Are business and economics alike?

This paper investigates the decision of Italian high school leavers to enroll at Economics or Business degree courses. We use data from National Student Register gathered by the Italian Ministry of Education, University and Research, which provides information for all the students that enroll at the university as well as their academic career. The academic years analysed are 2008-2015. From the aggregate data, we know that at matriculation, the ratio between the enrollment in Economics and Business is 1:3, but what happens in the following years? Is that proportion stable or does it change? We estimate a multiple equation system model for each field of study. First, we focus on the determinants of the decision to enroll. We analyse whether Economics and Business that might be perceived as similar at the time of enrollment, might instead be different in many respects. Second, we exploit the panel component of the dataset to investigate what happens after the first-year: is the student still enrolled in the same field? Or, is the student enrolled in a different major, or in a different topic? We offer policy implications

Even more discouraged? The NEET generation at the age of COVID-19

This paper evaluates if and to what extend the risk of becoming Not in Employment, Education or Training (NEET) has worsened during the Covid-19 pandemic in Italy. The analysis is based on a unique dataset from the merging of two sample surveys, the Italian Labor Force Survey and the Institutional Quality Index dataset. We find that the probability of being NEET significantly increased during the pandemic, but heterogeneously between age cohorts and geographical areas. The most affected categories have been young people (aged 25-34) and those living in North-West regions. Females are mostly affected compared to males, especially those experiencing motherhood and living in a Southern province. Investment in education reduces the NEET status, mainly for age-group 25-34 in the South. Participation in the civil society significantly reduces the probability to being NEET. Finally, active policies conducted at regional level are a further educational investment that protect from becoming NEET, although their effectiveness is not significant in the Southern regions. We provide novel evidence to inform policymakers and help building evidencebased policies, tailored on local needs

Who lost the most? Distributive effects of COVID-19 pandemic

This paper investigates what happened to the wage distribution in Italy during the first wave of the COVID-19 pandemic. It shows which categories of workers and economic sectors have suffered more than others and to what extent both the actual level of smart-working and the ability to Working From-Home can influence the wage distribution. We use a unique dataset relying on the merging of two sample surveys: the Italian Labor Force Survey set up by National Institute of Statistics and the Italian Survey of Professions conducted by the National Institute for Public Policy Analysis. We estimate quantile regression models accounting for selection. First, the findings reveal that the pandemic has affected the wages of the whole workers, but the effect is higher at the bottom of the wage distribution. Second, the actual working from home mitigates the negative distributional consequences of the COVID-19 observed for those at the bottom of the wage distribution. However, the advantage of workers at the bottom tail of the wage distribution seems to lessen in the long term once the health emergency is passed. Third, looking at sectoral heterogeneity, retail and the restaurant are the most hit sectors in terms of wage loss. Fourth, separating by gender, men have been mostly hit by the pandemic, particularly at lowest deciles, though they benefited more from working at home at higher deciles. Finally, women appear as the one that in the long run would benefit more from increasing working from home possibility

Dissecting the Role of Mesenchymal Stem Cells in Idiopathic Pulmonary Fibrosis:Cause or Solution

Idiopathic pulmonary fibrosis (IPF) is one of the most aggressive forms of idiopathic interstitial pneumonias, characterized by chronic and progressive fibrosis subverting the lung’s architecture, pulmonary functional decline, progressive respiratory failure, and high mortality (median survival 3 years after diagnosis). Among the mechanisms associated with disease onset and progression, it has been hypothesized that IPF lungs might be affected either by a regenerative deficit of the alveolar epithelium or by a dysregulation of repair mechanisms in response to alveolar and vascular damage. This latter might be related to the progressive dysfunction and exhaustion of the resident stem cells together with a process of cellular and tissue senescence. The role of endogenous mesenchymal stromal/stem cells (MSCs) resident in the lung in the homeostasis of these mechanisms is still a matter of debate. Although endogenous MSCs may play a critical role in lung repair, they are also involved in cellular senescence and tissue ageing processes with loss of lung regenerative potential. In addition, MSCs have immunomodulatory properties and can secrete anti-fibrotic factors. Thus, MSCs obtained from other sources administered systemically or directly into the lung have been investigated for lung epithelial repair and have been explored as a potential therapy for the treatment of lung diseases including IPF. Given these multiple potential roles of MSCs, this review aims both at elucidating the role of resident lung MSCs in IPF pathogenesis and the role of administered MSCs from other sources for potential IPF therapies

