Université de Bretagne Occidentale
Recent publications
Mercury’s motion has been studied using numerical methods in the framework of a model including only the non-relativistic Newtonian gravitational interactions of the solar system: eight major planets and Pluto in translation around the Sun. Since the true trajectory of Mercury is an open, non-planar curve, special attention to the exact definition of the advance of Mercury’s perihelion has been given. For this purpose, the concepts of an extended and a geometrical perihelion have been introduced. In addition, for each orbital period, a mean ellipse was fitted to the trajectory of Mercury. I have shown that the perihelion advance of Mercury deduced from the behavior of the Laplace–Runge–Lenz vector, as well as from the extended and geometrical perihelion advance depend on the fitting time interval and for intervals of the order of 1 000 years converge to a value of 532.1″\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^{\prime \prime }$$\end{document} per century. The behavior of the perihelia, either extended or geometrical, is strongly impacted by the influence of Jupiter. The advance of the extended perihelion depends on the time step used in the calculations, while the advance of the geometrical perihelion and that deduced by the rotation of the Laplace–Runge–Lenz vector depends only slightly on it.
In this article, we use Impoliteness Theory, defined as an intentional “face-threatening” deviant act, to understand consumer misbehavior in the luxury store subculture. Using a qualitative study based on Grounded Theory, we interviewed 14 luxury consumers and 18 salespeople working in luxury stores. We discovered that consumers use impoliteness in a normative exchange setting as a means of formulating their opposition to a brand’s symbolic violence. Our research on deviant consumer behavior in luxury stores brings to light a new concept: “Consumer-to-Brand Impoliteness”. Furthermore, we unveil four Consumer-to-Brand Impoliteness practices: “Being Crude”, “Interfering”, “Mastering”, and finally, “Blaspheming”. In a normative exchange context, understanding the underlying meanings of Consumer-to-Brand Impoliteness enables store managers to shape their responses according to the perceived level of such impoliteness practices.
Purpose Low-dose parenteral anticoagulation has demonstrated its efficacy for venous thromboembolism prophylaxis in randomized trials. However, current practice is not widely documented. In ambulatory settings, we aimed to provide an overview of the clinical use of low-dose parenteral anticoagulation in France and to assess the incidence of major bleeding and death rates. Methods A population-based prospective cohort study using the French national health data system (SNIIRAM) identified 142,815 adults living in five well-defined geographical areas who had a course of low-dose parenteral anticoagulants (a total of 150,389 courses) in the period 2013–2015. The main outcome measures were the types of low-dose parenteral anticoagulant, the duration and the clinical context. Adjusted incidence rate ratios (IRR) were derived from Poisson models. Results Enoxaparin was the most frequently prescribed anticoagulant (58.9%) followed by tinzaparin (27.3%) and fondaparinux (10.9%). Patients receiving unfractionated heparin (N = 766, 0.53%) were older, more frequently had renal disease (48.75%) and had a higher modified HAS-B(L)ED score (≥ 3 in 61.6%) than patients receiving low-molecular weight heparin (LMWH). Surgical thrombo-prophylaxis was the most frequent indication (47.6%), followed by medical prophylaxis (29.9%). Course durations were in line with regulatory agency specifications. Only 43 (0.028%) major bleeding events and 478 (0.32%) deaths were observed. Adjusted IRRs for major bleeding or death were not significantly different for dalteparin/nadroparin, tinzaparin or fondaparinux compared to enoxaparin. Conclusion Very low incidence rates of major bleeding and all-cause mortality were observed. Our study confirms the safety of LMWHs and fondaparinux in thrombo-prophylaxis in ambulatory settings. Trial registration ClinicalTrials.gov identifier: NCT02886533.
