Galaxy intrinsic alignments induce a major astrophysical contamination to weak gravitational lensing measurements and need to be modelled and mitigated when extracting cosmological information from... Show moreGalaxy intrinsic alignments induce a major astrophysical contamination to weak gravitational lensing measurements and need to be modelled and mitigated when extracting cosmological information from such measurements. This dissertation studies the signal of the intrinsic alignment of galaxies in large and small scales. Informative priors are provided for the signal, which improve the constraining power of weak lensing data. Moreover, the dependence of the signal with the observed wavelength is studied, finding significant differences in the alignment of galaxies observed in different bands. The source of this difference appear to be satellite galaxies, and the alignment of galaxies inside galaxy groups is explored, finding that the alignment signal depends on the scale of a galaxy, with outer regions being more strongly aligned that inner ones. Lastly, the alignment of galaxies with their host dark matter halo is probed by measuring the anisotropic weak lensing signal around them, which leads to the conclusion that outer regions of galaxies are also more aligned with their dark matter halo than inner ones. Show less
The shape, structure and connectivity of nerve cells are important aspects of neuronal function. Genetic and epigenetic factors that alter neuronal morphology or synaptic localization of pre- and... Show moreThe shape, structure and connectivity of nerve cells are important aspects of neuronal function. Genetic and epigenetic factors that alter neuronal morphology or synaptic localization of pre- and post-synaptic proteins contribute significantly to neuronal output and may underlie clinical states. To assess the impact of individual genes and disease-causing mutations on neuronal morphology, reliable methods are needed. Unfortunately, manual analysis of immuno-fluorescence images of neurons to quantify neuronal shape and synapse number, size and distribution is labor-intensive, time-consuming and subject to human bias and error. We have developed an automated image analysis routine using steerable filters and deconvolutions to automatically analyze dendrite and synapse characteristics in immuno-fluorescence images. Our approach reports dendrite morphology, synapse size and number but also synaptic vesicle density and synaptic accumulation of proteins as a function of distance from the soma as consistent as expert observers while reducing analysis time considerably. In addition, the routine can be used to detect and quantify a wide range of neuronal organelles and is capable of batch analysis of a large number of images enabling high-throughput analysis. (C) 2010 Elsevier B.V. All rights reserved. Show less