Marine Strategy Framework Directive - Descriptor 2, Non-Indigenous Species, Delivering solid recommendations for setting threshold values for non-indigenous species pressure on European seas

Marine Non-Indigenous Species (NIS) are animals and plants introduced accidently or deliberately into the European seas, originating from other seas of the globe. About 800 marine non-indigenous species (NIS) currently occur in the European Union national marine waters, several of which have negative impacts on marine ecosystem services and biodiversity. Under the Marine Strategy Framework Directive (MSFD) Descriptor 2 (D2), EU Member States (MSs) need to consider NIS in their marine management strategies. The Descriptor D2 includes one primary criterion (D2C1: new NIS introductions), and two secondary criteria (D2C2 and D2C3). The D2 implementation is characterized by a number of issues and uncertainties which can be applicable to the Descriptor level (e.g. geographical unit of assessment, assessment period, phytoplanktonic, parasitic, oligohaline NIS, etc.), to the primary criterion D2C1 level (e.g. threshold values, cryptogenic, questionable species, etc), and to the secondary criteria D2C2 and D2C3. The current report tackles these issues and provides practical recommendations aiming at a smoother and more efficient implementation of D2 and its criteria at EU level. They constitute a solid operational output which can result in more comparable D2 assessments among MSs and MSFD regions/subregions. When it comes to the policy-side, the current report calls for a number of different categories of NIS to be reported in D2 assessments, pointing the need for the species to be labelled/categorised appropriately in the MSFD reporting by the MSs. These suggestions are proposed to be communicated to the MSFD Working Group of Good Environmental Status (GES) and subsequently to the Marine Strategy Coordination Group (MSCG) of MSFD. Moreover, they can serve as an input for revising the Art. 8 Guidelines

Treatment with tocilizumab or corticosteroids for COVID-19 patients with hyperinflammatory state: a multicentre cohort study (SAM-COVID-19)

Objectives: The objective of this study was to estimate the association between tocilizumab or corticosteroids and the risk of intubation or death in patients with coronavirus disease 19 (COVID-19) with a hyperinflammatory state according to clinical and laboratory parameters. Methods: A cohort study was performed in 60 Spanish hospitals including 778 patients with COVID-19 and clinical and laboratory data indicative of a hyperinflammatory state. Treatment was mainly with tocilizumab, an intermediate-high dose of corticosteroids (IHDC), a pulse dose of corticosteroids (PDC), combination therapy, or no treatment. Primary outcome was intubation or death; follow-up was 21 days. Propensity score-adjusted estimations using Cox regression (logistic regression if needed) were calculated. Propensity scores were used as confounders, matching variables and for the inverse probability of treatment weights (IPTWs). Results: In all, 88, 117, 78 and 151 patients treated with tocilizumab, IHDC, PDC, and combination therapy, respectively, were compared with 344 untreated patients. The primary endpoint occurred in 10 (11.4%), 27 (23.1%), 12 (15.4%), 40 (25.6%) and 69 (21.1%), respectively. The IPTW-based hazard ratios (odds ratio for combination therapy) for the primary endpoint were 0.32 (95%CI 0.22-0.47; p < 0.001) for tocilizumab, 0.82 (0.71-1.30; p 0.82) for IHDC, 0.61 (0.43-0.86; p 0.006) for PDC, and 1.17 (0.86-1.58; p 0.30) for combination therapy. Other applications of the propensity score provided similar results, but were not significant for PDC. Tocilizumab was also associated with lower hazard of death alone in IPTW analysis (0.07; 0.02-0.17; p < 0.001). Conclusions: Tocilizumab might be useful in COVID-19 patients with a hyperinflammatory state and should be prioritized for randomized trials in this situatio

Proceedings of the Fifth Italian Conference on Computational Linguistics CLiC-it 2018

On behalf of the Program Committee, a very warm welcome to the Fifth Italian Conference on Computational Linguistics (CLiC-­‐it 2018). This edition of the conference is held in Torino. The conference is locally organised by the University of Torino and hosted into its prestigious main lecture hall “Cavallerizza Reale”. The CLiC-­‐it conference series is an initiative of the Italian Association for Computational Linguistics (AILC) which, after five years of activity, has clearly established itself as the premier national forum for research and development in the fields of Computational Linguistics and Natural Language Processing, where leading researchers and practitioners from academia and industry meet to share their research results, experiences, and challenges

Understanding the cost of retrofitting CO2 capture in an integrated oil refinery : reference base case plants: Economic evaluation

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