Professional fishing activities are subject to spatial pressures. The cohabitation between a traditional fishing activity and development of the offshore wind energy industry raises questions about space sharing and rules of use. This paper proposes to adapt the vulnerability methodology developed to deal with global threats of climate change to this example of local, non-climatic change using the case study of a floating wind turbine project between Groix and Belle-Île (France). To understand and compare the potential impact of the different artisanal fishing activities, the method aims to conceptualize vulnerability with the identification of social, economic, and environmental key pressures and address them in a composite index. Although the smallest fishing units appear to be the most vulnerable, this effect is associated with a high sensitivity to the area near the coast. This research also highlights the importance of transparency and clarity during the construction of the composite index to avoid misinterpretation. This case study supports the relevance of applying the vulnerability method on a local scale to facilitate dialogue between stakeholders and reduce negotiation costs.
Temporal correlations among demographic parameters can strongly influence population dynamics. Our empirical knowledge, however, is very limited regarding the direction and the magnitude of these correlations and how they vary among demographic parameters and species’ life histories. Here, we use long‐term demographic data from 15 bird and mammal species with contrasting pace of life to quantify correlation patterns among five key demographic parameters: juvenile and adult survival, reproductive probability, reproductive success and productivity. Correlations among demographic parameters were ubiquitous, more frequently positive than negative, but strongly differed across species. Correlations did not markedly change along the slow‐fast continuum of life histories, suggesting that they were more strongly driven by ecological than evolutionary factors. As positive temporal demographic correlations decrease the mean of the long‐run population growth rate, the common practice of ignoring temporal correlations in population models could lead to the underestimation of extinction risks in most species.
One of the physiological mechanisms that can limit a fish's ability to face hypoxia or elevated temperature, is maximal cardiac performance. Yet, few studies have measured how cardiac electrical activity and associated calcium cycling proteins change with acclimation to those environmental stressors. To examine this, we acclimated European sea bass for 6 weeks to three experimental conditions: a seasonal average temperature in normoxia (16 °C; 100% air sat.), an elevated temperature in normoxia (25 °C; 100% air sat.) and a seasonal average temperature in hypoxia (16 °C; 50% air sat.). Following each acclimation, the electrocardiogram was measured to assess how acclimation affected the different phases of cardiac cycle, the maximal heart rate (fHmax) and cardiac thermal performance during an acute increase of temperature. Whereas warm acclimation prolonged especially the diastolic phase of the ventricular contraction, reduced the fHmax and increased the cardiac arrhythmia temperature (TARR), hypoxic acclimation was without effect on these functional indices. We measured the level of two key proteins involved with cellular relaxation of cardiomyocytes, i.e. sarco(endo)plasmic reticulum Ca2+-ATPase (SERCA) and Na+/Ca2+ exchanger (NCX). Warm acclimation reduced protein level of both NCX and SERCA and hypoxic acclimation reduced SERCA protein levels without affecting NCX. The changes in ventricular NCX level correlated with the observed changes in diastole duration and fHmax as well as TARR. Our results shed new light on mechanisms of cardiac plasticity to environmental stressors and suggest that NCX might be involved with the observed functional changes, yet future studies should also measure its electrophysiological activity.
Objective: Sparse-view computed tomography (CT) reconstruction has been at the forefront of research in medical imaging. Reducing the total X-ray radiation dose to the patient while preserving the reconstruction accuracy is a big challenge. The sparse-view approach is based on reducing the number of rotation angles, which leads to poor quality reconstructed images as it introduces several artifacts. These artifacts are more clearly visible in traditional reconstruction methods like the filtered-backprojection (FBP) algorithm. Approach: Over the years, several model-based iterative and more recently deep learning-based methods have been proposed to improve sparse-view CT reconstruction. Many deep learning-based methods improve FBP-reconstructed images as a post- processing step. In this work, we propose a direct deep learning-based reconstruction that exploits the information from low-dimensional scout images, to learn the projection-to-image mapping. This is done by concatenating FBP scout images at multiple resolutions in the decoder part of a convolutional encoder-decoder (CED). Main results: This approach is investigated on two different networks, based on Dense Blocks and U-Net to show that a direct mapping can be learned from a sinogram to an image. The results are compared to two post-processing deep learning methods (FBP-ConvNet and DD-Net) and an iterative method that uses a total variation (TV) regularization. Significance: This work presents a novel method that uses information from both sinogram and low-resolution scout images for sparse-view CT image reconstruction. We also generalize this idea by demonstrating results with two different neural networks. This work is in the direction of exploring deep learning across the various stages of the image reconstruction pipeline involving data correction, domain transfer, and image improvement.
