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3,285 results on '"Geraud A"'

1. Rupture of an aneurysm of the gastroduodenal artery mimicking a tumor of the head of the pancreas in a case report.

Author

Geraud Akpo, MD, Ahma Dia, MD, Nfally Badji, MD, Hamidou Deme, Boucar Ndong, Marcel Mbarga, Ibrahima Niang, Abdoulaye Dione Diop, Sokhna Ba, and El hadji Niang

Subjects
Aneurysm, Gastruodenal, Rupture, Medical physics. Medical radiology. Nuclear medicine, R895-920
Abstract

Gastroduodenal artery aneurysms have a low incidence of less than 1.5% of all splanchnic aneurysms. Rupture is frequent and life-threatening. The diagnosis is made by CT scan and by coeliac angiography, which also plays a therapeutic role in stable or stabilized patients. Surgery remains the treatment of choice in case of hemodynamic instability. We reviewed the case of a ruptured aneurysm of the gastroduodenal artery mimicking a tumor of the pancreas’ head in a patient who died following a hemorrhagic shock.

Published
2022
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2. Building a Scalable, Effective, and Steerable Search and Ranking Platform

Author

Celikik, Marjan, Wasilewski, Jacek, Ramallo, Ana Peleteiro, Kurennoy, Alexey, Labzin, Evgeny, Ascione, Danilo, Gurbanov, Tural, Falher, Géraud Le, Dzhoha, Andrii, and Harris, Ian

Subjects
Computer Science - Information Retrieval, Computer Science - Machine Learning
Abstract

Modern e-commerce platforms offer vast product selections, making it difficult for customers to find items that they like and that are relevant to their current session intent. This is why it is key for e-commerce platforms to have near real-time scalable and adaptable personalized ranking and search systems. While numerous methods exist in the scientific literature for building such systems, many are unsuitable for large-scale industrial use due to complexity and performance limitations. Consequently, industrial ranking systems often resort to computationally efficient yet simplistic retrieval or candidate generation approaches, which overlook near real-time and heterogeneous customer signals, which results in a less personalized and relevant experience. Moreover, related customer experiences are served by completely different systems, which increases complexity, maintenance, and inconsistent experiences. In this paper, we present a personalized, adaptable near real-time ranking platform that is reusable across various use cases, such as browsing and search, and that is able to cater to millions of items and customers under heavy load (thousands of requests per second). We employ transformer-based models through different ranking layers which can learn complex behavior patterns directly from customer action sequences while being able to incorporate temporal (e.g. in-session) and contextual information. We validate our system through a series of comprehensive offline and online real-world experiments at a large online e-commerce platform, and we demonstrate its superiority when compared to existing systems, both in terms of customer experience as well as in net revenue. Finally, we share the lessons learned from building a comprehensive, modern ranking platform for use in a large-scale e-commerce environment.

Published
2024

3. TL properties of RE-Doped and Co-doped Sol-gel Silica Rods. Application to Passive (OSL) and Real-time (RL) Dosimetry

Author

Benabdesselam, Mourad, Bahout, J., Mady, Franck, Blanc, Wilfried, Hamzaoui, Hicham El, Cassez, Andy, Delplace-Baudelle, Karen, Habert, Remi, Bouwmans, Geraud, Bouazaoui, Mohamed, and Capoen, Bruno

Subjects
Physics - Optics
Abstract

Two rods made from sol-gel silica have been doped with Ce ions or co-doped with Ce and Tb ions respectively. First, a thermoluminescence (TL) characterization of the trapping and luminescence parameters is carried out to understand the physical mechanisms involved following the irradiation of these rods and to evaluate their dosimetric properties. The optically stimulated luminescence (OSL) and the radioluminescence (RL) responses as a function of respectively absorbed dose and dose rate are assessed. The OSL response of both rods is linear as a function of the absorbed dose. The RL sensitivity of both rods proves not only to be extremely high but also shows a linear behavior over more than 6 decades, allowing real-time detection of dose rates as low as few $\mu$Gy s$^{-1}$, a threshold that to our knowledge, has never been reached. The results from RL and OSL show that these silica-based doped rods are potentially suitable for medical dosimetry and environmental monitoring around nuclear sites.

Published
2024
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4. HYBRINFOX at CheckThat! 2024 -- Task 1: Enhancing Language Models with Structured Information for Check-Worthiness Estimation

Author

Faye, Géraud, Casanova, Morgane, Icard, Benjamin, Chanson, Julien, Gadek, Guillaume, Gravier, Guillaume, and Égré, Paul

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract

This paper summarizes the experiments and results of the HYBRINFOX team for the CheckThat! 2024 - Task 1 competition. We propose an approach enriching Language Models such as RoBERTa with embeddings produced by triples (subject ; predicate ; object) extracted from the text sentences. Our analysis of the developmental data shows that this method improves the performance of Language Models alone. On the evaluation data, its best performance was in English, where it achieved an F1 score of 71.1 and ranked 12th out of 27 candidates. On the other languages (Dutch and Arabic), it obtained more mixed results. Future research tracks are identified toward adapting this processing pipeline to more recent Large Language Models., Comment: Paper to appear in the Proceedings of the Conference and Labs of the Evaluation Forum (CLEF 2024 CheckThat!)

Published
2024

5. HYBRINFOX at CheckThat! 2024 -- Task 2: Enriching BERT Models with the Expert System VAGO for Subjectivity Detection

Author

Casanova, Morgane, Chanson, Julien, Icard, Benjamin, Faye, Géraud, Gadek, Guillaume, Gravier, Guillaume, and Égré, Paul

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract

This paper presents the HYBRINFOX method used to solve Task 2 of Subjectivity detection of the CLEF 2024 CheckThat! competition. The specificity of the method is to use a hybrid system, combining a RoBERTa model, fine-tuned for subjectivity detection, a frozen sentence-BERT (sBERT) model to capture semantics, and several scores calculated by the English version of the expert system VAGO, developed independently of this task to measure vagueness and subjectivity in texts based on the lexicon. In English, the HYBRINFOX method ranked 1st with a macro F1 score of 0.7442 on the evaluation data. For the other languages, the method used a translation step into English, producing more mixed results (ranking 1st in Multilingual and 2nd in Italian over the baseline, but under the baseline in Bulgarian, German, and Arabic). We explain the principles of our hybrid approach, and outline ways in which the method could be improved for other languages besides English., Comment: To appear in the Proceedings of the Conference and Labs of the Evaluation Forum (CLEF 2024 CheckThat!)

Published
2024

6. RobocupGym: A challenging continuous control benchmark in Robocup

Author

Beukman, Michael, Ingram, Branden, Tasse, Geraud Nangue, Rosman, Benjamin, and Ranchod, Pravesh

Subjects
Computer Science - Robotics, Computer Science - Machine Learning
Abstract

Reinforcement learning (RL) has progressed substantially over the past decade, with much of this progress being driven by benchmarks. Many benchmarks are focused on video or board games, and a large number of robotics benchmarks lack diversity and real-world applicability. In this paper, we aim to simplify the process of applying reinforcement learning in the 3D simulation league of Robocup, a robotic football competition. To this end, we introduce a Robocup-based RL environment based on the open source rcssserver3d soccer server, simple pre-defined tasks, and integration with a popular RL library, Stable Baselines 3. Our environment enables the creation of high-dimensional continuous control tasks within a robotics football simulation. In each task, an RL agent controls a simulated Nao robot, and can interact with the ball or other agents. We open-source our environment and training code at https://github.com/Michael-Beukman/RobocupGym.

Published
2024

7. Contextual Counting: A Mechanistic Study of Transformers on a Quantitative Task

Author

Golkar, Siavash, Bietti, Alberto, Pettee, Mariel, Eickenberg, Michael, Cranmer, Miles, Hirashima, Keiya, Krawezik, Geraud, Lourie, Nicholas, McCabe, Michael, Morel, Rudy, Ohana, Ruben, Parker, Liam Holden, Blancard, Bruno Régaldo-Saint, Cho, Kyunghyun, and Ho, Shirley

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Statistics - Machine Learning
Abstract

Transformers have revolutionized machine learning across diverse domains, yet understanding their behavior remains crucial, particularly in high-stakes applications. This paper introduces the contextual counting task, a novel toy problem aimed at enhancing our understanding of Transformers in quantitative and scientific contexts. This task requires precise localization and computation within datasets, akin to object detection or region-based scientific analysis. We present theoretical and empirical analysis using both causal and non-causal Transformer architectures, investigating the influence of various positional encodings on performance and interpretability. In particular, we find that causal attention is much better suited for the task, and that no positional embeddings lead to the best accuracy, though rotary embeddings are competitive and easier to train. We also show that out of distribution performance is tightly linked to which tokens it uses as a bias term.

Published
2024

8. Tomography of a single-atom-resolved detector in the presence of shot-to-shot number fluctuations

Author

Allemand, Maxime, Jannin, Raphael, Dupuy, Géraud, Bureik, Jan-Philipp, Pezzè, Luca, Boiron, Denis, and Clément, David

Subjects
Condensed Matter - Quantum Gases, Physics - Atomic Physics, Quantum Physics
Abstract

Tomography of single-particle-resolved detectors is of primary importance for characterizing particle correlations with applications in quantum metrology, quantum simulation and quantum computing. However, it is a non-trivial task in practice due to the unavoidable presence of noise that affects the measurement but does not originate from the detector. In this work, we address this problem for a three-dimensional single-atom-resolved detector where shot-to-shot atom number fluctuations are a central issue to perform a quantum detector tomography. We overcome this difficulty by exploiting the parallel measurement of counting statistics in sub-volumes of the detector, from which we evaluate the effect of shot-to-shot fluctuations and perform a local tomography of the detector. In addition, we illustrate the validity of our method from applying it to Gaussian quantum states with different number statistics. Finally, we show that the response of Micro-Channel Plate detectors is well-described from using a binomial distribution with the detection efficiency as a single parameter., Comment: 7 pages, 5 figures

Published
2024

10. Weakly Supervised Training for Hologram Verification in Identity Documents

Author

Pouliquen, Glen, Chiron, Guillaume, Chazalon, Joseph, Géraud, Thierry, and Awal, Ahmad Montaser

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

We propose a method to remotely verify the authenticity of Optically Variable Devices (OVDs), often referred to as ``holograms'', in identity documents. Our method processes video clips captured with smartphones under common lighting conditions, and is evaluated on two public datasets: MIDV-HOLO and MIDV-2020. Thanks to a weakly-supervised training, we optimize a feature extraction and decision pipeline which achieves a new leading performance on MIDV-HOLO, while maintaining a high recall on documents from MIDV-2020 used as attack samples. It is also the first method, to date, to effectively address the photo replacement attack task, and can be trained on either genuine samples, attack samples, or both for increased performance. By enabling to verify OVD shapes and dynamics with very little supervision, this work opens the way towards the use of massive amounts of unlabeled data to build robust remote identity document verification systems on commodity smartphones. Code is available at https://github.com/EPITAResearchLab/pouliquen.24.icdar, Comment: Accepted at the International Conference on Document Analysis and Recognition (ICDAR 2024)

Published
2024

11. A Multi-Label Dataset of French Fake News: Human and Machine Insights

Author

Icard, Benjamin, Maine, François, Casanova, Morgane, Faye, Géraud, Chanson, Julien, Gadek, Guillaume, Atemezing, Ghislain, Bancilhon, François, and Égré, Paul

Subjects
Computer Science - Computation and Language, Computer Science - Machine Learning
Abstract

We present a corpus of 100 documents, OBSINFOX, selected from 17 sources of French press considered unreliable by expert agencies, annotated using 11 labels by 8 annotators. By collecting more labels than usual, by more annotators than is typically done, we can identify features that humans consider as characteristic of fake news, and compare them to the predictions of automated classifiers. We present a topic and genre analysis using Gate Cloud, indicative of the prevalence of satire-like text in the corpus. We then use the subjectivity analyzer VAGO, and a neural version of it, to clarify the link between ascriptions of the label Subjective and ascriptions of the label Fake News. The annotated dataset is available online at the following url: https://github.com/obs-info/obsinfox Keywords: Fake News, Multi-Labels, Subjectivity, Vagueness, Detail, Opinion, Exaggeration, French Press, Comment: Paper to appear in the Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)

