Université de Picardie Jules Verne
Recent publications
The segmentation of tomographic images of the battery electrode is a crucial processing step, which will have an additional impact on the results of material characterization and electrochemical simulation. However, manually labeling X-ray CT images (XCT) is time-consuming, and these XCT images are generally difficult to segment with histographical methods. We propose a deep learning approach with an asymmetrical depth encode-decoder convolutional neural network (CNN) for real-world battery material datasets. This network achieves high accuracy while requiring small amounts of labeled data and predicts a volume of billions voxel within few minutes. While applying supervised machine learning for segmenting real-world data, the ground truth is often absent. The results of segmentation are usually qualitatively justified by visual judgement. We try to unravel this fuzzy definition of segmentation quality by identifying the uncertainty due to the human bias diluted in the training data. Further CNN trainings using synthetic data show quantitative impact of such uncertainty on the determination of material’s properties. Nano-XCT datasets of various battery materials have been successfully segmented by training this neural network from scratch. We will also show that applying the transfer learning, which consists of reusing a well-trained network, can improve the accuracy of a similar dataset.
Background Liberating patients from mechanical ventilation (MV) requires a systematic approach. In the context of a clinical trial, we developed a simple algorithm to identify patients who tolerate assisted ventilation but still require ongoing MV to be randomized. We report on the use of this algorithm to screen potential trial participants for enrollment and subsequent randomization in the Proportional Assist Ventilation for Minimizing the Duration of MV (PROMIZING) study. Methods The algorithm included five steps: enrollment criteria, pressure support ventilation (PSV) tolerance trial, weaning criteria, continuous positive airway pressure (CPAP) tolerance trial (0 cmH 2 O during 2 min) and spontaneous breathing trial (SBT): on fraction of inspired oxygen (F i O 2 ) 40% for 30–120 min. Patients who failed the weaning criteria, CPAP Zero trial, or SBT were randomized. We describe the characteristics of patients who were initially enrolled, but passed all steps in the algorithm and consequently were not randomized. Results Among the 374 enrolled patients, 93 (25%) patients passed all five steps. At time of enrollment, most patients were on PSV (87%) with a mean (± standard deviation) F i O 2 of 34 (± 6) %, PSV of 8.7 (± 2.9) cmH 2 O, and positive end-expiratory pressure of 6.1 (± 1.6) cmH 2 O. Minute ventilation was 9.0 (± 3.1) L/min with a respiratory rate of 17.4 (± 4.4) breaths/min. Patients were liberated from MV with a median [interquartile range] delay between initial screening and extubation of 5 [1–49] hours. Only 7 (8%) patients required reintubation. Conclusion The trial algorithm permitted identification of 93 (25%) patients who were ready to extubate, while their clinicians predicted a duration of ventilation higher than 24 h .
Undoped and RE 3+ (RE: Pr; Nd; Dy; Ho; Tm) doped 0.925Na 0.5 Bi 0.5 TiO 3-0.075K 0.5 Na 0.5 NbO 3 (NBTKN0.075/NBTKN0.075-RE) ceramics were synthesized using the solid-state synthesis method. X-ray diffraction analysis revealed a pure perovskite structure without secondary phases. The Ho, Dy and Tm ions revealed a dielectric curve with a more diffused phase transition associated with a high value of the dielectric constant, while the lowest diffusivities were found for the Nd and Pr ions doped NBTKN0.075. The ferroelectric hysteresis loops show the significant increase of polarization and electric breakdown strengths (BDS) in all doped samples, accompanied by P-E shape changes under the influence of the different RE 3+ ions. In the optical studies, the conversion of near-infrared light to visible light was investigated for Ho 3+ and Dy 3+ doped NBTKN0.075. The sample with Ho 3+ produced a strong green-yellow up-conversion (UC) emission. At an excitation of λ ex = 800 nm, the blue-green UC emission of the Dy ion showed that the UC is due to the energy transfer interaction. CIE diagram with the corresponding (x, y) coordinates were used to clearly identify the overall color of the multichromatic spectral emissions in each spectrum. The additional functionality of up-conversion emission in the ferroelectric NBTKN0.075-RE material, and its positive effects on the electrical proprieties, open the possibility to realize multifunctionality in a wide range of applications.
