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Engineered biomaterials are materials specifically designed to interact with biological systems for biomedical applications. This paper offers the comprehensive analysis of global clinical trial trends involving such materials. We surveyed 834 studies in the ClinicalTrials.gov database and explored biomaterial types, their initiation points, and durations in clinical trials. Predominantly, synthetic and natural polymers, particularly silicone and collagen, are used. Trials, focusing on ophthalmology, dentistry, and vascular medicine, are primarily conducted in the United States, Canada, and Italy. These trials encompass a broad demographic, and trials enrolled fewer than 100 participants. The study duration varied ranging from 0.5 to 4.5 years. These biomaterials are mainly bioresorbable or bioinert, with the integration of cells in biomaterials remaining an underexplored area. Our findings shed light on current practices and future potentials of engineered biomaterials in clinical research, offering insights for advancing this dynamic field globally. [ABSTRACT FROM AUTHOR]

The seismic‐electromagnetic phenomenon entails the generation of transient electromagnetic signals, which can be observed both simultaneously (co‐seismic) and preceding (pre‐seismic) a seismic wave arrival. Following the most accredited hypothesis, these signals are mainly due to electrokinetic effects, generated on microscopic scale in porous media containing electrolytic fluids. Thus, the seismic‐electromagnetic signals are expected to be suitable for the detection and tracking of crustal fluids. Despite the growing interest in this phenomenon, there is a lack of freely available observational database of earthquake‐related electromagnetic signals recorded at co‐located seismic and magnetotelluric stations. To fill this gap, we set up two multicomponent monitoring stations in two seismically active areas of Southern Italy: the Gargano Promontory and the High Agri Valley. This work is both aimed to systematically analyse earthquake‐generated seismic‐electromagnetic recordings and to make the collected database accessible to the scientific community. [ABSTRACT FROM AUTHOR]

The transition towards energy efficiency measures and green energy sources is strongly fostered by the European Union. Italy is among the EU countries that have heavily invested in renewable energy sources, more than doubling their share in gross final energy consumption. In particular, biogas has a pivotal role in the generation of electricity and can also be upgraded into biomethane, with a higher and more stable energy content. In this study, the sustainability of the supply chain of electricity from biogas in Italy has been thoroughly analyzed in the broader framework of the ARCADIA (Life Cycle Approach in Public Procurement and Italian LCA Database for Resource Efficiency) project. The environmental assessment, carried out by means of Life Cycle Assessment (LCA), provides a two-fold perspective. Firstly, it allows us to identify the main hotspots of the investigated system, such as the cultivation of dedicated crops, and to provide useful insights for improving environmental performance. Furthermore, a focus on the modeling of the dataset related to the production of electricity from biogas within the Italian electricity mix represents a step ahead in the LCA research, filling the lack of site-specific databases for reliable LCA results. [ABSTRACT FROM AUTHOR]

This research uses a large dataset from the Italian Seismic Microzonation Database, containing nearly 15,000 measured shear wave velocity (Vs) profiles across Italy, to investigate the uncertainties in seismic risk assessment. This extensive collection allows a detailed study of the seismic properties of soil with unparalleled precision. Our focus is on evaluating Vs variations with depth within uniformly clustered areas, known as seismic microzones. These zones are carefully identified based on their spatial correlation and homogeneity in geological, geophysical, and geotechnical characteristics, which are critical for accurate prediction of seismic response. We contrast these results with clusters formed purely based on geographic survey density (here defined geographic clusters), thereby assessing the depth of our understanding of the subsurface geological and geophysical context. These results were further compared with those reported in the seismic code and literature. This study of depth-dependent Vs variations helps to refine our models of subsurface seismic behaviour. Our main discoveries show that: 1) uncertainties associated with seismic microzones (geological and geophysical clusters) are consistently lower than those identified in geographic clusters, particularly in the first 30 m of depth; 2) Vs profile variations show negligible increases in uncertainty within a certain range of correlation distances (up to about 4,500 m); 3) uncertainties for seismic microzones are lower than those previously reported in seismic codes and in the literature, indicating the effectiveness and precision of our methodological approach. The results of this study significantly improve local seismic response analysis and highlight the critical role of depth and spatial correlation in understanding seismic hazard. The dataset is available at https://doi.org/10.5281/zenodo.10885590 (Mori et al., 2024). [ABSTRACT FROM AUTHOR]

