A Bayesian method with empirically fitted priors for the evaluation of environmental radioactivity: application to low-level radioxenon measurements

International audienceThe decision that a given detection level corresponds to the effective presence of a radionuclide is still widely made on the basis of a classic hypothesis test. However, the classic framework suffers several drawbacks, such as the conceptual and practical impossibility to provide a probability of zero radioactivity, and confidence intervals for the true activity level that are likely to contain negative and hence meaningless values. The Bayesian framework being potentially able to overcome these drawbacks, several attempts have recently been made to apply it to this decision problem. Here, we present a new Bayesian method that, unlike the previous ones, presents two major advantages together. First, it provides an estimate of the probability of no radioactivity, as well as physically meaningful point and interval estimates for the true radioactivity level. Second, whereas Bayesian approaches are often controversial because of the arbitrary choice of the priors they use, the proposed method permits to estimate the parameters of the prior density of radioactivity by fitting its marginal distribution to previously recorded activity data. The new scheme is first mathematically developed. Then, it is applied to the detection of radioxenon isotopes in noble gas measurement stations of the International Monitoring System of the Comprehensive Nuclear-Test-Ban Treaty

An Automation-Friendly Set Theory for the B Method

International audienceWe propose an automation-friendly set theory for the B method. This theory is expressed using first order logic extended to poly-morphic types and rewriting. Rewriting is introduced along the lines of deduction modulo theory, where axioms are turned into rewrite rules over both propositions and terms. We also provide experimental results of several tools able to deal with polymorphism and rewriting over a benchmark of problems in pure set theory (i.e. without arithmetic)

Approximation of a function and its derivative with a neural network

This paper deals with the approximation of both a function and its derivative by feedforward neural networks. We propose an explicit formula of approximation which is noise resistant and can be easily modified with the patterns. We apply these results to approach a function defined implicitly, which is useful in control theory

Constraint-Based Mining of Sequential Patterns over Datasets with Consecutive Repetitions

onstraint-based mining of sequential patterns is an active research area motivated by many application domains. In practice, the real sequence datasets can present consecutive repetitions of symbols (e.g., DNA sequences, discretized stock market data) that can lead to a very important consumption of resources during the extraction of patterns that can turn even efficient algorithms to become unusable. We propose a constraint-based mining algorithm using an approach that enables to compact these consecutive repetitions, reducing drastically the amount of data to process and speeding-up the extraction time. The technique introduced in this paper allows to retain the advantages of existing state-of-the-art algorithms based on the notion of occurrence lists, while permitting to extend their application fields to datasets containing consecutive repetitions. We analyze the benefits obtained using synthetic datasets, and show that the approach is of practical interest on real datasets

A semi-automated Computer Tool for the Analysis of Retinal Vessel Diameter Dynamics

International audienceRetinal vessels are directly accessible to clinical observation. This has numerous potential interests for medical investigations. Using the Retinal Vessel Analyzer, a dedicated eye fundus camera enabling dynamic, video-rate recording of micrometric changes of the diameter of retinal vessels, we developed a semi-automated computer tool that extracts the heart beat rate and pulse amplitude values from the records. The extracted data enabled us to show that there is a decreasing relationship between heart beat rate and pulse amplitude of arteries and veins. Such an approach will facilitate the modeling of hemodynamic interactions in small vessels

Squamous cell carcinomas are associated with verrucokeratotic cutaneous lesions but not with common warts in organ-transplant patients. A case-control study.

International audienceVerrucous papilloma and mainly verrucokeratotic lesions are strongly associated with the risk of SCC in organ transplant patients, whereas the most typical types of warts: verrucae vulgares and flat warts, are not

Severity of COVID-19 and survival in patients with rheumatic and inflammatory diseases: data from the French RMD COVID-19 cohort of 694 patients

