Detection of Faint BLR Components in the Starburst/Seyfert Galaxy NGC 6221 and Measure of the Central BH Mass

In the last decade, using single epoch virial based techniques in the optical band, it has been possible to measure the central black hole mass on large AGN1 samples. However these measurements use the width of the broad line region as a proxy of the virial velocities and are therefore difficult to be carried out on those obscured (type 2) or low luminosity AGN where the nuclear component does not dominate in the optical. Here we present the optical and near infrared spectrum of the starburst/Seyfert galaxy NGC 6221, observed with X-shooter/VLT. Previous observations of NGC 6221 in the X-ray band show an absorbed (N_H=8.5 +/- 0.4 x 10^21 cm^-2) spectrum typical of a type 2 AGN with luminosity log(L_14-195 keV) = 42.05 erg/s, while in the optical band its spectrum is typical of a reddened (A_V=3) starburst. Our deep X-shooter/VLT observations have allowed us to detect faint broad emission in the H_alpha, HeI and Pa_beta lines (FWHM ~1400-2300 km/s) confirming previous studies indicating that NGC 6221 is a reddened starburst galaxy which hosts an AGN. We use the measure of the broad components to provide a first estimate of its central black hole mass (M_BH = 10^(6.6 +/- 0.3) Msol, lambda_Edd=0.01-0.03), obtained using recently calibrated virial relations suitable for moderately obscured (N_H<10^24 cm^-2) AGN.Comment: 13 pages, 3 figures, 1 table. Published in Frontiers in Astronomy and Space Science

Extending Virial Black Hole Mass Estimates to Low-Luminosity or Obscured AGN: the cases of NGC 4395 and MCG -01-24-012

In the last decade, using single epoch (SE) virial based spectroscopic optical observations, it has been possible to measure the black hole (BH) mass on large type 1 Active Galactic Nuclei (AGN) samples. However this kind of measurements can not be applied on those obscured type 2 and/or low luminosity AGN where the nuclear component does not dominate in the optical. We have derived new SE relationships, based on the FWHM and luminosity of the broad line region component of the Pabeta emission line and/or the hard X-ray luminosity in the 14-195 keV band, which have the prospect of better working with low luminosity or obscured AGN. The SE relationships have been calibrated in the 10^5-10^9 M_sol mass range, using a sample of AGN whose BH masses have been previously measured using reverberation mapping techniques. Our tightest relationship between the reverberation-based BH mass and the SE virial product has an intrinsic spread of 0.20 dex. Thanks to these SE relations, in agreement with previous estimates, we have measured a BH mass of M_BH =1.7^+1.3_-0.7 X 10^5 M_sol for the low luminosity, type 1, AGN NGC 4395 (one of the smallest active galactic BH known). We also measured, for the first time, a BH mass of M_BH = 1.5^+1.1_-0.6 X 10^7 M_sol for the Seyfert 2 galaxy MCG -01-24-012.Comment: 10 pages, 7 figures. Accepted by MNRA

NGC 1275: An Outlier of the Black Hole-Host Scaling Relations

The active galaxy NGC 1275 lies at the center of the Perseus cluster of galaxies, being an archetypal BH-galaxy system that is supposed to fit well with the M-BH-host scaling relations obtained for quiescent galaxies. Since it harbors an obscured AGN, only recently our group has been able to estimate its black hole mass. Here our aim is to pinpoint NGC 1275 on the less dispersed scaling relations, namely the M-BH-sigma(*) and M-BH - L-bul planes. Starting from our previous work (Ricci et al., 2017a), we estimate that NGC 1275 falls well outside the intrinsic dispersion of the M-BH-sigma(*) plane being 1.2 dex (in black hole mass) displaced with respect to the scaling relations. We then perform a 2D morphological decomposition analysis on Spitzer/IRAC images at 3.6 mu m and find that, beyond the bright compact nucleus that dominates the central emission, NGC 1275 follows a de Vaucouleurs profile with no sign of significant star formation nor clear merger remnants. Nonetheless, its displacement on the M-BH - L-3.6,L-bul plane with respect to the scaling relation is as high as observed in the M-BH-sigma(*). We explore various scenarios to interpret such behaviors, of which the most realistic one is the evolutionary pattern followed by NGC 1275 to approach the scaling relation. We indeed speculate that NGC 1275 might be a specimen for those galaxies in which the black holes adjusted to its host

