Gruppo Italiano di Studio sulle Infezioni Gravi – GISIG 3: controversial issues of severe bacterial infections due to multidrug-resistant Gram-positive bacteria: introduction by the National Coordinators

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Hepatitis C virus relies on lipoproteins for its life cycle

Hepatitis C virus (HCV) infects over 150 million people worldwide. In most cases, HCV infection becomes chronic causing liver disease ranging from fibrosis to cirrhosis and hepatocellular carcinoma. Viral persistence and pathogenesis are due to the ability of HCV to deregulate specific host processes, mainly lipid metabolism and innate immunity. In particular, HCV exploits the lipoprotein machineries for almost all steps of its life cycle. The aim of this review is to summarize current knowledge concerning the interplay between HCV and lipoprotein metabolism. We discuss the role played by members of lipoproteins in HCV entry, replication and virion production

Assessing the performance of the Gaussian Process Regression algorithm to fill gaps in the time-series of daily actual evapotranspiration of different crops in temperate and continental zones using ground and remotely sensed data

The knowledge of crop evapotranspiration is crucial for several hydrological processes, including those related to the management of agricultural water sources. In particular, the estimations of actual evapotranspiration fluxes within fields are essential to managing irrigation strategies to save water and preserve water resources. Among the indirect methods to estimate actual evapotranspiration, ETa, the eddy covariance (EC) method allows to acquire continuous measurement of latent heat flux (LE). However, the time series of EC measurements are sometimes characterized by a lack of data due to the sensors' malfunctions. At this aim, Machine Learning (ML) techniques could represent a powerful tool to fill possible gaps in the time series. In this paper, the ML technique was applied using the Gaussian Process Regression (GPR) algorithm to fill gaps in daily actual evapotranspiration. The technique was tested in six different plots, two in Italy, three in the United States of America, and one in Canada, with different crops and climatic conditions in order to consider the suitability of the ML model in various contexts. For each site, the climate variables were not the same, therefore, the performance of the method was investigated on the basis of the available information. Initially, a comparison of ground and reanalysis data, where both databases were available, and between two different satellite products, when both databases were available, have been conducted. Then, the GPR model was tested. The mean and the covariance functions were set by considering a database of climate variables, soil water status measurements, and remotely sensed vegetation indices. Then, five different combinations of variables were analyzed to verify the suitability of the ML approach when limited input data are available or when the weather variables are replaced with reanalysis data. Cross-validation was used to assess the performance of the procedure. The model performances were assessed based on the statistical indicators: Root Mean Square Error (RMSE), coefficient of determination (R2), Mean Absolute Error (MAE), regression coefficient (b), and Nash-Sutcliffe efficiency coefficient (NSE). The quite high Nash Sutcliffe Efficiency (NSE) coefficient, and the root mean square error (RMSE) low values confirm the suitability of the proposed algorithm

Evaluation of daily crop reference evapotranspiration and sensitivity analysis of FAO Penman-Monteith equation using ERA5-Land reanalysis database in Sicily, Italy

Crop evapotranspiration (ET) is one of the most important components in many hydrological processes. The crop reference evapotranspiration (ETo) represents the atmospheric water demand in each crop type, development stage, and management practices. The Penman-Monteith equation in the version suggested by the Food and Agriculture Organization (FAO56-PM), is one of the most used methods to estimate ETo. In several regions of the world, meteorological observations are not always available. The most recent reanalysis database ERA5-Land, released in 2019, can be useful to overcome this limit. The database provides, with a spatial grid of 0.1◦ latitude and 0.1◦ longitude, several hourly climate data such as air temperature, dew point temperature, solar radiation, and wind speed components all at 2.0 m above the soil surface, except wind speed components at 10 m, useful to apply the FAO56-PM equation. The objective of this research is to assess the quality of ERA5-Land climate variables data to estimate daily ETo in Sicily, Italy. The effect of the weather station’s elevation associated with the statistical indicators was also evaluated to verify how the morphology affects the measurements. Finally, the sensitivity analysis of the FAO56-PM equation was carried out to identify which climate variables have the most influence on the ETo estimation. For the period 2006–2015, the comparison between air temperature, global solar radiation, wind speed, and relative air humidity, measured from 39 ground weather stations in Sicily, and ERA5-Land was carried out and then, through FAO56-PM equation daily ETo values were estimated using both databases. The statistical indicators Root Mean Square Error (RMSE) and Mean Bias Error (MBE) confirm the possibility of considering the ERA5-Land a suitable solution to estimate ETo. The sensitivity analysis showed that good ETo estimation depends mainly on the accuracy of the relative air humidity and air temperature data

