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Probabilistic Seismic Hazard Analysis (PSHA) typically requires tectonic b-values and seismic activity rates using declustered catalogues to compute the annual probability of exceedance of a given ground motion (for example, the Peak Ground Acceleration or PGA). In this work, we propose a methodology that includes the spatially-gridded time-dependent b-value and activity rate computation using seismic clusters in PSHA calculations. To account for the the spatial variability and the relationship of the earthquakes with the seismic sources, we incorporate the distance from the grid cell to the closest fault and the epicentre's uncertainty into the smoothing kernel as the average distance and the variance, respectively. To illustrate this methodology, we selected two scenarios, one in central Italy where L'Aquila earthquake happened and one in south-eastern Spain, where several earthquakes with a moment magnitude (Mw) greater than 4.0 have taken place over the last 30 years, including two earthquakes with greater than or equal to 5.0 Mw. We compared three different seismic activity models based on the parameters considered in the calculations (distance from spatial cells to faults and epicentral distance uncertainty) and we defined and calculated the changes of the annual probability of exceedance for a given background PGA value. The results reveal an oscillation of the changes of the annual probability of exceedance in the proximity of the occurrence of significant events. The increase is more significant in high seismicity areas, such as Italy, but it is no so evident in moderate seismicity regions as Spain. However, we have observed how, for moderate to low seismicity regions, the use of a non-declustered catalogue can be appropriate when computing time-dependent PSHA, as in the case of Spain. [ABSTRACT FROM AUTHOR]

Background and aims: People who use drugs (PWUD) represent an active reservoir of HCV infection. The prevalence of chronic HCV infection in PWUD in Italy remains unknown because of the lack of systematic screening. Thanks to direct‐acting antiviral agents (DAAs), hepatitis C can now be cured in most patients. Thus, the next challenge is to provide linkage‐to‐care for these patients. Methods: In this scenario, we conducted a screening programme in PWUD attending seven Addiction Centers in Southern Italy, as well as a treatment programme in the Liver Unit of the University Hospital of Salerno. We used the OraQuick HCV antibody test to screen the PWUD (from 1 April to 30 September 2018). Results: 593 subjects were consecutively enrolled in the programme; 250 (41.8%) were HCV‐Ab‐positive. 143 (24.1%) were aware of their infection and had been HCV‐RNA‐tested: 83 were positive and 60 negative. The remaining 107 subjects (18.1%) had never previously been tested and were unaware of their infection. A total of 160 (26.9%) HCV RNA‐positive patients were found and offered antiviral therapy with DAAs. The sustained virological response rate was 98.5% and no adverse events were recorded. Two patients voluntarily discontinued treatment. No reinfections have been recorded to date. Conclusions: The prevalence of HCV‐Ab positivity was high in the PWUDs enrolled in this study, and almost half the patients were unaware of being HCV‐positive. The linkage‐to‐care provided was safe and effective, and no case of reinfection was recorded. [ABSTRACT FROM AUTHOR]

• Hazelnut unsaponifiable compounds are promising geographical and varietal markers. • Untargeted profiling and fingerprinting both successfully authenticated hazelnuts. • Fingerprinting extracted more information from chromatographic data. • Untargeted profiling enabled easier chemical interpretability than fingerprinting. This study compares two data processing techniques (fingerprinting and untargeted profiling) to authenticate hazelnut cultivar and provenance based on its unsaponifiable fraction by GC–MS. PLS-DA classification models were developed on a selected sample set (n = 176). As test cases, cultivar models were developed for "Tonda di Giffoni" vs other cultivars, whereas provenance models were developed for three origins (Chile, Italy or Spain). Both fingerprinting and untargeted profiling successfully classified hazelnuts by cultivar or provenance, revealing the potential of the unsaponifiable fraction. External validation provided over 90 % correct classification, with fingerprinting slightly outperforming. Analysing PLS-DA models' regression coefficients and tentatively identifying compounds corresponding to highly relevant variables showed consistent agreement in key discriminant compounds across both approaches. However, fingerprinting in selected ion mode extracted slightly more information from chromatographic data, including minor discriminant species. Conversely, untargeted profiling acquired in full scan mode, provided pure spectra, facilitating chemical interpretability. [ABSTRACT FROM AUTHOR]