A redshift survey towards the CMB Cold Spot

We have carried out a redshift survey using the VIMOS spectrograph on the VLT towards the Cosmic Microwave Background cold spot. A possible cause of the cold spot is the Integrated Sachs-Wolfe effect imprinted by an extremely large void (hundreds of Mpc in linear dimension) at intermediate or low redshifts. The redshift distribution of over seven hundred z<1 emission-line galaxies drawn from an I-band flux limited sample of galaxies in the direction of the cold spot shows no evidence of a gap on scales of Delta-z> 0.05 as would be expected if such a void existed at 0.35<z<1. There are troughs in the redshift distribution on smaller scales (Delta-z ~0.01) indicating that smaller scale voids may connect regions separated by several degrees towards the cold spot. A comparison of this distribution with that generated from similarly-sized subsamples drawn from widely-spaced pointings of the VVDS survey does not indicate that the redshift distribution towards the cold spot is anomalous or that these small gaps can be uniquely attributed to real voids.Comment: MNRAS in press, 6 page

Hue-Saturation-Luminance Colour Space for Spatial and Temporal Segmentation

In this article, we focus on the Hue Saturation Luminance colour space, known for its appropriate representation of the human vision, and we illustrate its interest in the segmentation of image data, both in the spatial and temporal dimensions. The HSL space, with its particular properties (one angular component, the hue, and two scalar components, the saturation and the luminance), requires some original computation models. So our contribution is triple : first we will deal with colour representation in the HSL space and with specific computation methods which have to be involved. Then we will show the relevance of this colour space for automatic segmentation of image data in the two domains which are space and time. Spatial segmentation is considered under the problem of background and foreground separation for which we propose a multiresolution approach which requires a single image. Temporal segmentation corresponds to shot change detection in an image sequence, and the method we are proposing is based on the use of context-independent distance measures. Common properties of our both methods (spatial and temporal segmentations) are efficiency (processing time compatible with video framerate) and robustness (in particular against illumination changes). We illustrate these two approaches with results obtained in the domain of sport video sequences analysis and we compare in this context the use of HSL and RGB colour spaces.Dans cet article, nous nous focalisons sur l'espace Teinte Saturation Luminance, réputé pour sa meilleure représentation de la vision humaine, et illustrons son intérêt dans la segmentation de données image, que ce soit dans l'espace ou dans le temps. L'espace TSL, aux caractéristiques particulières (une composante angulaire, la teinte, et deux composantes scalaires, la saturation et la luminance) nécessite des modes de calcul originaux. Notre contribution est donc triple : tout d'abord nous nous attarderons sur la représentation des couleurs dans l'espace TSL et sur les méthodes de calcul spécifiques qui doivent être employées. Ensuite nous montrerons l'intérêt de cet espace dans la segmentation automatique de données image dans les deux domaines que sont l'espace et le temps. La segmentation spatiale est assimilée au problème de la séparation du fond et des objets pour cela nous proposons une approche multirésolution ne nécessitant qu'une seule image. La segmentation temporelle correspond à la détection des changements de plan dans une séquence d'images, et la méthode que nous proposons pour l'obtenir se base sur l'utilisation de mesures de distances indépendamment du contexte. Les caractéristiques communes de nos deux méthodes (segmentation spatiale et segmentation temporelle) sont l'efficacité (temps de traitement permettant de respecter la cadence vidéo) et la robustesse (notamment aux changements d'illumination). Nous illustrons ces deux approches par des résultats obtenus dans le domaine de l'analyse de séquences vidéo sportives et comparons dans ce contexte l'usage des espaces TSL et RVB

The Morphologically Divided Redshift Distribution of Faint Galaxies

We have constructed a morphologically divided redshift distribution of faint field galaxies using a statistically unbiased sample of 196 galaxies brighter than I = 21.5 for which detailed morphological information (from the Hubble Space Telescope) as well as ground-based spectroscopic redshifts are available. Galaxies are classified into 3 rough morphological types according to their visual appearance (E/S0s, Spirals, Sdm/dE/Irr/Pec's), and redshift distributions are constructed for each type. The most striking feature is the abundance of low to moderate redshift Sdm/dE/Irr/Pec's at I < 19.5. This confirms that the faint end slope of the luminosity function (LF) is steep (alpha < -1.4) for these objects. We also find that Sdm/dE/Irr/Pec's are fairly abundant at moderate redshifts, and this can be explained by strong luminosity evolution. However, the normalization factor (or the number density) of the LF of Sdm/dE/Irr/Pec's is not much higher than that of the local LF of Sdm/dE/Irr/Pec's. Furthermore, as we go to fainter magnitudes, the abundance of moderate to high redshift Irr/Pec's increases considerably. This cannot be explained by strong luminosity evolution of the dwarf galaxy populations alone: these Irr/Pec's are probably the progenitors of present day ellipticals and spiral galaxies which are undergoing rapid star formation or merging with their neighbors. On the other hand, the redshift distributions of E/S0s and spirals are fairly consistent those expected from passive luminosity evolution, and are only in slight disagreement with the non-evolving model.Comment: 11 pages, 4 figures (published in ApJ

Size of Outbreaks Near the Epidemic Threshold

The spread of infectious diseases near the epidemic threshold is investigated. Scaling laws for the size and the duration of outbreaks originating from a single infected individual in a large susceptible population are obtained. The maximal size of an outbreak n_* scales as N^{2/3} with N the population size. This scaling law implies that the average outbreak size scales as N^{1/3}. Moreover, the maximal and the average duration of an outbreak grow as t_* ~ N^{1/3} and ~ ln N, respectively.Comment: 4 pages, 5 figure

Cap mesenchyme cell swarming during kidney development is influenced by attraction, repulsion, and adhesion to the ureteric tip

Morphogenesis of the mammalian kidney requires reciprocal interactions between two cellular domains at the periphery of the developing organ: the tips of the epithelial ureteric tree and adjacent regions of cap mesenchyme. While the presence of the cap mesenchyme is essential for ureteric branching, how it is specifically maintained at the tips is unclear. Using ex vivo timelapse imaging we show that cells of the cap mesenchyme are highly motile. Individual cap mesenchyme cells move within and between cap domains. They also attach and detach from the ureteric tip across time. Timelapse tracks collected for >800 cells showed evidence that this movement was largely stochastic, with cell autonomous migration influenced by opposing attractive, repulsive and cell adhesion cues. The resulting swarming behaviour maintains a distinct cap mesenchyme domain while facilitating dynamic remodelling in response to underlying changes in the tip

SOOP Network Enhancement Report

Report on the network enhancement project, this will document (a) extension of network coverage to South Atlantic; (b) evaluation of improved EOV carbonate system; and (c) re-assessment of instrumentatio

Cor-Split: Defending Privacy in Data Re-Publication from Historical Correlations and Compromised Tuples

Abstract. Several approaches have been proposed for privacy preserving data publication. In this paper we consider the important case in which a certain view over a dynamic dataset has to be released a number of times during its history. The insufficiency of techniques used for one-shot publication in the case of subsequent releases has been previously recognized, and some new approaches have been proposed. Our research shows that relevant privacy threats, not recognized by previous proposals, can occur in practice. In particular, we show the cascading effects that a single (or a few) compromised tuples can have in data re-publication when coupled with the ability of an adversary to recognize historical correlations among released tuples. A theoretical study of the threats leads us to a defense algorithm, implemented as a significant extension of the m-invariance technique. Extensive experiments using publicly available datasets show that the proposed technique preserves the utility of published data and effectively protects from the identified privacy threats.