Combining the FAO56 agrohydrological model and remote sensing data to assess water demand in a Sicilian irrigation district

Agricultural water use in irrigated areas plays a key role in the Mediterranean regions characterized by semi-arid climate and water shortage. In the face of optimizing irrigation water use, farmers must revise their irrigation practices to increase the drought resilience of agricultural systems and to avoid severe damages in agro-ecosystems. In this direction, during the last decades, the research has been focused on mathematical models to simulate the process of driving mass transport and energy exchanges in the Soil-Plant-Atmosphere system. The objective of the paper was to test the suitability of the combination of FAO56 agrohydrological model with remote sensing data retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) platform, to assess the spatiotemporal distributions of crop water requirement and to schedule irrigation in an irrigation district of the south-west of Sicily, Italy. The proposed approach allowed obtaining the spatiotemporal distributions of soil and crop parameters used in the FAO56 model implemented in a GIS environment to simulate the water balance, as well as to assess the actual irrigation strategy. The GIS database was organized to include soil and crop parameters, as well as the irrigation volumes actually delivered to each farmer; the latter data can be used not only as input for water balance to evaluate the efficiency of the actual irrigation strategies but also to identify different irrigation scheduling scenario obtained by the FAO56 procedure. The first application was carried out for the period 2014-2017, to identify a combination of irrigation scheduling parameters to be implemented in the model aimed at reproducing the ordinary strategy adopted by the farmers, based on the spatiotemporal variability of soil and climate forcings. When the model outputs were aggregated for single crop types, a fairly good agreement was found between simulated and actual seasonal irrigation volumes delivered either at the level of district and secondary units. Alternative scenarios of irrigation water distribution were then identified and analyzed, to provide irrigation technicians and policymakers a decision support tool to improve the efficiency of irrigation systems and to optimize the distribution based on the availability of water resources

Sviluppo, messa a punto e sperimentazione di un sistema combinato batterie al litio-ferro-fosfato/FER per applicazioni in bassa tensione. Report 2 -Test e prove di funzionamento, anche in connessione con la rete elettrica di distribuzione.

Il presente documento costituisce il report dell’attività svolta nel periodo aprile - settembre 2013 avente per oggetto: “Sviluppo, messa a punto e sperimentazione di un sistema combinato batterie al litio-ferrofosfato/FER per applicazioni in bassa tensione”. Nel corso di tale attività, sono state eseguite molteplici prove in condizioni reali di funzionamento, integrando il sistema sviluppato (comprendente il pacco-batterie al litio-ferro-fosfato per una capacità complessiva di 16 kWh e l’insieme degli apparati di interfaccia - di potenza e di segnale - di controllo e di protezione), in una rete elettrica di distribuzione di bassa tensione attualmente in esercizio, al fine di verificare sperimentalmente sul campo l’operatività delle funzioni di protezione e comunicazione implementate. Nel presente Report: - è descritta la rete alla quale è stato collegato il dispositivo per l’esecuzione dei test e delle prove sperimentali; - sono elencati i test e le prove eseguite; - sono riportate le modalità di esecuzione dei test e delle prove; - è descritto e testato un nuovo algoritmo di gestione del sistema di controllo del dispositivo di accumulo; - sono riportati i risultati dei test e delle prove. Le attività sono state condotte in sinergia con il personale tecnico di ENEA e con la collaborazione dell’azienda Layer Electronics s.r.l. di Erice (TP)