Background/Objectives: Endometriosis is a female chronic inflammatory disease in which endometrial tissue develops outside the uterine cavity. It is a complex pathology, which significantly contributes to morbidity in premenopausal women, leading to chronic pain, infertility, and subfertility negatively impacting physical and emotional well-being and the overall quality of life. The public health burden of endometriosis remains elusive and challenging to determine, and this uncertainty can lead to inadequate healthcare services and treatments. The objective was to estimate the incidence and prevalence of endometriosis in Italy using the hospital discharge records database via a population-based retrospective study, nationwide between 2011 and 2020. Methods: From the National Hospital Discharge Database, we selected all admissions with a diagnosis of endometriosis (ICD-9-CM, codes 617.x), supported by the presence of a procedure code of laparoscopy or any other surgical procedure allowing for direct visualisation of the lesions. The main outcomes measured: incidence and prevalence of endometriosis were estimated for the entire 2011–2020 period and by individual year, analysing the time trend and variability in different geographical areas of Italy. Results: There were a total of 134,667,646 women aged 15–50 years with one or more hospitalisations for endometriosis in all Italian hospitals. The incidence of endometriosis in Italy during this period was 0.839 per 1000 women (CI95% 0.834–0.844), exhibiting a statistically significant decreasing trend over the years. A discernible north–south gradient was observed, with higher rates documented in the northern regions. The prevalence rate stood at 14.0 per 1000 during the same period, and a similar north–south geographical gradient was identifiable in the prevalence rates as well. Conclusions: The utilization of national-level hospital data enables the generation of incidence and prevalence data for endometriosis without variations in methods and definitions, facilitating the evaluation of temporal trends and regional comparisons. Understanding and quantifying this phenomenon is essential for appropriate healthcare planning in various Italian regions. [ABSTRACT FROM AUTHOR]

In the field of botany applied to archaeological and palaeoecological studies, the multi- and inter-disciplinary nature of this research produces a lack of data sharing and scattered articles in the specialty literature or in national and international journals. The vast production of archaeobotany and palynology data makes it necessary to develop a tool for the availability, accessibility, and dissemination of existing research. Many databases exist on palaeoecology, archaeobotany or pollen data. There are no collections focused on archaeological sites and human-induced environments and centred on Southern Europe and the Mediterranean. BRAIN - Botanical Records of Archaeobotany Italian Network is the first database listing sites from which all types of plant records are available in Italy and nearby Mediterranean regions. BRAIN represents the largest integrated collection of archaeo/palaeo-botanical data and a range of descriptive information that makes data recovery FAIR ready. This unique network hosts data on the availability of anthropogenic pollen, palynomorphs and plant macroremains in the same database, and experts of different research fields may contribute to it. [ABSTRACT FROM AUTHOR]

Sand boil formation at the toe of river embankments is the typical manifestation of the initiation and progression of an internal erosion process known as backward erosion piping, which is recognized to be a major concern in many river systems worldwide. In Italy, more than 130 sand boils have been detected along the Po River, many of them experiencing recurrent reactivations during high-water events. In recent years, as part of the activities of the European project LIFE SandBoil, the Italian authority responsible for flood protection and flood damage reduction along the Po River has implemented a GIS-based web application to catalogue the sand boils observed in its operating area. The resulting database allows keeping records of a comprehensive and varied set of information, in terms of predisposing factors, initiation conditions and surface effects. Taking as a reference a well-documented cross-section of the Po River prone to piping, this paper describes the main features of this versatile and flexible tool, whose long-term aim is to support vulnerability studies and the development of risk maps against piping. The database, which might also accommodate data from different river basins, is thus meant to help in flood risk management, by suggesting priorities for the implementation of mitigation measures and allowing the monitoring of intervention effectiveness. [ABSTRACT FROM AUTHOR]

