高密度可读写DVD技术分析

对高密度可读写DVD光盘所采用的相变记录技术、增加记录密度的方法、轨道格式的确定、前置技术、ZCLV转动控制技术、绿色和兰色激光技术等关键技术作了介绍和分析。     

抗氧化修饰低密度脂蛋白单克隆抗体的制备及其初步应用

用氧化修饰脂蛋白（ａ）对Ｂａｌｂ／ｃ小鼠免疫．利用淋巴细胞杂交瘤技术制备了鼠抗人氧化修饰低密度脂蛋白（ｏｘｉｄａｔｉｖｅｌｙｍｏｄｉｆｉｅｄｌｏｗｄｅｎｓｉｔｙｌｉｐｏｐｒｏｔｅｉｎ，ｏｘＬＤＬ）单克隆抗体细胞株．以单克隆抗体包被建立了酶联免疫吸附（ＥＬＩＳＡ）双抗夹心法．用此法对１０例冠心病患者、６例其他心脏病患者、１０例正常健康人血浆中ｏｘＬＤＬ的含量进行了测定．结果表明，冠心病患者血浆中ｏｘＬＤＬ水平明显高于其他心脏病组和正常对照组．本实验所建立的方法对诊断冠心病患者血浆中的ｏｘＬＤＬ具有重要意义     

Error reduction in density estimation under shape restrictions

For the problems of nonparametric estimation of nonincreasing and symmetric unimodal density functions with bounded supports we determine the projections of estimates onto the convex families of possible parent densities with respect to the weighted integrated squared error. We also describe the method of approximating the analogous projections onto the respective density classes satisfying some general moment conditions. The method of projections reduces the estimation errors for all possible values of observations of a given finite sample size in a uniformly optimal way and provides estimates sharing the properties of the parent densities.     

Modified weighted squared error estimation procedures with special emphasis on the stable laws

Two families of parameter estimation procedures for the stable laws based on a variant of the characteristic function are provided. The methodology which produces viable computational procedures for the stable laws is generally applicable to other families of distributions across a variety of settings. Both families of procedures may be described as a modified weighted chi-squared minimization procedure, and both explicitly take account of constraints on the parameter space. Influence func-tions for and efficiencies of the estimators are given. If x₁, x₂, …x_n random sample from an unknown distribution F , a method for determining the stable law to which F is attracted is developed. Procedures for regression and autoregres-sion with stable error structure are provided. A number of examples are given.     

Cross-Validated Assessments of Test Scoring Models

On a multiple choice test in which each item has r alternative options, a given number c of which are correct, various scoring models have been proposed. In one case the test-taker is allowed to choose any size solution subset and he/she is graded according to whether the subset is small and according to how many correct answers the subset contains. In a second case the test-taker is allowed to select only solution subsets of a prespecified maximum size and is graded as above. The first case is analogous to the situation where the test-taker is given a set of r options with each question; each question calls for a solution which consists of selecting that subset of the r responses which he/she believes to be correct. In the second case, when the prespecified solution subset is restricted to be of size at most one, the resulting scoring model corresponds to the usual model, referred to below as standard. The number c of correct options per item is usually known to the test-taker in this case.

Scoring models are evaluated according to how well they correctly identify the total scores of the individuals in the class of test-takers. Loss functions are constructed which penalize scoring models resulting in student scores which are not associated with the students true (or average) total score on the exam. Scoring models are compared on the basis of cross-validated assessments of the loss incurred by using each of the given models. It is shown that in many cases the assessment of the loss for scoring models which allow students the opportunity to choose more than one option for each question are smaller than the assessment of the loss for the standard scoring model.     

Bayesian Approaches to Nonparametric Estimation of Densities on the Unit Interval

This paper investigates nonparametric estimation of density on [0, 1]. The kernel estimator of density on [0, 1] has been found to be sensitive to both bandwidth and kernel. This paper proposes a unified Bayesian framework for choosing both the bandwidth and kernel function. In a simulation study, the Bayesian bandwidth estimator performed better than others, and kernel estimators were sensitive to the choice of the kernel and the shapes of the population densities on [0, 1]. The simulation and empirical results demonstrate that the methods proposed in this paper can improve the way the probability densities on [0, 1] are presently estimated.     

几种药物对降低尿素分解液中氨浓度的试验

在相同的外界条件下,在相同浓度的等量脲酶尿素液中加入脲酶抑制剂、吸附剂,在不同时间进行pH值和NH_3—N值的测定,研究各药物对降低氨浓度的强弱。结果表明:各试验组氨浓度极显著低于对照组(P<0.01);在添加剂量相同的情况下,脲酶抑制剂和药用炭的作用较强(P<0.05),二者之间差异不显著(P>0.05);浮石、滑石粉、BIO—ADE作用较弱且三者之间差异不显著(P>0.05),三者中以选择滑石粉较好(价格较便宜)。     

Uniform in Bandwidth Estimation of Integral Functionals of the Density Function

Abstract. We apply recent results on local U‐statistics to obtain uniform in bandwidth consistency and central limit theorems for some commonly used estimators of integral functionals of density functions.     

Power of the Neyman Smooth Test for Evaluating Multivariate Forecast Densities

We compare and investigate Neyman's smooth test, its components, and the Kolmogorov-Smirnov (KS) goodness-of-fit test for testing the uniformity of multivariate forecast densities. Simulations indicate that the KS test lacks power when the forecast distributions are misspecified, especially for correlated sequences of random variables. Neyman's smooth test and its components work well in samples of size typically available, although there sometimes are size distortions. The components provide directed diagnosis regarding the kind of departure from the null. For illustration, the tests are applied to forecast densities obtained from a bivariate threshold model fitted to high-frequency financial data.     

LDPC编码的最优化HARQ方案研究

使用高斯近似和最优化理论的方法,对基于LDPC码度分布的混合自动重发请求(HARQ)方案的性能进行了研究。研究表明,根据LDPC编码的度分布和初始信道条件,能够确定一个编码码字中各个度数的比特所对应的最优的重发比例,如果按照该比例进行重发,重发功率的效率能够最大化。计算结果显示基于LDPC码度分布的混合自动重发请求方案具有最优的重发比例,是一种最优化方案。