误解,保护活动在一定程度上伤害了民俗文化和民俗学学科。实际上,民俗的文化意义比非物质文化遗产保护名录更为重要,非遗保护只是民俗学的研究对象之一,而民俗学的研究既是学科发展的百年大计,更是文化建设的理论保障。非物质文化遗产保护工作与民俗学研究互为表里,相互促进,对中国文化建设带来积极影响。     

Robust nonparametric estimation with missing data

In this paper, under a nonparametric regression model, we introduce two families of robust procedures to estimate the regression function when missing data occur in the response. The first proposal is based on a local M$M$-functional applied to the conditional distribution function estimate adapted to the presence of missing data. The second proposal imputes the missing responses using the local M$M$-smoother based on the observed sample and then estimates the regression function with the completed sample. We show that the robust procedures considered are consistent and asymptotically normally distributed. A robust procedure to select the smoothing parameter is also discussed.     

A Bayesian approach to non-parametric monotone function estimation

Summary.  The paper proposes two Bayesian approaches to non-parametric monotone function estimation. The first approach uses a hierarchical Bayes framework and a characterization of smooth monotone functions given by Ramsay that allows unconstrained estimation. The second approach uses a Bayesian regression spline model of Smith and Kohn with a mixture distribution of constrained normal distributions as the prior for the regression coefficients to ensure the monotonicity of the resulting function estimate. The small sample properties of the two function estimators across a range of functions are provided via simulation and compared with existing methods. Asymptotic results are also given that show that Bayesian methods provide consistent function estimators for a large class of smooth functions. An example is provided involving economic demand functions that illustrates the application of the constrained regression spline estimator in the context of a multiple-regression model where two functions are constrained to be monotone.     

Optimality Of Some Two-Stage Sampling Methods

Two-stage sampling plans in which the estimator is computed from the second sample only, and has a guaranteed precision irrespective of the parameter value, are considered. We prove the following optimality property for existing strategies in binomial and Poisson populations: there exists no other

strategy, of the same form, that guarantees the same precision, without increasing the expected sample size for some parameter valucs. The method of proof is illustrnted by proving a similar result for normal populations     

A note on nonlinear regression for the autoregressive moving average with non-hd errors

Estimation by nonlinear regression of the parameters for the stationary and invertible autoregressive moving average (ARMA) model with mixing or martingale difference errors is considered. Simple proofs of consistency and asymptotic normality for the nonlinear least squares estimator are given by exploiting results from nonlinear estimation theory and mixing and mixingale theory.     

The Statistics of Simulating Chaos

When simulating a dynamical system, the computation is actually of a spatially discretized system, because finite machine arithmetic replaces continuum state space. For chaotic dynamical systems, the discretized simulations often have collapsing effects, to a fixed point or to short cycles. Statistical properties of these phenomena can be modelled with random mappings with an absorbing centre. The model gives results which are very much in line with computational experiments. The effects are discussed with special reference to the family of mappings f (x)=1-|1-2x|,x [0,1],1,<,,<,. Computer experiments show close agreement with predictions of the model.