Aims/hypothesis Diabetes has been recognised as a pejorative prognostic factor in coronavirus disease 2019 (COVID-19). Since diabetes is typically a disease of advanced age, it remains unclear whether diabetes remains a COVID-19 risk factor beyond advanced age and associated comorbidities. We designed a cohort study that considered age and comorbidities to address this question. Methods The Coronavirus SARS-CoV-2 and Diabetes Outcomes (CORONADO) initiative is a French, multicentric, cohort study of individuals with (exposed) and without diabetes (non-exposed) admitted to hospital with COVID-19, with a 1:1 matching on sex, age (±5 years), centre and admission date (10 March 2020 to 10 April 2020). Comorbidity burden was assessed by calculating the updated Charlson comorbidity index (uCCi). A predefined composite primary endpoint combining death and/or invasive mechanical ventilation (IMV), as well as these two components separately, was assessed within 7 and 28 days following hospital admission. We performed multivariable analyses to compare clinical outcomes between patients with and without diabetes. Results A total of 2210 pairs of participants (diabetes/no-diabetes) were matched on age (mean±SD 69.4±13.2/69.5±13.2 years) and sex (36.3% women). The uCCi was higher in individuals with diabetes. In unadjusted analysis, the primary composite endpoint occurred more frequently in the diabetes group by day 7 (29.0% vs 21.6% in the no-diabetes group; HR 1.43 [95% CI 1.19, 1.72], p<0.001). After multiple adjustments for age, BMI, uCCi, clinical (time between onset of COVID-19 symptoms and dyspnoea) and biological variables (eGFR, aspartate aminotransferase, white cell count, platelet count, C-reactive protein) on admission to hospital, diabetes remained associated with a higher risk of primary composite endpoint within 7 days (adjusted HR 1.42 [95% CI 1.17, 1.72], p<0.001) and 28 days (adjusted HR 1.30 [95% CI 1.09, 1.55], p=0.003), compared with individuals without diabetes. Using the same adjustment model, diabetes was associated with the risk of IMV, but not with risk of death, within 28 days of admission to hospital. Conclusions/interpretation Our results demonstrate that diabetes status was associated with a deleterious COVID-19 prognosis irrespective of age and comorbidity status. Trial registration ClinicalTrials.gov NCT04324736 Graphical abstract
Spatial neglect usually concerns left-sided events after right-hemisphere damage. Its anatomical correlates are debated, with evidence suggesting an important role for fronto-parietal white matter disconnections in the right hemisphere. Here, we describe the less frequent occurrence of neglect for right-sided events, observed in three right-handed patients after a focal stroke in the left hemisphere. Patients were tested 1 month and 3 months after stroke. They performed a standardized paper-and-pencil neglect battery and underwent brain MRI with both structural and diffusion tensor (DT) sequences, in order to assess both grey matter and white matter tracts metrics. Lesions were manually reconstructed for each patient. Patients presented signs of mild right-sided neglect during visual search and line bisection. One patient also showed pathological performance in everyday life. Structural MRI demonstrated left parietal strokes in two patients, in the region extending from the postcentral gyrus to the temporo-parietal junction. One of these two patients also had had a previous occipital stroke. The remaining patient had a left frontal stroke, affecting the precentral, the postcentral gyri and the basal ganglia. DT MRI tractography showed disconnections in the fronto-parietal regions, concerning principally the superior longitudinal fasciculus (SLF). These results suggest an important role for left SLF disconnection in right-side neglect, which complements analogous evidence for right SLF disconnection in left-side neglect.
