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The high seismic hazard of the Italian territory and the vulnerability of its historic masonry heritage require the development of fragility curves that must be increasingly reliable and robustly correlated to exposure. To date, national-scale seismic risk analyses mainly use empirical curves derived from the statistical analysis of damage induced by past events. These curves have shown good reliability, but they correlate only with a few typological-structural characteristics of the building, such as the number of floors, the vertical structure typology or the construction period. The present research paper aims to overcome this limitation with a hybrid approach that provides a better exposure characterisation. Specifically, the proposed strategy integrates the SAVE and Piecewise Rigid Displacement (PRD) methods. SAVE is an empirical approach based on the damage assessment due to past seismic events used to identify a seismic behaviour of a structure, while the PRD method is a numerical approach that solves the boundary value problem for normal, rigid, no-tension material. It can model different structural typologies, and as a result, it also provides the value of the horizontal static multiplier that drives the masonry construction to collapse. An extended numerical campaign is carried out considering a sample of 750 masonry buildings distributed throughout the Italian territory and extracted from the PLINIVS typological database. Looking at each construction, first, a PRD analysis is conducted to define its seismic capacity, paying special attention to modelling construction details. After that, the SAVE method is used to classify the construction in a specific seismic vulnerability class, i.e., from A to C, with decreasing vulnerability. All the buildings belonging to the same class are then collected, and three fragility curves representative of the collapse state (one for each vulnerability class) are derived and validated against empirical and analytical ones commonly adopted in the Literature. The integrated methodology shows a good agreement between simulations and observations, confirming the viability of the proposed hybrid methodology for the large-scale assessment of masonry buildings, providing an effective strategy to plan mitigation and rehabilitation interventions.

Abstract In patients intubated for hypoxemic acute respiratory failure (ARF) related to novel coronavirus disease (COVID-19), we retrospectively compared two weaning strategies, early extubation with immediate non-invasive ventilation (NIV) versus standard weaning encompassing spontaneous breathing trial (SBT), with respect to IMV duration (primary endpoint), extubation failures and reintubations, rate of tracheostomy, intensive care unit (ICU) length of stay and mortality (additional endpoints). All COVID-19 adult patients, intubated for hypoxemic ARF and subsequently extubated, were enrolled. Patients were included in two groups, early extubation followed by immediate NIV application, and conventionally weaning after passing SBT. 121 patients were enrolled and analyzed, 66 early extubated and 55 conventionally weaned after passing an SBT. IMV duration was 9 [6–11] days in early extubated patients versus 11 [6–15] days in standard weaning group (p = 0.034). Extubation failures [12 (18.2%) vs. 25 (45.5%), p = 0.002] and reintubations [12 (18.2%) vs. 22 (40.0%) p = 0.009] were fewer in early extubation compared to the standard weaning groups, respectively. Rate of tracheostomy, ICU mortality, and ICU length of stay were no different between groups. Compared to standard weaning, early extubation followed by immediate NIV shortened IMV duration and reduced the rate of extubation failure and reintubation.

In patients that are admitted to intensive care units (ICUs), the clinical outcome of severe infections depends on several factors, as well as the early administration of chemotherapies and comorbidities. Antimicrobials may be used in off-label regimens to maximize the probability of therapeutic concentrations within infected tissues and to prevent the selection of resistant clones. Interestingly, the literature clearly shows that the rate of tissue penetration is variable among antibacterial drugs, and the correlation between plasma and tissue concentrations may be inconstant. The present review harvests data about tissue penetration of antibacterial drugs in ICU patients, limiting the search to those drugs that mainly act as protein synthesis inhibitors and disrupting DNA structure and function. As expected, fluoroquinolones, macrolides, linezolid, and tigecycline have an excellent diffusion into epithelial lining fluid. That high penetration is fundamental for the therapy of ventilator and healthcare-associated pneumonia. Some drugs also display a high penetration rate within cerebrospinal fluid, while other agents diffuse into the skin and soft tissues. Further studies are needed to improve our knowledge about drug tissue penetration, especially in the presence of factors that may affect drug pharmacokinetics.