Seroprevalence of SARS-CoV-2–Specific Antibodies in Cancer Patients Undergoing Active Systemic Treatment: A Single-Center Experience from the Marche Region, Italy

none13noSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seroprevalence in cancer patients may vary widely dependent on the geographic area and this has significant implications for oncological care. The aim of this observational, prospective study was to assess the seroprevalence of SARS-CoV-2 IgM/IgG antibodies in solid cancer patients referred to the academic institution of the Marche Region, Italy, between 1 July and 26 October 2020 and to determine the accuracy of the rapid serological test. After performing 3767 GCCOV-402a rapid serological tests on a total of 949 patients, seroconversion was initially observed in 13 patients (1.4%). Ten (77% of the total positive) were IgG-positive, 1 (8%) were IgM-positive and 2 (15%) IgM-positive/IgG-positive. However, only 7 out of 13 were confirmed as positive at the reference serological test (true positives), thus seroprevalence after cross-checking was 0.7%. No false negatives were reported. The kappa value of the consistency analysis was 0.71. Due to rapid serological test high false positive rate, its role in assessing seroconversion rate is limited, and the standard serological tests should remain the gold standard. However, as rapid test negative predictive value is high, GCCOV-402a may instead be useful to monitor patient immunity over time, thus helping to assist ongoing vaccination programsopenCantini, Luca; Bastianelli, Lucia; Lupi, Alessio; Pinterpe, Giada; Pecci, Federica; Belletti, Giovanni; Stoico, Rosa; Vitarelli, Francesca; Moretti, Marco; Onori, Nicoletta; Giampieri, Riccardo; Rocchi, Marco Bruno Luigi; Berardi, RossanaCantini, Luca; Bastianelli, Lucia; Lupi, Alessio; Pinterpe, Giada; Pecci, Federica; Belletti, Giovanni; Stoico, Rosa; Vitarelli, Francesca; Moretti, Marco; Onori, Nicoletta; Giampieri, Riccardo; Rocchi, Marco Bruno Luigi; Berardi, Rossan

Remote sensing as tool for development of landslide databases: The case of the Messina Province (Italy) geodatabase

Landslide geodatabases, including inventories and thematic data, today are fundamental tools for national and/or local authorities in susceptibility, hazard and risk management. A well organized landslide geo-database contains different kinds of data such as past information (landslide inventory maps), ancillary data and updated remote sensing (space-borne and ground based) data, which can be integrated in order to produce landslide susceptibility maps, updated landslide inventory maps and hazard and risk assessment maps. Italy is strongly affected by landslide phenomena which cause victims and significant economic damage to buildings and infrastructure, loss of productive soils and pasture lands. In particular, the Messina Province (southern Italy) represents an area where landslides are recurrent and characterized by high magnitude, due to several predisposing factors (e.g. morphology, land use, lithologies) and different triggering mechanisms (meteorological conditions, seismicity, active tectonics and volcanic activity). For this area, a geodatabase was created by using different monitoring techniques, including remote sensing (e.g. SAR satellite ERS1/2, ENVISAT, RADARSAT-1, TerraSAR-X, COSMO-SkyMed) data, and in situ measurements (e.g. GBInSAR, damage assessment). In this paper a complete landslide geodatabase of the Messina Province, designed following the requirements of the local and national Civil Protection authorities, is presented. This geo-database was used to produce maps (e.g. susceptibility, ground deformation velocities, damage assessment, risk zonation) which today are constantly used by the Civil Protection authorities to manage the landslide hazard of the Messina Province

Experience-Based Food Insecurity Scales, a Non-Aggregative Approach to Synthesis of Indicators

Food security is a complex and multidimensional phenomenon, access to food is one of its dimensions and experience-based food insecurity scales have been, in the last decades, the main tool for investigating it. When the phenomenon is considered at the household level, then these scales are built from a set of dichotomous items reflecting experiences related to access to food that the household possibly had to deal with in the previous months. From the point of view of the statistical treatment, these scales are mainly tackled using two different approaches: the counting approach and the Rasch model. The first one is mainly adopted at a national level to compute prevalences of food insecurity at different levels of severity. On the other hand, the Rasch model approach is adopted by the Food and Agriculture Organization of the United Nations (FAO) with the aim of monitoring access to food at a global level by producing comparable prevalences of food insecurity across countries. Although following different statistical steps of the analysis, both the counting and the Rasch model approach consider the vector of responses of a household to a number of dichotomous items and condense all information into one value only, the range of which will determine the category of food insecurity the household belongs to.In this way, two households with the same value for the final indicator could have potentially affirmatively answered different items, with a consequent lost of information that would instead help differantiate the two households and better suggest strategies for policy-makers. The objective of our work is to provide, starting from the indicators of each domain of the access to food, synthesis adopting a non-aggregative approach, namely the Partial Order Set Theory (Poset). The resulting composite indicator, in contrast with the case of both the counting approach and the Rasch model, is not a number anymore but a Directed Acyclic Graph (DAG) called the Hasse diagram. This graph represents the set of partial comparabilities that can be established among different profiles households belong to. At the core of this approach is the idea that not all profiles resulting from answers to a set of dichotomous items can be directly and unambigously compared. Therefore, it can be of practical relvance to rely on a methodology that more realistically reflect the ordinal quality of the data. Analysis of this work concerns data from the food security section of the “National Survey on Life Conditions” in Guatemala in 2014. The non-aggregative approach allowed us to highlight differences in the eight regions of Guatemala that would otherwise not show up if adopting an aggregative approach to the synthesis of indicators