Lithium and sodium (Na) mixed polyanion solid electrolytes for all-solid-state batteries display some of the highest ionic conductivities reported to date. However, the effect of polyanion mixing on the ion-transport properties is still not fully understood. Here, we focus on Na1+xZr2SixP3−xO12 (0 ≤ x ≤ 3) NASICON electrolyte to elucidate the role of polyanion mixing on the Na-ion transport properties. Although NASICON is a widely investigated system, transport properties derived from experiments or theory vary by orders of magnitude. We use more than 2000 distinct ab initio-based kinetic Monte Carlo simulations to map the compositional space of NASICON over various time ranges, spatial resolutions and temperatures. Via electrochemical impedance spectroscopy measurements on samples with different sodium content, we find that the highest ionic conductivity (i.e., about 0.165 S cm–1 at 473 K) is experimentally achieved in Na3.4Zr2Si2.4P0.6O12, in line with simulations (i.e., about 0.170 S cm–1 at 473 K). The theoretical studies indicate that doped NASICON compounds (especially those with a silicon content x ≥ 2.4) can improve the Na-ion mobility compared to undoped NASICON compositions.
Leaf area index (LAI) is a key variable in understanding and modeling crop-environment interactions. With the advent of increasingly higher spatial resolution satellites and sensors mounted on remotely piloted aircrafts (RPAs), the use of remote sensing in precision agriculture is becoming more common. Since also the availability of methods to retrieve LAI from image data have also drastically expanded, it is necessary to test simultaneously as many methods as possible to understand the advantages and disadvantages of each approach. Ground-based LAI data from three years of barley experiments were related to remote sensing information using vegetation indices (VI), machine learning (ML) and radiative transfer models (RTM), to assess the relative accuracy and efficacy of these methods. The optimized soil adjusted vegetation index and a modified version of the Weighted Difference Vegetation Index performed slightly better than any other retrieval method. However, all methods yielded coefficients of determination of around 0.7 to 0.9. The best performing machine learning algorithms achieved higher accuracies when four Sentinel-2 bands instead of 12 were used. Also, the good performance of VIs and the satisfactory performance of the 4-band RTM, strongly support the synergistic use of satellites and RPAs in precision agriculture. One of the methods used, Sen2-Agri, an open source ML-RTM-based operational system, was also able to accurately retrieve LAI, although it is restricted to Sentinel-2 and Landsat data. This study shows the benefits of testing simultaneously a broad range of retrieval methods to monitor crops for precision agriculture.
The viability of using Alfa fibers as reinforcement material for developing lightweight sustainable construction materials in compliance with the valorization of local by-products concept has been investigated in this work. The specimens were produced based on the mix of hydraulic lime binder (NHL5) and varied Alfa fiber amounts of 0 % (Control Specimen), 7 %, 11 %, and 15 % vol. as binder replacement. The hardened properties of Alfa reinforced specimens including dry density, porosity, compressive and flexural strengths, elastic behavior, and dry thermal conductivity at different temperatures were investigated. The results have indicated that the addition of Alfa induced a moderate reduction in compressive strength which in turn allows to increase the deformability of specimen. Therefore, the addition of Alfa fibers induces failure mode change of specimen from brittle to ductile behavior, which results in improvement of toughness capacity. Test-results also highlighted the flexural strength enhancement of reinforced specimen for optimal amount value of 7% fibers, which exhibits a typical “composite” behavior. The corresponding strengthening rate of 139.4 % higher is due to the several reinforcement mechanisms like the high tensile strength of Alfa fibers and their bond reinforcement to the binder matrix. This leads to promote the load transfer mechanism from binder matrix to fibers which results in supporting a part of applied load before post-cracking phase. However, the use of Alfa fibers will make the reinforced specimen performed as regards the thermal insulation, where the thermal conductivity-value satisfies the basic requirement for using the sample in lightweight construction field as insulating-bearing material, according to the RILEM “class III” recommendations.
In this paper we prove the monotonicity of positive solutions to -Δpu=f(u)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ -\Delta _p u = f(u) $$\end{document} in half-spaces under zero Dirichlet boundary conditions, for (2N+2)/(N+2)<p<2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(2N+2)/(N+2)< p < 2$$\end{document} and for a general class of regular changing-sign nonlinearities f. The techniques used in the proof of the main result are based on a fine use of comparison and maximum principles and on an adaptation of the celebrated moving plane method to quasilinear elliptic equations in unbounded domains.