The challenging severity of some infections, especially in critically ill patients, makes the diffusion of antimicrobial drugs within tissues one of the cornerstones of chemotherapy. The knowledge of how antibacterial agents penetrate tissues may come from different sources: preclinical studies in animal models, phase I–III clinical trials and post-registration studies. However, the particular physiopathology of critically ill patients may significantly alter drug pharmacokinetics. Indeed, changes in interstitial volumes (the third space) and/or in glomerular filtration ratio may influence the achievement of bactericidal concentrations in peripheral compartments, while inflammation can alter the systemic distribution of some drugs. On the contrary, other antibacterial agents may reach high and effective concentrations thanks to the increased tissue accumulation of macrophages and neutrophils. Therefore, the present review explores the tissue distribution of beta-lactams and other antimicrobials acting on the cell wall and cytoplasmic membrane of bacteria in critically ill patients. A systematic search of articles was performed according to PRISMA guidelines, and tissue/plasma penetration ratios were collected. Results showed a highly variable passage of drugs within tissues, while large interindividual variability may represent a hurdle which must be overcome to achieve therapeutic concentrations in some compartments. To solve that issue, off-label dosing regimens could represent an effective solution in particular conditions.

Aim We aimed to characterise a large population of coronavirus disease 2019 (COVID-19) patients with moderate-to-severe hypoxaemic acute respiratory failure (ARF) receiving continuous positive airway pressure (CPAP) outside the intensive care unit (ICU), and to ascertain whether the duration of CPAP application increased the risk of mortality for patients requiring intubation. Methods In this retrospective, multicentre cohort study, we included adult COVID-19 patients, treated with CPAP outside ICU for hypoxaemic ARF from 1 March to 15 April, 2020. We collected demographic and clinical data, including CPAP therapeutic goal, hospital length of stay and 60-day in-hospital mortality. Results The study included 537 patients with a median (interquartile range (IQR) age of 69 (60–76) years. 391 (73%) were male. According to the pre-defined CPAP therapeutic goal, 397 (74%) patients were included in the full treatment subgroup, and 140 (26%) in the do not intubate (DNI) subgroup. Median (IQR) CPAP duration was 4 (1–8) days, while hospital length of stay was 16 (9–27) days. 60-day in-hospital mortality was 34% (95% CI 0.304–0.384%) overall, and 21% (95% CI 0.169–0.249%) and 73% (95% CI 0.648–0.787%) for full treatment and DNI subgroups, respectively. In the full treatment subgroup, in-hospital mortality was 42% (95% CI 0.345–0.488%) for 180 (45%) CPAP failures requiring intubation, and 2% (95% CI 0.008–0.035%) for the remaining 217 (55%) patients who succeeded. Delaying intubation was associated with increased mortality (hazard ratio 1.093, 95% CI 1.010–1.184). Conclusions We described a large population of COVID-19 patients treated with CPAP outside ICU. Intubation delay represents a risk factor for mortality. Further investigation is needed for early identification of CPAP failures.

The present paper applies the Linear Arch Static Analysis (LASA), which models the masonry material as unilateral, i.e., No-Tension material in the sense of Heyman, and the Safe Theorem of the Limit Analysis to the study of masonry spiral stairs. A comparison is made with a refined FE analysis of the same problem, obtained by means of the ANSYS Parametric Design Language (APDL). The objective is to prove that LASA can be a valid alternative to other more complex numerical methods, such as FE, especially when the modeling parameters, such as the boundary conditions, cannot be exactly defined. The case study of a small spiral staircase placed in the tower of Nisida, a small island close to Naples, Italy is taken into consideration. The results show that the LASA analysis provides results that fall within two limit FE cases in terms of stress and overall thrust, providing at the same time a meaningful insight into the equilibrium state of the structure.

(1) Methods for checking the condition of monumental masonry structures can still be considered understudied. Among the different approaches available in the literature, the graphical ones have a special role, due to their simplicity and effectiveness. (2) In this work, a 2D method (Thrust Line Analysis (TLA)), the Modified Thrust Line Method (MTLM), and the 3D Membrane Equilibrium Analysis (MEA) method are compared. All methods have the same starting concept: no tensile strength, no sliding between the stone blocks, infinite compressive strength. (3) The methods are compared in terms of stress distribution (for the same—or similar—thrust line), and in terms of the Geometrical Safety Factor ensured. (4) The work shows that these theories, if properly conveyed in a scientific methodology (as many authors are doing currently and have done in the past) demonstrate the effectiveness and the advantages of graphical methods for simple structures.

