A new meteorological pressure index to support a sustainable nuclear energy programme

Today, the evaluation of a site for innovative nuclear installations represents a fundamental step in supporting the implementation of a sustainable nuclear power program. One major concern is the potential for radioactive releases and their effects on the biosphere, particularly on human health. To address this issue, a new Meteorological Pressure Index (MPI) has been developed to identify sites with resilience capacity in terms of transport phenomena correlated to natural wind actions on a regional scale. The MPI utilizes a fuzzy approach that combines data on 3D wind speed, direction, and frequency, providing maps that are useful in the site selection process. The application of MPI in the Sicily region of Italy has allowed to identify bordering areas that that are more affected by efficient air mass transport mechanisms. Consistency analyses have been conducted among MPI maps, observed wind distributions using wind rose charts, and stagnation S and recirculation R factors. The results confirm the MPI's ability to aggregate meteorological data on a regional level, making it a suitable tool when compared to disaggregated data that may not always provide a comprehensive viewpoint

A new tool to process forecast meteorological data for atmospheric pollution dispersion simulations of accident scenarios: A Sicily-based case study

Emergency response plans to mitigate the severity of the accidental release of hazardous compounds in the air have become a primary concern in view of the many adverse events occurred over the years in high-risk plants. To do this, an accurate estimate of forecast meteorological data to be used in dispersion models can be very useful to respond in advance to emergency situations. In this field, FORCALM is a new tool developed to elaborate European Centre for Medium-Range Weather Forecasts data on a 3D computational domain with a high-resolution grid. FORCALM data can be used to perform predictive simulations of impacts on local and regional levels by using CALPUFF modelling system. A case study relevant to an accident, occurred in the “Mediterranea” Refinery at Milazzo (Italy) in 2014, has been also examined for validation purposes. A comparison with results obtained by using CALMET modelling system and observed meteorological data, covering the area under study, is also described. The validation work has allowed confirming that predictive assessments, carried out with the help of FORCALM, lead to information regarding potential environmental impacts with a good degree of accuracy

FMECA Application in Tomotherapy: Comparison between Classic and Fuzzy Methodologies

Accident analysis in radiotherapy highlighted the need to increase quality assurance (QA) programs by the identification of failures/errors with very low probability (rare event) but very severe consequences. In this field, a Failure Mode, Effects and Criticality Analysis (FMECA) technique, used in various industrial processes to rank critical events, has been met with much interest. The literature describes different FMECA methods; however, it is necessary to understand if these tools are incisive and effective in the healthcare sector. In this work, comparisons of FMECA methodologies in the risk assessment of patients undergoing treatments performed with helical tomotherapy are reported. Failure modes identified for the phases "treatment planning" and "treatment execution" are classified using the Risk Priority Number (RPN) index. Differences and similarities in the classification of failures/errors of the examined FMECA approaches are highlighted

SAPERO: a new tool for safety analyses in advanced radiotherapy

Improving safety standards in advanced radiotherapy technologies, where historical experience is not sufficient due to innovation aspects, raises the need to perform studies using new tools that follow a holistic view of the process chain. Such studies are useful to identify additional critical elements compared to safety analyses carried out by classic tools. In this field, SAPERO (La SicurezzA del PazientE: tecniche avanzate ed innovative per la valutazione del rischio di eventi indesiderati all’interno del percorso assistenziale nel settore RadioterapicO) is a new assessment tool that allows to use integrated of Hierarchical Task Analysis (HTA); Failure Mode Effects and Criticality Analysis (FMECA); Cognitive Task Analysis (CTA); Human Error Assessment Reduction Technique (HEART). The methodological approaches have been suitably modified to address their operating in the medical sector under study. Some improvements have concerned the application of the fuzzy theory in FMECA and the use of a linguistic approach in HEART. In this paper, SAPERO application on a case study related to treatment procedures in helical tomotherapy performed at the radiotherapy department of ARNAS Civico hospital, Italy, is described. The results have allowed to provide suggestions aimed to improve the examined process

Detection rate for significant cancer at confirmatory biopsy in men enrolled in Active Surveillance protocol: 20 cores vs 30 cores vs MRI/TRUS fusion prostate biopsy

Introduction: The detection rate for significant prostate cancer of extended vs saturation vs mMRI/TRUS fusion biopsy was prospectively evaluated in men enrolled in active surveillance (AS) protocol. Mterials and methods: From May 2013 to September 2016 75 men aged 66 years (median) with very low risk PCa were enrolled in an AS protocol and elegible criteria were: life expectancy greater than 10 years, cT1C, PSA below 10 ng/ml, PSA density < 0.20, 2 < unilateral positive biopsy cores, Gleason score (GS) equal to 6, greatest percentage of cancer (GPC) in a core < 50%. All patients underwent 3.0 Tesla pelvic mpMRI before confirmatory transperineal extended (20 cores) or saturation biopsy (SPBx; 30 cores) combined with mpMRI/TRUS fusion targeted biopsy (4 cores) of suspicious lesions (PI-RADS 3-5). Results: 21/75 (28%) patients were reclassified by SPBx based on upgraded GS ≥ 7; mpMRI lesions PI-RADS 4-5 vs PI-RADS 3-5 diagnosed 9/21 (42.8%) vs 16/21 (76.2%) significant PCa with 2 false positives (6.5%). The detection rate for significant PCa was equal to 76.2% (mpMRI/TRUS fusion biopsy) vs 81% (extended) vs 100% (SPBx) (p = 0.001); mpMRI/TRUS targeted biopsy and extended biopsy missed 5/21 (23.8%) and 4/21 (19%) significant PCa which were found by SPBx (p = 0.001) being characterised by the presence of a single positive core of GS ≥ 7 with GPC < 10%. Conclusions: Although mpMRI improve the diagnosis of clinically significant PCa, SPBx is provided of the best detection rate for PCa in men enrolled in AS protocols who underwent confirmatory biopsy

A hierarchical AI-based control plane solution for multitechnology deterministic networks

Following the Industry 4.0 vision of a full digitiSation of the industry, time-critical services and applications, allowing network infrastructures to deliver information with determinism and reliability, are becoming more and more relevant for a set of vertical sectors. As a consequence, deterministic network solutions are progressively emerging, albeit they are still bounded to specific technological domains. Even considering the existence of interconnected deterministic networks, the provision of an end-to-end (E2E) deterministic service over them must rely on a specific control plane architecture, capable of seamlessly integrate and control the underlying multi-technology data plane. In this work, we envision such a control plane solution, extending previous works and exploiting several innovations and novel architectural concepts. The proposed control architecture is service-centric, in order to provide the necessary flexibility, scalability, and modularity to deal with a heterogenous data plane. The architecture is hierarchical and encompasses a set of management platforms to interact with specific network technologies overarched by an E2E platform for the management, monitoring, and control of E2E deterministic services. Furthermore, Artificial Intelligence (AI) and Digital Twinning are used to enable network predictability and automation, as well as smart resource allocation, to ensure service reliability in dynamic scenarios where existing services may terminate and new ones may need to be deployed