Modeling “Equitable and Sustainable Well-being” (BES) Using Bayesian Networks: A Case Study of the Italian Regions

Measurement of well-being has been a highly debated topic since the end of the last century. While some specific aspects are still open issues, a multidimensional approach as well as the construction of shared and well-rooted systems of indicators are now accepted as the main route to measure this complex phenomenon. A meaningful effort, in this direction, is that of the Italian “Equitable and Sustainable Well-being” (BES) system of indicators, developed by the Italian National Institute of Statistics (ISTAT) and the National Council for Economics and Labour (CNEL). The BES framework comprises a number of atomic indicators measured yearly at regional level and reflecting the different domains of well-being (e.g. Health, Education, Work &amp; Life Balance, Environment,...). In this work we aim at dealing with the multidimensionality of the BES system of indicators and try to answer three main research questions: (I) What is the structure of the relationships among the BES atomic indicators; (II) What is the structure of the relationships among the BES domains; (III) To what extent the structure of the relationships reflects the current BES theoretical framework. We address these questions by implementing Bayesian Networks (BNs), a widely accepted class of multivariate statistical models, particularly suitable for handling reasoning with uncertainty. Implementation of a BN results in a set of nodes and a set of conditional independence statements that provide an effective tool to explore associations in a system of variables. In this work, we also suggest two strategies for encoding prior knowledge in the BN estimating algorithm so that the BES theoretical framework can be represented into the network

Comparison between Experience-based Food Insecurity scales

In order to face food insecurity as a global phenomenon, it is essential torely on measurement tools that guarantee comparability across countries. Althoughthe official indicator adopted by the United Nations in the context of the Sustain-able Development Goals (SDGs) and based on the Food Insecurity Experience Scale(FIES) already embeds cross-country comparability, other experience-based scalescurrently employ national thresholds. In this paper we address the issue of compara-bility by presenting two different studies. The first one between FIES and three na-tional scales (ELCSA, EMSA and EBIA) included in national surveys in Guatemala,Ecuador, Mexico and Brazil. The second one between the adult and children ver-sions of these national scales. Different methods from the equating practice of edu-cational testing are explored: parametric, nonparametric, classical and based on theItem Response Theory (IRT)

Towards global monitoring: equating the Food Insecurity Experience Scale (FIES) and food insecurity scales in Latin America

In order to face food insecurity as a global phenomenon, it is essential to rely on measurement tools that guarantee comparability across countries. Although the official indicators adopted by the United Nations in the context of the Sustainable Development Goals (SDGs) and based on the Food Insecurity Experience Scale (FIES) already embeds cross-country comparability, other experiential scales of food insecurity currently employ national thresholds and issues of comparability thus arise. In this work we address comparability of food insecurity experience-based scales by presenting two different studies. The first one involves the FIES and three national scales (ELCSA, EMSA and EBIA) currently included in national surveys in Guatemala, Ecuador, Mexico and Brazil. The second study concerns the adult and children versions of these national scales. Different methods from the equating practice of the educational testing field are explored: classical and based on the Item Response Theory (IRT

Structure Learning for Cyclic Linear Causal Models

We consider the problem of structure learning for linear causal models based on observational data. We treat models given by possibly cyclic mixed graphs, which allow for feedback loops and effects of latent confounders. Generalizing related work on bow-free acyclic graphs, we assume that the underlying graph is simple. This entails that any two observed variables can be related through at most one direct causal effect and that (confounding-induced) correlation between error terms in structural equations occurs only in absence of direct causal effects. We show that, despite new subtleties in the cyclic case, the considered simple cyclic models are of expected dimension and that a previously considered criterion for distributional equivalence of bow-free acyclic graphs has an analogue in the cyclic case. Our result on model dimension justifies in particular score-based methods for structure learning of linear Gaussian mixed graph models, which we implement via greedy search