Background: Upper limb movement patterns have not yet been identified in bimanual conditions despite the difficulties children with unilateral cerebral palsy have performing bimanual activities. The aim was to identify specific motor patterns from kinematic deviations during bimanual tasks in this population. Methods: Twenty children with unilateral cerebral palsy and 20 age-matched, typically developing children performed the five tasks of a 3D bimanual protocol. To evaluate upper limb kinematic deviations, 10 Arm Variable Scores were calculated for the affected /non-dominant upper limb of each participant for each task. Sparse K-means cluster analysis was applied to the 50 Arm Variable Scores of all the children to identify motor patterns and determining variables. Clinical tests of impairment (muscle strength, selectivity, spasticity) and function (Assisting hand assessment, Abilhand-Kids) were compared between the clusters obtained. Findings: Three different motor patterns were identified using the data from all the children: mild, proximal-distal and proximal-distal with trunk. The most important cluster determinants were the Arm Variable Scores for pronation-supination and wrist extension. In the cerebral palsy group, scores of impairments (p < .01) and function (Assisting Hand Assessment [p < .001] and Abilhand-Kids [p = .004]) differed for each motor pattern. Supination and wrist extension deviations differed significantly between the groups (p < .001). Interpretation: During performance of bimanual tasks, children with unilateral cerebral palsy used distinct motor patterns that each corresponded to a specific clinical profile. Elbow-wrist deviations were the largest and most decisive and were specific to the cerebral palsy group: they should be the target of interventions to enhance bimanual function. Clinicaltrials: gov identifier: NCT03888443.
Double-Cantilever Beam (DCB) testing is a common protocol to evaluate bonded interface toughness. The data-analysis procedures are initially based on the classical Linear Elastic Fracture Mechanics (LEFM) and have been extended to deal with plastic behavior. Nevertheless, those analyses are not suitable when time-dependent behavior is involved in the crack propagation process. In this paper, an analysis of crack propagation along a viscoelastic interface during a DCB test is conducted, assuming a Standard Linear Solid (SLS) model for the adhesive. During the self-similar crack propagation regime, a steady-state stress–strain distribution is achieved ahead of the crack tip and a Eulerian description is used. A finite-difference scheme is implemented to solve the set of differential equations from which stress–strain evolutions along the bondline are determined as the specimen deforms. The crack propagation response under stationary loading conditions is then simulated and the energy-based failure criteria are evaluated comparing both local and global estimations of the Strain-Energy Release Rate (SERR).
Background Cardiovascular deaths (CVDTs) are more frequent in patients with venous thromboembolism (VTE) than in the general population; however, risk factors associated with this increased risk of CVDT in patients with VTE are not described. Methods To determine the risk factors of CVDT in patients with VTE from a multicenter prospective cohort study, Fine and Gray subdistribution hazard models were conducted. Results Of the 3,988 included patients, 426 (10.7%) died of CVDT during a median follow-up of 5 years. The risk factors of CVDT after multivariate analyses were: age of 50 to 65 years (vs. <50 years, hazard ratio [HR]: 3.22, 95% confidence interval [CI]: 1.67–6.62), age >65 years (vs. <50 years, HR: 7.60, 95% CI: 3.73–15.52), cancer-associated VTE (vs. transient risk factor-related VTE, HR: 1.73, 95% CI: 1.15–2.61), unprovoked VTE (vs. transient risk factor-related VTE, HR: 1.42, 95% CI: 1.02–2.00), past tobacco use (vs. never, HR: 1.43, 95% CI: 1.06–1.94), current tobacco use (vs. never, HR: 1.87, 95% CI: 1.15–3.01), hypertension (HR: 2.11, 95% CI: 1.51–2.96), chronic heart failure (HR: 2.28, 95% CI: 1.37–3.79), chronic respiratory failure (HR: 1.72, 95% CI: 1.02–2.89), and atrial fibrillation (HR: 1.67, 95% CI: 1.06–2.60). The risk of CVDT was significantly reduced with direct oral anticoagulants (vs. vitamin-K antagonists) and with longer duration of treatment (>3 months). Conclusion Risk factors of CVDT after VTE include some traditional cardiovascular risk factors and other risk factors that are related to characteristics of VTE, and patients' comorbidities.