International audienceObjectives: There is little known about the impact of SARS-CoV-2 on patients with inflammatory rheumatic and musculoskeletal diseases (iRMD). We examined epidemiological characteristics associated with severe disease, then with death. We also compared mortality between patients hospitalised for COVID-19 with and without iRMD.Methods: Individuals with suspected iRMD-COVID-19 were included in this French cohort. Logistic regression models adjusted for age and sex were used to estimate adjusted ORs and 95% CIs of severe COVID-19. The most significant clinically relevant factors were analysed by multivariable penalised logistic regression models, using a forward selection method. The death rate of hospitalised patients with iRMD-COVID-19 (moderate-severe) was compared with a subset of patients with non-iRMD-COVID-19 from a French hospital matched for age, sex, and comorbidities.Results: Of 694 adults, 438 (63%) developed mild (not hospitalised), 169 (24%) moderate (hospitalised out of the intensive care unit (ICU) and 87 (13%) severe (patients in ICU/deceased) disease. In multivariable imputed analyses, the variables associated with severe infection were age (OR=1.08, 95% CI: 1.05-1.10), female gender (OR=0.45, 95% CI: 0.25-0.80), body mass index (OR=1.07, 95% CI: 1.02-1.12), hypertension (OR=1.86, 95% CI: 1.01-3.42), and use of corticosteroids (OR=1.97, 95% CI: 1.09-3.54), mycophenolate mofetil (OR=6.6, 95% CI: 1.47-29.62) and rituximab (OR=4.21, 95% CI: 1.61-10.98). Fifty-eight patients died (8% (total) and 23% (hospitalised)). Compared with 175 matched hospitalised patients with non-iRMD-COVID-19, the OR of mortality associated with hospitalised patients with iRMD-COVID-19 was 1.45 (95% CI: 0.87-2.42) (n=175 each group).Conclusions: In the French RMD COVID-19 cohort, as already identified in the general population, older age, male gender, obesity, and hypertension were found to be associated with severe COVID-19. Patients with iRMD on corticosteroids, but not methotrexate, or tumour necrosis factor alpha and interleukin-6 inhibitors, should be considered as more likely to develop severe COVID-19. Unlike common comorbidities such as obesity, and cardiovascular or lung diseases, the risk of death is not significantly increased in patients with iRMD

Severity of COVID-19 and survival in patients with rheumatic and inflammatory diseases: data from the French RMD COVID-19 cohort of 694 patients

International audienceObjectives: There is little known about the impact of SARS-CoV-2 on patients with inflammatory rheumatic and musculoskeletal diseases (iRMD). We examined epidemiological characteristics associated with severe disease, then with death. We also compared mortality between patients hospitalised for COVID-19 with and without iRMD.Methods: Individuals with suspected iRMD-COVID-19 were included in this French cohort. Logistic regression models adjusted for age and sex were used to estimate adjusted ORs and 95% CIs of severe COVID-19. The most significant clinically relevant factors were analysed by multivariable penalised logistic regression models, using a forward selection method. The death rate of hospitalised patients with iRMD-COVID-19 (moderate-severe) was compared with a subset of patients with non-iRMD-COVID-19 from a French hospital matched for age, sex, and comorbidities.Results: Of 694 adults, 438 (63%) developed mild (not hospitalised), 169 (24%) moderate (hospitalised out of the intensive care unit (ICU) and 87 (13%) severe (patients in ICU/deceased) disease. In multivariable imputed analyses, the variables associated with severe infection were age (OR=1.08, 95% CI: 1.05-1.10), female gender (OR=0.45, 95% CI: 0.25-0.80), body mass index (OR=1.07, 95% CI: 1.02-1.12), hypertension (OR=1.86, 95% CI: 1.01-3.42), and use of corticosteroids (OR=1.97, 95% CI: 1.09-3.54), mycophenolate mofetil (OR=6.6, 95% CI: 1.47-29.62) and rituximab (OR=4.21, 95% CI: 1.61-10.98). Fifty-eight patients died (8% (total) and 23% (hospitalised)). Compared with 175 matched hospitalised patients with non-iRMD-COVID-19, the OR of mortality associated with hospitalised patients with iRMD-COVID-19 was 1.45 (95% CI: 0.87-2.42) (n=175 each group).Conclusions: In the French RMD COVID-19 cohort, as already identified in the general population, older age, male gender, obesity, and hypertension were found to be associated with severe COVID-19. Patients with iRMD on corticosteroids, but not methotrexate, or tumour necrosis factor alpha and interleukin-6 inhibitors, should be considered as more likely to develop severe COVID-19. Unlike common comorbidities such as obesity, and cardiovascular or lung diseases, the risk of death is not significantly increased in patients with iRMD