A Graph-based Framework for Complex System Simulating and Diagnosis with Automatic Reconfiguration

Fault detection has a long tradition: the necessity to provide the most accurate diagnosis possible for a process plant criticality is somehow intrinsic in its functioning. Continuous monitoring is a possible way for early detection. However, it is somehow fundamental to be able to actually simulate failures. Reproducing the issues remotely allows to quantify in advance their consequences, causing literally no real damage. Within this context, signed directed graphs have played an essential role within the years, managing to model with a relatively simple theory diverse elements of an industrial network, as well as the logic relations between them.\\ In this work we present a quantitative approach, employing directed graphs to the simulation and automatic reconfiguration of a fault in a network. To model the typical operation of industrial plants, we propose several additions with respect to the standard graphs: 1. a quantitative measure to control the overall residual capacity, 2. nodes of different categories - and then different behaviors - and 3. a fault propagation procedure based on the predecessors and the redundancy of the system. The obtained graph is able to mimic the behaviour of the real target plant when one or more faults occur. Additionally, we also implement a generative approach capable to activate a particular category of nodes in order to contain the issue propagation, equipping the network with the capability of reconfigure itself and resulting then in a mathematical tool useful not only for simulating and monitoring, but also to design and optimize complex plants. The final asset of the system is provided in output with its complete diagnostics, and a detailed description of the steps that have been carried out to obtain the final realization

Deep learning-based reduced-order methods for fast transient dynamics

In recent years, large-scale numerical simulations played an essential role in estimating the effects of explosion events in urban environments, for the purpose of ensuring the security and safety of cities. Such simulations are computationally expensive and, often, the time taken for one single computation is large and does not permit parametric studies. The aim of this work is therefore to facilitate real-time and multi-query calculations by employing a non-intrusive Reduced Order Method (ROM). We propose a deep learning-based (DL) ROM scheme able to deal with fast transient dynamics. In the case of blast waves, the parametrised PDEs are time-dependent and non-linear. For such problems, the Proper Orthogonal Decomposition (POD), which relies on a linear superposition of modes, cannot approximate the solutions efficiently. The piecewise POD-DL scheme developed here is a local ROM based on time-domain partitioning and a first dimensionality reduction obtained through the POD. Autoencoders are used as a second and non-linear dimensionality reduction. The latent space obtained is then reconstructed from the time and parameter space through deep forward neural networks. The proposed scheme is applied to an example consisting of a blast wave propagating in air and impacting on the outside of a building. The efficiency of the deep learning-based ROM in approximating the time-dependent pressure field is shown

Prevalence and clinical relevance of digital ulcers in systemic sclerosis patients from the real-life: the experience of the SPRING Registry of the Italian Society for Rheumatology

ntroduction: Digital ulcers (DU) are one of the most frequent manifestations in systemic sclerosis (SSc). The presence of DU seems to be a sentinel sign of internal organ involvement and is related to a poor prognosis of the disease. The aim of this study was to evaluate the prevalence and the relationship of DU with clinical manifestations/variants in a large SSc cohort from the SPRING registry. Methods: SSc patients fulfilling the ACR/EULAR 2013 classification criteria without missing data on digital ulcers were enrolled in a cross-sectional study. Logistic regression models were built to test the association between the presence of DU and SSc-related features. Results: Among 1873 eligible SSc patients, the presence of DU was significantly associated with gastrointestinal involvement (OR 1.88, 2.04 and 1.74; p < 0.001) and serum ATA positivity (OR 2.15; p < 0.001), as well as with telangiectasias, sclerodactyly, digital pitting scar, and calcinosis (OR 1.40, p = 0.005; OR 3.43, p < 0.001, OR 9.12, p < 0.001 and OR 2.77, p < 0.001; respectively). In the multivariable regression models, even after adjustment for covariates, ATA positivity (OR 1.76, p = 0.039), puffy fingers (OR 2.82, p < 0.001), and a higher revEUSTAR-AI (OR 6.63, p < 0.001) emerged as risk factors for the presence of DU. Moreover, a low presence of DU was recorded in SSc patients with a history of previous immunosuppressive treatments (OR 0.53, p = 0.032). Conclusion: In our Italian SSc cohort, DUs were significantly associated with the presence of puffy fingers, high revEUSTR-AI, and ATA seropositivity. Noteworthy, immunosuppressive treatments were associated with a low rate of DU, suggesting that they might contribute to the prevention of these harmful manifestations. Key Points • Digital ulcers were significantly associated with the presence of puffy fingers, high disease activity, and anti-Scl70 seropositivity. • Immunosuppressive treatments were associated with a low rate of digital ulcers, suggesting that they might contribute to the prevention of these harmful manifestations. Keywords: Digital ulcers; Immunosuppressive therapy; Systemic sclerosis; Vascular disease

