CentraleSupélec

Electron precipitation by chorus whistler‐mode waves generated by the same electron population is expected to play an important role in the dynamics of the outer radiation belt, potentially setting a hard upper limit on trapped energetic electron fluxes. Here, we statistically analyze the relationship between equatorial electron fluxes and the power of mid‐latitude cyclotron‐resonant chorus waves precipitating these electrons, both inferred from ELFIN low‐altitude energy and pitch‐angle resolved electron flux measurements in 2020–2022. We provide clear evidence of a flux limitation coinciding with an exponential increase of precipitation. We statistically demonstrate that the actual inferred resonant wave power gains are well correlated with theoretical linear gains, as in the classical Kennel‐Petschek model, for moderately high linear gains and high fluxes. However, we also find a finite occurrence of very high fluxes, corresponding to resonant waves of moderate average amplitude, implying a softer, more dynamical upper limit than traditionally envisioned.

In recent years, embodied learning has gained currency in the field of education, allowing interactivity between users, thus contributing to collaborative learning in the flow of embodied immersive technology. Evidence based studies conducted in this field tackled the effectiveness of this approach on students’ performance and learning outcomes in children’s education. However, scarcity of scoping reviews treating the outcome of using embodied collaborative learning on higher education students’ performance was detected. Considering the relevance of building a theoretical background guiding further research in this current field, this meta-analysis was conducted to fill the gap. This article describes the current issues on research about embodied collaborative learning in STEM education in XR learning settings to identify advances and gaps. Published papers between 2013 and 2023 were selected from educational databases, identifying 12 documents related to the subject of interest of this meta-analysis. Results show that embodied learning have positive impact on social interactivity and collaboration between students. Positive impact on students’ academic outcomes was also detected. Alongside with the preceding, embodied collaborative learning has a positive impact on overall students’ social flow (motivation, cohesion, emotions, interaffectivity, satisfaction). This article presents a theoretical background for embodied collaborative testing tools based on embodied social presence and collaboration practical criteria.

Estimating accurate channel state information (CSI) is a prerequisite to benefit from the deployment of reconfigurable intelligent surfaces (RISs). However, pilot overhead is required for estimating the high-dimensionality cascaded channel in RIS-assisted wireless communication systems in addition to considering the scaling ambiguity for separate channel decomposition. In this paper, we exploit a large number of elements at a RIS and the resulting slow variations of the channels between the RIS and the user terminals (UTs). Specifically, we exploit the channel hardening effect between the RIS and UTs and propose an algorithm to estimate the individual channel components for the RIS-assisted system based on the conjugate-gradient method. Moreover, we resolve the channel ambiguity in estimating the separate channels and introduce a three-interval sounding procedure where in the first two intervals we eliminate the product of the RIS-UTs channel matrix with its Hermitian and replace it with a diagonal matrix. Thereby, we transform the channel estimation problem into a tractable form and avoid the bi-linearity in RIS-assisted systems. Then, we deploy the conjugate gradient method to estimate the BS-RIS channel, which is assumed to be constant. In the last sounding phase, the RIS-UTs channel is estimated using conventional techniques such as the least-squares (LS) or minimum mean square error (MMSE) estimators. The results confirm that hardening phenomena between the RIS and UTs channel make the channel estimation problem in the RIS-assisted system feasible and avoid the high degree of non-convexity.

Introduction Immune checkpoint blockers (ICBs) revolutionized the treatment of patients with advanced non-small cell lung cancer (NSCLC) but only a fraction of them obtain a response, and clinical benefit from these treatments is often difficult to predict. The aim of our study is to unveil the potential implications of antibody response to previous viral infections in predicting response to ICBs in patients with NSCLC. Methods Sera from patients treated with ICBs alone, chemotherapy (CT) or a combination of CT-ICBs were analyzed with VirScan (CDI Labs, USA), a high-throughput method that comprehensively analyzes epitope-level antiviral IgG antibodies via programmable phage display and immunoprecipitation sequencing.Total number of unique positive peptides (tUP) was defined as the total number of non-overlapping positive “is a hit” peptides for each patient. Results Overall, 387 patients were included. Of them, 129 were treated with ICBs alone, 66 with CT-ICBs and 195 with CT alone. 90 out of 129 patients treated with ICBs alone received ICBs as a subsequent line of treatment, while CT-ICBs and CT were administered as upfront therapies.A higher tUP was correlated with improved overall survival in patients treated with ICBs, and confirmed in the multivariate model (HR 0.43, 95% CI 0.24, 0.79, p=0.006), while it was not in those treated with CT-ICBs (p=0.8) and CT alone (p=0.1). tUP was not correlated with programmed death-ligand 1 (PD-L1) expression, while at the transcriptome level it was correlated with several immune-related pathways, particularly involving B cells. Conclusion A higher number of viral peptides recognized by serum antibodies might reflect increased immune fitness, resulting in improved outcomes in ICBs treated patients with NSCLC.

