Alstom (France)

Background: Submarines represent extremely confined environments where breathing air is continuously recirculated for extended periods with minimal renewal, generating complex multipollutant atmospheres. Objectives: This critical narrative review aims to (i) summarize sources and composition of submarine indoor air, (ii) evaluate respiratory and cardiovascular risks for crews, and (iii) assess current purification technologies. Methods: A narrative review was conducted following PRISMA recommendations applicable to non-systematic reviews. The PubMed search covered all years from inception to September 2025, complemented by backward citation tracking and technical reports. Results: Eligible studies consistently report elevated levels of CO2, VOCs, NOX, CO, PM2.5, and bioaerosols aboard submarines. Evidence from submariner cohorts and toxicological studies indicates risks of airway irritation, impaired mucociliary defenses, endothelial dysfunction, cardiovascular stress, and neurobehavioral alterations. Conclusions: Submarine indoor air quality is a credible determinant of crew health. Existing filtration systems mitigate some risks but do not address multipollutant mixtures adequately. Improved real-time monitoring, advanced filtration, CFD-guided airflow optimization, and longitudinal medical surveillance are necessary.

BackgroundAdolescents and young adults (AYA) with rare forms of diabetes – including Wolfram syndrome (WS), Alström syndrome (AS), Bardet-Biedl syndrome (BBS), and maturity-onset diabetes of the young (MODY) – face unique challenges during the transition to adult care. These challenges are intensified by multisystem endocrine involvement, neurocognitive and sensory impairments, and limited adult provider expertise.ObjectiveThis narrative review describes transition-specific barriers in rare diabetes syndromes, explores current initiatives, and proposes recommendations for care models and health system reform.Key issuesSyndromic forms of diabetes often involve complex endocrine dysfunctions beyond glycemic control, including diabetes insipidus, hypogonadism, and thyroid or pituitary anomalies. Transitions are further hindered by diagnostic uncertainty, fragmented care structures, and insufficient interdisciplinary coordination. Pediatric care is often proactive and family-centered, while adult services are fragmented and reactive. Dedicated multidisciplinary transition services remain scarce.RecommendationsBest practices include early transition planning, syndrome-specific education, the use of patient-reported outcome measures (PROMs), and integration of digital tools. Structured collaboration between pediatric and adult providers – including virtual models – should be supported. Patient-centered approaches must address both medical and psychosocial readiness, with tailored communication for those with sensory or cognitive impairments.Health system and policy needsSustainable transition programs require dedicated funding, institutional prioritization, and policy inclusion in national and European rare disease frameworks. Without adequate financial support, disparities in care continuity and outcomes are likely to persist.ConclusionA coordinated, multidisciplinary, and resourced transition model is essential to safeguard health, autonomy, and long-term outcomes in AYA with rare diabetes syndromes.Plain language summaryYoung people with rare forms of diabetes – such as Wolfram syndrome (WS), Alström syndrome (AS), Bardet-Biedl syndrome (BBS), or maturity-onset diabetes of the young (MODY) – face special challenges when moving from pediatric to adult healthcare. These rare conditions often affect more than just blood sugar and can involve vision, hearing, and other parts of the body. As they grow older, these adolescents must not only manage their complex health needs but also learn to take more responsibility for their care. This article explains why the transition to adult care is especially difficult for this group. It shares experiences from families and healthcare providers and describes what can help: early preparation, teamwork between child and adult doctors, digital tools, and emotional support. The authors call for stronger guidelines and better cooperation across healthcare systems so that young people with rare diabetes can stay healthy and feel supported during this important time in life.Graphical abstract

ABSTRACT This paper designs distance-constrained reference trajectories for trains that respect speed, acceleration, and jerk limitations. It constructs a piecewise-linear (with respect to distance) acceleration profile that verifies the specified jerk constraints, based on a specific first integral of the system. Inspired by the minimal-time synthesis, it provides a complete characterization of the points that can be connected while respecting the constraints imposed on the system. Allowing a maximum of three switches, it provides distance intervals that define the switching policy between two waypoints. Unlike the optimal synthesis, which defines a unique trajectory between two points, it proposes multiple trajectories, each adapted to the imposed distance. These trajectories are described in the mathematical proofs of two propositions that summarize our main results. These propositions are illustrated in three complete examples where a speed profile is generated between two stations in a distance-based framework. It is important to stress that all the provided results are analytic and, thus, compatible with a real-time implementation.

