Ten years of pluviometric analyses in Italy for civil protection purposes

The concept of climate change has grown in recent decades, influencing the scientific community to conduct research on meteorological parameters and their variabilities. Research on global warming, as well as on its possible economic and environmental consequences, has spread over the last 20 years. Diffused changes in trends have been stated by several authors throughout the world, with different developments observed depending on the continent. Following a period of approximately 40 days of almost continuous rain that occurred from October to November 2019 across the Italian territory and caused several hazards (e.g., floods and landslides), a relevant question for decision-makers and civil protection actors emerged regarding the relative frequencies of given rainfall events in the Warning Hazard Zones (WHZs) of Italy. The derived products of this work could answer this question for both weather and hydrogeological operators thanks to the frequency and spatio-temporal distribution analyses conducted on 10-year daily rainfall data over the entire Italian territory. This work aspires to be an additional tool used to analyse events that have occurred, providing further information for a better understanding of the probability of occurrence and distribution of future events

Cocaine abuse as an immunological trigger in a case diagnosed with eales disease

Background: Eales disease is a clinical syndrome affecting the mid-peripheral retina with an idiopathic occlusive vasculitis and possible subsequent retinal neovascularization. The disease can develop into visually threatening complications. Case Presentation: We report the case of a 40-year-old Caucasian male with a history of cocaine abuse who presented with blurred vision in the left eye (LE). Fundus examination showed vitreous hemorrhages, peripheral sheathing of venous blood vessels, areas of retinal neovascularization in the LE, and peripheral occlusive phlebitis in the right eye. The full serologic panel was negative except for the heterozygous mutation of factor V Leiden. Clinical and biochemical parameters suggested a diagnosis of Eales disease. Therapy with dexamethasone, 1 mg per kg per day, tapered down slowly over 4 months, and peripheral laser photocoagulation allowed a regression of clinical signs and symptoms. Conclusion: This case shows an uncommon presentation of Eales disease associated with cocaine abuse. Both cocaine abuse and a thrombophilic pattern, as cofactors, might have sensitized the retinal microcirculation on the pathogenetic route to this retinal pathology. Furthermore, in view of this hypothesis, a thorough ocular and general medical history investigating drug abuse and coagulation disorders is recommended for ophthalmologists in such cases

Real Estate Asset Management Companies’ Economies of Scale: Is It a Dream or Reality? The Italian Case

The research focuses on a sample of 26 Italian real estate asset management companies (Società di Gestione del Risparmio “SGR”)—whose asset management is totally linked to real estate funds—that considers a period of six years (2013–2018). Using some variables extrapolated from the internal accountability of each SGR, the analysis investigates possible relationships between them to verify the presence or absence of economies of scale of Italian real estate management companies by multivariate regressions. The results show that there is no single model for profit maximization and cost minimization, but all depends on the business model that each SGR decides to adopt

First-principles equation of state and phase stability for the Ni-Al system under high pressures

The equation of state (EOS) of alloys at high pressures is generalized with the cluster expansion method. It is shown that this provides a more accurate description. The low temperature EOSs of Ni-Al alloys on FCC and BCC lattices are obtained with density functional calculations, and the results are in good agreement with experiments. The merits of the generalized EOS model are confirmed by comparison with the mixing model. In addition, the FCC phase diagram of the Ni-Al system is calculated by cluster variation method (CVM) with both spin-polarized and non-spin-polarized effective cluster interactions (ECI). The influence of magnetic energy on the phase stability is analyzed. A long-standing discrepancy between ab initio formation enthalpies and experimental data is addressed by defining a better reference state. This aids both evaluation of an ab initio phase diagram and understanding the thermodynamic behaviors of alloys and compounds. For the first time the high-pressure behavior of order-disorder transition is investigated by ab initio calculations. It is found that order-disorder temperatures follow the Simon melting equation. This may be instructive for experimental and theoretical research on the effect of an order-disorder transition on shock Hugoniots.Comment: 27 pages, 12 figure