We address the problem of designing interpretable algorithms for image classification. Modern computer vision algorithms implement classification in two phases: feature extraction - the encoding - that relies on deep neural networks (DNN), followed by a task-oriented decision - the decoding - often also using a DNN. We propose to formulate this last phase as an argumentative DialoguE Between two agents relying on visual ATtributEs and Similarity to prototypes (DEBATES). DEBATES represents the combination of information provided by two encoders in a transparent and interpretable way. It relies on a dual process that combines similarity to prototypes and visual attributes, each extracted from an encoder. DEBATES makes explicit the agreements and conflicts between the two encoders managed by the two agents, reveals the causes of unintended behaviors, and helps identify potential corrective actions to improve performance. The approach is demonstrated on two problems of fine-grained image classification.

In acoustical imaging and source localization, several methods for the exploitation of asynchronous array measurements have been proposed, based on covariance matrix completion, Bayesian estimation, fusion of beamforming maps, etc. The goal of asynchronous measurements is to reach the performance of large and dense arrays, with reduced experimental effort, by moving an array of limited size between experiments, and fuse the obtained data to produce an estimation of the distribution of acoustical sources. In this study, we consider the performances that one can expect from asynchronous measurements, and investigate the actual performances of several methods from the state of the art. In particular, the mean squared errors of the estimation of the position and power of an acoustical source are estimated using simulations and experimental measurements.

In the aircraft industry, noise mitigation has emerged as an increasingly pressing issue, underscoring the critical importance of advancing our understanding of noise origins within turbofan engines. This paper presents the application of Positive Semi Definite Tensor Factorization (PSDTF), a potential method for the analysis of engine static tests conducted with far-field microphone arrays. By extending the capabilities of Non-negative Matrix Factorization (NMF), PSDTF offers an effective algorithm for source separation. Leveraging on cross spectral matrices to harness phase information across microphones, this approach aims at separating the contributions of several noise sources, avoiding the need for a precise acoustical model (sound propagation, source directivity, etc.). Experimental findings on a controlled experiment demonstrate the superiority of PSDTF over conventional NMF variants in achieving higher-quality source separation.

The strong variations of energetic electron fluxes in the Earth's inner magnetosphere are notoriously hard to forecast. Developing accurate empirical models of electron fluxes from low to high altitudes at all latitudes is therefore useful to improve our understanding of flux variations and to assess radiation hazards for spacecraft systems. In the present work, energy‐ and pitch‐angle‐resolved precipitating, trapped, and backscattered electron fluxes measured at low altitude by Electron Loss and Fields Investigation (ELFIN) CubeSats are used to infer omnidirectional fluxes at altitudes below and above the spacecraft, from 150 to 20,000 km, making use of adiabatic transport theory and quasi‐linear diffusion theory. The inferred fluxes are fitted as a function of selected parameters using a stepwise multivariate optimization procedure, providing an analytical model of omnidirectional electron flux along each geomagnetic field line, based on measurements from only one spacecraft in low Earth orbit. The modeled electron fluxes are provided as a function of L L‐shell, altitude, energy, and two different indices of past substorm activity, computed over the preceding 4 hr or 3 days, potentially allowing to disentangle impulsive processes (such as rapid injections) from cumulative processes (such as inward radial diffusion and wave‐driven energization). The model is validated through comparisons with equatorial measurements from the Van Allen Probes, demonstrating the broad applicability of the present method. The model indicates that both impulsive and time‐integrated substorm activity partly control electron fluxes in the outer radiation belt and in the plasma sheet.