The stator insulation of electrical machines used in industry is exposed to high frequencies and transient voltage stress. This stress is strengthened by the development of new technologies that offer high switching frequencies such as silicon carbide (SiC). Another significant factor influencing stress is high <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$dv / dt$</tex>. All of these factors are considered damaging to the insulation. These factors favor and contribute to the formation of partial discharges (PDs). There is evidence that PDs are the main mechanism that contributes to the degradation of insulation and destroy it over its lifetime. In accordance with international standards, the repetitive partial discharge inception voltage (RPDIV) and repetitive partial discharge extinction voltage (RPDEV) are defined as parameters that are used to characterize the lifetime of the insulation. Measuring these variables proves to be a challenge during operation. It is necessary to disconnect the frequency inverter and couple the varying pulse source. Both RPDIV and RPDEV exhibit a significant temperature dependence. As an alternative to RPDEV, the newly defined parameter repetitive partial discharge extinction temperature (RPDET) is defined. RPDET is determined by keeping the pulse voltage constant while continuously reducing the temperature. Changing the temperature can easily be done in most industrial drives making RPDET a good candidate for in-service monitoring of insulation without the need for disconnecting the machine and using special equipment like pulse voltage generators. As part of the analysis, RPDEV and RPDET are examined and subsequently compared with each other.

Automated welding process inspection is crucial to ensure good execution of the process. With the rise of Artificial Intelligence based solutions several proposals were made in this regard. In this research we study the possibilities of detecting welding process instabilities in sequential data and using sequential deep learning models. We propose a new sequential dataset that consists of four process states to validate our approach. These process states are as follows: no welding, welding and stable, welding and deviated (or shifted), welding and unstable. What characterizes this dataset is the introduction of temporal characteristic through sequential images, and the use of active vision. We test the proposed dataset on a state-of-the-art sequential classification model: ConvLSTM. The tested model is capable of successfully retrieving the patterns in the proposed dataset and classifying the different states of the process represented by a sequence of ten images, at an accuracy of 92%.

In order to minimize fuel cell aging, it is important to take into account the interactions of fuel cells with the auxiliaries required for their operation. In particular, in this study, we focus on the impact of current harmonics generated by the static converter connected to a Low Temperature Proton Exchange Membrane Fuel Cell (LT-PEMFC) technology stack. Indeed, today, there are still uncertainties about the influence of current harmonics on the acceleration of fuel cell aging, especially following technological developments tending to reduce the membrane thickness. In this paper, two endurance tests are carried out simultaneously on two test benches to compare the aging of an LT-PEMFC stack operating in the presence of current harmonics emulating the presence of a Boost DC-DC converter with a stack of the same technology operating at the same constant average current. The results obtained are analyzed and compared on the basis of voltage degradation rates observed during endurance and those recorded via polarization curves. The work presented in this study was carried out as part of the HEMOWHY (HEavy MObilities With HYdrogen) project.

Explainable Artificial Intelligence (XAI) is relatively new in offering the possibility for intelligent systems to give robust motivations for their decisions and behaviours. Since XAI is human-centred, it has strong connections with fuzzy systems. In this paper, we consider the local explanation of the output of a set of fuzzy linguistic rules from the contributions of the inputs to the output. The proposed contributions are defined from the average of the gradients on the line linking the start point to the end point. This approach ensures that the variation in the output is equal to the sum of the contributions of each input variable to the output. The considered application is based on avalanche expert knowledge expressed by a set of fuzzy rules that combines different physical variables to build an ordinal fuzzy scale of avalanche vigilance ("Relaxed", "Suspicious", "Alert", "Gamble"). The level of vigilance to be applied locally, along a mountain ski route, is explained in a way that is close to expert reasoning in order to decide modifications of the route.

Ensuring the efficient and safe operation of lithium-ion batteries requires accurate knowledge of its internal states. However, these internal battery variables cannot be measured in general and must therefore be estimated. In this context, we present an observer design that robustly estimates the state of charge of a lithium-ion cell. This design is appealing for several reasons. First, it is based on a reduced-order physics-based model from the literature, which has the distinctive feature to combine the advantages of equivalent circuit models in terms of simplicity and low computational effort, and of single particle electrochemical models, which more faithfully describe the internal dynamics of the battery. Second, the proposed observer is very simple to design and its robust convergence towards the battery internal states is systematically guaranteed based on Lyapunov arguments. Simulation results demonstrate the effectiveness of the designed observer in estimating the state of charge of the battery given data generated by a higher-fidelity model to emulate an experimental setting.