A probabilistic seismic hazard model consists of a set of weighted models/branches that describes the center, the body and the range of seismic hazard. Owing to the intrinsic nature of this kind of analysis, the weight of each model/branch represents its scientific credibility. However, practical uses of this model may sometimes require the selection of one or a few hazard curves that are sampled from the whole model, which often consists of thousands of branches. Here we put forward an innovative procedure that facilitates the scoring, ranking and selection of the hazard curves to account for the requirements of a specific application. The approach consists of a careful quality check of the data used for scoring and the adoption of a proper scoring rule. To show the applicability of this approach, we present an example that consists of scoring and ranking a set of multiple models/branches constituting a recent seismic hazard model of Italy. To score these branches, hazard estimates produced by each of them are compared with time series of macroseismic observations available in the Italian macroseismic database for a carefully selected set of localities deemed sufficiently representative, homogeneously distributed in space and complete with respect to time and intensity levels. The proper scoring parameter used for such a comparison is the logarithmic score, which can always be applied independently of the distribution of the data. [ABSTRACT FROM AUTHOR]

Here we present FOCA (Italian FlOod and Catchment Atlas), the first systematic collection of data on Italian river catchments for which historical discharge time series are available. Hydrometric information, including the annual maximum peak discharge and average daily annual maximum discharge, is complemented by several geomorphological, climatological, extreme rainfall, land-cover and soil-related catchment attributes. All hydrological information derives from the most recently released datasets of discharge and rainfall measurements. To enhance the reproducibility and transferability of the analysis, this paper provides a description of all the raw data and the algorithms used to build the basin attribute dataset. We also describe the approaches adopted to solve problems encountered during the digital elevation model elaboration in areas characterized by a complex morphology. Details about the data quality-control procedure developed to detect and correct errors are also reported. One of the main novelties of FOCA with respect to other national-scale datasets is the inclusion of a rich set of geomorphological attributes and extreme rainfall features for a large set of basins covering a wide range of elevations and areas. Using this first nationwide data collection (available at 10.5281/zenodo.10446258, Claps et al., 2023), a wide range of environmental applications, with a particular focus on flood studies, can be undertaken within the Italian territory. [ABSTRACT FROM AUTHOR]

The southern Apuan Alps (Italy) are prone to rainfall-induced landslides. A first attempt to calculate rainfall thresholds was made in 2006 using non-statistical and repeatable methods for the 1975–2002 period. This research aims to update, validate, and compare the results of that attempt through different statistical approaches. Furthermore, a new dataset of rainfall and landslides from 2008 to 2016 was collected and analyzed by reconstructing the rainfall events via an automatic procedure. To obtain the rainfall thresholds in terms of the duration–intensity relationship, we applied three different statistical methods for the first time in this area: logistic regression (LR), quantile regression (QR), and least-squares linear fit (LSQ). The updated rainfall thresholds, obtained through statistical methods and related to the 1975–2002 dataset, resulted in little difference from the ones obtained with non-statistical methods and have similar efficiency values among themselves. The best one is provided by the LR, with a landslide probability of 0.55 (efficiency of 89.8%). The new rainfall thresholds, calculated by applying the three statistical methods on the dataset from 2008–2016, are similar to the 1975–2002 ones, except for the LR threshold, which exhibits a higher slope. This result confirms the validity of the thresholds obtained with the old database. [ABSTRACT FROM AUTHOR]

The Herbarium Apenninicum (international code: APP), hosted in the Floristic Research Center of the Apennines (Abruzzo, central Italy), is approximately composed of about 80,000 specimens of vascular plants; 66,352 of them are mounted with data labels and entered in a database. The specimens from the Abruzzo administrative region (central Italy) correspond to more than half of the collection (57.8% of the specimens), while immediately afterwards, other neighboring provinces of central Italy follow. Outside of Italy, the most represented areas are Morocco and southern European countries. Most of the specimens were collected between 2001 and 2020; nevertheless, the herbarium also contains two historical collections from the end of the nineteenth century to the beginning of the twentieth century. The herbarium houses 146 types. [ABSTRACT FROM AUTHOR]