The ionosphere's electron density is a critical factor in long-distance communication and sky-wave propagation, directly affecting signal transmission quality. Accurate prediction of the ionosphere’s state is crucial for understanding signal perturbations and estimating key parameters for improved transmission. Space weather impacts on trans-ionospheric technological systems are well-documented. This study presents a web application that visualizes global day-to-day electron density variations using the NeQuickG model. Additionally, it analyzes hop data from ground-based HAM radio networks at various wavelengths (e.g., 10 m and 20 m) alongside electron density measurements obtained from space-based probes on the International Space Station (ISS). The electron density variations for 2017 are comprehensively represented. Optimization techniques are proposed to generate a denser, spatially-resolved ionospheric electron density map by employing a probabilistic approach to estimate the optimal weight function, minimizing error variance in areas with sparse data. This work emphasizes developing user-friendly metrics for amateur radio operators and the civil aviation sector. The web-based application has potential as an enhanced visualization tool for space weather forecasting. **The project, titled "Fellowship of the Ionosphere," was a Global Finalist in the 2022 NASA Space Apps Challenge, which saw over 31,400 participants from 162 countries and territories, with 5327 teams submitting more than 3000 projects. As a Global Finalist, this project was ranked among the top 35 submissions.

This chapter contains the final stakeholder analysis. It showcases the key actors involved in testing and deploying automated minibuses for public transport in European cities. This assessment helps construct a strategic overview of the expectations, needs, and impacts of the stakeholders and the connections between them. This stakeholder analysis relied on qualitative methods and involved four steps. As a first step, an initial stakeholder scan was conducted. Through a literature review, including both academic and grey literature, and stakeholder mapping techniques, the main stakeholder groups were defined. The second step involved semi-structured interviews to gain a thorough understanding of the objections, perceptions, and information-seeking behaviour of these stakeholder groups. In the third step, a content analysis of the interviews was conducted, which led to the depiction of six key themes. The initial three steps are centred on conducting an analysis at the EU level. The fourth step took a project-level perspective. A literature review and expert interviews were conducted to determine the main relations and themes for the AVENUE ecosystem, based on which the AVENUE stakeholder and mobility services map was developed. The analysis delivers valuable findings: The AVENUE-centred map shows that automated minibuses are expected to be integrated into a multi- and intermodal mobility system and offered as Mobility as a Service (MaaS). There is a need for collective action to settle one legal framework and specific guidelines for automated vehicles (AV) within the EU. Finally, the integration of AV into the mobility system must be promoted in synergy with the goals of Sustainable Urban Mobility Planning (SUMP). The stakeholder map at EU level demonstrates that not all actors possess equal influence on the advancement of automated minibuses in urban public transportation systems. Primary actors comprise city governments, public transport operators (PTO), manufacturers, software developers, the European Union, and citizens/end-users. The relationship between the city government and the PTO is central. The strategy presents key recommendations for stakeholders, such as: More emphasis should be given to the crucial role of the government and the legal framework in the deployment of automated minibuses. PTOs need more support from the local government, and they should reach out to other key stakeholders such as NGOs and policymakers. A MaaS platform should be operated in collaboration with private and public partners. There should be active involvement from citizens and civil society; this is done through strategic tools for citizens’ participation and inclusion in the debate about AV in general. For AVENUE and similar projects, it is important to involve stakeholders such as civil society organizations, e.g. as driver unions and environmental NGOs. Also, they need to cooperate more with city governments and focus on user-centric services and not only technological achievements.

The AVENUE project, carried out under Horizon 2020, demonstrated remarkable progress in automated public transport by deploying almost SAE Level 4 AVs in six European cities. Despite significant challenges, including COVID-19 restrictions and partner insolvency, the project successfully deployed automated minibuses that carried over 160,000 passengers and travelled a total of 168,000 km. This conclusion highlights AVENUE’s achievements in improving urban mobility through on-demand door-to-door services and emphasises the potential of using automated minibuses as game changer towards a more sustainable, efficient and citizen centric mobility which serves the general interest.

