Issy Media (France)

The current deployment of mega-constellations of telecommunication satellites in low Earth orbit is paving the way for global broadband connectivity and offers prospects for the Internet of Things, Earth observation and defence applications. However, the significant increase in the number of satellites in orbit, operating in the same frequency bands at these altitudes increases interference. In this paper, one analytical algorithm and one deep learning algorithm for low Earth orbit satellite interference detection tasks are introduced. These solutions are developed and tested on realistic synthetic data, using a customized orbital simulator. The proposed methods demonstrate promising performance, combining low computational complexity with high detection accuracy compared to state-of-the-art methods.

Traditional device fingerprinting methods primarily rely on data-intensive deep learning models, treating devices as black boxes. However, these approaches suffer from high computational complexity and sensitivity to noise, making them impractical for large-scale Internet-of-Things (IoT) deployments that demand real-time processing and energy efficiency. To address these challenges, we propose a physics-based fingerprinting model for optical wireless communication (OWC) systems. Instead of relying solely on statistical features, small yet significant non-linear response variations in LEDs are quantified as lumped parameters in an equivalent circuit model, serving as the foundation for physical fingerprint features. This physics-based fingerprint is not only interpretable but also enables compact feature representation, reducing reliance on extensive training data. Experimental results demonstrate that our method achieves an average classification accuracy of 90.88% under varying signal-to-noise ratio (SNR) conditions. Furthermore, compared to convolutional neural network (CNN) and long short-term memory (LSTM)-based models, our approach achieves higher accuracy with significantly lower computational overhead, making it particularly well-suited for resource-constrained IoT environments. By reducing both dataset dimensionality and training sample requirements, our framework provides an efficient and scalable solution for device authentication in OWC networks.

Introduction: Addressing the challenges in diabetic foot ulcer (DFU) management is critical, given the high morbidity, mortality, and healthcare costs associated with this devastating complication of diabetes. This study introduces an innovative strategy for DFU risk stratification using Electrochemical Skin Conductance (ESC) measurements from the Sudoscan device. It is a quick, non-invasive, painless, reproducible technique that does not require fasting or stopping treatment. Methods: The study involved 2157 diabetic patients from four French hospitals, evaluating the association between ESC measures and DFU risk stratification scores based on 10g monofilament testing. Results: Multivariate analysis affirmed the association, independently of others covariate (age, sex), between the ESC and the DFU grades. ROC curve analysis demonstrated good predictive power for DFU grades 3, 2, and 1 (AUC=0.82/0.62/0.62.) but revealed limitations for grade 0 (AUC=0.34) due to the wide range of ESC values. Heatmap analysis showcased ESC's granularity within low-grade patients, suggesting potential subgroups not captured by the standard grading system. Conclusion: With a quantifiable association between ESC measures and high DFU grades while revealing differences for low DFU grade, this approach offers an avenue for improving precision in risk assessment at early and reversible diabetic peripheral neuropathy stages therefore fostering early clinical intervention. Healthcare Equity: The standardized and objective nature of ESC measurements while having a low cost contributes to more equitable healthcare delivery. By reducing disparities in risk identification, this approach ensures consistent and accurate assessments, regardless of geographical location or healthcare provider. Disclosure B. Vittrant: Employee; Withings. J. Gautier: Board Member; Sanofi. Other Relationship; Sanofi. Speaker's Bureau; AstraZeneca, Novo Nordisk. Research Support; Novo Nordisk. Advisory Panel; Pfizer Inc. J. Riveline: Board Member; Abbott, Novo Nordisk A/S, Sanofi, Eli Lilly and Company, Medtronic, Dexcom, Inc., Insulet Corporation, Air Liquide, AstraZeneca. L. Potier: Research Support; Abbott. Consultant; AstraZeneca, Bayer Inc., Eli Lilly and Company, Novo Nordisk, Sanofi, Boehringer-Ingelheim. O. Bourron: Speaker's Bureau; Novo Nordisk, Sanofi, Lilly Diabetes, AstraZeneca, Bayer Inc. Research Support; Withings. P. Brunswick: Consultant; Impeto medical. B. Bauduceau: Consultant; Lilly Diabetes, Boehringer-Ingelheim, AstraZeneca. A. Criton: Employee; Withings.

À partir d’une séance de consultation unique avec une jeune femme évoquant son frère jumeau, les auteurs soulignent les entraves notamment mélancoliques du travail de séparation dans le contexte de la fin d’adolescence, ouvrant sur un dégagement vis-à-vis des objets d’amour primaire. Ce mouvement d’ensemble est souvent nommé sommairement « séparation » ; nous interrogeons par rebond le sens de ce terme, utilisé comme un mot bouchon amenant l’illusion d’une compréhension commune, immédiate et précise, pour lui substituer l’expression de différenciation/personnalisation.

Cultural policies can be a strategic key to shaping more inclusive and sustainable urban regeneration processes, especially exploiting the acceleration promoted through transition dynamics. The City of Issy-les-Moulineaux, for its recent and deep investment in culture, sustainability and innovation in a non-conflictual and socially homogeneous urban dense context, is a valuable demonstrator of the role and forms in which institutional cultural policies at the urban scale can produce a shift of values, acceleration or simplification of decision-making processes towards inclusive and sustainable ways of life. The presentation of examples of cultural policies and regeneration programmes aims to contribute to the identification of some innovation trajectories in this direction, looking especially at the management of cultural policies or spaces and their flexibility and openness to inhabitants. Conclusions sketch the potential of strengthening some regime-niche traits of cultural policies in Issy and creating a permanent experimental environment in the governance (and approach) to cultural policies that reshape from rigid to fluid, thus increasing the anti-fragile nature of public policies and practices.

Abstract Introduction: Breast cancer (BC) has particular characteristics in young women, with diagnosis at more advanced stages, a poorer prognosis and highly aggressive tumors. In NeoFit, we will use an activity tracker to identify and describe various digital profiles (heart rate, physical activity, and sleep patterns) in women below the age of 45 years on neoadjuvant chemotherapy for BC.Methods/Analysis: NeoFit is a prospective, national, multicenter, single-arm open-label study. It will include 300 women below the age of 45 years treated with neoadjuvant chemotherapy for BC. Participants will be asked to wear a Withing Steel HR activity tracker round the clock for 12 months. The principal assessments will be performed at baseline, at the end of neoadjuvant chemotherapy and at 12 months. We will evaluate clinical parameters, such as toxicity and the efficacy of chemotherapy, together with quality of life, fatigue, and parameters relating to lifestyle and physical activity. The women will complete REDCap form questionnaires via a secure internet link.Discussion: In this study, the use of an activity tracker will enable us to visualize changes in the lifestyle of young women on neoadjuvant chemotherapy for BC, over the course of a one-year period. This exploratory study will provide crucial insight into the digital phenotypes of young BC patients on neoadjuvant chemotherapy and the relationship between these phenotypes and the toxicity and efficacy of treatment. This trial will pave the way for interventional studies involving sleep and physical activity interventions. Citation Format: Lidia Delrieu, Anne-Sophie Hamy, Florence Coussy, Amyn Kassara, Bernard Asselain, Juliana Antero, Paul De Villèle, Elise Dumas, Nicolas Forstmann, Julien Guérin, Judicael Hotton, Christelle Jouannaud, Maud Milder, Armand Leopold, Adrien Sedeaud, Pauline Soibinet, Jean-François Toussaint, Vincent Vercamer, Enora Laas, Fabien Reyal. Digital phenotyping in young breast cancer patients treated with neoadjuvant chemotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr CT231.