We extend the previously described CMB Gibbs sampling framework to allow for exact Bayesian analysis of anisotropic universe models, and apply this method to the 5-year WMAP temperature observations. This involves adding support for non-diagonal signal covariance matrices, and implementing a general spectral parameter MCMC sampler. As a worked example we apply these techniques to the model recently introduced by Ackerman et al., describing for instance violations of rotational invariance during the inflationary epoch. After verifying the code with simulated data, we analyze the foreground-reduced 5-year WMAP temperature sky maps. For ℓ ≤ 400 and the W-band data, we find tentative evidence for a preferred direction pointing towards (l, b) = (110 • , 10 • ) with an anisotropy amplitude of g * = 0.15 ± 0.039. Similar results are obtained from the V-band data [g * = 0.10 ± 0.04; (l, b) = (130 • , 20 • )]. Further, the preferred direction is stable with respect to multipole range, seen independently in both ℓ = [2, 100] and [100, 400], although at lower statistical significance. We have not yet been able to establish a fully satisfactory explanation for the observations in terms of known systematics, such as non-cosmological foregrounds, correlated noise or asymmetric beams, but stress that further study of all these issues is warranted before a cosmological interpretation can be supported.

We revisit the anisotropic universe model previously developed by Ackerman, Carroll and Wise (ACW), and generalize both the theoretical and computational framework to include polarization and various forms of systematic effects. We apply our new tools to simulated WMAP data in order to understand the potential impact of asymmetric beams, noise mis-estimation and potential Zodiacal light emission. We find that neither has any significant impact on the results. We next show that the previously reported ACW signal is also present in the 1-year WMAP temperature sky map presented by Liu & Li (2009a), where data cuts are more aggressive. Finally, we reanalyze the 5-year WMAP data taking into account a previously neglected (−i) l−l ′ -term in the signal covariance matrix. We still find a strong detection of a preferred direction in the temperature map. Including multipoles up to ℓ = 400, the anisotropy amplitude for the W-band is found to be g = 0.29 ± 0.031, nonzero at 9σ. However, the corresponding preferred direction is also shifted very close to the ecliptic poles at (l, b) = (96, 30), in agreement with the analysis of Hanson & Lewis (2009), indicating that the signal is aligned along the plane of the solar system. This strongly suggests that the signal is not of cosmological origin, but most likely is a product of an unknown systematic effect. Determining the nature of the systematic effect is of vital importance, as it might affect other cosmological conclusions from the WMAP experiment. Finally, we provide a forecast for the Planck experiment including polarization.

We investigate the possibility of using cosmological observations to probe and constrain an imperfect dark energy fluid. We consider a general parametrization of the dark energy component accounting for an equation of state, speed of sound and viscosity. We use present and future data from the cosmic microwave background (CMB) radiation, large-scale structures and Type Ia supernovae. We find that both the speed of sound and viscosity parameters are difficult to nail down with the present cosmological data. Also, we argue that it will be hard to improve the constraints significantly with future CMB data sets. The implication is that a perfect fluid description might ultimately turn out to be a phenomenologically sufficient description of all the observational consequences of dark energy. The fundamental lesson is, however, that even then one cannot exclude, by appealing to observational evidence alone, the possibility of imperfectness in dark energy.

Transgenic animal models are invaluable research tools for elucidating the pathways and mechanisms involved in the development of neurodegenerative diseases. Mechanistic clues can be revealed by applying labelling techniques such as immunohistochemistry or in situ hybridisation to brain tissue sections. Precision in both assigning anatomical location to the sections and quantifying labelled features is crucial for output validity, with a stereological approach or image-based feature extraction typically used. However, both approaches are restricted by the need to manually delineate anatomical regions. To circumvent this limitation, we present the QUINT workflow for quantification and spatial analysis of labelling in series of rodent brain section images based on available 3D reference atlases. The workflow is semi-automated, combining three open source software that can be operated without scripting knowledge, making it accessible to most researchers. As an example, a brain region-specific quantification of amyloid plaques across whole transgenic Tg2576 mouse brain series, immunohistochemically labelled for three amyloid-related antigens is demonstrated. First, the whole brain image series were registered to the Allen Mouse Brain Atlas to produce customised atlas maps adapted to match the cutting plan and proportions of the sections (QuickNII software). Second, the labelling was segmented from the original images by the Random Forest Algorithm for supervised classification (ilastik software). Finally, the segmented images and atlas maps were used to generate plaque quantifications for each region in the reference atlas (Nutil software). The method yielded comparable results to manual delineations and to the output of a stereological method. While the use case demonstrates the QUINT workflow for quantification of amyloid plaques only, the workflow is suited to all mouse or rat brain series with labelling that is visually distinct from the background, for example for the quantification of cells or labelled proteins.

We report the discovery of a unique gravitational lens system, SDSS J2222+2745, producing five spectroscopically confirmed images of a z s = 2.82 quasar lensed by a foreground galaxy cluster at z l = 0.49. We also present photometric and spectroscopic evidence for a sixth lensed image of the same quasar. The maximum separation between the quasar images is 15. 1. Both the large image separations and the high image multiplicity of the lensed quasar are in themselves rare, and observing the combination of these two factors is an exceptionally unlikely occurrence in present datasets. This is only the third known case of a quasar lensed by a cluster, and the only one with six images. The lens system was discovered in the course of the Sloan Giant Arcs Survey, in which we identify candidate lenses in the Sloan Digital Sky Survey and target these for follow up and verification with the 2.56m Nordic Optical Telescope. Multi-band photometry obtained over multiple epochs from September 2011 to September 2012 reveals significant variability at the ∼ 10 − 30% level in some of the quasar images, indicating that measurements of the relative time delay between quasar images will be feasible. In this lens system we also identify a bright (g = 21.5) giant arc corresponding to a strongly lensed background galaxy at z s = 2.30. We fit parametric models of the lens system, constrained by the redshift and positions of the quasar images and the redshift and position of the giant arc. The predicted time delays between different pairs of quasar images range from ∼ 100 days to ∼ 6 years.