Women with Turner's Syndrome: helping them reach their full potential

The physical and psychological effects of Turner's Syndrome, a female sex chromosome abnormality, briefly are described. Principles for helping women master the special challenges posed by the disorder are discussed. The authors argue that women with TS must take control of defining their identities and potential in order to attain full status within society.     

福建建设生态强省的战略思考与若干对策

分析了实现持续发展所面临的巨大挑战与压力。结合福建省实际 ,提出建设生态强省的内涵与意义 ,并较为系统地阐述了发展思路与若干对策     

肥胖基因

肥胖症已经逐渐成为了一个严重的健康问题和社会问题 ,对肥胖症的研究已深入到分子水平。自肥胖基因被克隆以来 ,针对肥胖基因的结构、突变、表达及其产物的生物学作用已进行了大量的研究。本文就肥胖基因的发现和定位、结构和突变及其产物———瘦素的相关研究进行了综述 ,并指出了对肥胖基因进行深入研究的相关领域     

Implementation in generic environments

In this paper, we study implementation in “economic environments”. It is shown that there is a dense subset of the set of preference profiles such that given an arbitrary social choice function, f, and ε>0, there exists another social choice function, f _ε, within ε of f uniformly and implementable in Nash equilibrium on the dense subset.     

A Comparison of Partially Adaptive and Reweighted Least Squares Estimation

The small sample performance of least median of squares, reweighted least squares, least squares, least absolute deviations, and three partially adaptive estimators are compared using Monte Carlo simulations. Two data problems are addressed in the paper: (1) data generated from non-normal error distributions and (2) contaminated data. Breakdown plots are used to investigate the sensitivity of partially adaptive estimators to data contamination relative to RLS. One partially adaptive estimator performs especially well when the errors are skewed, while another partially adaptive estimator and RLS perform particularly well when the errors are extremely leptokur-totic. In comparison with RLS, partially adaptive estimators are only moderately effective in resisting data contamination; however, they outperform least squares and least absolute deviation estimators.     

Membranes, mitochondria and amoebae: shape models

Most real-world shapes and images are characterized by high variability- they are not rigid, like crystals, for example—but they are strongly structured. Therefore, a fundamental task in the understanding and analysis of such image ensembles is the construction of models that incorporate both variability and structure in a mathematically precise way. The global shape models introduced in Grenander's general pattern theory are intended to do this. In this paper, we describe the representation of two-dimensional mitochondria and membranes in electron microscope photographs, and three-dimensional amoebae in optical sectioning microscopy. There are three kinds of variability to all of these patterns, which these representations accommodate. The first is the variability in shape and viewing orientation. For this, the typical structure is represented via linear, circular and spherical templates, with the variability accomodated via the application of transformations applied to the templates. The transformations form groups: scale, rotation and translation. They are locally applied throughout the continuum and of high dimension. The second is the textural variability; the inside and outside of these basic shapes are subject to random variation, as well as sensor noise. For this, statistical sensor models and Markov random field texture models are used to connect the constituent structures of the shapes to the measured data. The third variability type is associated with the fact that each scene is made up of a variable number of shapes; this number is not assumed to be known a priori. Each scene has a variable number of parameters encoding the transformations of the templates appropriate for that scene. For this, a single posterior distribution is defined over the countable union of spaces representing models of varying numbers of shapes. Bayesian inference is performed via computation of the conditional expectation of the parametrically defined shapes under the posterior. These conditional mean estimates are generated using jump-diffusion processes. Results for membranes, mitochondria and amoebae are shown.     

奇葩争艳各领风骚——大学语文的比较阅读研究

比较阅读是学习大学语文的一种非常有实用价值的阅读方法.比较阅读包括对文本的文体比较、手法比较、人物形象比较、主题比较、语言比较、观点比较等等.通过比较,读者(大学生)能充分把握文学文本,解读文本.     

中小企业内部控制系统现状及完善对策的探讨

会计信息失真现象与社会环境、经济环境、市场经济的发育程度等企业的外部环境息息相关，但单位内部控制系统弱化是一个更重要、更直接的内部因素。因此，建立和加强单位的内部控制，使内部控制合理设计并有效实施，才能最大可能地防止会计造假等错弊行为的发生，保证会计信息的真实、完整、相关、透明，才能促使企业价值的增值。本文以中小企业作为研究对象，对中小企业如何加强与完善内部控制系统作了一些探讨，提出了一些具体的措施。     

Age Cohort, Ancestry, and Immigrant Generation Influences in Family Relations and Psychological Well-Being among Black Caribbean Family Members

Immigration is contributing to the U.S. population becoming increasingly ethnically diverse. This article examines the role of family relations and well-being among different generations of Black Caribbean immigrants. Family disruptions, such as migration, can have complex effects on the support networks and emotional well-being of family members. Data from a recently completed national study of American Blacks in the United States, however, reveal significant similarities across ancestry and immigrant status in family contact, solidarity and well-being. It is concluded that intrafamilial relations may serve to overcome barriers of geographical distance in providing comparable levels of contact, solidarity, and well-being for both U.S.-born and immigrant Black Caribbean family members of different generations. Because of the increasing numbers of immigrant elders, these sources of family support will become increasingly more important in bridging the gaps between government resources and needed assistance in an aging society.     

Data skeletons: simultaneous estimation of multiple quantiles for massive streaming datasets with applications to density estimation

We consider the problem of density estimation when the data is in the form of a continuous stream with no fixed length. In this setting, implementations of the usual methods of density estimation such as kernel density estimation are problematic. We propose a method of density estimation for massive datasets that is based upon taking the derivative of a smooth curve that has been fit through a set of quantile estimates. To achieve this, a low-storage, single-pass, sequential method is proposed for simultaneous estimation of multiple quantiles for massive datasets that form the basis of this method of density estimation. For comparison, we also consider a sequential kernel density estimator. The proposed methods are shown through simulation study to perform well and to have several distinct advantages over existing methods.