Chromatin-remodeling complex specificity and embryonic vascular development

Vascular development is a dynamic process that relies on the coordinated expression of numerous genes, but the factors that regulate gene expression during blood vessel development are not well defined. ATP-dependent chromatin-remodeling complexes are gaining attention for their specific temporal and spatial effects on gene expression during vascular development. Genetic mutations in chromatin-remodeling complex subunits are revealing roles for the complexes in vascular signaling pathways at discrete developmental time points. Phenotypic analysis of these models at various stages of vascular development will continue to expand our understanding of how chromatin remodeling impacts new blood vessel growth. Such research could also provide novel therapeutic targets for the treatment of vascular pathologies.     

Accurate Tree-based Missing Data Imputation and Data Fusion within the Statistical Learning Paradigm

Framework of this paper is statistical data editing, specifically how to edit or impute missing or contradictory data and how to merge two independent data sets presenting some lack of information. Assuming a missing at random mechanism, this paper provides an accurate tree-based methodology for both missing data imputation and data fusion that is justified within the Statistical Learning Theory of Vapnik. It considers both an incremental variable imputation method to improve computational efficiency as well as boosted trees to gain in prediction accuracy with respect to other methods. As a result, the best approximation of the structural risk (also known as irreducible error) is reached, thus reducing at minimum the generalization (or prediction) error of imputation. Moreover, it is distribution free, it holds independently of the underlying probability law generating missing data values. Performance analysis is discussed considering simulation case studies and real world applications.     

探讨带参数微分方程边值问题的解法

主要讨论带参数微分方程边值问题的逼近值及渐近值解法,并且利用基础解系、边值函数等概念,解决了带参数的微分方程中参数充分小的范围内解的变化趋势.     

对一种快速双重指数模算法的复杂度研究

最近提出了一种采用标准符号数二进制码(canonic signed-digit binary representation,CSDBR)来计算AXBY(modN)的快速双重指数模算法.该算法声明当指数的长度为k时,该算法平均仅需要1.306k次模乘.由于已知的此类算法至少需要1.503k次模乘,该算法具有明显的性能优势.然而,无论是该算法的提出者还是其他研究者均没有给出正确的复杂度分析.本文通过利用马尔科夫链模型对该算法进行正式的复杂度研究并进行一定规模的统计实验后证实,实际上该算法平均需要1.556k次模乘.这项研究的意义在于揭示到目前为止,基于标准符号数位码的双重指数模算法的最高性能仍然无法降低到1.5k次模乘以下.     

Illusory shifts in visual direction accompany adaptation of saccadic eye movements.

A central problem in human vision is to explain how the visual world remains stable despite the continual displacements of the retinal image produced by rapid saccadic movements of the eyes. Perceived stability has been attributed to 'efferent-copy' signals, representing the saccadic motor commands, that cancel the effects of saccade-related retinal displacements. Here we show, by means of a perceptual illusion, that traditional cancellation theories cannot explain stability. The perceptual illusion was produced by first inducing adaptive changes in saccadic gain (ratio of saccade size to target eccentricity). Following adaptation, subjects experienced an illusory mislocalization in which widely separated targets flashed before and after saccades appeared to be in the same place. The illusion shows that the perceptual system did not take the adaptive changes into account. Perceptual localization is based on signals representing the size of the initially-intended saccade, not the size of the saccade that is ultimately executed. Signals representing intended saccades initiate a visual comparison process used to maintain perceptual stability across saccades and to generate the oculomotor error signals that ensure saccadic accuracy.