Published
2024

12. Exposing propaganda: an analysis of stylistic cues comparing human annotations and machine classification

Author

Faye, Géraud, Icard, Benjamin, Casanova, Morgane, Chanson, Julien, Maine, François, Bancilhon, François, Gadek, Guillaume, Gravier, Guillaume, and Égré, Paul

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

This paper investigates the language of propaganda and its stylistic features. It presents the PPN dataset, standing for Propagandist Pseudo-News, a multisource, multilingual, multimodal dataset composed of news articles extracted from websites identified as propaganda sources by expert agencies. A limited sample from this set was randomly mixed with papers from the regular French press, and their URL masked, to conduct an annotation-experiment by humans, using 11 distinct labels. The results show that human annotators were able to reliably discriminate between the two types of press across each of the labels. We propose different NLP techniques to identify the cues used by the annotators, and to compare them with machine classification. They include the analyzer VAGO to measure discourse vagueness and subjectivity, a TF-IDF to serve as a baseline, and four different classifiers: two RoBERTa-based models, CATS using syntax, and one XGBoost combining syntactic and semantic features., Comment: Paper to appear in the EACL 2024 Proceedings of the Third Workshop on Understanding Implicit and Underspecified Language (UnImplicit 2024)

Published
2024

13. Counting Reward Automata: Sample Efficient Reinforcement Learning Through the Exploitation of Reward Function Structure

Author

Bester, Tristan, Rosman, Benjamin, James, Steven, and Tasse, Geraud Nangue

Subjects
Computer Science - Artificial Intelligence, I.2, F.4
Abstract

We present counting reward automata-a finite state machine variant capable of modelling any reward function expressible as a formal language. Unlike previous approaches, which are limited to the expression of tasks as regular languages, our framework allows for tasks described by unrestricted grammars. We prove that an agent equipped with such an abstract machine is able to solve a larger set of tasks than those utilising current approaches. We show that this increase in expressive power does not come at the cost of increased automaton complexity. A selection of learning algorithms are presented which exploit automaton structure to improve sample efficiency. We show that the state machines required in our formulation can be specified from natural language task descriptions using large language models. Empirical results demonstrate that our method outperforms competing approaches in terms of sample efficiency, automaton complexity, and task completion., Comment: 14 pages, 11 Figures, Published in AAAI W25: Neuro-Symbolic Learning and Reasoning in the era of Large Language Models (NuCLeaR)

Published
2023

15. AstroCLIP: A Cross-Modal Foundation Model for Galaxies

Author

Parker, Liam, Lanusse, Francois, Golkar, Siavash, Sarra, Leopoldo, Cranmer, Miles, Bietti, Alberto, Eickenberg, Michael, Krawezik, Geraud, McCabe, Michael, Ohana, Ruben, Pettee, Mariel, Blancard, Bruno Regaldo-Saint, Tesileanu, Tiberiu, Cho, Kyunghyun, and Ho, Shirley

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

We present AstroCLIP, a single, versatile model that can embed both galaxy images and spectra into a shared, physically meaningful latent space. These embeddings can then be used - without any model fine-tuning - for a variety of downstream tasks including (1) accurate in-modality and cross-modality semantic similarity search, (2) photometric redshift estimation, (3) galaxy property estimation from both images and spectra, and (4) morphology classification. Our approach to implementing AstroCLIP consists of two parts. First, we embed galaxy images and spectra separately by pretraining separate transformer-based image and spectrum encoders in self-supervised settings. We then align the encoders using a contrastive loss. We apply our method to spectra from the Dark Energy Spectroscopic Instrument and images from its corresponding Legacy Imaging Survey. Overall, we find remarkable performance on all downstream tasks, even relative to supervised baselines. For example, for a task like photometric redshift prediction, we find similar performance to a specifically-trained ResNet18, and for additional tasks like physical property estimation (stellar mass, age, metallicity, and sSFR), we beat this supervised baseline by 19\% in terms of $R^2$. We also compare our results to a state-of-the-art self-supervised single-modal model for galaxy images, and find that our approach outperforms this benchmark by roughly a factor of two on photometric redshift estimation and physical property prediction in terms of $R^2$, while remaining roughly in-line in terms of morphology classification. Ultimately, our approach represents the first cross-modal self-supervised model for galaxies, and the first self-supervised transformer-based architectures for galaxy images and spectra., Comment: 18 pages, accepted in Monthly Notices of the Royal Astronomical Society, Presented at the NeurIPS 2023 AI4Science Workshop

Published
2023
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16. Multiple Physics Pretraining for Physical Surrogate Models

Author

McCabe, Michael, Blancard, Bruno Régaldo-Saint, Parker, Liam Holden, Ohana, Ruben, Cranmer, Miles, Bietti, Alberto, Eickenberg, Michael, Golkar, Siavash, Krawezik, Geraud, Lanusse, Francois, Pettee, Mariel, Tesileanu, Tiberiu, Cho, Kyunghyun, and Ho, Shirley

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Statistics - Machine Learning
Abstract

We introduce multiple physics pretraining (MPP), an autoregressive task-agnostic pretraining approach for physical surrogate modeling of spatiotemporal systems with transformers. In MPP, rather than training one model on a specific physical system, we train a backbone model to predict the dynamics of multiple heterogeneous physical systems simultaneously in order to learn features that are broadly useful across systems and facilitate transfer. In order to learn effectively in this setting, we introduce a shared embedding and normalization strategy that projects the fields of multiple systems into a shared embedding space. We validate the efficacy of our approach on both pretraining and downstream tasks over a broad fluid mechanics-oriented benchmark. We show that a single MPP-pretrained transformer is able to match or outperform task-specific baselines on all pretraining sub-tasks without the need for finetuning. For downstream tasks, we demonstrate that finetuning MPP-trained models results in more accurate predictions across multiple time-steps on systems with previously unseen physical components or higher dimensional systems compared to training from scratch or finetuning pretrained video foundation models. We open-source our code and model weights trained at multiple scales for reproducibility.

Published
2023

17. xVal: A Continuous Numerical Tokenization for Scientific Language Models

Author

Golkar, Siavash, Pettee, Mariel, Eickenberg, Michael, Bietti, Alberto, Cranmer, Miles, Krawezik, Geraud, Lanusse, Francois, McCabe, Michael, Ohana, Ruben, Parker, Liam, Blancard, Bruno Régaldo-Saint, Tesileanu, Tiberiu, Cho, Kyunghyun, and Ho, Shirley

Subjects
Statistics - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Computation and Language, Computer Science - Machine Learning
Abstract

Due in part to their discontinuous and discrete default encodings for numbers, Large Language Models (LLMs) have not yet been commonly used to process numerically-dense scientific datasets. Rendering datasets as text, however, could help aggregate diverse and multi-modal scientific data into a single training corpus, thereby potentially facilitating the development of foundation models for science. In this work, we introduce xVal, a strategy for continuously tokenizing numbers within language models that results in a more appropriate inductive bias for scientific applications. By training specially-modified language models from scratch on a variety of scientific datasets formatted as text, we find that xVal generally outperforms other common numerical tokenization strategies on metrics including out-of-distribution generalization and computational efficiency., Comment: 15 pages, 12 figures. Appendix: 8 pages, 2 figures. Accepted contribution at the NeurIPS Workshop on ML for the Physical Sciences

Published
2023

18. ROSARL: Reward-Only Safe Reinforcement Learning

Author

Tasse, Geraud Nangue, Love, Tamlin, Nemecek, Mark, James, Steven, and Rosman, Benjamin

Subjects
Computer Science - Machine Learning
Abstract

An important problem in reinforcement learning is designing agents that learn to solve tasks safely in an environment. A common solution is for a human expert to define either a penalty in the reward function or a cost to be minimised when reaching unsafe states. However, this is non-trivial, since too small a penalty may lead to agents that reach unsafe states, while too large a penalty increases the time to convergence. Additionally, the difficulty in designing reward or cost functions can increase with the complexity of the problem. Hence, for a given environment with a given set of unsafe states, we are interested in finding the upper bound of rewards at unsafe states whose optimal policies minimise the probability of reaching those unsafe states, irrespective of task rewards. We refer to this exact upper bound as the "Minmax penalty", and show that it can be obtained by taking into account both the controllability and diameter of an environment. We provide a simple practical model-free algorithm for an agent to learn this Minmax penalty while learning the task policy, and demonstrate that using it leads to agents that learn safe policies in high-dimensional continuous control environments.

Published
2023

19. Diagnostic tomodensitométrique d'une hernie de Spiegel étranglée: à propos d'une observation

Author

Geraud Akpo, Hamidou Deme, Nfally Badji, Fallou Niang, Mohamadou Toure, Ibrahima Niang, Malick Diouf, and El Hadj Niang

Subjects
hernie spiegel, tomodensitométrie, étranglement, Medicine
Abstract

Nous rapportons un cas de hernie de Spiegel compliquée d'occlusion chez une femme de 86 ans dont le diagnostic a été posé à la tomodensitométrie. Elle avait consulté aux urgences chirurgicales pour des douleurs de la fosse iliaque droite d'apparitions brutales associées à des vomissements. L'examen physique a retrouvé une patiente fébrile (38,2), une masse localisée à la fosse iliaque droite ferme, sensible et mobile par rapport aux deux plans. La tomodensitométrie abdominale avait objectivé au niveau de la fosse iliaque droite, en avant de l'aponévrose du muscle oblique externe, un sac herniaire avec un collet mesuré à 13 mm .Il contenait de la graisse et une anse grêle en arceau présentant deux zones de transition donnant un aspect de double bec au niveau du collet. La paroi de l'anse incarcérée ne se rehaussait pas après injection de produit de contraste. Le diagnostic de hernie de spiegel étranglée avec signe d'ischémie artérielle de la paroi digestive a été retenu. Le traitement a été chirurgical avec des suites opératoires simples

Published
2016
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20. Diagnostic scanographique d'une hernie inguino-scrotale de la vessie à propos d'un cas

Author

Nfally Badji, Hamidou Deme, Geraud Akpo, Mouhamadou Toure, Boucar Ndong, and El Hadji Niang

Subjects
vessie, hernie inguino-scrotale, tdm, Medicine
Abstract

Nous rapportons le cas d'un patient âgé de 67 ans aux antécédents de cure de hernie inguinale, qui présentait une grosse bourse indolore évoluant depuis plusieurs mois associée à des troubles urinaires à type de pollakiurie. L'échographie avait permis de mettre en évidence une vacuité de la loge vésicale, une stase urinaire et une collection liquide dans le scrotum qui faisait évoquer une hydrocèle. La TDM abdomino-pelvienne a mis en évidence une vessie en situation intra scrotale droite associée à une hernie inguinale gauche directe et à une stase urinaire bilatérale. Le diagnostic a été confirmé par l'exploration chirurgicale. Les suites opératoires étaient simples. La hernie inguinoscrotale à contenu exclusivement vésical est une entité exceptionnelle. La TDM doit être demandée devant toute hernie inguinoscrotale associée à des troubles urinaires ( Mery's Sign ).