The COVID-19 pandemic is not only a medical emergency but also a business emergency that has created the need for organizations to be resilient and versatile in managing the impact of the pandemic on their business operations. At this time, small- and medium-sized enterprises (SMEs) are the most vulnerable to the economic disaster caused by the recent crisis, because these companies do not have the necessary resources to absorb losses. This research reviewed the impact of digital technologies on SMEs’ resilience during the pandemic, focusing on companies in developing countries. Based on the 96 SMEs surveyed across six developing countries, the study shows that digital technology has helped SMEs to survive the pandemic, assisting SMEs in becoming more robust and ensuring their survival. This research fills a significant research gap in the literature, highlighting the inherent challenges of SMEs in developing countries and their digital transformation strategies. This study also offers practical recommendations for SMEs, tech developers, and policymakers to invest more effort in putting new procedures in place to ensure the efficacy of digital technology.
In IoT networks, authentication of nodes is primordial and RF fingerprinting is one of the candidates as a non-cryptographic method. RF fingerprinting is a physical-layer security method consisting of authenticated wireless devices using their components’ impairments. In this paper, we propose the RF eigenfingerprints method, inspired by face recognition works called eigenfaces. Our method automatically learns important features using singular value decomposition (SVD), selects important ones using Ljung–Box test, and performs authentication based on a statistical model. We also propose simulation, real-world experiment, and FPGA implementation to highlight the performance of the method. Particularly, we propose a novel RF fingerprinting impairments model for simulation. The end of the paper is dedicated to a discussion about good properties of RF fingerprinting in IoT context, giving our method as an example. Indeed, RF eigenfingerprint has interesting properties such as good scalability, low complexity, and high explainability, making it a good candidate for implementation in IoT context.
Tidal volume monitoring may help minimize lung injury during respiratory assistance. Surface imaging using time-of-flight camera is a new, non-invasive, non-contact, radiation-free, and easy-to-use technique that enables tidal volume and respiratory rate measurements. The objectives of the study were to determine the accuracy of Time-of-Flight volume (VTTOF) and respiratory rate (RRTOF) measurements at the bedside, and to validate its application for spontaneously breathing patients under high flow nasal canula. Data analysis was performed within the ReaSTOC data-warehousing project (ClinicalTrials.gov identifier NCT02893462). All data were recorded using standard monitoring devices, and the computerized medical file. Time-of-flight technique used a Kinect V2 (Microsoft, Redmond, WA, USA) to acquire the distance information, based on measuring the phase delay between the emitted light-wave and received backscattered signals. 44 patients (32 under mechanical ventilation; 12 under high-flow nasal canula) were recorded. High correlation (r = 0.84; p < 0.001), with low bias (-1.7 mL) and acceptable deviation (75 mL) was observed between VTTOF and VTREF under ventilation. Similar performance was observed for respiratory rate (r = 0.91; p < 0.001; bias < 1b/min; deviation ≤ 5b/min). Measurements were possible for all patients under high-flow nasal canula, detecting overdistension in 4 patients (tidal volume > 8 mL/kg) and low ventilation in 6 patients (tidal volume < 6 mL/kg). Tidal volume monitoring using time-of-flight camera (VTTOF) is correlated to reference values. Time-of-flight camera enables continuous and non-contact respiratory monitoring under high-flow nasal canula, and enables to detect tidal volume and respiratory rate changes, while modifying flow. It enables respiratory monitoring for spontaneously patients, especially while using high-flow nasal oxygenation.
