The spin temperature of high-redshift damped Lyman-α\alpha systems

We report results from a programme aimed at investigating the temperature of neutral gas in high-redshift damped Lyman-$\alpha$ absorbers (DLAs). This involved (1) HI 21cm absorption studies of a large DLA sample, (2) VLBI studies to measure the low-frequency quasar core fractions, and (3) optical/ultraviolet spectroscopy to determine DLA metallicities and velocity widths. Including literature data, our sample consists of 37 DLAs with estimates of the spin temperature $T_s$ and the covering factor. We find a strong $4\sigma$) difference between the $T_s$ distributions in high-z (z>2.4) and low-z (z<2.4) DLA samples. The high-z sample contains more systems with high $T_s$ values, $\gtrsim 1000$ K. The $T_s$ distributions in DLAs and the Galaxy are also clearly (~$6\sigma$) different, with more high-$T_s$ sightlines in DLAs than in the Milky Way. The high $T_s$ values in the high-z DLAs of our sample arise due to low fractions of the cold neutral medium. For 29 DLAs with metallicity [Z/H] estimates, we confirm the presence of an anti-correlation between $T_s$ and [Z/H], at $3.5\sigma$ significance via a non-parametric Kendall-tau test. This result was obtained with the assumption that the DLA covering factor is equal to the core fraction. Monte Carlo simulations show that the significance of the result is only marginally decreased if the covering factor and the core fraction are uncorrelated, or if there is a random error in the inferred covering factor. We also find evidence for redshift evolution in DLA $T_s$ values even for the z>1 sub-sample. Since z>1 DLAs have angular diameter distances comparable to or larger than those of the background quasars, they have similar efficiency in covering the quasars. Low covering factors in high-z DLAs thus cannot account for the observed redshift evolution in spin temperatures. (Abstract abridged.)Comment: 37 pages, 22 figures. Accepted for publication in Monthly Notices of the Royal Astronomical Societ

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G0^0 Electronics and Data Acquisition (Forward-Angle Measurements)

The G$^0$ parity-violation experiment at Jefferson Lab (Newport News, VA) is designed to determine the contribution of strange/anti-strange quark pairs to the intrinsic properties of the proton. In the forward-angle part of the experiment, the asymmetry in the cross section was measured for $\vec{e}p$ elastic scattering by counting the recoil protons corresponding to the two beam-helicity states. Due to the high accuracy required on the asymmetry, the G$^0$ experiment was based on a custom experimental setup with its own associated electronics and data acquisition (DAQ) system. Highly specialized time-encoding electronics provided time-of-flight spectra for each detector for each helicity state. More conventional electronics was used for monitoring (mainly FastBus). The time-encoding electronics and the DAQ system have been designed to handle events at a mean rate of 2 MHz per detector with low deadtime and to minimize helicity-correlated systematic errors. In this paper, we outline the general architecture and the main features of the electronics and the DAQ system dedicated to G$^0$ forward-angle measurements.Comment: 35 pages. 17 figures. This article is to be submitted to NIM section A. It has been written with Latex using \documentclass{elsart}. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment In Press (2007

The highly rearranged mitochondrial genomes of the crabs Maja crispata and Maja squinado (Majidae) and gene order evolution in Brachyura

Abstract We sequenced the mitochondrial genomes of the spider crabs Maja crispata and Maja squinado (Majidae, Brachyura). Both genomes contain the whole set of 37 genes characteristic of Bilaterian genomes, encoded on both \u3b1- and \u3b2-strands. Both species exhibit the same gene order, which is unique among known animal genomes. In particular, all the genes located on the \u3b2-strand form a single block. This gene order was analysed together with the other nine gene orders known for the Brachyura. Our study confirms that the most widespread gene order (BraGO) represents the plesiomorphic condition for Brachyura and was established at the onset of this clade. All other gene orders are the result of transformational pathways originating from BraGO. The different gene orders exhibit variable levels of genes rearrangements, which involve only tRNAs or all types of genes. Local homoplastic arrangements were identified, while complete gene orders remain unique and represent signatures that can have a diagnostic value. Brachyura appear to be a hot-spot of gene order diversity within the phylum Arthropoda. Our analysis, allowed to track, for the first time, the fully evolutionary pathways producing the Brachyuran gene orders. This goal was achieved by coupling sophisticated bioinformatic tools with phylogenetic analysis

The relationships between problem characteristics, achievement-related behaviors, and academic achievement in problem-based learning

This study investigated the influence of five problem characteristics on students' achievement-related classroom behaviors and academic achievement. Data from 5,949 polytechnic students in PBL curricula across 170 courses were analyzed by means of path analysis. The five problem characteristics were: (1) problem clarity, (2) problem familiarity, (3) the extent to which the problem stimulated group discussion, (4) self-study, and (5) identification of learning goals. The results showed that problem clarity led to more group discussion, identification of learning goals, and self-study than problem familiarity. On the other hand, problem familiarity had a stronger and direct impact on academic achievement

Low Complexity Regularization of Linear Inverse Problems

Inverse problems and regularization theory is a central theme in contemporary signal processing, where the goal is to reconstruct an unknown signal from partial indirect, and possibly noisy, measurements of it. A now standard method for recovering the unknown signal is to solve a convex optimization problem that enforces some prior knowledge about its structure. This has proved efficient in many problems routinely encountered in imaging sciences, statistics and machine learning. This chapter delivers a review of recent advances in the field where the regularization prior promotes solutions conforming to some notion of simplicity/low-complexity. These priors encompass as popular examples sparsity and group sparsity (to capture the compressibility of natural signals and images), total variation and analysis sparsity (to promote piecewise regularity), and low-rank (as natural extension of sparsity to matrix-valued data). Our aim is to provide a unified treatment of all these regularizations under a single umbrella, namely the theory of partial smoothness. This framework is very general and accommodates all low-complexity regularizers just mentioned, as well as many others. Partial smoothness turns out to be the canonical way to encode low-dimensional models that can be linear spaces or more general smooth manifolds. This review is intended to serve as a one stop shop toward the understanding of the theoretical properties of the so-regularized solutions. It covers a large spectrum including: (i) recovery guarantees and stability to noise, both in terms of $\ell^2$-stability and model (manifold) identification; (ii) sensitivity analysis to perturbations of the parameters involved (in particular the observations), with applications to unbiased risk estimation ; (iii) convergence properties of the forward-backward proximal splitting scheme, that is particularly well suited to solve the corresponding large-scale regularized optimization problem

Origin of reduced magnetization and domain formation in small magnetite nanoparticles

The structural, chemical, and magnetic properties of magnetite nanoparticles are compared. Aberration corrected scanning transmission electron microscopy reveals the prevalence of antiphase boundaries in nanoparticles that have significantly reduced magnetization, relative to the bulk. Atomistic magnetic modelling of nanoparticles with and without these defects reveals the origin of the reduced moment. Strong antiferromagnetic interactions across antiphase boundaries support multiple magnetic domains even in particles as small as 12–14 nm