The AVENUE project, which was carried out in Geneva, Lyon, Luxembourg, and Copenhagen, demonstrates the innovative integration of automated vehicles (AVs) into urban public transport systems. This initiative investigated the use of AVs in different urban environments and achieved remarkable progress in the areas of mobility, environmental sustainability, and accessibility. Through real-world testing, the project identified key success factors such as technological integration, social acceptance, and infrastructural adaptation. Achievements include on-demand services, seamless integration into existing transport networks and the promotion of multimodal transport solutions. The experiences from the AVENUE project provide crucial insights into operational and societal aspects of AV implementation in public transport and emphasise the importance of ongoing innovation and research in the field of automated mobility for future urban transport ecosystems.

This chapter provides a comprehensive analysis of the economic and environmental externalities associated with the use of automated minibuses in public transport, using a mixture of scenario planning and an externality model in the context of the AVENUE project cities. By analysing six different deployment scenarios, including the substitution of automated minibuses for buses and private cars, this study sheds light on the potential shifts in external costs and benefits. This chapter carefully assesses the impact of the deployment of automated minibuses on reducing external costs, taking into account factors such as energy efficiency, connectivity, automation features passenger numbers and vehicle utilisation rates. The results show that the environmental and economic outcomes of deploying automated minibuses depend significantly on the specific deployment strategies, highlighting scenarios in which automated minibuses could either reduce or exacerbate external costs. Through a detailed assessment of these scenarios, the chapter provides a nuanced understanding of how the strategic integration of automated minibuses into urban transport systems can influence the broader goals of economic sustainability and environmental protection. The study emphasises the importance of aligning automated minibus deployment strategies with city-specific goals and the broader sustainability agenda and provides valuable insights for policymakers, urban planners and transport stakeholders.

This chapter presents results from the AVENUE social impact assessment. The assessment focuses on the social impacts of the deployment of automated minibuses in the four official AVENUE cities: Luxembourg, Copenhagen, Geneva, and Lyon. The following studies have been conducted: (1) a qualitative study on mobility needs, mobility gaps, and expectations on automated minibuses in the pilot site Nordhavn, in Copenhagen, Denmark, as well as in a potential replicator site in Singen, Germany; (2) a quantitative, representative study on mobility behaviour, attitudes on automated minibuses, and social acceptance of automated minibuses in the four AVENUE cities; and (3) a study on user experiences of passengers of the automated minibuses service in Nordhavn, Copenhagen. This social impact assessment revealed that the majority of citizens have not yet adopted a clear position towards automated minibuses (AM) but rather a positive, open-minded (benevolent) attitude. As there are no stable attitudes yet, there is a possibility to influence (nudge) preferences through well-targeted communication campaigns. The willingness to use the automated minibus service is higher when it is offered on-demand, door-to-door, integrated into a public transport system. The automated minibus is considered as an alternative to the use of their private car, with 45% of car drivers ‘willing’ (22%) or even ‘very willing’ (23%) to give up using their own car to use automated minibuses to bridge the first and the last mile. In addition, users of the automated minibus are generally satisfied with this experience, which even leads to increasing acceptance and a reduction of perceived risks compared to non-users. An important prerequisite for users to shift from using their private car to an automated minibus service is to increase flexibility of use by providing an on-demand, door-to-door service. If an automated minibus is integrated into the urban public and private transport system, it has the potential to become a real game changer for urban mobility. The integration of automated minibuses therefore represents a real system innovation that takes into account the mobility needs of potential users.

In this chapter we aim to provide pragmatic recommendations and exemplary concrete transition measures for consultants and ecosystem stakeholders to get valuable practice proven cornerstones and hints for successfully achieving their individually designed mobility vision. Hereby we describe the transition planning as a systemic and systematic approach designed as a pragmatic process with essential key methods from the status quo (2020) of all existing states towards a desired common future vision of AV in ITS to be achieved in 2030. For this purpose we visualised a ‘Big Picture’ of transition management work packages and a roadmap as a ‘common thread’, conceptional guide and orientation for all stakeholders of the transition. This roadmap of multifaceted recommendations is structured into phases which are systematically building on one another, outlining the transition from the status quo with no automated minibuses (AM) via the milestones: AM, AM System, AM in MaaS, AM in MaaS/ITS to the future mobility Vision 2030 (Chap. 18 ). These recommendations are the basis for individual operational measures which have to be documented in an implementation plan. Finally, a general transition plan is suggested consisting of all scenarios, steps and planning results of the transition concept. This should serve all stakeholders as an orientation guide as well as a strategic and operational basis for the entire mobility transition.