Background The prevalence of peri-device leak (PDL) of left atrial appendage occlusion (LAAO) devices has been previously reported. However, there have been only few data that compared different existing devices. The aim of this study was to assess the incidence of PDL with both devices WATCHMAN®, Boston Scientific and AMPLATZER Amulet®, Abbott Laboratories and to evaluate the clinical outcome at 12 months.Methods Consecutive patients who underwent LAAO between January 2018 and 2020 were randomly assigned to either WATCHMAN or AMPLATZER Amulet implantation based on a systematic 2-week alternation between both devices. LAA measurements were assessed using cardiac computed tomography angiography (CCTA) prior to and transesophageal echocardiography (TEE) during the procedure. At 8 weeks post-LAAO, patients underwent TEE and/or CCTA to identify the presence of PDL and/or device-related complications. Patients were then followed for 12 months to identify major adverse cardiovascular/embolic events.ResultsThe cohort consisted of 51 patients (25 WATCHMAN, 26 AMPLATZER Amulet; mean age 76 ± 7 years; male gender 76%). Both groups were identically matched for demographics, comorbidities, and indication for LAAO. There were 19 patients who had PDL (13 WATCHMAN vs. 6 AMPLATZER Amulet, P-value = 0.033). Of them, 8 (15%) patients had significant PDL (7 WATCHMAN vs. 1 AMPLATZER Amulet, P-value = 0.018). On CCTA, the landing zone maximal diameter of the AMPLATZER Amulet device had the strongest correlation with the final deployed device size (Spearman’s rho 0.92, P-value < 0.0001). In the multivariate analysis, male gender and device type were independent predictors of any PDL (P-values 0.016 and 0.031, respectively). On a mean follow-up of 12 months, the total number of events was more prevalent in the WATCHMAN group (P-value 0.008), but the incidence of cardio-embolic events reached borderline significance (16% vs. 0%, P-value = 0.051).Conclusions Among patients who underwent LAAO, almost 15% had significant PDL with the majority belonging to the WATCHMAN group. Still, larger studies are warranted to evaluate its effectiveness in stroke prevention.
Marine business and resources play a major role in the economics and way of life in coastal West African countries. Such countries see great profitability from their marine resources while also facing challenges that come with a bordering sea. Despite this fact, there has been limited research into the optimal way for West African Coastal States to coexist with, and sustainably use their marine resources, a research deficit that is mainly due to a lack of infrastructure for in-situ work, lack of capacity development, and comprehensive datasets to undertake oceanographic research. The Coastal Ocean Environment Summer School in Ghana (COESSING; www.coessing.org) was developed to help meet some of these challenges. Each summer since 2015, ocean scientists (e.g., biologists, chemists, physicists, hydrologists) from the USA and Europe have collaborated with West African colleagues to lead a week-long intensive summer school in Accra, Ghana, alternating in location between the Regional Maritime University and the University of Ghana. The school receives in excess of 100 participants drawn from universities, government agencies, and the private sector organizations, mainly from Ghana and neighboring Liberia, Nigeria, Togo, and Benin, among others. The format of the school includes morning lectures, afternoon field trips, and hands-on laboratory exercises and one-on-one coaching of students. Important to the COESSING program is the satellite oceanography component which introduces participants to the extensive and often free, remotely sensed oceanographic datasets. Participants develop skills that allow them to access, process, and analyze these datasets in order to better understand regional oceanographic phenomena, such as upwelling, pollution, habitat characterization, sea level rise, and coastal erosion. Following the school, facilitators keep in touch with program participants, helping them acquire and analyze data for their studies, dissertations, and often graduate school applications, etc. In summary, schools such as COESSING are critical not only for science in the region but for the global ocean community as such training develops eager, bright minds while leading to improved regional observing and modeling strategies in severely under-sampled seas. Here, we describe a unique case in which satellite oceanography has led to such outcomes for countries bordering the Gulf of Guinea, West Africa.
