Semi-supervised dimensionality reduction based on partial least squares for visual analysis of high dimensional data

Dimensionality reduction is employed for visual data analysis as a way to obtaining reduced spaces for high dimensional data or to mapping data directly into 2D or 3D spaces. Although techniques have evolved to improve data segregation on reduced or visual spaces, they have limited capabilities for adjusting the results according to user's knowledge. In this paper, we propose a novel approach to handling both dimensionality reduction and visualization of high dimensional data, taking into account user's input. It employs Partial Least Squares (PLS), a statistical tool to perform retrieval of latent spaces focusing on the discriminability of the data. The method employs a training set for building a highly precise model that can then be applied to a much larger data set very effectively. The reduced data set can be exhibited using various existing visualization techniques. The training data is important to code user's knowledge into the loop. However, this work also devises a strategy for calculating PLS reduced spaces when no training data is available. The approach produces increasingly precise visual mappings as the user feeds back his or her knowledge and is capable of working with small and unbalanced training sets.

Social Networks, Segregation and Poverty in Sao Paulo

The associations between segregation and urban poverty have been intensely scrutinized by the sociology and urban studies literatures. More recently, several studies have emphasized the importance of social networks for living conditions. Yet relatively few studies have tested the precise effects of social networks, and fewer still have focused on the joint effects of residential segregation and social networks on living conditions. This article explores the associations between networks, segregation and some of the most important dimensions of access to goods and services obtained in markets: escaping from social precariousness and obtaining monetary income. It is based on a study of the personal networks of 209 individuals living in situations of poverty in seven locales in the metropolitan area of Sao Paulo. Using network analysis and multivariate techniques, I show that relational settings strongly influence the access individuals have to markets, leading some individuals into worse living conditions and poverty. At the same time, although segregation plays an important role in poverty, its effects tend to be mediated by the networks in which individuals are embedded. Networks in this sense may enhance or mitigate the effects of isolation produced by space.

Meiotic segregation and interchromosomal effect in the sperm of a double translocation carrier: a case report

Abstract Background Infertility is a natural mechanism of selection intended to prevent the delivery of a child with malformations or mental retardation. Male infertility is closely related to chromosomal abnormalities. This study was focused on the analysis of meiotic segregation involving a Robertsonian translocation, 45,XY,der(13;13) [56]/45,XY,der(13;14) [44] and the evaluation of possible interchromosomal effects. Results Hybridisation with LSI 13q14 and subtelomere 14q probes and WCP13 SpectrumGreen and WCP14 SpectrumOrange probes showed a high proportion of unbalanced gametes, corresponding to 71.2% of the spermatozoa. The disomic frequencies of the sexual chromosomes and chromosome 18 of the patient were higher (5.28% and 2.55%, respectively) than those of the control (0.6% and 0.59%, respectively). Conclusion Meiotic segregation studies in sperm are an important tool for genetic counselling of chromosomal aberrations, allowing for a prediction of the risks and consequent implications for the reproductive life. The patient with this rare translocation exhibited meiotic segregation fidelity, and a high rate of unbalanced gametes with disomic spermatozoa.