Artificial intelligence for renal cancer: From imaging to histology and beyond

Artificial intelligence (AI) has made considerable progress within the last decade and is the subject of contemporary literature. This trend is driven by improved computational abilities and increasing amounts of complex data that allow for new approaches in analysis and interpretation. Renal cell carcinoma (RCC) has a rising incidence since most tumors are now detected at an earlier stage due to improved imaging. This creates considerable challenges as approximately 10%–17% of kidney tumors are designated as benign in histopathological evaluation; however, certain co-morbid populations (the obese and elderly) have an increased peri-interventional risk. AI offers an alternative solution by helping to optimize precision and guidance for diagnostic and therapeutic decisions. The narrative review introduced basic principles and provide a comprehensive overview of current AI techniques for RCC. Currently, AI applications can be found in any aspect of RCC management including diagnostics, perioperative care, pathology, and follow-up. Most commonly applied models include neural networks, random forest, support vector machines, and regression. However, for implementation in daily practice, health care providers need to develop a basic understanding and establish interdisciplinary collaborations in order to standardize datasets, define meaningful endpoints, and unify interpretation

The Italian open data meteorological portal: MISTRAL

At the national level, in Italy, observational and forecast data are collected by various public bodies and are often kept in various small, heterogeneous and non-interoperable repositories, released under different licenses, thus limiting the usability for external users. In this context, MISTRAL (the Meteo Italian SupercompuTing PoRtAL) was launched as the first Italian meteorological open data portal, with the aim of promoting the reuse of meteorological data sets available at national level coverage. The MISTRAL portal provides (and archives) meteorological data from various observation networks, both public and private, and forecast data that are generated and post-processed within the Consortium for Small-scale Modeling-Limited Area Model Italia (COSMO-LAMI) agreement using high performance computing (HPC) facilities. Also incorporated is the Italy Flash Flood use case, implemented with the collaboration of European Centre for Medium-Range Weather Forecasts (ECMWF), which exploits cutting edge advances in HPC-based post-processing of ensemble precipitation forecasts, for different model resolutions, and applies those to deliver novel blended-resolution forecasts specifically for Italy. Finally, in addition to providing architectures for the acquisition and display of observational data, MISTRAL also delivers an interactive system for visualizing forecast data of different resolutions as superimposed multi-layer maps

The Italian open data meteorological portal: MISTRAL

AbstractAt the national level, in Italy, observational and forecast data are collected by various public bodies and are often kept in various small, heterogeneous and non‐interoperable repositories, released under different licenses, thus limiting the usability for external users. In this context, MISTRAL (the Meteo Italian SupercompuTing PoRtAL) was launched as the first Italian meteorological open data portal, with the aim of promoting the reuse of meteorological data sets available at national level coverage. The MISTRAL portal provides (and archives) meteorological data from various observation networks, both public and private, and forecast data that are generated and post‐processed within the Consortium for Small‐scale Modeling‐Limited Area Model Italia (COSMO‐LAMI) agreement using high performance computing (HPC) facilities. Also incorporated is the Italy Flash Flood use case, implemented with the collaboration of European Centre for Medium‐Range Weather Forecasts (ECMWF), which exploits cutting edge advances in HPC‐based post‐processing of ensemble precipitation forecasts, for different model resolutions, and applies those to deliver novel blended‐resolution forecasts specifically for Italy. Finally, in addition to providing architectures for the acquisition and display of observational data, MISTRAL also delivers an interactive system for visualizing forecast data of different resolutions as superimposed multi‐layer maps

Awareness of cognitive decline trajectories in asymptomatic individuals at risk for AD

Background: Lack of awareness of cognitive decline (ACD) is common in late-stage Alzheimer’s disease (AD). Recent studies showed that ACD can also be reduced in the early stages. Methods: We described different trends of evolution of ACD over 3 years in a cohort of memory-complainers and their association to amyloid burden and brain metabolism. We studied the impact of ACD at baseline on cognitive scores’ evolution and the association between longitudinal changes in ACD and in cognitive score. Results: 76.8% of subjects constantly had an accurate ACD (reference class). 18.95% showed a steadily heightened ACD and were comparable to those with accurate ACD in terms of demographic characteristics and AD biomarkers. 4.25% constantly showed low ACD, had significantly higher amyloid burden than the reference class, and were mostly men. We found no overall effect of baseline ACD on cognitive scores’ evolution and no association between longitudinal changes in ACD and in cognitive scores. Conclusions: ACD begins to decrease during the preclinical phase in a group of individuals, who are of great interest and need to be further characterized. Trial registration: The present study was conducted as part of the INSIGHT-PreAD study. The identification number of INSIGHT-PreAD study (ID-RCB) is 2012-A01731-42