Nowadays, cloud computing offers a digital infrastructure for smart city development. Cognitive cities are steadily automating daily urban processes. The ever expanding objective‐driven communities gather and share sensitive data that must be stored securely. Cloud computing offers a suitable platform that allows cognitive smart cities to access and re‐access data to learn from their past to adapt its current behaviour. However, the cloud is an untrusted entity that may expose data when decrypted for processing by systems. In this paper, we treat the issue of encrypted data processing. Often, the data is encrypted prior to transferring it to the cloud, where the cloud must have the data in clear to be able to make calculations which raises security and privacy threats if the cloud is considered untrusted. The scenario of asking users to make the calculations after decrypting the received cloud data and encrypting the obtained results before sending them back to the cloud is not a practical solution in distributed multi‐tenant architectures. Homomorphic encryption allows offers a solution for processing encrypted data. Many existing homomorphic encryption schemes suffer from limitations that hinder their usability. This paper presents an efficient fully homomorphic encryption scheme using twin key encryption and magic number fragmentation. The details of the scheme are presented along with cryptanalytic attacks to assess its effectiveness. The proposed scheme exhibits strong resilience against brute‐force attacks compared to its rivals from the literature. Finally, we illustrate the applicability of the proposed scheme using a cognitive smart city application.
Deep learning techniques have recently brought many improvements in the field of neural network training, especially for prognosis and health management. The success of such an intelligent health assessment model depends not only on the availability of labeled historical data but also on the careful samples selection. However, in real operating systems such as induction machines, which generally have a long reliable life, storing the entire operation history, including deterioration (i.e. bearings), will be very expensive and difficult to feed accurately into the training model. Other alternatives sequentially store samples that hold degradation patterns similar to real ones in damage behavior by imposing an accelerated deterioration. Labels lack and differences in distributions caused by the imposed deterioration will ultimately discriminate the training model and limit its knowledge capacity. In an attempt to overcome these drawbacks, a novel sequence-by-sequence deep learning algorithm able to expand the generalization capacity by transferring obtained knowledge from life cycles of similar systems is proposed. The new algorithm aims to determine health status by involving long short-term memory neural network as a primary component of adaptive learning to extract both health stage and health index inferences. Experimental validation performed using the PRONOSTIA induction machine bearing degradation datasets clearly proves the capacity and higher performance of the proposed deep learning knowledge transfer-based prognosis approach.
The paper deals with second-order evolution problems driven by time and state dependent maximal monotone operators with non-Lipschitz perturbations. Systems governed by a couple of an evolution inclusion involving time and state dependent maximal monotone operator and a differential equation with fractional derivatives are also investigated.
Out of various moving average filter (MAF)-based phase-locked-loop (PLL), quasi type-1 PLL (QT1-PLL) is widely adopted due to its fast dynamic performance, implementation simplicity, and harmonics rejection abilities. However, the performance of QT1-PLL deteriorates in the presence of an off-nominal frequency unbalanced grid voltage component. Moreover, the sensitivity towards the fundamental frequency negative sequence (FFNS) component is high. Hence, this paper proposes a novel enhanced QT1-PLL solution that is insensitive to unbalance in the grid voltage signal during off-nominal frequency conditions. The proposed adaptive phase detector makes it possible to estimate both the fundamental frequency positive sequence (FFPS) and FFNS components with a high degree of immunity against harmonics. Notably, the pre-loop separation of the FFPS and the FFNS components helps suppress the second harmonic oscillations for improving the parameter estimation accuracy. The loop-filter design of QT1-PLL remains unaffected and requires a proportional gain to estimate the fundamental phase and frequency information. To address the DC offset issue, a modified delayed signal cancellation method is also proposed, which can theoretically eliminates the DC offset for any arbitrary delay length. A small-signal model of the proposed PLL is developed for the sake of stability analysis. Comparative results are provided
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2,877 members
Muhammad Fahad Zia
  • UMR CNRS 6027 IRDL - Institut de Recherche Dupuy de Lôme
Alain Plantec
  • Département d'Informatique (Brest)
Yann Le Grand
  • Département de Physique
Jacques Déverchère
  • Institut Universitaire Européen de la Mer (IUEM)
Julien Thebault
  • Laboratoire des Sciences de l’Environnement Marin- LEMAR (UMR 6539)
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