This chapter examines the environmental impacts of integrating automated minibuses into public transport systems, focusing on the trade-offs between energy savings and increased energy demand due to connectivity and automation features. A comprehensive life cycle assessment (LCA) is used to analyse the potential environmental benefits and problems of automated minibuses. The results show that the environmental benefits of these vehicles depend significantly on the electricity mix for charging, passenger occupancy, and vehicle utilisation throughout their lifetime. In particular, scenarios with renewable energy sources, high passenger occupancy, and optimal vehicle utilisation show the significant potential of automated minibuses to contribute to a more sustainable transport system. This study highlights the importance of holistic considerations, including technological, operational, and infrastructural factors, in maximising the environmental benefits of automated minibuses in urban mobility. It provides a nuanced understanding of the conditions under which automated minibuses can act as a catalyst for the transition to greener public transport.

This chapter introduces the AVENUE sustainability assessment methodology, which is rooted in the Sustainable Urban Mobility Plan (SUMP) framework to formulate a comprehensive approach to an urban mobility assessment. The chapter explores how the AVENUE project is adapting to SUMP by improving public transport and incorporating innovative mobility solutions like automated vehicles (AVs) and Mobility as a Service (MaaS). Through an interdisciplinary lens, this chapter details how the different work packages of the AVENUE project contribute to an integrated and sustainable urban mobility ecosystem assessment. It emphasises the crucial role of stakeholder engagement in shaping mobility solutions that are not only technologically advanced, but also environmentally sustainable, economically viable and socially inclusive. The chapter demonstrates the practical application of SUMP principles in different urban environments, providing valuable insights for policymakers, urban planners and the mobility sector in general. This research underlines the importance of a holistic assessment framework that includes environmental, economic and social impact assessments and also technical and governance issues. It provides a possible interdisciplinary methodology to assess all the facets of future sustainable urban mobility developments.

The first chapter explores three pathways for incorporating automated vehicles (AVs) into future mobility ecosystems: privately owned AVs, robotaxis and automated minibuses in a Mobility-as-a-Service (MaaS) and (later) in an Intelligent Transport System (ITS). The chapter emphasises that automated minibuses, when seamlessly integrated into a MaaS, could emerge as pivotal “game changer”, complementing and fostering other means of transport, in particular mass transport. Integrating in a next step AVs within an ITS could further make it possible to use mobility data and artificial intelligence (AI) to improve the transport system to a higher level of mobility evolution. By employing both fast and slow closed AI loops, it envisions a transport ecosystem that not only operates more efficiently and flexibly but is also consequently citizen-centric and addresses sustainability challenges. The successful implementation of this concept hinges on open data, Application Protocol Interface (APIs) and the potential of AI to create a self-learning transport system to serve the general interest. A sustainable and citizen-centric mobility is thus possible without a coercive (technology push) transport policy. Instead, it champions an approach that increases the transport options and enhances the provided mobility services (demand & attractiveness pull). Depending on the local governance, even privately owned or privately shared cars can be part of the model, justified, e.g. in areas where mobility infrastructure deficits loom large or when travel time is too high. This chapter therefore forms the basis for a vision to redesign our mobility ecosystem and marks the beginning of a disrupting system innovation, where integrated sustainability and citizen centricity reshape the nature of mobility.

The AVENUE sustainability assessment integrates the environmental, economic and social assessment of the pilot trials of AVENUE. A step further, it adopts an interdisciplinary approach to conduct the analysis and to better understand the complexity of deploying a new form of mobility in urban areas and as part of the transportation system. The goal is to implement new mobility solutions that benefit the city and complement public transport. The findings from the social, environmental and economic impact assessments are embedded in a multidimensional set of indicators for the sustainability assessment of the automated minibuses. As a result, mobility radars are built to illustrate the assessment of the AVENUE demonstrator sites. The results reveal the state of the art of the current deployment of the automated minibuses in the AVENUE test sites. In addition, this study highlights other crucial elements for a sustainable deployment that rely on the mode of deployment of the automated minibuses, the level of integration to urban public transport or within MaaS perspective and the alignment with the city’s goals, planning and strategies for sustainable mobility. Ultimately, the automated minibuses are an innovative piece within the mobility ecosystem that could support intermodality, MaaS, mobility hubs and the use of soft modes of transport.