Depopulation in Italy is causing the marginalization of several inner territories and municipalities, with consequences for the preservation of different levels of heritage. The Italian National Strategy for Inner Areas (SNAI) aims to address these issues, but in some cases, the policies undertaken are not effective enough to improve development. In this context, the integration of Historic Building Information Modeling (HBIM) and Geographic Information System (GIS), as a potential solution in the enhancement of knowledge, information, and project management, could be an important resource to lean on. To investigate this aspect, the municipality of Dosso del Liro in the Northern part of Lake Como (Lombardy) has been chosen as a case study, based on its marginality and its territorial variety. The research methodology involves a combination of field data collection, bibliographical and archival investigations, database research, and digital recording of heritage, with the purpose of modelling and analyzing the territorial context on different aspects and at different scales. Precisely, multi-disciplinarity and multi-scalarity (but also multi-temporality) are the key points for the HBIM-GIS modelling. Thus, trying to integrate and interpret in this innovative way the information acquired, the research aims to investigate the possibility of improvement for the creation of effective strategies and projects in the Inner Areas. The idea, in fact, is that with an increased knowledge and awareness of the heritage, the requirements for the design phase will be better in sight, and the quality of the intervention will be increased. [ABSTRACT FROM AUTHOR]

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Relational databases are established and widespread tools for storing and managing information. The efficient collection of information in a database appears to be a promising solution for bridge management (BM), thus facilitating the digital transition. The Italian regulatory framework on infrastructure operation and maintenance (O&M) is complex and is constantly being updated. The current plan for implementing its guidelines envisages that infrastructure managers, also on a regional scale, equip themselves with their own digital database for BM. Within this context, this research proposes an integrated methodology that collects information derived from project documentation, in situ inspections, digital surveys, and monitoring and field tests in a queryable database for digitalising, georeferencing, and creating models of many bridges. Structured query language (SQL) statements are used to efficiently export specific shared information, enabling network cross-analysis. Furthermore, the database represents the source of a geographic information system (GIS) catalogue and the basis for deriving models for building information modelling (BIM). The methodology focuses on the infrastructural context of the Lazio region, Italy, the first beneficiary of the research. [ABSTRACT FROM AUTHOR]

• Laboratory-based enterovirus surveillance detected an outbreak of echovirus 11. • Echovirus 11 only infected children; neonates were the most severely affected. • Echovirus 11 strains belonged to the D5 genogroup. • Echovirus 11 strains were related to the lineage circulating in Europe in 2022-23. Following the alert of echovirus 11 (E-11) infection in neonates in EU/EEA Member States, we conducted an investigation of E-11 circulation by gathering data from community and hospital surveillance of enterovirus (EV) in northern Italy from 01 August 2021 to 30 June 2023. Virological results of EVs were obtained from the regional sentinel surveillance database for influenza-like illness (ILI) in outpatients, and from the laboratory database of ten hospitals for inpatients with either respiratory or neurological symptoms. Molecular characterization of EVs was performed by sequence analysis of the VP1 gene. In our ILI series, the rate of EV-positive specimens showed an upward trend from the end of May 2023, culminating at the end of June, coinciding with an increase in EV-positive hospital cases. The E-11 identified belonged to the D5 genogroup and the majority (83%) were closely associated with the novel E-11 variant, first identified in severe neonatal infections in France since 2022. E-11 was identified sporadically in community cases until February 2023, when it was also found in hospitalized cases with a range of clinical manifestations. All E-11 cases were children, with 14 out of 24 cases identified through hospital surveillance. Of these cases, 60% were neonates, and 71% had severe clinical manifestations. Baseline epidemiological data collected since 2021 through EV laboratory-based surveillance have rapidly tracked the E-11 variant since November 2022, alongside its transmission during the late spring of 2023. [ABSTRACT FROM AUTHOR]