Gamma-Ray Burst observations by the high-energy charged particle detector on board the CSES-01 satellite between 2019 and 2021

In this paper we report the detection of five strong Gamma-Ray Bursts (GRBs) by the High-Energy Particle Detector (HEPD-01) mounted on board the China Seismo-Electromagnetic Satellite (CSES-01), operational since 2018 on a Sun-synchronous polar orbit at a $\sim$ 507 km altitude and 97$^\circ$ inclination. HEPD-01 was designed to detect high-energy electrons in the energy range 3 - 100 MeV, protons in the range 30 - 300 MeV, and light nuclei in the range 30 - 300 MeV/n. Nonetheless, Monte Carlo simulations have shown HEPD-01 is sensitive to gamma-ray photons in the energy range 300 keV - 50 MeV, even if with a moderate effective area above $\sim$ 5 MeV. A dedicated time correlation analysis between GRBs reported in literature and signals from a set of HEPD-01 trigger configuration masks has confirmed the anticipated detector sensitivity to high-energy photons. A comparison between the simultaneous time profiles of HEPD-01 electron fluxes and photons from GRB190114C, GRB190305A, GRB190928A, GRB200826B and GRB211211A has shown a remarkable similarity, in spite of the different energy ranges. The high-energy response, with peak sensitivity at about 2 MeV, and moderate effective area of the detector in the actual flight configuration explain why these five GRBs, characterised by a fluence above $\sim$ 3 $\times$ 10$^{-5}$ erg cm$^{-2}$ in the energy interval 300 keV - 50 MeV, have been detected.Comment: Accepted for publication in The Astrophysical Journal (ApJ

The ALICE experiment at the CERN LHC

ALICE (A Large Ion Collider Experiment) is a general-purpose, heavy-ion detector at the CERN LHC which focuses on QCD, the strong-interaction sector of the Standard Model. It is designed to address the physics of strongly interacting matter and the quark-gluon plasma at extreme values of energy density and temperature in nucleus-nucleus collisions. Besides running with Pb ions, the physics programme includes collisions with lighter ions, lower energy running and dedicated proton-nucleus runs. ALICE will also take data with proton beams at the top LHC energy to collect reference data for the heavy-ion programme and to address several QCD topics for which ALICE is complementary to the other LHC detectors. The ALICE detector has been built by a collaboration including currently over 1000 physicists and engineers from 105 Institutes in 30 countries. Its overall dimensions are 161626 m3 with a total weight of approximately 10 000 t. The experiment consists of 18 different detector systems each with its own specific technology choice and design constraints, driven both by the physics requirements and the experimental conditions expected at LHC. The most stringent design constraint is to cope with the extreme particle multiplicity anticipated in central Pb-Pb collisions. The different subsystems were optimized to provide high-momentum resolution as well as excellent Particle Identification (PID) over a broad range in momentum, up to the highest multiplicities predicted for LHC. This will allow for comprehensive studies of hadrons, electrons, muons, and photons produced in the collision of heavy nuclei. Most detector systems are scheduled to be installed and ready for data taking by mid-2008 when the LHC is scheduled to start operation, with the exception of parts of the Photon Spectrometer (PHOS), Transition Radiation Detector (TRD) and Electro Magnetic Calorimeter (EMCal). These detectors will be completed for the high-luminosity ion run expected in 2010. This paper describes in detail the detector components as installed for the first data taking in the summer of 2008

Mapping local social protection data in Italy

People living in close geographic areas can experience different quality of life standards. This depends on many factors among which the performance of local welfare systems may play a relevant role. In this paper, we examine Italian official statistics in order to identify available information on local social protection activities. The main objective is to assess if it is possible to convey a complete view of the level and quality of social protection services delivered by local actors. Furthermore, we present some analysis of municipalities’ social expenditure at Nuts 2 and 3 levels to show evidence of disparities among territories

Development of a Carbon-fiber reinforced polymer-based mechanics for embedding ALPIDE pixel sensors in the High-Energy Particle Detector space module onboard the CSES-02 satellite.

The mission CSES (China Seismo-Electromagnetic Satellite) will put into orbit satellites to study perturbations in the ionosphere, possibly correlated with the occurrence of seismic events. CSES-02, the second satellite of the constellation, will be supplied with a High-Energy Particle Detector (HEPD), composed by a tracker, a trigger system and a calorimeter, designed for the detection of electrons (protons) in the 3-100 (30-200) MeV energy range. The tracker is based on the innovative monolithic pixel sensors ALPIDE, developed for the ALICE experiment, at CERN. The adaptation of the ALPIDE technology to the use in space environments, demanded for ad-hoc solutions for the mechanics, as supporting structures have to withstand structural and vibrational stresses in a wide energy range, maintaining their capability to dissipate the heat generated by ALPIDE operations. This work presents the HEPD-02 tracker, consisting of 150 pixel sensors, supported by Carbon Fiber Reinforced Plastic (CFRPs) and enclosed in an Aluminum frame, focusing on the limited impact that devised solutions have on the physics performance. We report results from an intense campaign of qualification tests, conducted according to the space register and constituting an important premise for using monolithic active pixel sensors in future space cosmic ray experiments

