我国中小企业境外参展中的专利风险及应对措施

我国中小企业境外参展存在较多的专利风险,主要是参展展品本身涉嫌侵权、参展品外观设计涉嫌侵权、参展商品的外包装、卡具涉嫌侵权以及参展图片、样本涉嫌侵权等问题。原因是我国法律中有关专利的保护内容不尽完善、我国中小企业专利保护意识不强、我国涉外参展组织过程不够有力和政府有关部门的规范管理工作不到位等原因所致。通过健全我国专利保护的法律法规、建立专利预警机制和维权机制、努力提高中小企业的专利法律意识、加强政府涉外参展的规范管理职能等措施,可以有效防范中小企业境外参展中的专利风险。     

社会治理视域下防范和应对突发事件的策略研究

目前我国的社会正在经历前所未有的深层次变革,社会各项事业正在面临深层创新与发展。在这一特定的历史时期内,多元化社会矛盾所导致的突发事件大量出现,为我国社会治理提出了严峻的挑战。突发事件形成的原因不仅有社会转型与体制转轨的诱发、基层政府社会治理水平的不足、社会自我调控能力的薄弱,同时也有法治建设的不完善以及社会保障的诸多漏洞等。因此,必须要从加强社会治理,维护社会稳定、提高政府的社会治理水平、培育多元社会治理主体、推进法制与社会保障建设等途径入手提高整个社会防范与应对突发事件的综合能力。     

A Proposed ASEAN Disaster Response, Training and Logistic Centre Enhancing Regional Governance in Disaster Management

The Southeast Asian region is remarkably vulnerable to natural disasters which repeatedly cause devastations to both human lives and properties. However, current disaster relief efforts have not lived up to the high standards. Even worse is that humanitarian efforts have been frequently frustrated by the rejections from national authorities under the name of “sovereignty”. All these problems necessitate a widely accepted, politically neutral, well coordinated and effectively governed organization within the region. We, hereby propose a Disaster Response Training and Logistic Centre under the umbrella of the Association of Southeast Asian Nations (ASEAN), which aims to mitigate the devastation of disasters, to provide accurate relief assessment, and training for relief team on a regular basis, and to allocate and mobilize humanitarian aid. The Centre will be endorsed through an agreement by all ASEAN governments. The philosophy underpinning the organization reflects a regional approach whereby stronger government involvement and regional integration in disaster relief is indispensable in the context of the Southeast Asian region.      

通信反馈法对大学生二语写作效果的实验研究

研究采用定量分析法考查了非英语专业一年级152名大学生的作文测试成绩、性格因素对通信反馈机制功效的影响和学生对通信反馈教学的态度。结果发现基于内容的通信反馈教学比传统批改反馈方式对学生英语写作能力的提高有更积极的促进作用,尤其是在丰富写作内容、增强连贯方面效果较显著。研究能启发我们更好地理解写作的过程、认识和把握写作的本质、帮助提高二语写作教学效果。     

新时期工会工作的三个转型

坚持与时俱进,是我们党进行革命、建设和改革等各种实践活动的一贯指导方针,是赋予马克思主义生命力和创造力,指导我们事业取得成功的重要保证.因此,我们所进行的任何一项工作都必须坚持与时俱进.工会工作自然也不例外,要与时俱进,要随着形势的发展而转型.这种转型,可以概括为"三个转型",即从娱乐型转变为参政型,从福利型转变为维权型,从传统型转变为现代型.     

The beta distribution as a latent response model for ordinal data (I): Estimation of location and dispersion parameters

Ordinal data are often modeled using a continuous latent response distribution, which is partially observed through windows of adjacent intervals defined by cutpoints. In this paper we propose the beta distribution as a model for the latent response. The beta distribution has several advantages over the other common distributions used, e.g. , normal and logistic. In particular, it enables separate modeling of location and dispersion effects which is essential in the Taguchi method of robust design. First, we study the problem of estimating the location and dispersion parameters of a single beta distribution (representing a single treatment) from ordinal data assuming known equispaced cutpoints. Two methods of estimation are compared: the maximum likelihood method and the method of moments. Two methods of treating the data are considered: in raw discrete form and in smoothed continuousized form. A large scale simulation study is carried out to compare the different methods. The mean square errors of the estimates are obtained under a variety of parameter configurations. Comparisons are made based on the ratios of the mean square errors (called the relative efficiencies). No method is universally the best, but the maximum likelihood method using continuousized data is found to perform generally well, especially for estimating the dispersion parameter. This method is also computationally much faster than the other methods and does not experience convergence difficulties in case of sparse or empty cells. Next, the problem of estimating unknown cutpoints is addressed. Here the multiple treatments setup is considered since in an actual application, cutpoints are common to all treatments, and must be estimated from all the data. A two-step iterative algorithm is proposed for estimating the location and dispersion parameters of the treatments, and the cutpoints. The proposed beta model and McCullagh's (1980) proportional odds model are compared by fitting them to two real data sets.     

Nonparametric binary regression using a Gaussian process prior

The article describes a nonparametric Bayesian approach to estimating the regression function for binary response data measured with multiple covariates. A multiparameter Gaussian process, after some transformation, is used as a prior on the regression function. Such a prior does not require any assumptions like monotonicity or additivity of the covariate effects. However, additivity, if desired, may be imposed through the selection of appropriate parameters of the prior. By introducing some latent variables, the conditional distributions in the posterior may be shown to be conjugate, and thus an efficient Gibbs sampler to compute the posterior distribution may be developed. A hierarchical scheme to construct a prior around a parametric family is described. A robustification technique to protect the resulting Bayes estimator against miscoded observations is also designed. A detailed simulation study is conducted to investigate the performance of the proposed methods. We also analyze some real data using the methods developed in this article.     

A numerical study for comparing two response-adaptive designs for continuous treatment effects

We study two sequential, response-adaptive randomized designs for clinical trials; one has been proposed in Bandyopadhyay and Biswas (Biometrika 88: 409–419, 2001) and in Biswas and Basu (Sankhya Ser B 63:27–42, 2001), the other stems from the randomly reinforced urn introduced and studied in Muliere et al. (J Stat Plan Inference 136:1853–1874, 2006a). Both designs can be used in clinical trials where the response from each patient is a continuous variable. Comparison is conducted through numerical studies and along a new guideline for the evaluation of a response-adaptive design.     

On some robust estimation procedures for quantiles based on data

This paper introduces some robust estimation procedures to estimate quantiles of a continuous random variable based on data, without any other assumptions of probability distribution. We construct a reasonable linear regression model to connect the relationship between a suitable symmetric data transformation and the approximate standard normal statistics. Statistical properties of this linear regression model and its applications are studied, including estimators of quantiles, quartile mean, quartile deviation, correlation coefficient of quantiles and standard errors of these estimators. We give some empirical examples to illustrate the statistical properties and apply our estimators to grouping data.