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Enhanced spontaneous emission from nanodiamonds with NV centers integrated to silicon nitride photonic structures
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"Repenser la Conception et la Consommation - le Défi d’une Soutenabilité Forte" - Séminaire D-TechnoSS
No full textCette planche synthétise sous forme d’illustrations graphiques les réflexions menées lors de la table ronde “Repenser la Conception et la Consommation - le Défi d’une Soutenabilité Forte” dans le cadre du séminaire D-TechnoSS - 8 juillet 2025.Depuis les années 1970, le rapport Meadows a mis en évidence la crise socio-écologique actuelle. La dernière décennie a vu une prise de conscience collective et la nécessité de lutter contre le changement climatique, ce qui entraîne une mobilisation pour développer des connaissances, des réglementations et des technologies visant à intensifier la décarbonation de la société. En réalité, le changement climatique n’est qu’une des six limites planétaires déjà dépassées aujourd’hui (Richardson et al., 2023 ; Rockström et al., 2009 ; Steffen et al., 2015). La plupart des actions mises en place pour répondre aux défis socio-écologiques restent axées sur des approches techno-centrées et/ou ne remettent pas en question le modèle économique actuel. Ces actions, fondées sur l’économie circulaire, les technologies vertes, l’éco-conception, les modèles économiques traditionnels et les stratégies de décarbonation, demeurent insuffisantes pour relever les défis socio-écologiques mis en évidence par l’économie du donut (Brozovic, 2020 ; de Oliveira Neto et al., 2018 ; Raworth, 2017 ; Vilochani et al., 2024). Il est devenu important de développer de nouvelles démarches de co-construction des solutions soutenables entre les concepteurs et les consommateurs et des modes de consommation plus durables pourraient sans doute favoriser une transition vers une soutenabilité forte. Ce séminaire a pour objectif d’approfondir le concept de soutenabilité forte ainsi que sa relation avec les comportements du consommateur et les produits et services intégrant les enjeux socio-écologiques en conception. Il s'inscrit dans le cadre du projet D-TechnoSS financé par l’ANR et mené par l’Université de Technologie de Troyes, l’École des Mines de Saint-Étienne et l’Université Paris Nanterre. Il vise à développer une meilleure compréhension des mécanismes de changements des comportements afin d'adopter des démarches de co-construction de soutenabilité forte
Towards systemic participatory prototyping of interactive software
No full textInternational audienceWith several planetary limits being exceeded, the problem of the sustainability of IT systems is becoming ever more urgent. From the outset, participatory design (PD) has encouraged end-users to take control of the design of the IT tools they are to use by fostering co-designing and collaborative prototyping, but we increasingly need to attend to the wider ecological and societal influence of the systems it helps create. Systemic design (SD) has been identified as an approach that makes it possible to address issues of strong sustainability by taking into account several scales in all their complexity. This paper therefore frames the methodological question of how participatory design of software tools and systemic design might be combined in a way that keeps participatory prototyping meaningful while bringing systemic concerns into the discussion. Building on Jones& van Patter's four design levels, we discuss the use of PD tools usually meant for interventions at levels 1-2 for supporting levels 3-4 analyses. We identify two research gaps: (1) sustainability-oriented PD rarely make use of SD tools, and (2) relevant SD representations for PD may be too abstract for end-users immersed in contextual prototyping. An exploratory use case provides an initial probe. Five researchers co-created a prototype of a digital travel diary during a workshop and later revisited the concept analyzing rebound effects and causal loops. The insights from these workshops show a potential to inform the design of future workshops where systemic prompts will be included from the start. We contribute two aspects: (1) a level-based perspective that identifies research gaps with respect to methods and tools, and (2) a first exploration, based on a workshop, offering insights into emerging perspectives. Together, these findings outline next steps for developing systemic participatory prototyping at multiple scales
Detection of Mercury Ions at ng/L Scale by Surface Plasmon Resonance (SPR) on DNA Aptamer Biochips
No full textInternational audienceMercury pollution is an important environmental problem due to its toxicity to humans, even at very low concentrations. Presently, several methods enable the detection of this element at environmental concentrations. Although sufficiently sensitive in most cases, measurements are typically made punctually. Here, we present the development of a continuous flow detection system for two mercury forms: the mercuric ion (Hg2+ ) and the methylmercury ion (CH3-Hg+). We used a compact SPR device based on gold chips functionalized with tailored aptamers. Leveraging the specific affinity between DNA aptamers and mercuric ions, this reliable technique allowed the detection of mercuric ion concentrations in the ng/L range. The high sensitivity is attributed to the expected DNA folding into a hairpin shape in the presence of mercuric ions. Circular Dichroism (CD) spectroscopy confirmed that a conformational change in the DNA occurs starting from 3 mercuric ions per aptamer. Below this threshold (1 or 2 ions), the strand does not fold, whereas from 3 ions onward, folding is observed. This study highlights the strong potential of compact SPR associated with specific DNA aptamers for the realization of a portable real-time detection device
Updates on the Advantages and Disadvantages of Microscopic and Spectroscopic Characterization of Magnetotactic Bacteria for Biosensor Applications