The assessment of the equilibrium and the safety of masonry vaults is of high relevance for the conservation and restoration of historical heritage. In the literature many approaches have been proposed for this tasks, starting from the 17th century. In this work we focus on the Membrane Equilibrium Analysis, developed under the Heyman’s theory of Limit Analysis. Within this theory, the equilibrium of a vault is assessed if it is possible to find at least one membrane surface, between the volume of the vaults, being in equilibrium under the given loads through a purely compressive stress field. The equilibrium of membranes is described by a second order partial differential equation, which is definitely elliptic only when a negative semidefinite stress is assigned, and the shape is the unknown of the problem. The proposed algorithm aims at finding membrane shapes, entirely comprised between the geometry of the vault, in equilibrium with admissible stress fields, through the minimization of an error function with respect to shape parameters of the stress potential, and then, with respect to the boundary values of the membrane shape. The application to two test cases shows the viability of this tool for the assessment of the equilibrium of existing masonry vaults.

An accurate monitoring of power system behavior is a hot-topic for modern grid operation. Low-frequency oscillations (LFO), such as inter-area electromechanical oscillations, are detrimental phenomena impairing the development of the grid itself and also the integration of renewable sources. An interesting countermeasure to prevent the occurrence of such oscillations is to continuously identify their characteristic electromechanical mode parameters, possibly realizing an online monitoring system. In this paper an attempt to develop an online modal parameters identification system is done using machine learning techniques. An approach based on the development of a proper artificial neural network exploiting the frequency measurements coming from actual PMU devices is presented. The specifically developed offline training stage is fully detailed. The output results from the dynamic mode decomposition method are considered as reference in order to validate the machine learning approach. Some results are presented in order to validate the effectiveness of the proposed approach on data coming from recordings of real grid events. The main key points affecting the performance of the proposed technique are discussed by means of proper validation scenarios. This contribution is the first step of a more extended project whose final aim is the development of an artificial neural networks (ANN) architecture able to predict the system behavior (in a given time span) in terms of LFO modal parameters, and to classify the contingencies/disturbances based on an online training that has memory of the passed training samples.

Aneurysmal subarachnoid hemorrhage (SAH) is associated with high morbidity and mortality. In SAH patients, plasma osteopontin (OPN) has been shown to independently predict poor outcome. The aim of the study is to investigate, in a selected population with severe SAH, OPN time course in cerebrospinal fluid (CSF) and plasma during the first week after aneurism rupture, and OPN prognostic value. We included 44 patients with the following criteria: (1) age 18 and 80 years, (2) diagnosis of SAH from cerebral aneurysm rupture, (3) insertion of external ventricular drain. Plasma and CSF were sampled at day 1, 4, and 8. OPN levels, in CSF and plasma, displayed a weak correlation on day 1 and were higher, in CSF, in all time points. Only in poor prognosis patients, OPN levels in CSF significantly increased at day 4 and day 8. Plasma OPN at day 1 and 4 was predictor of poor outcome. In conclusion, plasma and CSF OPN displays a weak correlation, on day 1. The higher levels of OPN found in the CSF compared to plasma, suggest OPN production within the CNS after SAH. Furthermore, plasma OPN, at day 1 and 4, seems to be an independent predictor of poor outcome.

This work presents the feasibility study of an on-line monitoring technique aimed to discover unwanted variations of longitudinal impedance along the line (also named “impedance discontinuities”) and, possibly, incipient faults typically occurring on high voltage power transmission lines, like those generated by oxidated midspan joints or bolted joints usually present on such lines. In this paper, the focus is placed on the application and proper customization of a technique based on the time-domain reflectometry (TDR) technique when applied to an in-service high-voltage overhead line. An extensive set of numerical simulations are provided in order to highlight the critical points of this particular application scenario, especially those that concern the modeling of both the TDR signal injection strategy and the required high-voltage coupling devices, and to plan a measurement activity. The modeling and simulation approach followed for the study of either the overhead line or the on-line TDR system is fully detailed, discussing three main strategies. Furthermore, some measurement data that were used to characterize the specific coupling device selected for this application at high frequency—that is, a capacitive voltage transformer (CVT)—are presented and discussed too. This work sets the basic concepts underlying the implementation of an on-line remote monitoring system based on reflectometric principles for in-service lines, showing how much impact is introduced by the high-voltage coupling strategy on the amplitude of the detected reflected voltage waves (also named “voltage echoes”).