Blazar Flaring Patterns (B-FlaP): Classifying Blazar Candidates of Uncertain type in the third Fermi-LAT catalog by Artificial Neural Networks

The Fermi Large Area Telescope (LAT) is currently the most important facility for investigating the GeV $\gamma$-ray sky. With Fermi LAT more than three thousand $\gamma$-ray sources have been discovered so far. 1144 ($\sim40\%$) of the sources are active galaxies of the blazar class, and 573 ($\sim20\%$) are listed as Blazar Candidate of Uncertain type (BCU), or sources without a conclusive classification. We use the Empirical Cumulative Distribution Functions (ECDF) and the Artificial Neural Networks (ANN) for a fast method of screening and classification for BCUs based on data collected at $\gamma$-ray energies only, when rigorous multiwavelength analysis is not available. Based on our method, we classify 342 BCUs as BL Lacs and 154 as FSRQs, while 77 objects remain uncertain. Moreover, radio analysis and direct observations in ground-based optical observatories are used as counterparts to the statistical classifications to validate the method. This approach is of interest because of the increasing number of unclassified sources in Fermi catalogs and because blazars and in particular their subclass High Synchrotron Peak (HSP) objects are the main targets of atmospheric Cherenkov telescopes.Comment: 18 pages, 17 figures, accepted for publication on MNRA

Optical counterparts of undetermined type γ\gamma-ray Active Galactic Nuclei with blazar-like Spectral Energy Distributions

During its first four years of scientific observations, the Fermi Large Area Telescope (Fermi-LAT) detected 3033 $\gamma$-ray sources above a 4$\sigma$ significance level. Although most of the extra-Galactic sources are active galactic nuclei (AGN) of the blazar class, other families of AGNs are observed too, while a still high fraction of detections ($\sim 30\%$) remains with uncertain association or classification. According to the currently accepted interpretation, the AGN $\gamma$-ray emission arises from inverse Compton (IC) scattering of low energy photons by relativistic particles confined in a jet that, in the case of blazars, is oriented very close to our line of sight. Taking advantage of data from radio and X-ray wavelengths, which we expect to be produced together with $\gamma$-rays, providing a much better source localization potential, we focused our attention on a sample of $\gamma$-ray Blazar Candidates of Undetermined Type (BCUs), starting a campaign of optical spectroscopic observations. The main aims of our investigation include a census of the AGN families that contribute to $\gamma$-ray emission and a study of their redshift distribution, with the subsequent implications on the intrinsic source power. We furthermore analyze which $\gamma$-ray properties can better constrain the nature of the source, thus helping in the study of objects not yet associated with a reliable low frequency counterpart. In this communication we report on the instruments and techniques used to identify the optical counterparts of $\gamma$-ray sources, we give an overview on the status of our work, and we discuss the implications of a large scale study of $\gamma$-ray emitting AGNs.Comment: 9 pages, 2 figures, proceedings of the 10th Serbian Conference on Spectral Line Shapes in Astrophysics. JOAA, accepte

Epstein-Barr virus and multiple sclerosis.

PURPOSE OF REVIEW: Recent studies have revived interest in the long-scrutinized association between Epstein-Barr virus (EBV) and multiple sclerosis (MS). We review this evidence and discuss it in relation to MS pathological and clinical features and patients' response to immunosuppressive therapies. RECENT FINDINGS: Serological evidence of previous exposure to EBV in children with MS supports a role for EBV infection early in MS pathogenesis, as already indicated by prospective studies in adults. Higher antibody titers and T-cell responses to EBV in patients compared to healthy EBV carriers indicate possible continuous viral reactivation, whereas there is some evidence that EBV could break immune tolerance to myelin antigens through molecular mimicry. Detection of EBV-infected B-cells in patients' brain raises the possibility that intrathecal B-cell abnormalities and T-cell-mediated immunopathology in MS are the consequence of a persistently dysregulated EBV infection. Accordingly, targeting T-cells and/or B-cells with monoclonal antibody therapies ameliorates MS. Whether EBV has a causative or pathogenic role in MS can now be addressed in relation to genetic, hormonal and other environmental influences that may affect EBV-host interactions. SUMMARY: By shedding light on the involvement of EBV in MS, these findings will pave the way to disease prevention and increase the therapeutic index of future treatments