Published
2016
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21. Apport de l'IRM dans la prise en charge des compressions médullaires lentes non traumatiques

Author

Nfally Badji, Hamidou Deme, Geraud Akpo, Boucar Ndong, Mouhamadou Hamine Toure, Sokhna Ba Diop, and El Hadji Niang

Subjects
irm, compressions médullaires lentes, épidurites infectieuses, épidurites métastatiques, Medicine
Abstract

Les compressions médullaires lentes sont dues au développement dans le canal médullaire d'une lésion expansive. C'est une pathologie très fréquente dont le diagnostic est essentiellement clinique. L'imagerie par résonnance magnétique occupe une place incontournable dans le diagnostic de localisation et la recherche étiologique. En Europe l'étiologie tumorale est prépondérante. Le but de cette étude était de décrire les aspects IRM des compressions médullaires lentes et de déterminer le profil étiologique. Il d'une étude rétrospective portant sur 97 observations colligées au service de radiologie du CHUN de Fann sur une période de 30 mois (du 08/03/10 au 29/09/12). On été inclus dans l'étude, tous les patients adressés pour un tableau de compression médullaire lente survenu dans un contexte non traumatique. L'âge moyen des patients était de 42,6 ans avec des extrêmes compris entre 04 mois et 85 ans. Nous avons étudié la topographie des lésions (étage rachidien, compartiments canalaires) leur rehaussement et les critères d'orientation étiologique. Le protocole d'examen permettait la réalisation de séquence pondérées T1 sans avec injection de gado, T2, STIR et T2 DRIVE centrées sur les niveaux lésionnels ou les zones suspectes. L'IRM a permis de préciser le siège exact et l'étendue des lésions. L'atteinte du rachis dorsal représentait 42% des cas, suivi du rachis cervical avec 32% des cas. Les atteintes lombo-sacrées et pluri-étagées représentaient respectivement 18% et 08% des cas. Les lésions extradurales représentaient 87% des cas, suivi des lésions intradurales extramédullaires avec 08% des cas et des lésions intramédullaires dans 05% des cas. La particularité du profil étiologique de notre étude est la prédominance des épidurites infectieuses et la fréquence relative des épidurites métastatiques comparée aux séries occidentales. L'RM vertébro-médullaire occupe une place capitale dans le diagnostic positif, topographique et étiologique des compressions médullaires.

Published
2016
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23. A forensic analysis of the Google Home: repairing compressed data without error correction

Author

Barral, Hadrien, Jaloyan, Georges-Axel, Thomas-Brans, Fabien, Regnery, Matthieu, Géraud-Stewart, Rémi, Heckmann, Thibaut, Souvignet, Thomas, and Naccache, David

Subjects
Computer Science - Cryptography and Security, Computer Science - Information Retrieval
Abstract

This paper provides a detailed explanation of the steps taken to extract and repair a Google Home's internal data. Starting with reverse engineering the hardware of a commercial off-the-shelf Google Home, internal data is then extracted by desoldering and dumping the flash memory. As error correction is performed by the CPU using an undisclosed method, a new alternative method is shown to repair a corrupted SquashFS filesystem, under the assumption of a single or double bitflip per gzip-compressed fragment. Finally, a new method to handle multiple possible repairs using three-valued logic is presented., Comment: 28 pages, modified version of paper that appeared originally at Forensic Science International: Digital Investigation

Published
2022
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24. Optical properties of SiV and GeV color centers in nanodiamonds under hydrostatic pressures up to 180 GPa

Author

Vindolet, Baptiste, Adam, Marie-Pierre, Toraille, Loïc, Chipaux, Mayeul, Hilberer, Antoine, Dupuy, Géraud, Razinkovas, Lukas, Alkauskas, Audrius, Thiering, Gergő, Gali, Adam, De Feudis, Mary, Ngambou, Midrel Wilfried Ngandeu, Achard, Jocelyn, Tallaire, Alexandre, Schmidt, Martin, Becher, Christoph, and Roch, Jean-François

Subjects
Quantum Physics, Condensed Matter - Materials Science
Abstract

We investigate the optical properties of silicon-vacancy (SiV) and germanium-vacancy (GeV) color centers in nanodiamonds under hydrostatic pressure up to 180 GPa. The nanodiamonds were synthetized by Si or Ge-doped plasma assisted chemical vapor deposition and, for our experiment, pressurized in a diamond anvil cell. Under hydrostatic pressure we observe blue-shifts of the SiV and GeV zero-phonon lines by 17 THz (70 meV) and 78 THz (320 meV), respectively. These measured pressure induced shifts are in good agreement with ab initio calculations that take into account the lattice compression based on the equation of state of diamond and that are extended to the case of the tin-vacancy (SnV) center. This work provides guidance on the use of group-IV-vacancy centers as quantum sensors under extreme pressures that will exploit their specific optical and spin properties induced by their intrinsic inversion-symmetric structure., Comment: 7 pages, 4 figures

Published
2022
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26. Long Covid: a global health issue – a prospective, cohort study set in four continents

Author

Synne Jenum, Renaud Tamisier, Clark D Russell, Rachel Evans, Piero Valentini, Sylvain Diamantis, Dominique Deplanque, Jordi Rello, Agnes Meybeck, Maxime Hentzien, Clotilde Allavena, André Cabié, Firouzé Bani-Sadr, Patrick Rossignol, Lionel Piroth, Mathieu Blot, Marie-Pierre Debray, François Angoulvant, Marc Leone, Ewen M Harrison, Maria Zambon, Michael Edelstein, Florentia Kaguelidou, Marc Lambert, Olivier Lairez, Tom Solomon, Carrol Gamble, Laura Marsh, Christiana Kartsonaki, Natalie Wright, Behzad Nadjm, Srinivas Murthy, Gail Carson, Jake Dunning, Laura Merson, Peter Horby, Timothy M Uyeki, Piero Olliaro, Guillermo Maestro de la Calle, Stephen R Knight, Thomas M Drake, Marlene Murris, Aurore Bousquet, Kenneth A McLean, Hugues Cordel, Marc Fabre, Laurence Bouillet, Katrina Hann, Xavier Duval, James Lee, Christian Rabaud, Paul Klenerman, Jean-Christophe Lucet, Jean-François Timsit, Jennifer Lee, David J Lowe, Nicolas Terzi, Saad Nseir, Gwenhaël Colin, Steve Webb, Kalynn Kennon, Caroline Mudara, Diana Hernández, Yazdan Yazdanpanah, Jean-François Payen, Samreen Ijaz, Joanne McPeake, Meera Chand, Catherine A Shaw, Cameron J Fairfield, Bruno Levy, Eric D'ortenzio, Pierre Delobel, Tiphaine Goulenok, Bronner P Gonçalves, Arnaud Scherpereel, Danilo Buonsenso, Mark G Pritchard, Susanne Dudman, Adrien Auvet, Caterina Caminiti, Debby Bogaert, Elisabeth Botelho-Nevers, Amandine Gagneux-Brunon, Merce Jourdain, Sue Smith, Jia Wei, Antoine Khalil, Clément Le Bihan, Nathalie Pansu, Vincent Le Moing, Victor Fomin, Christophe Fraser, Daniel Munblit, William Greenhalf, François-Xavier Lescure, Nicolas Carlier, Saye Khoo, Annemarie B Docherty, Christopher A Green, Riinu Pius, Louise Sigfrid, Sophie Halpin, Clare Jackson, Antonia Ho, Malcolm G Semple, Andrew Dagens, Carlo Palmieri, Lance Turtle, Zeno Bisoffi, Thomas Flament, Julie Mankikian, Romain Basmaci, Peter Openshaw, Rob Fowler, Tom Fletcher, Adrien Lemaignen, Pierre Tattevin, Christelle Delmas, Hélène Espérou, Claire Lévy-Marchal, Olivier Picone, Jeanne Sibiude, Cecile Yelnik, Michelle Girvan, Piero L Olliaro, Beatrice Alex, Benjamin Bach, Wendy S Barclay, Graham S Cooke, Ana da Silva Filipe, Alexander J Mentzer, Alison M Meynert, Mahdad Noursadeghi, Shona C Moore, Massimo Palmarini, William A Paxton, Georgios Pollakis, David L Robertson, Vanessa Sancho-Shimizu, Janet T Scott, Shiranee Sriskandan, David Stuart, Charlotte Summers, Emma C Thomson, Ryan S Thwaites, Lance C W Turtle, Hayley Hardwick, Wilna Oosthuyzen, Fiona Griffiths, Jo Dalton, Egle Saviciute, Stephanie Roberts, Janet Harrison, Marie Connor, Gary Leeming, Ross Hendry, Victoria Shaw, Jade Ghosn, Lucille Blumberg, Nicolas Benech, Odile Launay, Yoan Lavie-Badie, Minh Le, Elise Artaud-Macari, Muge Cevik, Nicola Latronico, Mylène Maillet, Didier Laureillard, Ben Morton, Claire Hastie, Nicholas Sedillot, Anne-Sophie Boureau, Laurent Abel, Guillaume Martin-Blondel, Valérie Garrait, Isabelle Delacroix, Andrea Cortegiani, Jean-Benoît Arlet, Raphaël Borie, Kévin Bouiller, Vincent Langlois, Mélanie Roriz, Vincent Dubée, John H Amuasi, Madiha Hashmi, Edwin Jesudason, Jan Cato Holter, Anders Benjamin Kildal, Luis Felipe Reyes, Anna Beltrame, Sulaiman Lakoh, Stéphanie Fry, Lynsey Goodwin, Laurent Plantier, Anna Casey, Denis Malvy, Nina Jamieson, François Dubos, Jean-Sébastien Hulot, Paola Rodari, Frank Bloos, Cécile Tromeur, Paul Loubet, Marina Esposito-Farèse, France Mentré, Valérie Gaborieau, Cécile Goujard, Vincent Thibault, Adam Ali, Sadie Kelly, Fernando A Bozza, Bertrand Dussol, Marion Schneider, Marielle Buisson, Yves Levy, Carine Roy, Walter Picard, Olivier Sanchez, Nazir Lone, Antoine Kimmoun, Roberto Roncon-Albuquerque, Nathan Peiffer-Smadja, Julien Poissy, Lila Bouadma, Bruno Lina, Maude Bouscambert, Alexandre Gaymard, Gilles Peytavin, Jeremie Guedj, Claire Andrejak, Cedric Laouenan, Anissa Chair, Samira Laribi, Marie-Capucine Tellier, Sandrine Couffin-Cadiergues, Ventzislava Petrov-Sanchez, Alpha Diallo, Sarah Tubiana, Patrick Imbert, Emmanuelle Mercier, Waasila Jassat, Arsene Kpangon, Dominique Luton, Simone Piva, Sophie Mahy, Pierre-Adrien Bolze, Sarah Moore, Raphael Favory, Andrea Angheben, Andrea Rossanese, Matthew Hall, Johann Auchabie, Christophe Rapp, Vincent Peigne, Fredrik Müller, Christl A Donnelly, François Goehringer, Elodie Curlier, Catherine Chirouze, Vegard Skogen, Stéphane Jaureguiberry, Laurent Bitker, Hodane Yonis, Laurent Mandelbrot, Jérémie Pasquier, Bato Hammarström, Thushan de Silva, Polina Bugaeva, Julie Chas, Dario Sinatti, Arne Søraas, Murray Wham, Sara Clohisey, Seán Keating, Thibault Chiarabini, Agnes Sommet, Hugues Aumaître, Charlotte Charpentier, Sylvie LeGac, Sarah E McDonald, Jeanne Truong, Anne-Hélène Boivin, Mariachiara Ippolito, Ellen Pauley, Diane Descamps, Sérgio Gaião, Stéphane Lasry, Amanda Rojek, Charlotte Salmon Gandonniere, Sebastien Preau, Benoit Thill, Karine Faure, Denis Garot, Grégory Corvaisier, Elsa Nyamankolly, Merete Ellingjord-Dale, Eva Geraud, Barbara Wanjiru Citarella, Kévin Alexandre, Nathalie Allou, Séverine Ansart, Laurène Azemar, Cecile Azoulay, Delphine Bachelet, Claudine Badr, Valeria Balan, Marie Bartoli, Joaquín Baruch, Jules Bauer, Alexandra Bedossa, Husna Begum, Marine Beluze, Delphine Bergeaud, Giulia Bertoli, Simon Bessis, Sybille Bevilcaqua, Karine Bezulier, Krishna Bhavsar, Laetitia Bodenes, Isabela Bolaños, Olivier Bouchaud, Sabelline Bouchez, Camile Bouisse, Marielle Boyer-Besseyre, Axelle Braconnier, Ingrid G Bustos, Denis Butnaru, Eder Caceres, Cyril Cadoz, Valentine Campana, Pauline Caraux-Paz, Thierry Carmoi, Marie-Christine Carret, Maire-Laure Casanova, Guylaine Castor-Alexandre, François-Xavier Catherine, Minerva Cervantes-Gonzalez, Catherine Chakveatze, Jean-Marc Chapplain, Antoine Cheret, Bernard Cholley, Marie-Charlotte Chopin, Roxane Courtois, Stéphanie Cousse, Alexa Debard, Nathalie DeCastro, Romain Decours, Eve Defous, Karen Delavigne, Elisa Demonchy, Emmanuelle Denis, Mathilde Desvallées, Kévin Didier, Jean-Luc Diehl, Vincent Dinot, Fara Diop, Alphonsine Diouf, Félix Djossou, Céline Dorival, Nathalie Dournon, Murray Dryden, Alexandre Ducancelle, Paul Dunand, Brigitte Elharrar, Philippine Eloy, Isabelle Enderle, Ilka Engelmann, Vincent Enouf, Olivier Epaulard, Manuel Etienne, Isabelle Fabre, François-Xavier Ferrand, Eglantine Ferrand Devouge, Nicolas Ferriere, Céline Ficko, Erwan Fourn, Rostane Gaci, Jean-Charles Gagnard, Esteban Garcia-Gallo, Tristan Gigante, Guillermo Giordano, Valérie Gissot, Petr Glybochko, Marie Gominet, Isabelle Gorenne, Laure Goubert, Pascal Granier, Segolène Greffe, Martin Guego, Romain Guery, Anne Guillaumot, Laurent Guilleminault, Thomas Guimard, Ali Hachemi, Nadir Hadri, Rebecca Hamidfar, Lars Heggelund, Rupert Higgins, Hikombo Hitoto, Alexandre Hoctin, Isabelle Hoffmann, Ikram Houas, Margaux Isnard, Danielle Jaafar, Salma Jaafoura, Julien Jabot, Florence Jego, Cédric Joseph, Ouifiya Kafif, Sabina Kali, Younes Kerroumi, Marie Lachatre, Marie Lacoste, Marie Lagrange, Fabrice Laine, Antonio Lalueza, Marie Langelot-Richard, Delphine Lariviere, Andy Law, Laurent Lefebvre, Bénédicte Lefebvre, Benjamin Lefèvre, Jean-Daniel Lelievre, Véronique Lemee, Anthony Lemeur, Quentin Lepiller, Olivier Lesens, Mathieu Lesouhaitier, Geoffrey Liegeon, Guillaume Lingas, Sylvie Lion-Daolio, Marine Livrozet, Bouchra Loufti, Guillame Louis, Liem Luong, Moïse Machado, Gabriel Macheda, Rafael Mahieu, Thomas Maitre, Victoria Manda, Aldric Manuel, Samuel Markowicz, Martin Martinot, Mathieu Mattei, Laurence Maulin, Thierry Mazzoni, Cécile Mear-Passard, Antoine Merckx, Mayka Mergeay-Fabre, Vanina Meysonnier, Mehdi Mezidi, Isabelle Michelet, Lucia Moro, Julien Moyet, Jimmy Mullaert, Nadège Neant, Nikita Nekliudov, Anthony Nghi, Duc Nguyen, Nadia Ouamara, Rachida Ouissa, Eric Oziol, Justine Pages Maïder Pagadoy, Aurélie Papadopoulos, Bruno Pastene, Christelle Paul, Florent Peelman, Daniel Perez, Thomas Perpoint, Vincent Pestre, Ryadh Pokeerbux, Diane Ponscarme, Marie Rafiq, Blandine Rammaert, Stanislas Rebaudet, Sarah Redl, Anne-Sophie Resseguier, Matthieu Revest, Laurent Richier, Patrick Rispal, Karine Risso, Olivier Robineau, Manuel Rosa-Calatrava, Benoît Roze, Hélène Salvator, Pierre-François Sandrine, Benjamine Sarton, Eric Senneville, Albert Sotto, Sarah Stabler, Andrey Svistunov, Coralie Tardivon, François Téoulé, Olivier Terrier, Simon-Djamel Thiberville, Peter S Timashev, Noémie Tissot, Tiffany Trouillon, Christelle Tual, Noémie Vanel, Charline Vauchy, Aurélie Veislinger, Fanny Vuotto, Aurélie Wiedemann, Marion Zabbe, David Zucman, Silvio Hamacher, Ekaterina Pazukhina, Allegra Chatterjee, Kyle Gomez, Matteo Puntoni, Oksana Kruglova, Yock Ping Chow, Yash Doshi, Sara Isabel Duque Vallejo, Elsa D Ibáñez-Prada, Yuli V Fuentes, Margaret E O'Hara, Tigist Menkir, Amal Abrous, Younes Ait Tamlihat, Aliya Mohammed Alameen, Marta Alessi, Kazali Enagnon Alidjnou, Jean Baptiste Assie, Eyvind W Axelsen, John Kenneth Baillie, José Luis Bernal Sobrino, Sonja Hjellegjerde Brunvoll, Roar Bævre-Jensen, Jose Andres Calvache, Léo Chenard, Juan Luis Cruz Bermúdez, Jaime Cruz Rojo, Charlene Da Silveira, John Arne Dahl, Etienne De Montmollin, Cristina De Rose, Fernanda Dias Da Silva, Thomas Drake, Amiel A Dror, Anne Margarita Dyrhol-Riise, Linn Margrete Eggesbø, Mohammed El Sanharawi, William Finlayson, Aline-Marie Florence, Linda Gail Skeie, Noelia García Barrio, Anatoliy Gavrylov, Louis Gerbaud Morlaes, Yanay Gorelik, Mette Stausland Istre, Silje Bakken Jørgensen, Karl Trygve Kalleberg, Beathe Kiland Granerud, Eyrun Floerecke Kjetland Kjetland, Gry Kloumann Bekken, Galyna Kutsyna, Nadhem Lafhej, Cyril Le Bris, Georges Le Falher, Lucie Le Fevre, Quentin Le Hingrat, Marion Le Maréchal, Soizic Le Mestre, Gwenaël Le Moal, Hervé Le Nagard, Sophie Letrou, Wei Shen Lim, Andreas Lind, Carlos Lumbreras Bermejo, Miles Lunn, Olga Martynenko, Roberta Meta, Lina Morales Cely, Clara Mouton Perrot, Alamin Mustafa, Karl Erik Müller, Ebrahim Ndure, Anders Benteson Nygaard, Claudia Milena Orozco-Chamorro, Paul Otiku, Miguel Pedrera Jiménez, Frank Olav Pettersen, Chiara Piubelli, Víctor Quirós González, Else Quist-Paulsen, Dag Henrik Reikvam, Antonia Ricchiuto, Aleksander Rygh Holten, Nadia Saidani, Pablo Serrano Balazote, Nassima Si Mohammed, Lene Bergendal Solberg, Edouard Soum, Elisabetta Spinuzza, Trude Steinsvik, Birgitte Stiksrud, Mathew Thorpe, Vadim Tieroshyn, Kristian Tonby, Anders Tveita, Sylvie Van Der Werf, Paul Henri Wicky, Ibrahim Richard Bangura, Leonardo Bastos, Daniel Cassaglia, Barbara Citarella, Sarah Duque, Anne Margarita Dyrhol Riise, Annelies Gillesen, Bronner P Goncalvez, Margareta O’Hara, Lars Hegelund, Aquiles Henriquez Trujillo, Elsa D Ibañez, Jane Ireson, Oksana Krugalova, Sam Lissaeur, Sinnadurai Manohan, Prasan K Panda, Daniel R Plotkin, Liliana Resende, Sergio Ruiz Saltana, Steffi Ryckaert, Girish Sindhwani Pulm, and Caroline Vika

