Finite element modelling of stress field perturbations and interseismic crustal deformation in the Val d'Agri region, southern Apennines, Italy

The Val d'Agri area provides the opportunity to analyse active structures in a seismic region for which a large amount of subsurface data is available. This area, which was struck in 1857 by one of the most destructive earthquakes in Italy (MW = 7.03), represents a unique natural laboratory to gain new insights into geometry, modes and rates of faulting controlling crustal deformation in an actively extending orogen. In this study, a crustal geological section through the southern Apennines is discretized into a finite element model (FEM). We present a 2D elastoplastic FEM that reproduces stress perturbations and strain field around the Val d'Agri active fault system. The influence of fault strand activity on interseismic crustal deformation is tested by a series of computer models, whose predictions are compared with the horizontal velocity components of continuous GPS sites in the region and with stress directions and geological data. The best fit with available geological and geophysical constraints is obtained with a 300 km long, 29 km deep model formed by a multilayer including three components having different rheological characteristics and including several shallow, locked fault segments, which branch into a freely slipping major basement fault at depth. Finite element modelling provides new insights into the controversial and widely debated active tectonic setting of the study area, pointing out the fundamental role played by a structural reactivation process involving inherited, long-lived, mature fault systems at depth. Our FEM, reconciling apparently contrasting geological and geophysical constraints from the study area, points to maximum stress build up and strain accumulation at a depth of 15 ± 5 km. Such a depth range is suggested as the most likely one for the nucleation of large events such as the 1857 Val d'Agri earthquak

Adaptive Control for Building Thermo-hygrometric Analysis: A Novel Dynamic Simulation Code for Indoor Spaces with Multi-enclosed Thermal Zones☆

AbstractA novel dynamic simulation model, called DETECt 2.3.1, purposely developed for thermo-hygrometric energy performance analyses of multi-zone buildings, is presented. Relevant novelties vs. previous implemented code releases are discussed. They regard: i) the simulation model for building spaces with multi-enclosed thermal zones; ii) a novel temperature-humidity control algorithm based on a reference adaptive control scheme. Such algorithm enables the online adaptation of the control gains, in order to overcome the well-known problems of classical fixed gain control algorithms. With the aim to show the features and the potentialities of the simulation code coupled with this new control scheme, a suitable case study related to special indoor hospitals spaces including multiple infant-incubators is developed. The robustness of the designed control approach is confirmed through the good regulation performance obtained for both the indoor air temperature and humidity, simultaneously

Fuzzy logic–based clinical decision support system for the evaluation of renal function in post‐Transplant Patients

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Predictive Analysis of Healthcare-Associated Blood Stream Infections in the Neonatal Intensive Care Unit Using Artificial Intelligence: A Single Center Study

Background: Neonatal infections represent one of the six main types of healthcare-associated infections and have resulted in increasing mortality rates in recent years due to preterm births or problems arising from childbirth. Although advances in obstetrics and technologies have minimized the number of deaths related to birth, different challenges have emerged in identifying the main factors affecting mortality and morbidity. Dataset characterization: We investigated healthcare-associated infections in a cohort of 1203 patients at the level III Neonatal Intensive Care Unit (ICU) of the “Federico II” University Hospital in Naples from 2016 to 2020 (60 months). Methods: The present paper used statistical analyses and logistic regression to identify an association between healthcare-associated blood stream infection (HABSIs) and the available risk factors in neonates and prevent their spread. We designed a supervised approach to predict whether a patient suffered from HABSI using seven different artificial intelligence models. Results: We analyzed a cohort of 1203 patients and found that birthweight and central line catheterization days were the most important predictors of suffering from HABSI. Conclusions: Our statistical analyses showed that birthweight and central line catheterization days were significant predictors of suffering from HABSI. Patients suffering from HABSI had lower gestational age and birthweight, which led to longer hospitalization and umbilical and central line catheterization days than non-HABSI neonates. The predictive analysis achieved the highest Area Under Curve (AUC), accuracy and F1-macro score in the prediction of HABSIs using Logistic Regression (LR) and Multi-layer Perceptron (MLP) models, which better resolved the imbalanced dataset (65 infected and 1038 healthy)

thermal structure of the outer northern apennines along the crop 03 profile

In this study, we elaborated a 2D model that reproduces the thermal structure of the central-northern Adriatic offshore and adjacent onshore area of the Italian peninsula. Based on the crustal structure along the trace of the CROP-03 deep section, the geotherms offshore Gabicce (northern Marche region) were obtained by an analytical procedure taking into account the role of thrusting within the sedimentary cover. Basement involvement at depth beneath the neighbouring Mondaino area to the SW, where a crustal thrust ramp dips towards the hinterland, required the use of a different analytical procedure. The results obtained in this study allowed us to define a satisfactory description of the thermal state of the northern Marche coastal area and adjacent Adriatic offshore. These results, integrated with those obtained by previous studies, confirm that the isotherms of 250°C and 400°C are placed in the stable Adriatic lithosphere at depths of about 11 km and 22 km, respectively. Furthermore, the 400°C isotherm is deeper in the onshore area, reaching a depth of about 30 km in the zone comprised between Gabicce and Mondaino, whereas the 250°C isotherm deepens towards the SW along the Adriatic Sea sector, to reach a maximum depth of 13 km in coastal area, rising again at a depth of 11 km in the innermost sector of the studied section