No full textInternational audienceMagnetotactic bacteria (MTB), a unique group of Gram-negative prokaryotes, have the remarkable ability to biomineralize magnetic nanoparticles (MNPs) intracellularly, making them promising candidates for various biomedical applications such as biosensors, drug delivery, imaging contrast agents, and cancer-targeted therapies. To fully exploit the potential of MTB, a precise understanding of the structural, surface, and functional properties of these biologically produced nanoparticles is required. Given these concerns, this review provides a focused synthesis of the most widely used microscopic and spectroscopic methods applied in the characterization of MTB and their associated MNPs, covering the latest research from January 2022 to May 2025. Specifically, various optical microscopy techniques (e.g., transmission electron microscopy (TEM), scanning electron microscopy (SEM), and atomic force microscopy (AFM)) and spectroscopic approaches (e.g., localized surface plasmon resonance (LSPR), surface-enhanced Raman scattering (SERS), and X-ray photoelectron spectroscopy (XPS)) relevant to ultrasensitive MTB biosensor development are herein discussed and compared in term of their advantages and disadvantages. Overall, the novelty of this work lies in its clarity and structure, aiming to consolidate and simplify access to the most current and effective characterization techniques. Furthermore, several gaps in the characterization methods of MTB were identified, and new directions of methods that can be integrated into the study, analysis, and characterization of these bacteria are suggested in exhaustive manner. Finally, to the authors’ knowledge, this is the first comprehensive overview of characterization techniques that could serve as a practical resource for both younger and more experienced researchers seeking to optimize the use of MTB in the development of advanced biosensing systems and other biomedical tools
An unsupervised fault detection support system for railway turnouts
No full textInternational audienceContext and motivationsRailway turnouts guide trains between tracks. Due to their complexity, they are inherently prone to faults. Their monitoring is vital for safety and operational efficiency.The increasing digitalization and connectivity of railway infrastructure has led to the generation of large volumes of data, offering new opportunities for the monitoring of turnouts.Manual annotation is not only time-consuming and resource-intensive, requiring input from multiple experts, but also susceptible to human error. This reveals clear limitations of traditional approaches. Key challenges include:Complex systems: Data contains multiple, unidentified normal operating modes. Imbalance: Some operating modes are underrepresented in the dataset. Expensive and unsafe: Manual labeling is intractable due to data scale, complexity, and safety concerns.</div
Minimizing the total completion time for a class of semi-online single machine scheduling problems
No full textInternational audienceSemi-online single machine scheduling problems with information on jobs' processing times and the objective to minimize the total completion time are considered. In these problems, a set of jobs arriving over time are to be scheduled on a single machine and their characteristics become known only upon arrival. Some of the studied problems are shown to have the same competitive ratio as the online problem and online scheduling algorithms can be applied. Given some constraints on the processing times of successive jobs, new lower bounds can be achieved and a new semi-online algorithm, called ϕD-SPT, is presented along with its competitive analysis
Évaluation et modélisation de l'évolution des microstructures vasculaires durant le vieillissement normal et pathologique par utilisation de microtomographie 3D rayon-X synchrotron
No full textInternational audienceVascular aging is characterized by slow, insidious, and asymptomatic alterations of vascular microstructures, such as the elastic lamellae. Nevertheless, the early events forecasting these alterations remain mostly undocumented.To address this critical question, MEDyC uses synchrotron X-ray microcomputed imaging to capture the discrete and fine alterations occurring during the silent phases of the aging process in mouse in normal and pathological conditions. For a single aorta, tomographic volume images of 3948×3948×2048 voxels (voxel size 0.65 µm) are recorded in the thoracic to abdominal region of the aorta. Finding, extracting, and analysing these massive and information-rich data is a considerable challenge. Indeed, they contain a wide range of details at different scales, which induces semantic noise in addition to acquisition noise that may disturb the analysis.We have developed a prototype of a fully automated segmentation approach, able to process the images by relying both on standard image processing paradigms and deep-learning strategies (Siamese networks).We are now able to measure and compare intramural features in aorta from animals experiencing normal (C57Bl6J strain) or pathologic (db/db strain, diabetes) aging.The results obtained so far show that diabetic mice have smoother elastic lamellae than normal mice at the same age. Lamellae from diabetic mice have lost 24.8% of their reserve length. This effect is consistent with the fact that diabetic individuals are hypertensive. Further, we observe a concomitant loss of the lattice-like filamentous structure we have discovered within elastic lamellae.We are currently collecting more data from healthy and diabetic animals (2-24 months, n = 15 for each time point) with the objective of modelling and predicting the evolution of aortic features during aging (ANR MODELAGE project)
Sequential Detection of an Unknown Transient Change Profile by the Finite Moving Average Test
No full textInternational audienceThe paper addresses the sequential transient change detection (TCD) by using the finite moving average (FMA) test. Unlike the conventional quickest change detection, which assumes that the post-change period is infinitely long, sometimes it is necessary to detect a change with an \emph{a priori} upper-bounded (usually short) detection delay. All detections that exceed the required time to alert are assumed missed. We relax the assumption that the profile of a transient change is known. New versions of the FMA test are designed by using the generalized likelihood ratio (GLR) test in the Gaussian mean case. A Gaussian linear model with transient changes and nuisance parameters is also considered. These new quadratic FMA tests are compared to each other and with the FMA test based on the \emph{a priori} known transient change profile by their operating characteristics
How much is the Source Mismatch an Important Problem for Deepfake Detection ? *
No full textInternational audienceOver the past few decades, AI generative methods have advanced significantly, making it increasingly challenging to distinguish genuine photographs from AI-generated images, sometimes also referred to as deepfakes. In response, numerous deepfake detection methods and models have been developed, achieving high accuracy. However, the evaluation of these detection methods is often limited to a single dataset, which is typically created by generating multiple images using a specific deepfake generation methods and a fixed set of hyperparameters. This dataset is then randomly split into training and testing sets, but such an approach cannot take into account the variations of hyperparameters on deepfake detection performance. This paper addresses the fundamental question of source mismatch, where a model is trained on a specific deepfake generation source (including hyperparameters) and tested on a different one, highlighting the need to investigate the causes and impacts of such a mismatch as well as to develop solutions to this critical issue.</div