Subjects
Medicine (General), R5-920, Infectious and parasitic diseases, RC109-216
Abstract

Introduction A proportion of people develop Long Covid after acute COVID-19, but with most studies concentrated in high-income countries (HICs), the global burden is largely unknown. Our study aims to characterise long-term COVID-19 sequelae in populations globally and compare the prevalence of reported symptoms in HICs and low-income and middle-income countries (LMICs).Methods A prospective, observational study in 17 countries in Africa, Asia, Europe and South America, including adults with confirmed COVID-19 assessed at 2 to

Published
2024
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27. World Value Functions: Knowledge Representation for Learning and Planning

Author

Tasse, Geraud Nangue, Rosman, Benjamin, and James, Steven

Subjects
Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

We propose world value functions (WVFs), a type of goal-oriented general value function that represents how to solve not just a given task, but any other goal-reaching task in an agent's environment. This is achieved by equipping an agent with an internal goal space defined as all the world states where it experiences a terminal transition. The agent can then modify the standard task rewards to define its own reward function, which provably drives it to learn how to achieve all reachable internal goals, and the value of doing so in the current task. We demonstrate two key benefits of WVFs in the context of learning and planning. In particular, given a learned WVF, an agent can compute the optimal policy in a new task by simply estimating the task's reward function. Furthermore, we show that WVFs also implicitly encode the transition dynamics of the environment, and so can be used to perform planning. Experimental results show that WVFs can be learned faster than regular value functions, while their ability to infer the environment's dynamics can be used to integrate learning and planning methods to further improve sample efficiency., Comment: Accepted at the Planning and Reinforcement Learning Workshop at ICAPS 2022. arXiv admin note: text overlap with arXiv:2205.08827

Published
2022

28. A Proof of the Tree of Shapes in n-D

Author

GÉraud, Thierry, Boutry, Nicolas, Crozet, Sébastien, Carlinet, Edwin, and Najman, Laurent

Subjects
Computer Science - Discrete Mathematics, Computer Science - Data Structures and Algorithms, Electrical Engineering and Systems Science - Image and Video Processing, Mathematics - Geometric Topology
Abstract

In this paper, we prove that the self-dual morphological hierarchical structure computed on a n-D gray-level wellcomposed image u by the algorithm of G{\'e}raud et al. [1] is exactly the mathematical structure defined to be the tree of shape of u in Najman et al [2]. We recall that this algorithm is in quasi-linear time and thus considered to be optimal. The tree of shapes leads to many applications in mathematical morphology and in image processing like grain filtering, shapings, image segmentation, and so on.

Published
2022

29. Automated Discovery of New $L$-Function Relations

Author

Barral, Hadrien, Géraud-Stewart, Rémi, Léonard, Arthur, Naccache, David, Vermande, Quentin, and Vivien, Samuel

Subjects
Mathematics - Number Theory
Abstract

$L$-functions typically encode interesting information about mathematical objects. This paper reports 29 identities between such functions that hitherto never appeared in the literature. Of these we have a complete proof for 9; all others are extensively numerically checked and we welcome proofs of their (in)validity. The method we devised to obtain these identities is a two-step process whereby a list of candidate identities is automatically generated, obtained, tested, and ultimately formally proven. The approach is however only \emph{semi-}automated as human intervention is necessary for the post-processing phase, to determine the most general form of a conjectured identity and to provide a proof for them. This work complements other instances in the literature where automated symbolic computation has served as a productive step toward theorem proving and can be extended in several directions further to explore the algebraic landscape of $L$-functions and similar constructions.

