Objective During the most aggressive phase of the COVID-19 outbreak in Italy, the Regional Authority of Lombardy identified a number of hospitals, named Hubs, chosen to serve the whole region for highly specialised cases, including vascular surgery. This study reports the experience of the four Hubs for Vascular Surgery in Lombardy and provides a comparison of in hospital mortality and major adverse events (MAEs) according to COVID-19 testing. Methods Data from all patients who were referred to the Vascular Surgery Department of Hubs from 9 March to 28 April 2020 were collected prospectively and analysed. A positive COVID-19 polymerase chain reaction swab test, or symptoms (fever > 37.5°C, upper respiratory tract symptoms, chest pain, and contact/travel history) associated with interstitial pneumonia on chest computed tomography scan were considered diagnostic of COVID-19 disease. Patient characteristics, operative variables, and in hospital outcomes were compared according to COVID-19 testing. A multivariable model was used to identify independent predictors of in hospital death and MAEs. Results Among 305 included patients, 64 (21%) tested positive for COVID-19 (COVID group) and 241 (79%) did not (non-COVID group). COVID patients presented more frequently with acute limb ischaemia than non-COVID patients (64% vs. 23%; p < .001) and had a significantly higher in hospital mortality (25% vs. 6%; p < .001). Clinical success, MAEs, re-interventions, and pulmonary and renal complications were significantly worse in COVID patients. Independent risk factors for in hospital death were COVID (OR 4.1), medical treatment (OR 7.2), and emergency setting (OR 13.6). COVID (OR 3.4), obesity class V (OR 13.5), and emergency setting (OR 4.0) were independent risk factors for development of MAEs. Conclusion During the COVID-19 pandemic in Lombardy, acute limb ischaemia was the most frequent vascular disease requiring surgical treatment. COVID-19 was associated with a fourfold increased risk of death and a threefold increased risk of major adverse events.

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PurposeThis paper looks at state-owned enteprises (SOEs) from the angle of the Market for Corporate Control (MCC) and analyzes in detail the reported rationales of a sample of 355 M&A deals performed by SOEs as acquirers over the period [2002][2003][2004][2005][2006][2007][2008][2009][2010][2011][2012]. The aim, after having created a taxonomy of deal motivations, is to empirically test two alternative hypotheses: Deviation versus Convergence of M&A deal rationales between state-owned and private enterprises. Design/methodology/approachThe data set is obtained by combining firm-level information from two sources, Zephyr and Orbis (Bureau Van Dijk). A recursive algorithm is developed to infer the ownership nature of the enterprises at the time the deal took place and then we double-check the identity of the global ultimate owner by visual inspection of all the available information. Motivations are analyzed through a case-by-case analysis and classified into several categories, thereby providing a taxonomy of rationales behind SOE M&As and discussing their differences and similarities relative to private firms. FindingsMore than 60% of the deals performed by SOEs as acquirers are driven by "shareholder-value maximization" motives, similarly to private enterprise acquirers. The other 40% of deals are almost equally spread among three rationales that specifically relate to the role of modern state capitalism in the economy. "Financial distress" motivation, which is the only one clearly deviating from the objectives of profit maximization typical of private ownership, is far less important than the others. OriginalityExisting literature has mainly focused on private corporate M&A deals or has just disregarded the ownership status of the acquiring firm. This paper focuses on the motivations for SOE deals in order to elaborate a taxonomy of SOE deal rationales and to identify differences and similarities between private corporate firms. Research limitationsThe paper does not analyze in detail the case studies. Neither does it correlate the evidence with the quality of corporate governance or the quality of institutions in the country. This 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 Policy implicationsThe paper suggests some policy implications in terms of reforms of the corporate governance of the SOEs and accountability of their management against clearly stated public missions.It also calls for the need for citizens to be informed in a transparent way about the rationales of major M&A deals when a SOE is on the acquirer side, and the consistency of such rationales with the mission assigned by governments to the enterprises they own. Finally, it underlines that regulatory concerns raised in many countries by the rise of cross-border SOE M&As are in most of the cases unfounded.JEL Codes: L32, L33, G34

Recently, features and techniques from speech processing have started to gain increasing attention in the Structural Health Monitoring (SHM) community, in the context of vibration analysis. In particular, the Cepstral Coefficients (CCs) proved to be apt in discerning the response of a damaged structure with respect to a given undamaged baseline. Previous works relied on the Mel-Frequency Cepstral Coefficients (MFCCs). This approach, while efficient and still very common in applications, such as speech and speaker recognition, has been followed by other more advanced and competitive techniques for the same aims. The Teager-Kaiser Energy Cepstral Coefficients (TECCs) is one of these alternatives. These features are very closely related to MFCCs, but provide interesting and useful additional values, such as e.g., improved robustness with respect to noise. The goal of this paper is to introduce the use of TECCs for damage detection purposes, by highlighting their competitiveness with closely related features. Promising results from both numerical and experimental data were obtained.

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