Scientific Publications of the University of Toulouse II Le Mirail
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Deep Learning to Differentiate Parkinsonian Syndromes Using Multimodal Magnetic Resonance Imaging : A Proof‐of‐Concept Study
No full textInternational audienceBackground The differentiation between multiple system atrophy (MSA) and Parkinson's disease (PD) based on clinical diagnostic criteria can be challenging, especially at an early stage. Leveraging deep learning methods and magnetic resonance imaging (MRI) data has shown great potential in aiding automatic diagnosis. Objective The aim was to determine the feasibility of a three‐dimensional convolutional neural network (3D CNN)–based approach using multimodal, multicentric MRI data for differentiating MSA and its variants from PD. Methods MRI data were retrospectively collected from three MSA French reference centers. We computed quantitative maps of gray matter density (GD) from a T1‐weighted sequence and mean diffusivity (MD) from diffusion tensor imaging. These maps were used as input to a 3D CNN, either individually (“monomodal,” “GD” or “MD”) or in combination (“bimodal,” “GD‐MD”). Classification tasks included the differentiation of PD and MSA patients. Model interpretability was investigated by analyzing misclassified patients and providing a visual interpretation of the most activated regions in CNN predictions. Results The study population included 92 patients with MSA (50 with MSA‐P, parkinsonian variant; 33 with MSA‐C, cerebellar variant; 9 with MSA‐PC, mixed variant) and 64 with PD. The best accuracies were obtained for the PD/MSA (0.88 ± 0.03 with GD‐MD), PD/MSA‐C&PC (0.84 ± 0.08 with MD), and PD/MSA‐P (0.78 ± 0.09 with GD) tasks. Patients misclassified by the CNN exhibited fewer and milder image alterations, as found using an image‐based z score analysis. Activation maps highlighted regions involved in MSA pathophysiology, namely the putamen and cerebellum. Conclusions Our findings hold promise for developing an efficient, MRI‐based, and user‐independent diagnostic tool suitable for differentiating parkinsonian syndromes in clinical practice
Génération de soliton de cavité par self-injection locking sur un résonateur Fabry-Perot fibré avec puissance de pompe sub-100 mW
No full textNational audienceGénération de solitons par self-injection locking d'un DFB sur un résonateur Fabry-Perot fibré. Le processus de verrouillage est étudié analytiquement, incluant l'automodulation de phase. La théorie comme l'expérience révèlent un large intervalle de verrouillage assurant un accès stable à divers peignes de fréquences et un faible bruit de phase
Entropic Fluctuation Theorems for the Spin-Fermion Model
No full textInternational audienceWe study entropic fluctuations in the Spin-Fermion model describing an -level quantum system coupled to several independent thermal free Fermi gas reservoirs. We establish the quantum Evans-Searles and Gallavotti-Cohen fluctuation theorems and identify their link with entropic ancilla state tomography and quantum phase space contraction of non-equilibrium steady state. The method of proof involves the spectral resonance theory of quantum transfer operators developed by the authors in previous works
Measuring Variable Importance in Heterogeneous Treatment Effects with Confidence
No full textInternational audienceCausal machine learning holds promise for estimating individual treatment effects from complex data. For successful real-world applications of machine learning methods, it is of paramount importance to obtain reliable insights into which variables drive heterogeneity in the response to treatment. We propose PermuCATE, an algorithm based on the Conditional Permutation Importance (CPI) method, for statistically rigorous global variable importance assessment in the estimation of the Conditional Average Treatment Effect (CATE). Theoretical analysis of the finite sample regime and empirical studies show that PermuCATE has lower variance than the Leave-One-Covariate-Out (LOCO) reference method and provides a reliable measure of variable importance. This property increases statistical power, which is crucial for causal inference in the limited-data regime common to biomedical applications. We empirically demonstrate the benefits of PermuCATE in simulated and real-world health datasets, including settings with up to hundreds of correlated variables
LANGAGE DE SPÉCIFICATION PARALLEL-DEVS POUR LA MODÉLISATION : APPROCHE MATHÉMATIQUE ET GRAMMAIRE