Published
2022

30. Some equivalence relation between persistent homology and morphological dynamics

Author

Boutry, Nicolas, Najman, Laurent, and Géraud, Thierry

Subjects
Computer Science - Computer Vision and Pattern Recognition, Electrical Engineering and Systems Science - Image and Video Processing, Electrical Engineering and Systems Science - Signal Processing, Mathematics - Algebraic Topology, Mathematics - Differential Geometry
Abstract

In Mathematical Morphology (MM), connected filters based on dynamics are used to filter the extrema of an image. Similarly, persistence is a concept coming from Persistent Homology (PH) and Morse Theory (MT) that represents the stability of the extrema of a Morse function. Since these two concepts seem to be closely related, in this paper we examine their relationship, and we prove that they are equal on n-D Morse functions, n $\ge$ 1. More exactly, pairing a minimum with a 1-saddle by dynamics or pairing the same 1-saddle with a minimum by persistence leads exactly to the same pairing, assuming that the critical values of the studied Morse function are unique. This result is a step further to show how much topological data analysis and mathematical morphology are related, paving the way for a more in-depth study of the relations between these two research fields., Comment: Journal of Mathematical Imaging and Vision, Springer Verlag, In press

Published
2022

31. Skill Machines: Temporal Logic Skill Composition in Reinforcement Learning

Author

Tasse, Geraud Nangue, Jarvis, Devon, James, Steven, and Rosman, Benjamin

Subjects
Computer Science - Machine Learning, Computer Science - Logic in Computer Science
Abstract

It is desirable for an agent to be able to solve a rich variety of problems that can be specified through language in the same environment. A popular approach towards obtaining such agents is to reuse skills learned in prior tasks to generalise compositionally to new ones. However, this is a challenging problem due to the curse of dimensionality induced by the combinatorially large number of ways high-level goals can be combined both logically and temporally in language. To address this problem, we propose a framework where an agent first learns a sufficient set of skill primitives to achieve all high-level goals in its environment. The agent can then flexibly compose them both logically and temporally to provably achieve temporal logic specifications in any regular language, such as regular fragments of linear temporal logic. This provides the agent with the ability to map from complex temporal logic task specifications to near-optimal behaviours zero-shot. We demonstrate this experimentally in a tabular setting, as well as in a high-dimensional video game and continuous control environment. Finally, we also demonstrate that the performance of skill machines can be improved with regular off-policy reinforcement learning algorithms when optimal behaviours are desired., Comment: Published as a conference paper at ICLR 2024

Published
2022

32. World Value Functions: Knowledge Representation for Multitask Reinforcement Learning

Author

Tasse, Geraud Nangue, James, Steven, and Rosman, Benjamin

Subjects
Computer Science - Machine Learning
Abstract

An open problem in artificial intelligence is how to learn and represent knowledge that is sufficient for a general agent that needs to solve multiple tasks in a given world. In this work we propose world value functions (WVFs), which are a type of general value function with mastery of the world - they represent not only how to solve a given task, but also how to solve any other goal-reaching task. To achieve this, we equip the agent with an internal goal space defined as all the world states where it experiences a terminal transition - a task outcome. The agent can then modify task rewards to define its own reward function, which provably drives it to learn how to achieve all achievable internal goals, and the value of doing so in the current task. We demonstrate a number of benefits of WVFs. When the agent's internal goal space is the entire state space, we demonstrate that the transition function can be inferred from the learned WVF, which allows the agent to plan using learned value functions. Additionally, we show that for tasks in the same world, a pretrained agent that has learned any WVF can then infer the policy and value function for any new task directly from its rewards. Finally, an important property for long-lived agents is the ability to reuse existing knowledge to solve new tasks. Using WVFs as the knowledge representation for learned tasks, we show that an agent is able to solve their logical combination zero-shot, resulting in a combinatorially increasing number of skills throughout their lifetime., Comment: Accepted to the 5th Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM), 2022

Published
2022

38. Safety and Efficacy of Mini-Invasive Left Atrial Appendage Closure: A Propensity-Score Analysis

Author

Denis, Catherine, Clerfond, Guillaume, Chalard, Aurélie, Riocreux, Clément, Pereira, Bruno, Lamallem, Ouarda, Guizani, Taieb, Catalan, Pierre-Antoine, Boudias, Antoine, Jean, Frédéric, Bouchant-Pioche, Marion, Abu-Alrub, Saer, Combaret, Nicolas, Souteyrand, Géraud, Motreff, Pascal, Jabaudon, Matthieu, Futier, Emmanuel, Massoullie, Grégoire, and Eschalier, Romain

Published
2024
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39. Tapered multi-core fiber for lensless endoscopes

Author

Moussawi, Fatima El, Hofer, Matthias, Labat, Damien, Cassez, Andy, Bouwmans, Géraud, Sivankutty, Siddharth, Cossart, Rosa, Vanvincq, Olivier, Rigneault, Hervé, and Andresen, Esben Ravn

Subjects
Physics - Optics
Abstract

We present a novel fiber-optic component, a "tapered multi-core fiber (MCF)", designed for integration into ultra-miniaturized endoscopes for minimally invasive two-photon point-scanning imaging and to address the power delivery issue that has faced MCF based lensless endoscopes. With it we achieve experimentally a factor 6.0 increase in two-photon signal yield while keeping the ability to point-scan by the memory effect, and a factor 8.9 sacrificing the memory effect. To reach this optimal design we first develop and validate a fast numerical model capable of predicting the essential properties of an arbitrarily tapered MCF from its structural parameters. We then use this model to identify the tapered MCF design parameters that result in a chosen set of target properties (point-spread function, delivered power, presence or absence of memory effect). We fabricate the identified target designs by stack-and-draw and post-processing on a CO$_{2}$ laser-based glass processing and splicing system. Finally we demonstrate the performance gain of the fabricated tapered MCFs in two-photon imaging when used in a lensless endoscope system. Our results show that tailoring of the taper profile brings new degrees of freedom that can be efficiently exploited for lensless endoscopes.

Published
2022

40. Miniature 120-beam coherent combiner with 3D printed optics for multicore fiber based endoscopy

Author

Sivankutty, Siddharth, Bertoncini, Andrea, Tsvirkun, Victor, Kumar, Naveen Gajendra, Brévalle, Gaelle, Bouwmans, Géraud, Andresen, Esben Ravn, Liberale, Carlo, and Rigneault, Hervé

Subjects
Physics - Optics, Physics - Applied Physics
Abstract

We report high efficiency, miniaturized, ultra-fast coherent beam combining with 3D printed micro-optics directly on the tip of a multicore fiber bundle. The highly compact device foot-print (180 micron diameter) facilitates its incorporation into a minimally invasive ultra-thin nonlinear endoscope to perform two-photon imaging, Comment: Published in Optics Letters

Published
2022
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41. Hierarchical Reinforcement Learning with AI Planning Models

Author

Lee, Junkyu, Katz, Michael, Agravante, Don Joven, Liu, Miao, Tasse, Geraud Nangue, Klinger, Tim, and Sohrabi, Shirin

Subjects
Computer Science - Artificial Intelligence
Abstract

Two common approaches to sequential decision-making are AI planning (AIP) and reinforcement learning (RL). Each has strengths and weaknesses. AIP is interpretable, easy to integrate with symbolic knowledge, and often efficient, but requires an up-front logical domain specification and is sensitive to noise; RL only requires specification of rewards and is robust to noise but is sample inefficient and not easily supplied with external knowledge. We propose an integrative approach that combines high-level planning with RL, retaining interpretability, transfer, and efficiency, while allowing for robust learning of the lower-level plan actions. Our approach defines options in hierarchical reinforcement learning (HRL) from AIP operators by establishing a correspondence between the state transition model of AI planning problem and the abstract state transition system of a Markov Decision Process (MDP). Options are learned by adding intrinsic rewards to encourage consistency between the MDP and AIP transition models. We demonstrate the benefit of our integrated approach by comparing the performance of RL and HRL algorithms in both MiniGrid and N-rooms environments, showing the advantage of our method over the existing ones., Comment: 30 pages, 15 figures

Published
2022

42. Local Intensity Order Transformation for Robust Curvilinear Object Segmentation

Author

Shi, Tianyi, Boutry, Nicolas, Xu, Yongchao, and Géraud, Thierry

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

Segmentation of curvilinear structures is important in many applications, such as retinal blood vessel segmentation for early detection of vessel diseases and pavement crack segmentation for road condition evaluation and maintenance. Currently, deep learning-based methods have achieved impressive performance on these tasks. Yet, most of them mainly focus on finding powerful deep architectures but ignore capturing the inherent curvilinear structure feature (e.g., the curvilinear structure is darker than the context) for a more robust representation. In consequence, the performance usually drops a lot on cross-datasets, which poses great challenges in practice. In this paper, we aim to improve the generalizability by introducing a novel local intensity order transformation (LIOT). Specifically, we transfer a gray-scale image into a contrast-invariant four-channel image based on the intensity order between each pixel and its nearby pixels along with the four (horizontal and vertical) directions. This results in a representation that preserves the inherent characteristic of the curvilinear structure while being robust to contrast changes. Cross-dataset evaluation on three retinal blood vessel segmentation datasets demonstrates that LIOT improves the generalizability of some state-of-the-art methods. Additionally, the cross-dataset evaluation between retinal blood vessel segmentation and pavement crack segmentation shows that LIOT is able to preserve the inherent characteristic of curvilinear structure with large appearance gaps. An implementation of the proposed method is available at https://github.com/TY-Shi/LIOT., Comment: Accepted by IEEE TIP

Published
2022
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44. Endovascular therapy in patients with a large ischemic volume at presentation: An aggregate patient-level analysis

Author

Kerleroux, Basile, Hak, Jean François, Lapergue, Bertrand, Bricout, Nicolas, Zhu, François, Inoue, Manabu, Janot, Kevin, Dargazanli, Cyril, Kaesmacher, Johannes, Rouchaud, Aymeric, Forestier, Géraud, Gortais, Hugo, Benzakoun, Joseph, Yoshimoto, Takeshi, Consoli, Arturo, Ben Hassen, Wagih, Henon, Hilde, Naggara, Olivier, and Boulouis, Grégoire

Published
2024
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47. Environmental variation predicts patterns of genomic variation in an African tropical forest frog

Author

Courtney A. Miller, Geraud C. Tasse Taboue, Eric B. Fokam, Katy Morgan, Ying Zhen, Ryan J. Harrigan, Vinh Le Underwood, Kristen Ruegg, Paul R. Sesink Clee, Stephan Ntie, Patrick Mickala, Jean Francois Mboumba, Trevon Fuller, Breda M. Zimkus, Thomas B. Smith, and Nicola M. Anthony

Subjects
Central Africa, amphibians, RAD-seq, environmental gradients, genomic vulnerability, climate change, General. Including nature conservation, geographical distribution, QH1-199.5
Abstract

Central African rainforests are predicted to be disproportionately affected by future climate change. How species will cope with these changes is unclear, but rapid environmental changes will likely impose strong selection pressures. Here we examined environmental drivers of genomic variation in the central African puddle frog (Phrynobatrachus auritus) to identify areas of elevated environmentally-associated turnover. We also compared current and future climate models to pinpoint areas of high genomic vulnerability where allele frequencies will have to shift the most in order to keep pace with future climate change. Neither physical landscape barriers nor the effects of past Pleistocene refugia influenced genomic differentiation. Alternatively, geographic distance and seasonal aspects of precipitation are the most important drivers of SNP allele frequency variation. Patterns of genomic differentiation coincided with key ecological gradients across the forest-savanna ecotone, montane areas, and a coastal to interior rainfall gradient. Areas of greatest vulnerability were found in the lower Sanaga basin, the southeastern region of Cameroon, and southwest Gabon. In contrast with past conservation efforts that have focused on hotspots of species richness or endemism, our findings highlight the importance of maintaining environmentally heterogeneous landscapes to preserve genomic variation and ongoing evolutionary processes in the face of climate change.

Published
2024
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48. A systematic literature review on the impact of AI models on the security of code generation

Author

Claudia Negri-Ribalta, Rémi Geraud-Stewart, Anastasia Sergeeva, and Gabriele Lenzini

Subjects
artificial intelligence, security, software engineering, programming, code generation, Information technology, T58.5-58.64
Abstract

IntroductionArtificial Intelligence (AI) is increasingly used as a helper to develop computing programs. While it can boost software development and improve coding proficiency, this practice offers no guarantee of security. On the contrary, recent research shows that some AI models produce software with vulnerabilities. This situation leads to the question: How serious and widespread are the security flaws in code generated using AI models?MethodsThrough a systematic literature review, this work reviews the state of the art on how AI models impact software security. It systematizes the knowledge about the risks of using AI in coding security-critical software.ResultsIt reviews what security flaws of well-known vulnerabilities (e.g., the MITRE CWE Top 25 Most Dangerous Software Weaknesses) are commonly hidden in AI-generated code. It also reviews works that discuss how vulnerabilities in AI-generated code can be exploited to compromise security and lists the attempts to improve the security of such AI-generated code.DiscussionOverall, this work provides a comprehensive and systematic overview of the impact of AI in secure coding. This topic has sparked interest and concern within the software security engineering community. It highlights the importance of setting up security measures and processes, such as code verification, and that such practices could be customized for AI-aided code production.

