Remove unwanted variation retrieves unknown experimental designs

Remove unwanted variation (RUV) is an estimation and normalization system in which the underlying correlation structure of a multivariate dataset is estimated from negative control measurements, typically gene expression values, which are assumed to stay constant across experimental conditions. In this paper we derive the weight matrix which is estimated and incorporated into the generalized least squares estimates of RUV-inverse, and show that this weight matrix estimates the average covariance matrix across negative control measurements. RUV-inverse can thus be viewed as an estimation method adjusting for an unknown experimental design. We show that for a balanced incomplete block design (BIBD), RUV-inverse recovers intra- and interblock estimates of the relevant parameters and combines them as a weighted sum just like the best linear unbiased estimator (BLUE), except that the weights are globally estimated from the negative control measurements instead of being individually optimized to each measurement as in the classical, single measurement BIBD BLUE.     

欧盟最新技术转让协议竞争规则研究

在知识经济时代,为了避免重复研发,并使技术的投入产出最大化,技术转让成为企业间的一项重要的交易内容。但是在促进技术创新的知识产权制度在保护创新技术的同时,在技术转让的过程中也会造成技术垄断和市场垄断,给市场公平竞争带来损害。欧盟是技术转让市场频繁和活跃的地区,随着经济的发展,欧盟修改了规制知识产权技术转让协议的竞争规则,通过以技术转让协议集体豁免条例为主的考察方法,全面、深入地分析相关竞争规则的立法背景、主要内容、特点及实践中的运行状况,特别是新协议中的安全港制度、经济分析的方法,为我国参与欧盟技术转让的企业提供借鉴。     

中国古代对颗粒物质特性的认知与应用

对颗粒物质特性的应用在人民生活中起着不可或缺的作用,在我国古代科技实用中更有着不可忽略的地位。以现代颗粒物质力学进展为基础,着重探究颗粒物质在生活实践中的一系列应用实例,借以考证中国古代科学对颗粒物质特性较深层次的认知,从多个角度分析、理解中国古代科学文化中的颗粒学部分的实用价值以及对今后继续探索颗粒物质领域的启示与推动作用。     

后危机时代我国对外贸易摩擦问题研究——与发达国家、发展中国家贸易摩擦的比较研究

2008年全球性金融危机爆发后,世界经济进入衰退期,虽然目前全球经济有企稳回升迹象但全球国际贸易环境恶化,某些国家贸易保护主义抬头。作为世界第一大出口国,中国更是面临着日益严峻的国际贸易环境,在与发达国家贸易摩擦持续的同时,与发展中国家的贸易摩擦也不断升级。因此,对中国与发达国家、发展中国家的贸易摩擦进行比较分析,具体对两类贸易摩擦的特点、原因和对策进行比较研究,有助于我们更加系统全面地了解我国对外贸易摩擦的实质性问题。     

Density Estimation by Total Variation Penalized Likelihood Driven by the Sparsity ℓ1 Information Criterion

Abstract. We propose a non‐linear density estimator, which is locally adaptive, like wavelet estimators, and positive everywhere, without a log‐ or root‐transform. This estimator is based on maximizing a non‐parametric log‐likelihood function regularized by a total variation penalty. The smoothness is driven by a single penalty parameter, and to avoid cross‐validation, we derive an information criterion based on the idea of universal penalty. The penalized log‐likelihood maximization is reformulated as an ?₁‐penalized strictly convex programme whose unique solution is the density estimate. A Newton‐type method cannot be applied to calculate the estimate because the ?₁‐penalty is non‐differentiable. Instead, we use a dual block coordinate relaxation method that exploits the problem structure. By comparing with kernel, spline and taut string estimators on a Monte Carlo simulation, and by investigating the sensitivity to ties on two real data sets, we observe that the new estimator achieves good L ₁ and L ₂ risk for densities with sharp features, and behaves well with ties.     

