Warm Dark Haloes Accretion Histories and their Gravitational Signatures

We study clusters in Warm Dark Matter (WDM) models of a thermally produced dark matter particle $0.5$ keV in mass. We show that, despite clusters in WDM cosmologies having similar density profiles as their Cold Dark Matter (CDM) counterparts, the internal properties, such as the amount of substructure, shows marked differences. This result is surprising as clusters are at mass scales that are {\em a thousand times greater} than that at which structure formation is suppressed. WDM clusters gain significantly more mass via smooth accretion and contain fewer substructures than their CDM brethren. The higher smooth mass accretion results in subhaloes which are physically more extended and less dense. These fine-scale differences can be probed by strong gravitational lensing. We find, unexpectedly, that WDM clusters have {\em higher} lensing efficiencies than those in CDM cosmologies, contrary to the naive expectation that WDM clusters should be less efficient due to the fewer substructures they contain. Despite being less dense, the larger WDM subhaloes are more likely to have larger lensing cross-sections than CDM ones. Additionally, WDM subhaloes typically reside at larger distances, which radially stretches the critical lines associated with strong gravitational lensing, resulting in excess in the number of clusters with large radial cross-sections at the $\sim2\sigma$ level. Though lensing profile for an individual cluster vary significantly with the line-of-sight, the radial arc distribution based on a sample of $\gtrsim100$ clusters may prove to be the crucial test for the presence of WDM.Comment: 13 pages, 14 figures, submitted to MNRA

Graph Signal Processing: Overview, Challenges and Applications

Research in Graph Signal Processing (GSP) aims to develop tools for processing data defined on irregular graph domains. In this paper we first provide an overview of core ideas in GSP and their connection to conventional digital signal processing. We then summarize recent developments in developing basic GSP tools, including methods for sampling, filtering or graph learning. Next, we review progress in several application areas using GSP, including processing and analysis of sensor network data, biological data, and applications to image processing and machine learning. We finish by providing a brief historical perspective to highlight how concepts recently developed in GSP build on top of prior research in other areas.Comment: To appear, Proceedings of the IEE

Dynamique et hétérogénéité de l’emploi en déséquilibre

Pour rendre compte à un niveau macroéconomique des hétérogénéités qui caractérisent le marché du travail, la démarche la plus indiquée est l’agrégation par intégration des micromarchés en déséquilibre. Afin d’enrichir la structure dynamique de ce modèle d’équilibre avec rationnements quantitatifs, nous incluons des variables latentes retardées dans les équations d’offre ou de demande de travail ainsi que les rationnements passés dans l’équation de salaire. À la lumière des derniers développements proposés par Laroque et Salanié (1993), l’estimation de ce type de modèle est désormais envisageable. Leur méthode repose sur une extension du pseudo-maximum de vraisemblance simulé au cas dynamique.Notre objectif est, d’une part, d’étudier l’emploi en déséquilibre et la formation des salaires et d’autre part, de tester l’existence de micromarchés. L’application sur données macroéconomiques trimestrielles françaises met en évidence les résultats suivants. L’hypothèse d’existence de micromarchés ne semble pas rejetée. Néanmoins, depuis la fin des années 70, la contribution de l’imparfaite réallocation entre micromarchés à la montée du chômage se serait réduite. En outre, des effets de report dynamiques semblent affecter la demande de travail et les déséquilibres à la fois présents et passés pèseraient sur la croissance des salaires.The heterogeneity that caracterizes the labour market is taken into account by the aggregation of micro-markets disequilibria. In order to get a more realistic dynamic structure, lagged latent variables are included in labour demand, labour supply and wage equations. Such a model is estimated by the recent method proposed by Laroque and Salanié (1993). They suggest an extension of the simulated pseudo-maximum likelihood method to dynamic cases.Our aim is first, to study in a disequilibrium framework the unemployment and the wage setting process and second, to test the existence of micro-markets. The application of this model to French quarterly data gives the following results. The hypothesis of micro- markets could not be rejected. Nevertheless, since the end of the 70's, the contribution of the imperfect reallocation between micro-markets to the unemployment rise has decreased. Furthermore, intertemporal spillover effects seem to rather concern the labour demand whereas present and past disequilibria would affect the wage formation

Low-Complexity LP Decoding of Nonbinary Linear Codes

Linear Programming (LP) decoding of Low-Density Parity-Check (LDPC) codes has attracted much attention in the research community in the past few years. LP decoding has been derived for binary and nonbinary linear codes. However, the most important problem with LP decoding for both binary and nonbinary linear codes is that the complexity of standard LP solvers such as the simplex algorithm remains prohibitively large for codes of moderate to large block length. To address this problem, two low-complexity LP (LCLP) decoding algorithms for binary linear codes have been proposed by Vontobel and Koetter, henceforth called the basic LCLP decoding algorithm and the subgradient LCLP decoding algorithm. In this paper, we generalize these LCLP decoding algorithms to nonbinary linear codes. The computational complexity per iteration of the proposed nonbinary LCLP decoding algorithms scales linearly with the block length of the code. A modified BCJR algorithm for efficient check-node calculations in the nonbinary basic LCLP decoding algorithm is also proposed, which has complexity linear in the check node degree. Several simulation results are presented for nonbinary LDPC codes defined over Z_4, GF(4), and GF(8) using quaternary phase-shift keying and 8-phase-shift keying, respectively, over the AWGN channel. It is shown that for some group-structured LDPC codes, the error-correcting performance of the nonbinary LCLP decoding algorithms is similar to or better than that of the min-sum decoding algorithm.Comment: To appear in IEEE Transactions on Communications, 201

Chicken BAFF

Members of the tumor necrosis factor (TNF) family play key roles in the regulation of inflammation, immune responses and tissue homeostasis. Here we describe the identification of the chicken homologue of mammalian B cell activating factor of the TNF family (BAFF/BLyS). By searching a chicken EST database we identified two overlapping cDNA clones that code for the entire open reading frame of chicken BAFF (chBAFF), which contains a predicted transmembrane domain and a putative furin protease cleavage site like its mammalian counterparts. The amino acid identity between soluble chicken and human BAFF is 76%, considerably higher than for most other known cytokines. The chBAFF gene is most strongly expressed in the bursa of Fabricius. Soluble recombinant chBAFF produced by human 293T cells interacted with the mammalian cell-surface receptors TACI, BCMA and BAFF-R. It bound to chicken B cells, but not to other lymphocytes, and it promoted the survival of splenic chicken B cells in culture. Furthermore, bacterially expressed chBAFF induced the selective expansion of B cells in the spleen and cecal tonsils when administered to young chicks. Our results suggest that like its mammalian counterpart, chBAFF plays an important role in survival and/or proliferation of chicken B cells