The assembly of massive galaxies from NIR observations of the Hubble Deep Field South

We use a deep K(AB)<25 galaxy sample in the Hubble Deep Field South to trace the evolution of the cosmological stellar mass density from z~ 0.5 to z~3. We find clear evidence for a decrease of the average stellar mass density at high redshift, 2<z<3.2, that is 15^{+25}_{-5}% of the local value, two times higher than what observed in the Hubble Deep Field North. To take into account for the selection effects, we define a homogeneous subsample of galaxies with 10^{10}M_\odot \leq M_* \leq 10^{11}M_\odot: in this sample, the mass density at z>2 is 20^{+20}_{-5} % of the local value. In the mass--limited subsample at z>2, the fraction of passively fading galaxies is at most 25%, although they can contribute up to about 40% of the stellar mass density. On the other hand, star--forming galaxies at z>2 form stars with an average specific rate at least ~4 x10^{-10} yr$^{-1}$, 3 times higher than the z<~1 value. This implies that UV bright star--forming galaxies are substancial contributors to the rise of the stellar mass density with cosmic time. Although these results are globally consistent with $\Lambda$--CDM scenarios, the present rendition of semi analytic models fails to match the stellar mass density produced by more massive galaxies present at z>2.Comment: Accepted for publication on ApJLetter

ASTRI SST-2M prototype and mini-array simulation chain, data reduction software, and archive in the framework of the Cherenkov Telescope Array

The Cherenkov Telescope Array (CTA) is a worldwide project aimed at building the next-generation ground-based gamma-ray observatory. Within the CTA project, the Italian National Institute for Astrophysics (INAF) is developing an end-to-end prototype of the CTA Small-Size Telescopes with a dual-mirror (SST-2M) Schwarzschild-Couder configuration. The prototype, named ASTRI SST-2M, is located at the INAF "M.C. Fracastoro" observing station in Serra La Nave (Mt. Etna, Sicily) and is currently in the scientific and performance validation phase. A mini-array of (at least) nine ASTRI telescopes has been then proposed to be deployed at the Southern CTA site, by means of a collaborative effort carried out by institutes from Italy, Brazil, and South-Africa. The CTA/ASTRI team is developing an end-to-end software package for the reduction of the raw data acquired with both ASTRI SST-2M prototype and mini-array, with the aim of actively contributing to the global ongoing activities for the official data handling system of the CTA observatory. The group is also undertaking a massive Monte Carlo simulation data production using the detector Monte Carlo software adopted by the CTA consortium. Simulated data are being used to validate the simulation chain and evaluate the ASTRI SST-2M prototype and mini-array performance. Both activities are also carried out in the framework of the European H2020-ASTERICS (Astronomy ESFRI and Research Infrastructure Cluster) project. A data archiving system, for both ASTRI SST-2M prototype and mini-array, has been also developed by the CTA/ASTRI team, as a testbed for the scientific archive of CTA. In this contribution, we present the main components of the ASTRI data handling systems and report the status of their development.Comment: Proceedings of the 35th International Cosmic Ray Conference (ICRC 2017), Bexco, Busan, Korea. All CTA contributions at arXiv:1709.0348

The evolution of the galaxy luminosity function in the rest frame blue band up to z=3.5

We present an estimate of the cosmological evolution of the field galaxy luminosity function (LF) in the rest frame 4400 Angstrom B -band up to redshift z=3.5. To this purpose, we use a composite sample of 1541 I--selected galaxies selected down to I_(AB)=27.2 and 138 galaxies selected down to K_(AB)=25 from ground-based and HST multicolor surveys, most notably the new deep JHK images in the Hubble Deep Field South (HDF-S) taken with the ISAAC instrument at the ESO-VLT telescope. About 21% of the sample has spectroscopic redshifts, and the remaining fraction well calibrated photometric redshifts. The resulting blue LF shows little density evolution at the faint end with respect to the local values, while at the bright end (M_B(AB)<-20) a brightening increasing with redshift is apparent with respect to the local LF. Hierarchical CDM models overpredict the number of faint galaxies by about a factor 3 at z=1. At the bright end the predicted LFs are in reasonable agreement only at low and intermediate redshifts (z=1), but fail to reproduce the pronounced brightening observed in the high redshift (z=2-3) LF. This brightening could mark the epoch where a major star formation activity is present in the galaxy evolution.Comment: 14 pages, 2 figures, Astrophysical Journal Letters, in pres

Mobilization of Iron Stored in Bacterioferritin Is Required for Metabolic Homeostasis in Pseudomonas aeruginosa

Iron homeostasis offers a significant bacterial vulnerability because pathogens obtain essential iron from their mammalian hosts, but host-defenses maintain vanishingly low levels of free iron. Although pathogens have evolved mechanisms to procure host-iron, these depend on well-regulated iron homeostasis. To disrupt iron homeostasis, our work has targeted iron mobilization from the iron storage protein bacterioferritin (BfrB) by blocking a required interaction with its cognate ferredoxin partner (Bfd). The blockade of the BfrB–Bfd complex by deletion of the bfd gene (Δbfd) causes iron to irreversibly accumulate in BfrB. In this study we used mass spectrometry and NMR spectroscopy to compare the proteomic response and the levels of key intracellular metabolites between wild type (wt) and isogenic ΔbfdP. aeruginosa strains. We find that the irreversible accumulation of unusable iron in BfrB leads to acute intracellular iron limitation, even if the culture media is iron-sufficient. Importantly, the iron limitation and concomitant iron metabolism dysregulation trigger a cascade of events that lead to broader metabolic homeostasis disruption, which includes sulfur limitation, phenazine-mediated oxidative stress, suboptimal amino acid synthesis and altered carbon metabolism

A framework to identify structured behavioral patterns within rodent spatial trajectories

Animal behavior is highly structured. Yet, structured behavioral patterns—or “statistical ethograms”—are not immediately apparent from the full spatiotemporal data that behavioral scientists usually collect. Here, we introduce a framework to quantitatively characterize rodent behavior during spatial (e.g., maze) navigation, in terms of movement building blocks or motor primitives. The hypothesis that we pursue is that rodent behavior is characterized by a small number of motor primitives, which are combined over time to produce open-ended movements. We assume motor primitives to be organized in terms of two sparsity principles: each movement is controlled using a limited subset of motor primitives (sparse superposition) and each primitive is active only for time-limited, time-contiguous portions of movements (sparse activity). We formalize this hypothesis using a sparse dictionary learning method, which we use to extract motor primitives from rodent position and velocity data collected during spatial navigation, and successively to reconstruct past trajectories and predict novel ones. Three main results validate our approach. First, rodent behavioral trajectories are robustly reconstructed from incomplete data, performing better than approaches based on standard dimensionality reduction methods, such as principal component analysis, or single sparsity. Second, the motor primitives extracted during one experimental session generalize and afford the accurate reconstruction of rodent behavior across successive experimental sessions in the same or in modified mazes. Third, in our approach the number of motor primitives associated with each maze correlates with independent measures of maze complexity, hence showing that our formalism is sensitive to essential aspects of task structure. The framework introduced here can be used by behavioral scientists and neuroscientists as an aid for behavioral and neural data analysis. Indeed, the extracted motor primitives enable the quantitative characterization of the complexity and similarity between different mazes and behavioral patterns across multiple trials (i.e., habit formation). We provide example uses of this computational framework, showing how it can be used to identify behavioural effects of maze complexity, analyze stereotyped behavior, classify behavioral choices and predict place and grid cell displacement in novel environments