Management of pregnancy in autoimmune rheumatic diseases: maternal disease course, gestational and neonatal outcomes and use of medications in the prospectiveItalian P-RHEUM.it study

Objectives To investigate pregnancy outcomes in women with autoimmune rheumatic diseases (ARD) in the Italian prospective cohort study P-RHEUM.it. Methods Pregnant women with different ARD were enrolled for up to 20 gestational weeks in 29 Rheumatology Centres for 5 years (2018-2023). Maternal and infant information were collected in a web-based database. Results We analysed 866 pregnancies in 851 patients (systemic lupus erythematosus was the most represented disease, 19.6%). Maternal disease flares were observed in 135 (15.6%) pregnancies. 53 (6.1%) pregnancies were induced by assisted reproduction techniques, 61 (7%) ended in miscarriage and 11 (1.3%) underwent elective termination. Obstetrical complications occurred in 261 (30.1%) pregnancies, including 2.3% pre-eclampsia. Two cases of congenital heart block were observed out of 157 pregnancies (1.3%) with anti-Ro/SSA. Regarding treatments, 244 (28.2%) pregnancies were treated with glucocorticoids, 388 (44.8%) with hydroxychloroquine, 85 (9.8%) with conventional synthetic disease-modifying anti-rheumatic drugs and 122 (14.1%) with biological disease-modifying anti-rheumatic drugs. Live births were 794 (91.7%), mostly at term (84.9%); four perinatal deaths (0.5%) occurred. Among 790 newborns, 31 (3.9%) were small-for-gestational-age and 169 (21.4%) had perinatal complications. Exclusive maternal breast feeding was received by 404 (46.7%) neonates. The Edinburgh Postnatal Depression Scale was compiled by 414 women (52.4%); 89 (21.5%) scored positive for emotional distress. Conclusions Multiple factors including preconception counselling and treat-to-target with pregnancy-compatible medications may have contributed to mitigate disease-related risk factors, yielding limited disease flares, good pregnancy outcomes and frequency of complications which were similar to the Italian general obstetric population. Disease-specific issues need to be further addressed to plan preventative measures

A genome-wide association study for survival from a multi-centre European study identified variants associated with COVID-19 risk of death

The clinical manifestations of SARS-CoV-2 infection vary widely among patients, from asymptomatic to life-threatening. Host genetics is one of the factors that contributes to this variability as previously reported by the COVID-19 Host Genetics Initiative (HGI), which identified sixteen loci associated with COVID-19 severity. Herein, we investigated the genetic determinants of COVID-19 mortality, by performing a case-only genome-wide survival analysis, 60 days after infection, of 3904 COVID-19 patients from the GEN-COVID and other European series (EGAS00001005304 study of the COVID-19 HGI). Using imputed genotype data, we carried out a survival analysis using the Cox model adjusted for age, age2, sex, series, time of infection, and the first ten principal components. We observed a genome-wide significant (P-value < 5.0 x 10(-8)) association of the rs117011822 variant, on chromosome 11, of rs7208524 on chromosome 17, approaching the genome-wide threshold (P-value = 5.19 x 10(-8)). A total of 113 variants were associated with survival at P-value < 1.0 x 10(-5) and most of them regulated the expression of genes involved in immune response (e.g., CD300 and KLR genes), or in lung repair and function (e.g., FGF19 and CDH13). Overall, our results suggest that germline variants may modulate COVID-19 risk of death, possibly through the regulation of gene expression in immune response and lung function pathways