Sample size determination for testing equality in frequency data under an incomplete block crossover design

When there are more than two treatments under comparison, we may consider the use of the incomplete block crossover design (IBCD) to save the number of patients needed for a parallel groups design and reduce the duration of a crossover trial. We develop an asymptotic procedure for simultaneously testing equality of two treatments versus a control treatment (or placebo) in frequency data under the IBCD with two periods. We derive a sample size calculation procedure for the desired power of detecting the given treatment effects at a nominal-level and suggest a simple ad hoc adjustment procedure to improve the accuracy of the sample size determination when the resulting minimum required number of patients is not large. We employ Monte Carlo simulation to evaluate the finite-sample performance of the proposed test, the accuracy of the sample size calculation procedure, and that with the simple ad hoc adjustment suggested here. We use the data taken as a part of a crossover trial comparing the number of exacerbations between using salbutamol or salmeterol and a placebo in asthma patients to illustrate the sample size calculation procedure.     

Parametric Inference in Stationary Time Series Models with Dependent Errors

This article is concerned with inference for the parameter vector in stationary time series models based on the frequency domain maximum likelihood estimator. The traditional method consistently estimates the asymptotic covariance matrix of the parameter estimator and usually assumes the independence of the innovation process. For dependent innovations, the asymptotic covariance matrix of the estimator depends on the fourth‐order cumulants of the unobserved innovation process, a consistent estimation of which is a difficult task. In this article, we propose a novel self‐normalization‐based approach to constructing a confidence region for the parameter vector in such models. The proposed procedure involves no smoothing parameter, and is widely applicable to a large class of long/short memory time series models with weakly dependent innovations. In simulation studies, we demonstrate favourable finite sample performance of our method in comparison with the traditional method and a residual block bootstrap approach.     

Community Based Rural Health Care in India

SUMMARY

India is a large country, geographically as well as popula-tionwise. The majority of its population lives in rural areas, i.e., villages. Again, most of the villages are in remote areas. The State has been making sincere efforts to make the basic social services accessible to all in the rural area. Health being one of the vital services, it has been a challenging task before the State to extend it to the remote rural areas, many of which are not yet connected by motorable roads. As a result of various experiments carried out over the last five decades, the State has developed a fairly well-designed primary health care service, and it is in operation in rural areas. However, there appears to be a striking gap between the delivery of health services in rural areas and utilization of the services by the people. Attempts have been made in this article to apprise the readers of the health service system in India, and it discusses the issue of health service delivery at the village level. The discussion is based on a small study carried out in a rural area in the State of West Bengal (India) where students of social work of the University to which the author belongs are placed for field work. Following the inputs received through supervision of the students' work, the study was initiated and conducted.

This article based on the study seeks to focus on peoples' perception of the health services as provided by the State in rural areas, which in turn gets reflected in the extent to which they utilize the services. Social workers being an integral part of the health set up, their role bears special significance. Discussion, therefore, centres on scope for social work intervention at the community level as well as in institutional level of the health service delivery system to make the services meaningful and effective in rural areas. In fact, it has to take the leadership role in reforming the service delivery system when required.     

印尼J区块层序地层与沉积相特征研究

利用层序地层学理论,对印尼J区块古近系—新近系的层序地层和沉积相特征进行了研究。古近系—新近系可以分为7个中期基准面旋回（SQ1SQ7）和17个短期基准面旋回。SQ1SQ7沉积时期,沉积环境从陆相河流环境逐渐过渡到三角洲环境和浅海环境,再到河流环境,为一完整的水进-水退旋回。中下部层序上升旋回占主体,属海进式沉积组合序列;上部层序下降旋回占主体,多为海退式沉积组合序列。结合层序特征,指出区块西部凸起带SQ5旋回的浊积砂体、基底风化壳、碳酸盐岩台地和东部斜坡带的下切谷为区块的有利勘探区带。研究结果对该盆地的石油勘探具有指导意义。     

相位旋转的速率为2的空时分组码

速率为2的空时分组码(R2-STBC)能达到全速率全分集,然而其译码复杂度与调制阶数的平方成正比。为了降低译码复杂度,提出了一种基于相位旋转的、速率为2的空时分组码(PR-R2-STBC),发送端根据反馈信息将部分发送信号旋转一定的角度,实现了信号在传输过程中两两正交,从而使得其译码复杂度与调制阶数成正比。仿真结果显示,与R2-STBC相比,该编码仅需反馈7 bit就极大地降低了译码复杂度。