Stability and Reversible Oxidation of Sub-Nanometric Cu5 Metal Clusters: Integrated Experimental Study and Theoretical Modeling**

Sub-nanometer metal clusters have special physical and chemical properties, significantly different from those of nanoparticles. However, there is a major concern about their thermal stability and susceptibility to oxidation. In situ X-ray Absorption spectroscopy and Near Ambient Pressure X-ray Photoelectron spectroscopy results reveal that supported Cu5 clusters are resistant to irreversible oxidation at least up to 773 K, even in the presence of 0.15 mbar of oxygen. These experimental findings can be formally described by a theoretical model which combines dispersion-corrected DFT and first principles thermochemistry revealing that most of the adsorbed O2 molecules are transformed into superoxo and peroxo species by an interplay of collective charge transfer within the network of Cu atoms and large amplitude “breathing” motions. A chemical phase diagram for Cu oxidation states of the Cu5-oxygen system is presented, clearly different from the already known bulk and nano-structured chemistry of Cu

Circular polarization in a non-magnetic resonant tunneling device

We have investigated the polarization-resolved photoluminescence (PL) in an asymmetric n-type GaAs/AlAs/GaAlAs resonant tunneling diode under magnetic field parallel to the tunnel current. The quantum well (QW) PL presents strong circular polarization (values up to -70% at 19 T). The optical emission from GaAs contact layers shows evidence of highly spin-polarized two-dimensional electron and hole gases which affects the spin polarization of carriers in the QW. However, the circular polarization degree in the QW also depends on various other parameters, including the g-factors of the different layers, the density of carriers along the structure, and the Zeeman and Rashba effects

The Mass-Metallicity relation explored with CALIFA: I. Is there a dependence on the star formation rate?

We present the results on the study of the global and local M-Z relation based on the first data available from the CALIFA survey (150 galaxies). This survey provides integral field spectroscopy of the complete optical extent of each galaxy (up to 2-3 effective radii), with enough resolution to separate individual HII regions and/or aggregations. Nearly $\sim$3000 individual HII regions have been detected. The spectra cover the wavelength range between [OII]3727 and [SII]6731, with a sufficient signal-to-noise to derive the oxygen abundance and star-formation rate associated with each region. In addition, we have computed the integrated and spatially resolved stellar masses (and surface densities), based on SDSS photometric data. We explore the relations between the stellar mass, oxygen abundance and star-formation rate using this dataset. We derive a tight relation between the integrated stellar mass and the gas-phase abundance, with a dispersion smaller than the one already reported in the literature ($\sigma_{\Delta{\rm log(O/H)}}=$0.07 dex). Indeed, this dispersion is only slightly larger than the typical error derived for our oxygen abundances. However, we do not find any secondary relation with the star-formation rate, other than the one induced due to the primary relation of this quantity with the stellar mass. We confirm the result using the $\sim$3000 individual HII regions, for the corresponding local relations. Our results agree with the scenario in which gas recycling in galaxies, both locally and globally, is much faster than other typical timescales, like that of gas accretion by inflow and/or metal loss due to outflows. In essence, late-type/disk dominated galaxies seem to be in a quasi-steady situation, with a behavior similar to the one expected from an instantaneous recycling/closed-box model.Comment: 19 Pages, 8 figures, Accepted for Publishing in Astronomy and Astrophysics (A&A

Shape modeling technique KOALA validated by ESA Rosetta at (21) Lutetia

We present a comparison of our results from ground-based observations of asteroid (21) Lutetia with imaging data acquired during the flyby of the asteroid by the ESA Rosetta mission. This flyby provided a unique opportunity to evaluate and calibrate our method of determination of size, 3-D shape, and spin of an asteroid from ground-based observations. We present our 3-D shape-modeling technique KOALA which is based on multi-dataset inversion. We compare the results we obtained with KOALA, prior to the flyby, on asteroid (21) Lutetia with the high-spatial resolution images of the asteroid taken with the OSIRIS camera on-board the ESA Rosetta spacecraft, during its encounter with Lutetia. The spin axis determined with KOALA was found to be accurate to within two degrees, while the KOALA diameter determinations were within 2% of the Rosetta-derived values. The 3-D shape of the KOALA model is also confirmed by the spectacular visual agreement between both 3-D shape models (KOALA pre- and OSIRIS post-flyby). We found a typical deviation of only 2 km at local scales between the profiles from KOALA predictions and OSIRIS images, resulting in a volume uncertainty provided by KOALA better than 10%. Radiometric techniques for the interpretation of thermal infrared data also benefit greatly from the KOALA shape model: the absolute size and geometric albedo can be derived with high accuracy, and thermal properties, for example the thermal inertia, can be determined unambiguously. We consider this to be a validation of the KOALA method. Because space exploration will remain limited to only a few objects, KOALA stands as a powerful technique to study a much larger set of small bodies using Earth-based observations.Comment: 15 pages, 8 figures, 2 tables, accepted for publication in P&S

Characterisation of feline renal cortical fibroblast cultures and their transcriptional response to transforming growth factor beta 1

Chronic kidney disease (CKD) is common in geriatric cats, and the most prevalent pathology is chronic tubulointerstitial inflammation and fibrosis. The cell type predominantly responsible for the production of extra-cellular matrix in renal fibrosis is the myofibroblast, and fibroblast to myofibroblast differentiation is probably a crucial event. The cytokine TGF-β1 is reportedly the most important regulator of myofibroblastic differentiation in other species. The aim of this study was to isolate and characterise renal fibroblasts from cadaverous kidney tissue of cats with and without CKD, and to investigate the transcriptional response to TGF-β1

