DiffECG: A Generalized Probabilistic Diffusion Model for ECG Signals Synthesis

In recent years, deep generative models have gained attention as a promising data augmentation solution for heart disease detection using deep learning approaches applied to ECG signals. In this paper, we introduce a novel approach based on denoising diffusion probabilistic models for ECG synthesis that covers three scenarios: heartbeat generation, partial signal completion, and full heartbeat forecasting. Our approach represents the first generalized conditional approach for ECG synthesis, and our experimental results demonstrate its effectiveness for various ECG-related tasks. Moreover, we show that our approach outperforms other state-of-the-art ECG generative models and can enhance the performance of state-of-the-art classifiers.Comment: under revie

Leveraging Statistical Shape Priors in GAN-based ECG Synthesis

Due to the difficulty of collecting electrocardiogram (ECG) data during emergency situations, ECG data generation is an efficient solution for dealing with highly imbalanced ECG training datasets. However, due to the complex dynamics of ECG signals, the synthesis of such signals is a challenging task. In this paper, we present a novel approach for ECG signal generation based on Generative Adversarial Networks (GANs). Our approach combines GANs with statistical ECG data modeling to leverage prior knowledge about ECG dynamics in the generation process. To validate the proposed approach, we present experiments using ECG signals from the MIT-BIH arrhythmia database. The obtained results show the benefits of modeling temporal and amplitude variations of ECG signals as 2-D shapes in generating realistic signals and also improving the performance of state-of-the-art arrhythmia classification baselines.Comment: 6 figures, 26 page

Semantic and Contextual Knowledge Representation for Lexical Disambiguation: Case of Arabic-French Query Translation

We present in this paper, an automatic query translation system in cross-language information retrieval (Arabic-French). For the lexical disambiguation, our system combines between two resources: a bilingual dictionary and a parallel corpus. To select the best translation, our method is based on a correspondence measure between two semantic networks. The first one represents the senses of ambiguous terms of the query. The second one is a semantic network contextually enriched, representing the collection of sentences responding to the query. This collection forms the knowledge base of our disambiguation method and it is obtained by alignment with the relevant sentences in Arabic. The evaluation of the proposed system shows the advantage of the contextual enrichment on the quality of the translation. We obtained a high precision, relatively proportional to the precision provided by the used alignment. Finally, our translation demonstrates its potential by comparing its Bleu score with that of Google translate.</p

Giant gastric lipoma mimicking well-differentiated liposarcoma

Authors report the case of a 51-year-old man, presenting with epigastralgia of recent onset. Physical exam was unremarkable. Endoscopy revealed a large, ulcerated, submucosal, antral tumor. CT scan reveals an antral mass with fat attenuation. The patient underwent a total gastrectomy. Macroscopic examination identified in the antral wall a 9-cm, well-circumscribed, nodular lesion, with a yellow, greasy cut surface. On histological examination, the tumor was composed of a mature adipocytes proliferation, showing significant variation in cell size, associated to some lipoblasts. Nuclei were sometimes large, slightly irregular, but without hyperchromasia nor mitosis. Diagnosis of a well-differentiated liposarcoma was suspected and molecular cytogenetic analyses showed no MDM2 nor CDK4 gene amplification on fluorescent in situ hybridization. The diagnosis of lipoma was made. Twelve months following surgery, the patient is doing well.Pan African Medical Journal 2012; 13:1

Training during the COVID-19 lockdown : knowledge, beliefs, and practices of 12,526 athletes from 142 countries and six continents

OBJECTIVE Our objective was to explore the training-related knowledge, beliefs, and practices of athletes and the influence of lockdowns in response to the coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). METHODS Athletes (n = 12,526, comprising 13% world class, 21% international, 36% national, 24% state, and 6% recreational) completed an online survey that was available from 17 May to 5 July 2020 and explored their training behaviors (training knowledge, beliefs/attitudes, and practices), including specific questions on their training intensity, frequency, and session duration before and during lockdown (March–June 2020). RESULTS Overall, 85% of athletes wanted to “maintain training,” and 79% disagreed with the statement that it is “okay to not train during lockdown,” with a greater prevalence for both in higher-level athletes. In total, 60% of athletes considered “coaching by correspondence (remote coaching)” to be sufficient (highest amongst world-class athletes). During lockdown, < 40% were able to maintain sport-specific training (e.g., long endurance [39%], interval training [35%], weightlifting [33%], most (83%) training for “general fitness and health maintenance” during lockdown. Athletes trained alone (80%) and focused on bodyweight (65%) and cardiovascular (59%) exercise/training during lockdown. Compared with before lockdown, most athletes reported reduced training frequency (from between five and seven sessions per week to four or fewer), shorter training sessions (from ≥ 60 to < 60 min), and lower sport-specific intensity (~ 38% reduction), irrespective of athlete classification. CONCLUSIONS COVID-19-related lockdowns saw marked reductions in athletic training specificity, intensity, frequency, and duration, with notable within-sample differences (by athlete classification). Higher classification athletes had the strongest desire to “maintain” training and the greatest opposition to “not training” during lockdowns. These higher classification athletes retained training specificity to a greater degree than others, probably because of preferential access to limited training resources. More higher classification athletes considered “coaching by correspondence” as sufficient than did lower classification athletes. These lockdown-mediated changes in training were not conducive to maintenance or progression of athletes’ physical capacities and were also likely detrimental to athletes’ mental health. These data can be used by policy makers, athletes, and their multidisciplinary teams to modulate their practice, with a degree of individualization, in the current and continued pandemic-related scenario. Furthermore, the data may drive training-related educational resources for athletes and their multidisciplinary teams. Such upskilling would provide athletes with evidence to inform their training modifications in response to germane situations (e.g., COVID related, injury, and illness).A specific funding was provided by the National Sports Institute of Malaysia for this study.The National Sports Institute of Malaysia.https://www.springer.com/journal/40279am2023Sports Medicin