Published
2024
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49. TDP1 mutation causing SCAN1 neurodegenerative syndrome hampers the repair of transcriptional DNA double-strand breaks

Author

Mathéa Geraud, Agnese Cristini, Simona Salimbeni, Nicolas Bery, Virginie Jouffret, Marco Russo, Andrea Carla Ajello, Lara Fernandez Martinez, Jessica Marinello, Pierre Cordelier, Didier Trouche, Gilles Favre, Estelle Nicolas, Giovanni Capranico, and Olivier Sordet

Subjects
CP: Molecular biology, Biology (General), QH301-705.5
Abstract

Summary: TDP1 removes transcription-blocking topoisomerase I cleavage complexes (TOP1ccs), and its inactivating H493R mutation causes the neurodegenerative syndrome SCAN1. However, the molecular mechanism underlying the SCAN1 phenotype is unclear. Here, we generate human SCAN1 cell models using CRISPR-Cas9 and show that they accumulate TOP1ccs along with changes in gene expression and genomic distribution of R-loops. SCAN1 cells also accumulate transcriptional DNA double-strand breaks (DSBs) specifically in the G1 cell population due to increased DSB formation and lack of repair, both resulting from abortive removal of transcription-blocking TOP1ccs. Deficient TDP1 activity causes increased DSB production, and the presence of mutated TDP1 protein hampers DSB repair by a TDP2-dependent backup pathway. This study provides powerful models to study TDP1 functions under physiological and pathological conditions and unravels that a gain of function of the mutated TDP1 protein, which prevents DSB repair, rather than a loss of TDP1 activity itself, could contribute to SCAN1 pathogenesis.

Published
2024
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50. Characteristics and outcomes of COVID-19 patients admitted to hospital with and without respiratory symptoms