Dynamical Patterns of Cattle Trade Movements

Despite their importance for the spread of zoonotic diseases, our understanding of the dynamical aspects characterizing the movements of farmed animal populations remains limited as these systems are traditionally studied as static objects and through simplified approximations. By leveraging on the network science approach, here we are able for the first time to fully analyze the longitudinal dataset of Italian cattle movements that reports the mobility of individual animals among farms on a daily basis. The complexity and inter-relations between topology, function and dynamical nature of the system are characterized at different spatial and time resolutions, in order to uncover patterns and vulnerabilities fundamental for the definition of targeted prevention and control measures for zoonotic diseases. Results show how the stationarity of statistical distributions coexists with a strong and non-trivial evolutionary dynamics at the node and link levels, on all timescales. Traditional static views of the displacement network hide important patterns of structural changes affecting nodes' centrality and farms' spreading potential, thus limiting the efficiency of interventions based on partial longitudinal information. By fully taking into account the longitudinal dimension, we propose a novel definition of dynamical motifs that is able to uncover the presence of a temporal arrow describing the evolution of the system and the causality patterns of its displacements, shedding light on mechanisms that may play a crucial role in the definition of preventive actions

Dynamical Patterns of Cattle Trade Movements

Despite their importance for the spread of zoonotic diseases, our understanding of the dynamical aspects characterizing the movements of farmed animal populations remains limited as these systems are traditionally studied as static objects and through simplified approximations. By leveraging on the network science approach, here we are able for the first time to fully analyze the longitudinal dataset of Italian cattle movements that reports the mobility of individual animals among farms on a daily basis. The complexity and inter-relations between topology, function and dynamical nature of the system are characterized at different spatial and time resolutions, in order to uncover patterns and vulnerabilities fundamental for the definition of targeted prevention and control measures for zoonotic diseases. Results show how the stationarity of statistical distributions coexists with a strong and non-trivial evolutionary dynamics at the node and link levels, on all timescales. Traditional static views of the displacement network hide important patterns of structural changes affecting nodes' centrality and farms' spreading potential, thus limiting the efficiency of interventions based on partial longitudinal information. By fully taking into account the longitudinal dimension, we propose a novel definition of dynamical motifs that is able to uncover the presence of a temporal arrow describing the evolution of the system and the causality patterns of its displacements, shedding light on mechanisms that may play a crucial role in the definition of preventive actions

CALIFA, the Calar Alto Legacy Integral Field Area survey: I. Survey presentation

We present here the Calar Alto Legacy Integral Field Area (CALIFA) survey, which has been designed to provide a first step in this direction.We summarize the survey goals and design, including sample selection and observational strategy.We also showcase the data taken during the first observing runs (June/July 2010) and outline the reduction pipeline, quality control schemes and general characteristics of the reduced data. This survey is obtaining spatially resolved spectroscopic information of a diameter selected sample of $\sim600$ galaxies in the Local Universe (0.005< z <0.03). CALIFA has been designed to allow the building of two-dimensional maps of the following quantities: (a) stellar populations: ages and metallicities; (b) ionized gas: distribution, excitation mechanism and chemical abundances; and (c) kinematic properties: both from stellar and ionized gas components. CALIFA uses the PPAK Integral Field Unit (IFU), with a hexagonal field-of-view of \sim1.3\sq\arcmin', with a 100% covering factor by adopting a three-pointing dithering scheme. The optical wavelength range is covered from 3700 to 7000 {\AA}, using two overlapping setups (V500 and V1200), with different resolutions: R\sim850 and R\sim1650, respectively. CALIFA is a legacy survey, intended for the community. The reduced data will be released, once the quality has been guaranteed. The analyzed data fulfill the expectations of the original observing proposal, on the basis of a set of quality checks and exploratory analysis. We conclude from this first look at the data that CALIFA will be an important resource for archaeological studies of galaxies in the Local Universe.Comment: 32 pages, 29 figures, Accepted for publishing in Astronomy and Astrophysic

Modeling what we sample and sampling what we model: challenges for zooplankton model assessment

Zooplankton are the intermediate trophic level between phytoplankton and fish, and are an important component of carbon and nutrient cycles, accounting for a large proportion of the energy transfer to pelagic fishes and the deep ocean. Given zooplankton's importance, models need to adequately represent zooplankton dynamics. A major obstacle, though, is the lack of model assessment. Here we try and stimulate the assessment of zooplankton in models by filling three gaps. The first is that many zooplankton observationalists are unfamiliar with the biogeochemical, ecosystem, size-based and individual-based models that have zooplankton functional groups, so we describe their primary uses and how each typically represents zooplankton. The second gap is that many modelers are unaware of the zooplankton data that are available, and are unaccustomed to the different zooplankton sampling systems, so we describe the main sampling platforms and discuss their strengths and weaknesses for model assessment. Filling these gaps in our understanding of models and observations provides the necessary context to address the last gap—a blueprint for model assessment of zooplankton. We detail two ways that zooplankton biomass/abundance observations can be used to assess models: data wrangling that transforms observations to be more similar to model output; and observation models that transform model outputs to be more like observations. We hope that this review will encourage greater assessment of zooplankton in models and ultimately improve the representation of their dynamics