COVID-19 lockdown : a global study investigating athletes’ sport classification and sex on training practices

PURPOSE : To investigate differences in athletes’ knowledge, beliefs, and training practices during COVID-19 lockdowns with reference to sport classification and sex. This work extends an initial descriptive evaluation focusing on athlete classification. METHODS : Athletes (12,526; 66% male; 142 countries) completed an online survey (May–July 2020) assessing knowledge, beliefs, and practices toward training. Sports were classified as team sports (45%), endurance (20%), power/technical (10%), combat (9%), aquatic (6%), recreational (4%), racquet (3%), precision (2%), parasports (1%), and others (1%). Further analysis by sex was performed. RESULTS : During lockdown, athletes practiced body-weight-based exercises routinely (67% females and 64% males), ranging from 50% (precision) to 78% (parasports). More sport-specific technical skills were performed in combat, parasports, and precision (∼50%) than other sports (∼35%). Most athletes (range: 50% [parasports] to 75% [endurance]) performed cardiorespiratory training (trivial sex differences). Compared to prelockdown, perceived training intensity was reduced by 29% to 41%, depending on sport (largest decline: ∼38% in team sports, unaffected by sex). Some athletes (range: 7%–49%) maintained their training intensity for strength, endurance, speed, plyometric, change-of-direction, and technical training. Athletes who previously trained ≥5 sessions per week reduced their volume (range: 18%–28%) during lockdown. The proportion of athletes (81%) training ≥60 min/session reduced by 31% to 43% during lockdown. Males and females had comparable moderate levels of training knowledge (56% vs 58%) and beliefs/attitudes (54% vs 56%). CONCLUSIONS : Changes in athletes’ training practices were sport-specific, with few or no sex differences. Team-based sports were generally more susceptible to changes than individual sports. Policy makers should provide athletes with specific training arrangements and educational resources to facilitate remote and/or home-based training during lockdown-type events.https://journals.humankinetics.com/view/journals/ijspp/ijspp-overview.xmlhj2023Sports Medicin

Détermination des contraintes internes par méthode dynamique résonante : application aux massifs revêtus

The aim of this work is to use a new vibratory formalism in order to determine the level of internal stresses in coated materials using the dynamic resonant method. This requires the improvement of vibratory formalism, which allows to link the stress level to the variation of resonance frequency in free flexural mode. This study was conducted by doing three different approaches: numerical, analytical and experimental measurements in real coating. Numerical simulations were conducted by finite element method in static mode to determine the stress distribution in depth. Furthermore, we made other numerical simulations in dynamic mode to evaluate the effect of these static results on the resonant frequency, in comparison with those of coated material without stress. At this stage, these numerical studies let us to develop the vibratory formalism analytically. To validate this latter formalism, we applied it in a real coating for measuring the stress level and we made comparisons with results from others methods(DRX/Stoney). This confrontation (numerical-analytical/experimental measurements) found that dynamic resonant method is efficient for coated material having a thickness ratio moreimportant than 0,01.L’objet de ce travail de thèse consiste à utiliser un formalisme vibratoire pour la détermination de contraintes dans les dépôts à l’aide de la méthode dynamique résonante. Ceci a nécessité le développement d’un formalisme vibratoire adapté aux massifs revêtus, en reliant le niveau de contrainte à la variation des fréquences de résonance mesurées. L’étude a été effectuée en menant trois approches en parallèle : numérique, analytique et expérimentale. En premier lieu, nous avons réalisé des simulations numériques par éléments finis, afin de déterminer la distribution de contraintes dans l’épaisseur d’une poutre composite contrainte et d’évaluer l’effet de ces profils de contraintes sur la fréquence de résonance. Les résultats numériques ont permis d’optimiser le développement d’un nouveau formalisme vibratoire analytique. Pour valider ce dernier formalisme, il nous a fallu l’appliquer sur des dépôts réels,en confrontation avec les résultats d’autres méthodes de mesures de contraintes (DRX/Stoney). Cette confrontation numérique-analytique/expérimentale a révélé que la méthode dynamique résonante est pertinente pour des systèmes de dépôts ayant des rapports d’épaisseur supérieur à0,01