Author

Barbara Wanjiru Citarella, Christiana Kartsonaki, Elsa D. Ibáñez-Prada, Bronner P. Gonçalves, Joaquin Baruch, Martina Escher, Mark G. Pritchard, Jia Wei, Fred Philippy, Andrew Dagens, Matthew Hall, James Lee, Demetrios James Kutsogiannis, Evert-Jan Wils, Marília Andreia Fernandes, Bharath Kumar Tirupakuzhi Vijayaraghavan, Prasan Kumar Panda, Ignacio Martin-Loeches, Shinichiro Ohshimo, Arie Zainul Fatoni, Peter Horby, Jake Dunning, Jordi Rello, Laura Merson, Amanda Rojek, Michel Vaillant, Piero Olliaro, Luis Felipe Reyes, S.A. Moharam, Sabriya Abdalasalam, Alaa Abdalfattah Abdalhadi, Naana Reyam Abdalla, Walaa Abdalla, Almthani Hamza Abdalrheem, Ashraf Abdalsalam, Saedah Abdeewi, Esraa Hassan Abdelgaum, Mohamed Abdelhalim, Mohammed Abdelkabir, Israa Abdelrahman, Sheryl Ann Abdukahil, Lamees Adil Abdulbaqi, Salaheddin Abdulhamid, Widyan Abdulhamid, Nurul Najmee Abdulkadir, Eman Abdulwahed, Rawad Abdunabi, Ryuzo Abe, Laurent Abel, Ahmed Mohammed Abodina, Amal Abrous, Lara Absil, Kamal Abu Jabal, Nashat Abu Salah, Abdurraouf Abusalama, Tareg Abdallah Abuzaid, Subhash Acharya, Andrew Acker, Elisabeth Adam, Safia Adem, Manuella Ademnou, Francisca Adewhajah, Diana Adrião, Anthony Afum-Adjei Awuah, Melvin Agbogbatey, Saleh Al Ageel, Aya Mustafa Ahmed, Musaab Mohammed Ahmed, Shakeel Ahmed, Zainab Ahmed Alaraji, Abdulrahman Ahmed Elhefnawy Enan, Reham Abdelhamid Ahmed Khalil, Ali Mostafa Ahmed Mohamed Abdelaziz, Kate Ainscough, Eka Airlangga, Tharwat Aisa, Ali Aisha, Bugila Aisha, Ali Ait Hssain, Younes Ait Tamlihat, Takako Akimoto, Ernita Akmal, Chika Akwani, Eman Al Qasim, Ahmed Alajeeli, Ahmed Alali, Razi Alalqam, Aliya Mohammed Alameen, Mohammed Al-Aquily, Zinah A. Alaraji, Khalid Albakry, Safa Albatni, Angela Alberti, Osama Aldabbourosama, Tala Al-dabbous, Amer Aldhalia, Abdulkarim Aldoukali, Senthilkumar Alegesan, Marta Alessi, Beatrice Alex, Kévin Alexandre, Abdulrahman Al-Fares, Asil Alflite, Huda Alfoudri, Qamrah Alhadad, Hoda Salem Alhaddad, Maali Khalid Mohamed Abdalla Alhasan, Ahmad Nabil Alhouri, Hasan Alhouri, Adam Ali, Imran Ali, Maha TagElser Mohammed Ali, Syed Ali Abbas, Yomna Ali Abdelghafar, Naseem Ali Sheikh, Kazali Enagnon Alidjnou, Mahmoud Aljadi, Sarah Aljamal, Mohammed Alkahlout, Akram Alkaseek, Qabas Alkhafajee, Clotilde Allavena, Nathalie Allou, Lana Almasri, Abdulrahman Almjersah, Raja Ahmed Alqandouz, Walaa Alrfaea, Moayad Alrifaee, Rawan Alsaadi, Yousef Al-Saba'a, Entisar Alshareea, Eslam Alshenawy, Aneela Altaf, João Melo Alves, João Alves, Rita Alves, Joana Alves Cabrita, Maria Amaral, Amro Essam Amer, Nur Amira, Amos Amoako Adusei, John Amuasi, Roberto Andini, Claire Andrejak, Andrea Angheben, François Angoulvant, Sophia Ankrah, Séverine Ansart, Sivanesen Anthonidass, Massimo Antonelli, Carlos Alexandre Antunes de Brito, Ardiyan Apriyana, Yaseen Arabi, Irene Aragao, Francisco Arancibia, Carolline Araujo, Antonio Arcadipane, Patrick Archambault, Lukas Arenz, Jean-Benoît Arlet, Christel Arnold-Day, Lovkesh Arora, Rakesh Arora, Elise Artaud-Macari, Diptesh Aryal, Angel Asensio, Elizabeth A. Ashley, Muhammad Ashraf, Muhammad Sheharyar Ashraf, Abir Ben Ashur, Franklin Asiedu-Bekoe, Namra Asif, Mohammad Asim, Grace Assi, Jean Baptiste Assie, Amirul Asyraf, Fouda Atangana, Ahmed Atia, Minahel Atif, Asia Atif Abdelrhman Abdallahrs, Anika Atique, Moad Atlowly, AM Udara Lakshan Attanyake, Johann Auchabie, Hugues Aumaitre, Adrien Auvet, Abdelmalek Awad Ali Mohammed, Eyvind W. Axelsen, Ared Ayad, Ahmed Ayman Hassan Helmi, Laurène Azemar, Mohammed Azizeldin, Cecile Azoulay, Hakeem Babatunde, Benjamin Bach, Delphine Bachelet, Claudine Badr, Roar Bævre-Jensen, Nadia Baig, John Kenneth Baillie, J Kevin Baird, Erica Bak, Agamemnon Bakakos, Nazreen Abu Bakar, Hibah Bileid Bakeer, Ashraf Bakri, Andriy Bal, Mohanaprasanth Balakrishnan, Irene Bandoh, Firouzé Bani-Sadr, Renata Barbalho, Nicholas Yuri Barbosa, Wendy S. Barclay, Saef Umar Barnett, Michaela Barnikel, Helena Barrasa, Cleide Barrigoto, Marie Bartoli, Joaquín Baruch, Romain Basmaci, Muhammad Fadhli Hassin Basri, AbdAlkarim Batool, Denise Battaglini, Jules Bauer, Diego Fernando Bautista Rincon, Denisse Bazan Dow, Abigail Beane, Alexandra Bedossa, Ker Hong Bee, Husna Begum, Sylvie Behilill, Albertus Beishuizen, Aleksandr Beljantsev, David Bellemare, Anna Beltrame, Beatriz Amorim Beltrão, Marine Beluze, Nicolas Benech, Lionel Eric Benjiman, Suzanne Bennett, Luís Bento, Jan-Erik Berdal, Lamis Berdeweel, Delphine Bergeaud, Hazel Bergin, Giulia Bertoli, Lorenzo Bertolino, Simon Bessis, Sybille Bevilcaqua, Karine Bezulier, Amar Bhatt, Krishna Bhavsar, Isabella Bianchi, Claudia Bianco, Sandra Bichoka, Farah Nadiah Bidin, Felwa Bin Humaid, Mohd Nazlin Bin Kamarudin, Muhannud Binnawara, Zeno Bisoffi, Patrick Biston, Laurent Bitker, Mustapha Bittaye, Jonathan Bitton, Pablo Blanco-Schweizer, Catherine Blier, Frank Bloos, Mathieu Blot, Filomena Boccia, Laetitia Bodenes, Debby Bogaert, Anne-Hélène Boivin, Ariel Bolanga, Isabela Bolaños, Pierre-Adrien Bolze, François Bompart, Aurelius Bonifasius, Joe Bonney, Diogo Borges, Raphaël Borie, Hans Martin Bosse, Elisabeth Botelho-Nevers, Lila Bouadma, Olivier Bouchaud, Sabelline Bouchez, Damien Bouhour, Kévin Bouiller, Laurence Bouillet, Camile Bouisse, Latsaniphone Bountthasavong, Anne-Sophie Boureau, John Bourke, Maude Bouscambert, Aurore Bousquet, Marielle Boyer-Besseyre, Maria Boylan, Fernando Augusto Bozza, Axelle Braconnier, Cynthia Braga, Timo Brandenburger, Filipa Brás Monteiro, Luca Brazzi, Dorothy Breen, Patrick Breen, David Brewster, Kathy Brickell, Tessa Broadley, Helen Brotherton, Alex Browne, Nicolas Brozzi, Sonja Hjellegjerde Brunvoll, Marjolein Brusse-Keizer, Petra Bryda, Nina Buchtele, Polina Bugaeva, Marielle Buisson, Danilo Buonsenso, Erlina Burhan, Donald Buri, Aidan Burrell, Ingrid G. Bustos, Denis Butnaru, André Cabie, Susana Cabral, Joana Cabrita, Eder Caceres, Cyril Cadoz, Rui Caetano Garcês, Kate Calligy, Jose Andres Calvache, João Camões, Valentine Campana, Paul Campbell, Josie Campisi, Cecilia Canepa, Mireia Cantero, Janice Caoili, Pauline Caraux-Paz, Sheila Cárcel, Filipa Cardoso, Filipe Cardoso, Nelson Cardoso, Sofia Cardoso, Simone Carelli, Nicolas Carlier, Thierry Carmoi, Gayle Carney, Inês Carqueja, Marie-Christine Carret, François Martin Carrier, Ida Carroll, Gail Carson, Maire-Laure Casanova, Mariana Cascão, Siobhan Casey, José Casimiro, Bailey Cassandra, Silvia Castañeda, Nidyanara Castanheira, Guylaine Castor-Alexandre, Ivo Castro, Ana Catarino, François-Xavier Catherine, Paolo Cattaneo, Roberta Cavalin, Giulio Giovanni Cavalli, Alexandros Cavayas, Adrian Ceccato, Masaneh Ceesay, Shelby Cerkovnik, Minerva Cervantes-Gonzalez, Muge Cevik, Anissa Chair, Catherine Chakveatze, Adrienne Chan, Meera Chand, Jean-Marc Chapplain, Charlotte Charpentier, Julie Chas, Muhammad Mobin Chaudry, Jonathan Samuel Chávez Iñiguez, Anjellica Chen, Yih-Sharng Chen, Léo Chenard, Matthew Pellan Cheng, Antoine Cheret, Thibault Chiarabini, Julian Chica, Suresh Kumar Chidambaram, Leong Chin Tho, Catherine Chirouze, Davide Chiumello, Sung-Min Cho, Bernard Cholley, Danoy Chommanam, Marie-Charlotte Chopin, Yock Ping Chow, Ting Soo Chow, Nathaniel Christy, Hiu Jian Chua, Jonathan Chua, Jose Pedro Cidade, José Miguel Cisneros Herreros, Anna Ciullo, Jennifer Clarke, Rolando Claure-Del Granado, Sara Clohisey, Cassidy Codan, Caitriona Cody, Jennifer Coles, Megan Coles, Gwenhaël Colin, Michael Collins, Pamela Combs, Jennifer Connolly, Marie Connor, Anne Conrad, Elaine Conway, Graham S. Cooke, Hugues Cordel, Amanda Corley, Sabine Cornelis, Alexander Daniel Cornet, Arianne Joy Corpuz, Andrea Cortegiani, Grégory Corvaisier, Camille Couffignal, Sandrine Couffin-Cadiergues, Roxane Courtois, Stéphanie Cousse, Juthaporn Cowan, Rachel Cregan, Gloria Crowl, Jonathan Crump, Claudina Cruz, Marc Csete, Ailbhe Cullen, Matthew Cummings, Gerard Curley, Elodie Curlier, Colleen Curran, Paula Custodio, Ana da Silva Filipe, Charlene Da Silveira, Al-Awwab Dabaliz, John Arne Dahl, Darren Dahly, Umberto D'Alessandro, Peter Daley, Zaina Dalloul, Heidi Dalton, Jo Dalton, Seamus Daly, Juliana Damas, Joycelyn Dame, Cammandji Damien, Nick Daneman, Jorge Dantas, Frédérick D'Aragon, Gillian de Loughry, Diego de Mendoza, Etienne De Montmollin, Rafael Freitas de Oliveira França, Ana Isabel de Pinho Oliveira, Rosanna De Rosa, Cristina De Rose, Thushan de Silva, Peter de Vries, Jillian Deacon, David Dean, Alexa Debard, Bianca DeBenedictis, Marie-Pierre Debray, Nathalie DeCastro, William Dechert, Romain Decours, Eve Defous, Isabelle Delacroix, Alexandre Delamou, Eric Delaveuve, Karen Delavigne, Nathalie M. Delfos, Ionna Deligiannis, Andrea Dell'Amore, Christelle Delmas, Pierre Delobel, Corine Delsing, Elisa Demonchy, Emmanuelle Denis, Dominique Deplanque, Pieter Depuydt, Diane Descamps, Mathilde Desvallées, Santi Dewayanti, Pathik Dhangar, Alpha Diallo, Souleymane Taran Diallo, Sylvain Diamantis, André Dias, Fernanda Dias Da Silva, Rodrigo Diaz, Juan Jose Diaz, Priscila Diaz, Bakary K. Dibba, Kévin Didier, Jean-Luc Diehl, Wim Dieperink, Jérôme Dimet, Vincent Dinot, Fara Diop, Alphonsine Diouf, Yael Dishon, Cedric Djadda, Félix Djossou, Annemarie B. Docherty, Helen Doherty, Arjen M. Dondorp, Christl A. Donnelly, Yoann Donohue, Sean Donohue, Peter Doran, Céline Dorival, Eric D'Ortenzio, Yash Doshi, Phouvieng Douangdala, James Joshua Douglas, Renee Douma, Nathalie Dournon, Joanne Downey, Mark Downing, Thomas Drake, Aoife Driscoll, Ibrahim Kwaku Duah, Claudio Duarte Fonseca, Vincent Dubee, François Dubos, Audrey Dubot-Pérès, Alexandre Ducancelle, Toni Duculan, Susanne Dudman, Abhijit Duggal, Paul Dunand, Mathilde Duplaix, Emanuele Durante-Mangoni, Lucian Durham, III, Bertrand Dussol, Juliette Duthoit, Xavier Duval, Anne Margarita Dyrhol-Riise, Sim Choon Ean, Ada Ebo, Marco Echeverria-Villalobos, Michael Edelstein, Siobhan Egan, Linn Margrete Eggesbø, Khadeja Ehzaz, Carla Eira, Mohammed El Sanharawi, Marwan El Sayed, Mohammed Elabid, Mohamed Bashir Elagili, Subbarao Elapavaluru, Mohammad Elbahnasawy, Sohail Elboshra, Brigitte Elharrar, Jacobien Ellerbroek, Merete Ellingjord-Dale, Hamida ELMagrahi, Mohammad Muatasm Elmubark, Loubna Elotmani, Lauren Eloundou, Philippine Eloy, Basma Elshaikhy, Tarek Elshazly, Wafa Elsokni, Aml Ahmed Eltayeb, Iqbal Elyazar, Zarief Kamel Emad, Hussein Embarek, Isabelle Enderle, Tomoyuki Endo, Gervais Eneli, Chan Chee Eng, Ilka Engelmann, Vincent Enouf, Olivier Epaulard, Haneen Esaadi, Mariano Esperatti, Hélène Esperou, Catarina Espírito Santo, Marina Esposito-Farese, Rachel Essaka, Lorinda Essuman, João Estevão, Manuel Etienne, Anna Greti Everding, Mirjam Evers, Isabelle Fabre, Marc Fabre, Ismaila Fadera, Asgad Osman Abdalla Fadlalla, Amna Faheem, Arabella Fahy, Cameron J. Fairfield, Zul Fakar, Komal Fareed, Pedro Faria, Ahmed Farooq, Hanan Fateena, Mohamed Fathi, Salem Fatima, Karine Faure, Raphaël Favory, Mohamed Fayed, Niamh Feely, Jorge Fernandes, Susana Fernandes, François-Xavier Ferrand, Eglantine Ferrand Devouge, Joana Ferrão, Mário Ferraz, Benigno Ferreira, Isabel Ferreira, Bernardo Ferreira, Sílvia Ferreira, Nicolas Ferriere, Céline Ficko, Claudia Figueiredo-Mello, William Finlayson, Thomas Flament, Tom Fletcher, Aline-Marie Florence, Letizia Lucia Florio, Brigid Flynn, Deirdre Flynn, Jean Foley, Victor Fomin, Tatiana Fonseca, Patricia Fontela, Karen Forrest, Simon Forsyth, Denise Foster, Giuseppe Foti, Berline Fotso, Erwan Fourn, Robert A. Fowler, Marianne Fraher, Diego Franch-Llasat, Christophe Fraser, John F. Fraser, Marcela Vieira Freire, Ana Freitas Ribeiro, Craig French, Caren Friedrich, Ricardo Fritz, Stéphanie Fry, Nora Fuentes, Masahiro Fukuda, G. Argin, Valérie Gaborieau, Rostane Gaci, Massimo Gagliardi, Jean-Charles Gagnard, Amandine Gagneux-Brunon, Abdou Gai, Sérgio Gaião, Linda Gail Skeie, Adham Mohamed Galal Mohamed Ramadan, Phil Gallagher, Carrol Gamble, Yasmin Gani, Arthur Garan, Rebekha Garcia, Julia Garcia-Diaz, Esteban Garcia-Gallo, Navya Garimella, Denis Garot, Valérie Garrait, Basanta Gauli, Anatoliy Gavrylov, Alexandre Gaymard, Johannes Gebauer, Eva Geraud, Louis Gerbaud Morlaes, Nuno Germano, Malak Ghemmeid, Praveen Kumar Ghisulal, Jade Ghosn, Marco Giani, Tristan Gigante, Elaine Gilroy, Guillermo Giordano, Michelle Girvan, Valérie Gissot, Gezy Giwangkancana, Daniel Glikman, Petr Glybochko, Eric Gnall, Geraldine Goco, François Goehringer, Siri Goepel, Jean-Christophe Goffard, Jin Yi Goh, Brigitta Golács, Jonathan Golob, Kyle Gomez, Joan Gómez-Junyent, Marie Gominet, Alicia Gonzalez, Patricia Gordon, Isabelle Gorenne, Laure Goubert, Cécile Goujard, Tiphaine Goulenok, Margarite Grable, Jeronimo Graf, Edward Wilson Grandin, Pascal Granier, Giacomo Grasselli, Lorenzo Grazioli, Christopher A. Green, Courtney Greene, William Greenhalf, Segolène Greffe, Domenico Luca Grieco, Matthew Griffee, Fiona Griffiths, Ioana Grigoras, Albert Groenendijk, Fassou Mathias Grovogui, Heidi Gruner, Yusing Gu, Jérémie Guedj, Martin Guego, Anne-Marie Guerguerian, Daniela Guerreiro, Romain Guery, Anne Guillaumot, Laurent Guilleminault, Maisa Guimarães de Castro, Thomas Guimard, Marieke Haalboom, Daniel Haber, Ali Hachemi, Abdurrahman Haddud, Nadir Hadri, Wael Hafez, Fakhir Raza Haidri, Fatima Mhd Rida Hajij, Sheeba Hakak, Adam Hall, Sophie Halpin, Shaher Hamdan, Abdelhafeez Hamdi, Jawad Hameed, Ansley Hamer, Raph L. Hamers, Rebecca Hamidfar, Bato Hammarström, Naomi Hammond, Terese Hammond, Lim Yuen Han, Matly Hanan, Rashan Haniffa, Kok Wei Hao, Hayley Hardwick, Ewen M. Harrison, Janet Harrison, Samuel Bernard Ekow Harrison, Alan Hartman, Sulieman Hasan, Mohammad Ali Nabil Hasan, Mohd Shahnaz Hasan, Junaid Hashmi, Madiha Hashmi, Amoni Hassan, Ebtisam Hassanin, Muhammad Hayat, Ailbhe Hayes, Leanne Hays, Jan Heerman, Lars Heggelund, Ahmed Helmi, Ross Hendry, Martina Hennessy, Aquiles Rodrigo Henriquez-Trujillo, Maxime Hentzien, Diana Hernandez, Andrew Hershey, Liv Hesstvedt, Astarini Hidayah, Eibhlin Higgins, Rupert Higgins, Samuel Hinton, Hiroaki Hiraiwa, Haider Hirkani, Hikombo Hitoto, Antonia Ho, Yi Bin Ho, Alexandre Hoctin, Isabelle Hoffmann, Wei Han Hoh, Oscar Hoiting, Rebecca Holt, Jan Cato Holter, Juan Pablo Horcajada, Ikram Houas, Mabrouka Houderi, Catherine L. Hough, Stuart Houltham, Jimmy Ming-Yang Hsu, Jean-Sébastien Hulot, Abby Hurd, Iqbal Hussain, Aliae Mohamed Hussein, Mahmood Hussein, Fatima Ibrahim, Bashir Ibran, Samreen Ijaz, M. Arfan Ikram, Carlos Cañada Illana, Patrick Imbert, Muhammad Imran Ansari, Rana Imran Sikander, Hugo Inácio, Carmen Infante Dominguez, Yun Sii Ing, Mariachiara Ippolito, Vera Irawany, Sarah Isgett, Tiago Isidoro, Nadiah Ismail, Margaux Isnard, Mette Stausland Istre, Junji Itai, Daniel Ivulich, Danielle Jaafar, Salma Jaafoura, Hamza Jaber, Julien Jabot, Clare Jackson, Abubacarr Jagne, Stéphane Jaureguiberry, Denise Jaworsky, Florence Jego, Anilawati Mat Jelani, Synne Jenum, Ruth Jimbo-Sotomayor, Ong Yiaw Joe, Ruth Noemí Jorge García, Silje Bakken Jørgensen, Cédric Joseph, Mark Joseph, Swosti Joshi, Mercé Jourdain, Philippe Jouvet, Anna Jung, Hanna Jung, Dafsah Juzar, Ouifiya Kafif, Florentia Kaguelidou, Neerusha Kaisbain, Thavamany Kaleesvran, Sabina Kali, Karl Trygve Kalleberg, Smaragdi Kalomoiri, Muhammad Aisar Ayadi Kamaluddin, Armand Saloun Kamano, Zul Amali Che Kamaruddin, Nadiah Kamarudin, Kavita Kamineni, Darshana Hewa Kandamby, Kong Yeow Kang, Darakhshan Kanwal, Dyah Kanyawati, Mohamed Karghul, Pratap Karpayah, Todd Karsies, Daisuke Kasugai, Kevin Katz, Christy Kay, Lamees Kayyali, Seán Keating, Pulak Kedia, Andrea Kelly, Aoife Kelly, Claire Kelly, Niamh Kelly, Sadie Kelly, Yvelynne Kelly, Maeve Kelsey, Kalynn Kennon, Sommay Keomany, Maeve Kernan, Younes Kerroumi, Sharma Keshav, Shams Khail, Sarah Khaled, Imrana Khalid, Antoine Khalil, Irfan Khan, Quratul Ain Khan, Sushil Khanal, Abid Khatak, Krish Kherajani, Michelle E. Kho, Denisa Khoo, Ryan Khoo, Saye Khoo, Muhammad Nasir Khoso, Amin Khuwaja, Khor How Kiat, Yuri Kida, Peter Kiiza, Beathe Kiland Granerud, Anders Benjamin Kildal, Jae Burm Kim, Antoine Kimmoun, Detlef Kindgen-Milles, Nobuya Kitamura, Eyrun Floerecke Kjetland Kjetland, Paul Klenerman, Rob Klont, Gry Kloumann Bekken, Stephen R. Knight, Robin Kobbe, Paa Kobina Forson, Chamira Kodippily, Malte Kohns Vasconcelos, Sabin Koirala, Mamoru Komatsu, Franklina Korkor Abebrese, Volkan Korten, Stephanie Kouba, Mohamed Lamine Kourouma, Karifa Kourouma, Arsène Kpangon, Karolina Krawczyk, Ali Kredan, Vinothini Krishnan, Sudhir Krishnan, Oksana Kruglova, Anneli Krund, Pei Xuan Kuan, Ashok Kumar, Deepali Kumar, Ganesh Kumar, Mukesh Kumar, Dinesh Kuriakose, Ethan Kurtzman, Demetrios Kutsogiannis, Galyna Kutsyna, Ama Kwakyewaa Bedu-Addo, Sylvie Kwedi, Konstantinos Kyriakoulis, Marie Lachatre, Marie Lacoste, John G. Laffey, Nadhem Lafhej, Marie Lagrange, Fabrice Laine, Olivier Lairez, Sanjay Lakhey, Marc Lambert, François Lamontagne, Marie Langelot-Richard, Vincent Langlois, Eka Yudha Lantang, Marina Lanza, Cédric Laouénan, Samira Laribi, Delphine Lariviere, Stéphane Lasry, Sakshi Lath, Naveed Latif, Youssef Latifeh, Odile Launay, Didier Laureillard, Yoan Lavie-Badie, Andy Law, Cassie Lawrence, Teresa Lawrence, Minh Le, Clément Le Bihan, Cyril Le Bris, Georges Le Falher, Lucie Le Fevre, Quentin Le Hingrat, Marion Le Maréchal, Soizic Le Mestre, Gwenaël Le Moal, Vincent Le Moing, Hervé Le Nagard, Ema Leal, Marta Leal Santos, Biing Horng Lee, Heng Gee Lee, Su Hwan Lee, Jennifer Lee, Todd C. Lee, Yi Lin Lee, Gary Leeming, Bénédicte Lefebvre, Laurent Lefebvre, Benjamin Lefèvre, Sylvie LeGac, Merili-Helen Lehiste, Jean-Daniel Lelievre, François Lellouche, Adrien Lemaignen, Véronique Lemee, Anthony Lemeur, Gretchen Lemmink, Ha Sha Lene, Jenny Lennon, Rafael León, Marc Leone, Tanel Lepik, Quentin Lepiller, François-Xavier Lescure, Olivier Lesens, Mathieu Lesouhaitier, Amy Lester-Grant, Andrew Letizia, Sophie Letrou, Bruno Levy, Yves Levy, Claire Levy-Marchal, Katarzyna Lewandowska, Erwan L'Her, Gianluigi Li Bassi, Janet Liang, Ali Liaquat, Geoffrey Liegeon, Kah Chuan Lim, Wei Shen Lim, Chantre Lima, Bruno Lina, Lim Lina, Andreas Lind, Maja Katherine Lingad, Guillaume Lingas, Sylvie Lion-Daolio, Keibun Liu, Marine Livrozet, Patricia Lizotte, Antonio Loforte, Navy Lolong, Leong Chee Loon, Diogo Lopes, Dalia Lopez-Colon, Anthony L. Loschner, Paul Loubet, Bouchra Loufti, Guillame Louis, Silvia Lourenco, Lara Lovelace-Macon, Lee Lee Low, Marije Lowik, Jia Shyi Loy, Jean Christophe Lucet, Carlos M. Luna, Olguta Lungu, Miles Lunn, Liem Luong, Nestor Luque, Dominique Luton, Olavi Maasikas, Moïse Machado, Sara Machado, Gabriel Macheda, Mustafa Magzoub, Rafael Mahieu, Sophie Mahy, Ana Raquel Maia, Lars S. Maier, Oumou Maiga Ascofare, Mylène Maillet, Thomas Maitre, Nimisha Abdul Majeed, Maximilian Malfertheiner, Nadia Malik, Paddy Mallon, Fernando Maltez, Denis Malvy, Victoria Manda, Laurent Mandelbrot, Frank Manetta, Julie Mankikian, Edmund Manning, Aldric Manuel, Veronika Maráczi, Ceila Maria Sant′Ana Malaque, Flávio Marino, Samuel Markowicz, Ana Marques, Catherine Marquis, Laura Marsh, Brian Marsh, Megan Marshal, John Marshall, Celina Turchi Martelli, Dori-Ann Martin, Emily Martin, Guillaume Martin-Blondel, Alessandra Martinelli, F. Eduardo Martinez, Martin Martinot, Alejandro Martín-Quiros, Ana Martins, João Martins, Nuno Martins, Caroline Martins Rego, Gennaro Martucci, Olga Martynenko, Eva Miranda Marwali, Marsilla Marzukie, David Maslove, Sabina Mason, Sobia Masood, Fatma Masoud, Moise Massoma, Palmer Masumbe, Mohd Basri Mat Nor, Moshe Matan, Henrique Mateus Fernandes, Meghena Mathew, Christina Mathew, Mathieu Mattei, Laurence Maulin, Juergen May, Javier Maynar, Mayfong Mayxay, Thierry Mazzoni, Lisa Mc Sweeney, Colin McArthur, Naina McCann, Peter McCanny, Aine McCarthy, Anne McCarthy, Colin McCloskey, Rachael McConnochie, Sherry McDermott, Sarah E. McDonald, Aine McElroy, Samuel McElwee, Natalie McEvoy, Allison McGeer, Kenneth A. McLean, Paul McNally, Bairbre McNicholas, Edel Meaney, Cécile Mear-Passard, Maggie Mechlin, Nastia Medombou, Omar Mehkri, Ferruccio Mele, Luis Melo, Kashif Ali Memon, João João Mendes, Ogechukwu Menkiti, Kusum Menon, France Mentré, Alexander J. Mentzer, Emmanuelle Mercier, Noémie Mercier, Antoine Merckx, Mayka Mergeay-Fabre, Blake Mergler, António Mesquita, Roberta Meta, Osama Metwally, Agnès Meybeck, Dan Meyer, Alison M. Meynert, Vanina Meysonnier, Mehdi Mezidi, Céline Michelanglei, Isabelle Michelet, Efstathia Mihelis, Vladislav Mihnovit, Duha Milad Abdullah, Jennene Miller, Hugo Miranda-Maldonado, Nor Arisah Misnan, Nik Nur Eliza Mohamed, Nouralsabah Mohamed, Tahira Jamal Mohamed, Alaa Mohamed Ads, Ahmed Reda Mohamed Elsayed Abdelhalim, Libya Mohammed, Shrouk Fawze Mohammed Mostafa, Manahil Omer Abdelrahman Mohammedahmed, Omer Abdullah Mohammedelhassan, Asma Moin, Walaa Mokhtar, Elena Molinos, Brenda Molloy, Mary Mone, Agostinho Monteiro, Claudia Montes, Giorgia Montrucchio, Sarah Moore, Shona C. Moore, Lina Morales Cely, Marwa Morgom, Lucia Moro, Catherine Motherway, Ana Motos, Hugo Mouquet, Clara Mouton Perrot, Julien Moyet, Suleiman Haitham Mualla, Mohamed Muftah, Aisha Kalsoom Mufti, Ng Yong Muh, Mo'nes Muhaisen, Dzawani Muhamad, Jimmy Mullaert, Fredrik Müller, Karl Erik Müller, Daniel Munblit, Syed Muneeb Ali, Nadeem Munir, Laveena Munshi, Aisling Murphy, Patrick Murray, Marlène Murris, Srinivas Murthy, Himed Musaab, Alamin Mustafa, Mus'ab Mustafa, Dana Mustafa, Himasha Muvindi, Dimitra Melia Myrodia, Farah Nadia Mohd-Hanafiah, Behzad Nadjm, Dave Nagpal, Alex Nagrebetsky, Blanka Nagybányai-Nagy, Herwin Nanda Boudoin, Mangala Narasimhan, Nageswaran Narayanan, Prashant Nasa, Rashid Nasim Khan, Ahmad Nasrallah, Adel Gerges Nassif Metri, Alasdair Nazerali-Maitland, Nadège Neant, Holger Neb, Nikita Nekliudov, Matthew Nelder, Erni Nelwan, Raul Neto, Emily Neumann, Wing Yiu Ng, Pauline Yeung Ng, Anthony Nghi, Duc Nguyen, Orna Ni Choileain, Niamh Ni Leathlobhair, Nerissa Niba, Alistair D. 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Eoin West, Murray Wham, Bryan Whelan, Nicole White, Paul Henri Wicky, Aurélie Wiedemann, Surya Otto Wijaya, Keith Wille, Sue Willems, Bailey Williams, Patricia J. Williams, Virginie Williams, Jessica Wittman, Calvin Wong, Xin Ci Wong, Yew Sing Wong, Teck Fung Wong, Natalie Wright, Lim Saio Xian, Ioannis Xynogalas, Siti Rohani Binti Mohd Yakop, Masaki Yamazaki, Elizabeth Yarad, Yazdan Yazdanpanah, Nicholas Yee Liang Hing, Abdelrahman Yehia Mahmoud Abdelaal, Cécile Yelnik, Chian Hui Yeoh, Stephanie Yerkovich, Touxiong Yiaye, Toshiki Yokoyama, Hodane Yonis, Obada Yousif, Saptadi Yuliarto, Akram Zaaqoq, Marion Zabbe, Gustavo E. Zabert, Kai Zacharowski, Masliza Zahid, Maram Zahran, Nor Zaila Binti Zaidan, Maria Zambon, Miguel Zambrano, Alberto Zanella, Nurul Zaynah, Hiba Zayyad, Alexander Zoufaly, and David Zucman