No full textInternational audienceIn this article, we propose a new formal language called the Formal Parallel-DEVS Modeling Language (FPDEVSML) as a platform-independent specification of the Parallel-DEVS (PDEVS) formalism. The DEVS (Discrete Event Systems Specification) formalism enables the specification of discrete event models in a hierarchical and modular manner, providing a solid foundation for the modeling, simulation, and analysis of discrete systems. FPDEVSML is based on a grammar with a rigorous mathematical structure that formalizes the sets and mathematical objects used in PDEVS modeling. The main objective of the proposed approach is to provide a formal framework for specifying and analyzing a system and to improve interoperability between PDEVS simulators. FPDEVSML can be used as an intermediate target language for DSLs. The specified models can then be translated into different forms of code using code generators and then executed with various tools for model verification and execution.Dans cet article, nous proposons un nouveau langage formel, le Formal Parallel-DEVS Modeling Language (FPDEVSML), comme langage de spécification indépendante de la plateforme du formalisme Parallel-DEVS (PDEVS). Le formalisme DEVS (Discrete Event Systems Specification) permet de spécifier des modèles à événements discrets de manière hiérarchique et modulaire, offrant ainsi une base solide pour la modélisation, la simulation et l'analyse de systèmes discrets. FPDEVSML repose sur une grammaire dotée d'une structure mathématique rigoureuse qui formalise les ensembles et objets mathématiques utilisés dans la modélisation PDEVS. L'objectif principal de l'approche proposée est de fournir un cadre formel pour la spécification et l'analyse d'un système et d'améliorer l'interopérabilité entre les simulateurs PDEVS. FPDEVSML peut être utilisé comme langage cible intermédiaire pour les DSL. Les modèles spécifiés peuvent ensuite être traduits en différentes code des langages de programmation à l'aide de générateurs de code, puis exécutés avec divers outils de vérification et d'exécution de modèles
A weighted Hankel approach and Cramér–Rao bound analysis for quantitative acoustic microscopy imaging
No full textInternational audienceQuantitative acoustic microscopy (QAM) is a cutting-edge imaging modality that leverages very highfrequency ultrasound to characterize the acoustic and mechanical properties of biological tissues at microscopic resolutions. Radio-frequency signals are digitized and processed to yield two-dimensional maps. This paper introduces a weighted Hankel-based spectral method with a reweighting strategy to enhance robustness with regard to noise and reduce unreliable acoustic parameter estimates. Additionally, we derive, for the first time in QAM, Cramér–Rao bounds to establish theoretical performance benchmarks for acoustic parameter estimation. Simulations and experimental results demonstrate that the proposed method consistently outperform standard autoregressive approach under challenging conditions. These advancements promise to improve the accuracy and reliability of tissue characterization, enhancing the potential of QAM for biomedical applications
LSD's rapid antidepressant effects are modulated by 5-HT2B receptors
No full textInternational audienceRecent clinical trials show that serotonergic psychedelics, including the prototypical hallucinogen lysergic acid diethylamide (LSD), possess a great promise for treating affective disorders. Interestingly, LSD displays strong functional activity on 5-HT2B receptors and a modulatory role of the latter receptors in anxious and depressive-like behaviors has been reported. Using behavioral and in vivo electrophysiological tools in naive rats, the effects of acute administration of LSD were evaluated in the: forced swim test (FST), open field test, foot shock-induced ultrasonic vocalization, on the head-twitch response (HTR) and on the dorsal raphe serotonin 5-HT cell activity. By comparison, the antidepressant-, anxiolytic- and hallucinogenic-like effects of LSD were then assessed in naïve mice using the FST, the black & white box test and HTR. We show here that acute administration of LSD induced fast antidepressant-, anxiolytic- and hallucinatory-like effects as well as a suppression of 5-HT neuronal activity that were all counteracted by the selective pharmacological blockade of 5-HT2B receptors, including the potent and selective 5-HT2B receptors antagonist RS-127445. Interestingly, depletion of 5-HT prevented the action of LSD in FST and HTR. In contrast in mice, acute injection of LSD failed to produce an antidepressant- or anxiolytic-like response, and the hallucinogenic-like effect of LSD was not altered by a pretreatment with RS-127445. Together, these findings indicate that LSD, acutely administered, acts as a rapid-onset antidepressant in naïve rat, but not in naïve mice, through mechanisms involving activation of 5-HT2B receptors
: Réflexions sur les méthodes d'enseignement du vocabulaire en chinois langue étrangère - l'impact des connaissances socio-culturelles sur l'acquisition du vocabulaire
No full textInternational audience汉语二外学习者可以利用猜词策略，在阅读过程中习得文中的生词。通过阅读学习生词的过程和结果受多方因素影响，例如学习者对汉语圈社会文化知识的了解程度等。在面向法语母语者的实际教学中，我们也发现，蕴含一定文化背景知识的中文词对于法国学生来说通常难以理解并记忆，且这类词往往没有相对应的法语词。为了探究这一因素在汉语二外词汇学习中的具体影响，我们进行了一项针对法语母语者的实验。实验结果表明，蕴含文化背景知识的中文词在词义猜测成功率和后续词义保留这两方面的总体表现不如其它类目标词。但值得注意的是，如果某个汉语词语义透明度高，且学习者掌握了这个词中构成字的含义，无论这个词在学习者的母语中是否存在，构成字都可以在词义理解和记忆方面起到积极作用。由此，我们建议对外汉语教师在教授蕴含文化背景的生词时应该借助更多元化的教材和方法进行直接、明晰的信息输入。此外，“字本位”理念应该在汉语词汇教学中被着重强调。在具体操作上，汉语教师应该帮助学生通过已掌握的字作为节点，建立并整合心理词汇网，以便学生更高效迅速地丰富他们的汉语词汇
Catecismos dialogados castellanos del xvi en tiempos de los coloquios de religión
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Les agriculteurs face au capitalisme de plateforme. Une analyse de la résistance aux plateformes numérique par les usages
No full textInternational audienceLes agriculteurs face au capitalisme de plateforme. Une analyse de la résistance aux plateformes numérique par les usages