Noise in multiple sclerosis: unwanted and necessary

As our knowledge about the etiology of multiple sclerosis (MS) increases, deterministic paradigms appear insufficient to describe the pathogenesis of the disease, and the impression is that stochastic phenomena (i.e. random events not necessarily resulting in disease in all individuals) may contribute to the development of MS. However, sources and mechanisms of stochastic behavior have not been investigated and there is no proposed framework to incorporate nondeterministic processes into disease biology. In this report, we will first describe analogies between physics of nonlinear systems and cell biology, showing how small-scale random perturbations can impact on large-scale phenomena, including cell function. We will then review growing and solid evidence showing that stochastic gene expression (or gene expression “noise”) can be a driver of phenotypic variation. Moreover, we will describe new methods that open unprecedented opportunities for the study of such phenomena in patients and the impact of this information on our understanding of MS course and therapy

Neural Structures to Predict River Stages in Heavily Urbanized Catchments

Accurate flow forecasting may support responsible institutions in managing river systems and limiting damages due to high water levels. Machine-learning models are known to describe many nonlinear hydrological phenomena, but up to now, they have mainly provided a single future value with a fixed information structure. This study trains and tests multi-step deep neural networks with different inputs to forecast the water stage of two sub-alpine urbanized catchments. They prove effective for one hour ahead flood stage values and occurrences. Convolutional neural networks (CNNs) perform better when only past information on the water stage is used. Long short-term memory nets (LSTMs) are more suited to exploit the data coming from the rain gauges. Predicting a set of water stages over the following hour rather than just a single future value may help concerned agencies take the most urgent actions. The paper also shows that the architecture developed for one catchment can be adapted to similar ones maintaining high accuracy

The Hilbert space operator formalism within dynamical reduction models

Unlike standard quantum mechanics, dynamical reduction models assign no particular a priori status to `measurement processes', `apparata', and `observables', nor self-adjoint operators and positive operator valued measures enter the postulates defining these models. In this paper, we show why and how the Hilbert-space operator formalism, which standard quantum mechanics postulates, can be derived from the fundamental evolution equation of dynamical reduction models. Far from having any special ontological meaning, we show that within the dynamical reduction context the operator formalism is just a compact and convenient way to express the statistical properties of the outcomes of experiments.Comment: 25 pages, RevTeX. Changes made and two figures adde

Chamber basis of the Orlik-Solomon algebra and Aomoto complex

We introduce a basis of the Orlik-Solomon algebra labeled by chambers, so called chamber basis. We consider structure constants of the Orlik-Solomon algebra with respect to the chamber basis and prove that these structure constants recover D. Cohen's minimal complex from the Aomoto complex.Comment: 16 page

Reshaping the Museum of Zoology in Rome by Visual Storytelling and Interactive Iconography

This article summarizes the concept of a new immersive and interactive setting for the Zoology Museum in Rome, Italy. The concept, co-designed with all the museum’s curators, is aimed at enhancing the experiential involvement of the visitors by visual storytelling and interactive iconography. Thanks to immersive and interactive technologies designed by Centro Studi Logos, developed by Logosnet and known as e-REALâ and MirrorMeä, zoological findings and memoirs come to life and interact directly with the visitors in order to deepen their understanding, visualize stories and live experiences, and interact with the founder of the Museum (Mr. Arrigoni degli Oddi) who is now a virtualized avatar, or digital human, able to talk with the visitors. All the interactions are powered through simple hand gestures and, in a few cases, vocal inputs that transform into recognized commands from multimedia systems