Lights and shadows of COVID-19, Technology and Industry 4.0

Scientific discoveries and technologies played a significant role in the digital revolution that occurred over the last years. But what is their role in the turmoil brought by the current pandemic? The aim of this paper is to show how digital technologies are operating during this first phase of the spreading of COVID-19. The study analyses and debates the current and potential role of digital technologies, focusing on their influence in the industrial and social fields. More specifically we used the blogging platform "Medium", which has seen an exponential growth in its production of articles over the last couple of months. Even if different from esteemed scientific sources, this platform provides a structure that suits our analysis. We searched how many times digital technologies are mentioned in articles regarding Coronavirus and, after collecting these articles, we collected page tags (comparable to "keywords" in scientific articles) and classified them (technology tags and non-technology tags), to create a graph showing the relation between them. This network allowed us to acknowledge and picture how technologies are currently debated. This was the starting point to discuss the key implications for an imminent future, and question about the impact on industry, society and labour market. What are the opportunities or threats of using technologies of Industry 4.0? Which are the needs rising because of the pandemic and how can technologies help in their fulfillment? How will the industrial scenario change after this pandemic? How will the labour market be affected? How can technologies be advantageous in the emerging social challenges

Workers 4.0: skills, profiles and jobs in different business functions

The term “Industry 4.0” refers to a new production paradigm, radically different from the previous ones because of its global scope and its certain (if not clearly defined) impact on social, economic and political structures. The key characteristics of the Industry 4.0 includes the integration of electronics and computer science observed in machine to machine communication (nowadays known as the Industrial Internet of Things), the possibilities opened up by cloud computing, the opportunities to explore big data, and augmented and/or virtual reality made possible by the past investments in computer games. The need to manage the use of these new technologies is likely to bring about a radical change in the design of products, how they are produced and, concomitantly, the organisation of work. This suggests that consideration needs to be given to the skills needs that are likely to arise. While predicting emerging skills needs from Industry 4.0 is still in its infancy, it is vitally important that steps are made to identifying those skills which people will need in the future. This chapter builds upon the previous one by Fantoni and his colleagues to: (i) Identify where, according to the Porter value-chain model, the effects of Industry 4.0 will take place; and (ii) Building on (i) identify the basic competences associated with the emerging job profiles resulting from Industry 4.0. After having identified and clustered competences by using text mining techniques, the chapter analyses how competences are distributed among company functions (i.e. marketing, sales, production, design, R&D, maintenance, etc.). Data are drawn from Scopus – the abstract and citation database – and O*NET. These provide information on emerging job/professional profiles and associated skill profiles respectively. Porter’s value-chain describes the structure of an organisation as a limited set of processes; it is divided into nine main processes, five primary and four supports. The primary processes are those which directly contribute to the creation of output, while the supporting ones are necessary for the latter to be produced. Using this model it is possible to identify the functions within organisations most affected by Industry 4.0. The result is a matrix that cross-classifies workers’ Industry 4.0 job profiles by business functions. From the analysis it is possible to notice not only where the new skills will have a particular impact, but also which are the professional profiles associated with them and in which business area they will contribute most

Biochemical and mass spectrometric characterization of soluble ecto-5'-nucleotidase from bull seminal plasma.

Ecto-5'-nucleotidase (ecto-5'-NT) is a glycosylphosphatidylinositol-anchored membrane-bound protein that is ubiquitous in mammalian tissues. It is a target for a number of therapeutic drugs since increased levels of the enzyme correlate with various disease states. In this investigation, we describe the properties of a soluble ecto-5'-NT derived from bull seminal plasma. The protein was highly heterogeneous as demonstrated by chromatofocusing and two-dimensional PAGE. Sequencing analyses revealed a truncated polypeptide lacking the glycosylphospatidylinositol attachment site, suggesting that it is produced post-translationally by cleavage at Gln(547) and/or Phe(548). Heterogeneity was largely due to differential glycosylation, especially in the oligosaccharides linked to Asn(403). Significant differences in substrate specificity were observed between isoforms and, on the basis of molecular-modelling studies, were interpreted in terms of variable glycosylation causing steric hindrance of the substrate-binding site. Thus the soluble forms of ecto-5'-NT found in bull seminal plasma are unique both biochemically and structurally, and have a putative role in signalling interactions with spermatozoa following ejaculation and capacitation in the female reproductive tract