The Italian Society for Rheumatology guidelines on reproductive health in patients with rheumatic diseases

Objective. To date, there is no shared national guideline in Italy for the management of reproductive health in rheumatic diseases (RHRD). The Italian Society for Rheumatology has committed to developing clinical practice recommendations to provide guidance on both management and treatment regarding RHRD in Italy. Methods. Using the GRADE-ADOLOPMENT methodology, a systematic literature review was conducted to update the scientific evidence that emerged after the publication of the reference recommendations from the American College of Rheumatology. A multidisciplinary group of 18 clinicians with specialist experience in rheumatology, allergy and clinical immunology, internal medicine, nephrology, gynecology and obstetrics, and neonatology, a professional nurse, a clinical psychologist, and a representative from the National Association of Rheumatic Patients discussed the recommendations in collaboration with the evidence review working group. Subsequently, a group of stakeholders was consulted to examine and externally evaluate the developed recommendations. Results. Recommendations were formulated for each area of interest: contraception, assisted reproductive technology, preconception counseling, and use of drugs before, during, and after pregnancy and during breastfeeding, considering both paternal and maternal exposure. Conclusions. The new SIR recommendations provide the rheumatology community with a practical guide based on updated scientific evidence for the management of RHRD

A genome-wide association study for survival from a multi-centre European study identified variants associated with COVID-19 risk of death

: The clinical manifestations of SARS-CoV-2 infection vary widely among patients, from asymptomatic to life-threatening. Host genetics is one of the factors that contributes to this variability as previously reported by the COVID-19 Host Genetics Initiative (HGI), which identified sixteen loci associated with COVID-19 severity. Herein, we investigated the genetic determinants of COVID-19 mortality, by performing a case-only genome-wide survival analysis, 60 days after infection, of 3904 COVID-19 patients from the GEN-COVID and other European series (EGAS00001005304 study of the COVID-19 HGI). Using imputed genotype data, we carried out a survival analysis using the Cox model adjusted for age, age2, sex, series, time of infection, and the first ten principal components. We observed a genome-wide significant (P-value < 5.0 × 10-8) association of the rs117011822 variant, on chromosome 11, of rs7208524 on chromosome 17, approaching the genome-wide threshold (P-value = 5.19 × 10-8). A total of 113 variants were associated with survival at P-value < 1.0 × 10-5 and most of them regulated the expression of genes involved in immune response (e.g., CD300 and KLR genes), or in lung repair and function (e.g., FGF19 and CDH13). Overall, our results suggest that germline variants may modulate COVID-19 risk of death, possibly through the regulation of gene expression in immune response and lung function pathways

A genome-wide association study for survival from a multi-centre European study identified variants associated with COVID-19 risk of death

The clinical manifestations of SARS-CoV-2 infection vary widely among patients, from asymptomatic to life-threatening. Host genetics is one of the factors that contributes to this variability as previously reported by the COVID-19 Host Genetics Initiative (HGI), which identified sixteen loci associated with COVID-19 severity. Herein, we investigated the genetic determinants of COVID-19 mortality, by performing a case-only genome-wide survival analysis, 60 days after infection, of 3904 COVID-19 patients from the GEN-COVID and other European series (EGAS00001005304 study of the COVID-19 HGI). Using imputed genotype data, we carried out a survival analysis using the Cox model adjusted for age, age2, sex, series, time of infection, and the first ten principal components. We observed a genome-wide significant (P-value < 5.0 × 10) association of the rs117011822 variant, on chromosome 11, of rs7208524 on chromosome 17, approaching the genome-wide threshold (P-value = 5.19 × 10). A total of 113 variants were associated with survival at P-value < 1.0 × 10 and most of them regulated the expression of genes involved in immune response (e.g., CD300 and KLR genes), or in lung repair and function (e.g., FGF19 and CDH13). Overall, our results suggest that germline variants may modulate COVID-19 risk of death, possibly through the regulation of gene expression in immune response and lung function pathways