Subjects
COVID-19, Non-respiratory symptoms, Respiratory symptoms, Risk factors, Mortality, Science (General), Q1-390, Social sciences (General), H1-99
Abstract

Background: COVID-19 is primarily known as a respiratory illness; however, many patients present to hospital without respiratory symptoms. The association between non-respiratory presentations of COVID-19 and outcomes remains unclear. We investigated risk factors and clinical outcomes in patients with no respiratory symptoms (NRS) and respiratory symptoms (RS) at hospital admission. Methods: This study describes clinical features, physiological parameters, and outcomes of hospitalised COVID-19 patients, stratified by the presence or absence of respiratory symptoms at hospital admission. RS patients had one or more of: cough, shortness of breath, sore throat, runny nose or wheezing; while NRS patients did not. Results: Of 178,640 patients in the study, 86.4 % presented with RS, while 13.6 % had NRS. NRS patients were older (median age: NRS: 74 vs RS: 65) and less likely to be admitted to the ICU (NRS: 36.7 % vs RS: 37.5 %). NRS patients had a higher crude in-hospital case-fatality ratio (NRS 41.1 % vs. RS 32.0 %), but a lower risk of death after adjusting for confounders (HR 0.88 [0.83–0.93]). Conclusion: Approximately one in seven COVID-19 patients presented at hospital admission without respiratory symptoms. These patients were older, had lower ICU admission rates, and had a lower risk of in-hospital mortality after adjusting for confounders.

Published
2024
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