This paper addresses the problems of distribution network design and gain sharing in a collaborative context. We propose mathematical models to compare the performance of three scenarios based on several sustainability indicators: logistics costs, CO2 emissions, created job opportunities, noise level, and accident risk. The scenarios assume multi-period transportation planning, performed by a heterogeneous fleet of vehicles. Mathematical models are used to determine the number of hubs, their capacities, and their locations, as well as the links between network nodes, the quantities transported, the quantities delayed, the inventory level, and the number and type of vehicles used in each period. Single-objective optimization is performed in an exact manner for small instances, while the genetic algorithm is used to solve large instances. Multi-objective resolution is performed using the ε-constraint method for small instances and the non-dominated sorting genetic algorithm II for large instances. We use a distribution network located in France for our numerical experiments. The costs of collaboration were shared by three approaches: egalitarian approach, volume method, and Shapley value. Experimental results and sensitivity analysis reveal some interesting findings: (1) it is always beneficial to design a collaborative distribution network; (2) relaxing delivery times and increasing the number of available vehicles further improve collaborative performance; and (3) cooperative game-theoretic approaches are most appropriate for sharing costs.
Biomembranes constitute the first lines of defense of cells. While small molecules can often permeate cell walls in bacteria and plants, they are generally unable to penetrate the barrier constituted by the double layer of phospholipids, unless specific receptors or channels are present. Antimicrobial or cell-penetrating peptides are in fact highly specialized molecules able to bypass this barrier and even discriminate among different cell types. This capacity is made possible by the intrinsic properties of its phospholipids, their distribution between the internal and external leaflet, and their ability to mutually interact, modulating the membrane fluidity and the exposition of key headgroups. Although common phospholipids can be found in the membranes of most organisms, some are characteristic of specific cell types. Here, we review the properties of the most common lipids and describe how they interact with each other in biomembrane. We then discuss how their assembly in bilayers determines some key physical-chemical properties such as permeability, potential and phase status. Finally, we describe how the exposition of specific phospholipids determines the recognition of cell types by membrane-targeting molecules.
Summary Background Data EA is the most frequent congenital esophageal malformation. Long gap EA remains a therapeutic challenge for pediatric surgeons. A case case-control prospective study from a multi-institutional national French data base was performed to assess the outcome, at age of 1 and 6 years, of long gap esophageal atresia (EA) compared with non-long gap EA/tracheo-esophageal fistula (TEF). The secondary aim was to assess whether initial treatment (delayed primary anastomosis of native esophagus vs. esophageal replacement) influenced mortality and morbidity at ages 1 and 6 years. Methods A multicentric population-based prospective study was performed and included all patients who underwent EA surgery in France from January 1, 2008 to December 31, 2010. A comparative study was performed with non-long gap EA/TEF patients. Morbidity at birth, 1 year, and 6 years was assessed. Results Thirty-one patients with long gap EA were compared with 62 non-long gap EA/TEF patients. At age 1 year, the long gap EA group had longer parenteral nutrition support and longer hospital stay and were significantly more likely to have complications both early post-operatively and before age 1 year compared with the non-long gap EA/TEF group. At 6 years, digestive complications were more frequent in long gap compared to non-long gap EA/TEF patients. Tracheomalacia was the only respiratory complication that differed between the groups. Spine deformation was less frequent in the long gap group. There were no differences between conservative and replacement groups at ages 1 and 6 years except feeding difficulties that were more common in the native esophagus group. Conclusions Long gap strongly influenced digestive morbidity at age 6 years.
This paper presents a parallel solution based on the coarse-grained multicomputer (CGM) model using the four-splitting technique to solve the optimal binary search tree problem. The well-known sequential algorithm of Knuth solves this problem in O(n^2) time and space, where n is the number of keys used to build the optimal binary search tree. To parallelize this algorithm on the CGM model, the irregular partitioning technique, consisting in subdividing the dependency graph into subgraphs (or blocks) of variable size, has been proposed to tackle the trade-off of minimizing the number of communication rounds and balancing the load of processors. This technique however induces a high latency time of processors (which accounts for most of the global communication time) because varying the blocks' sizes does not enable them to start evaluating some blocks as soon as the data they need are available. The four-splitting technique proposed in this paper solves this shortcoming by evaluating a block as a sequence of computation and communication steps of four subblocks. This CGM-based parallel solution requires O(n^2/\sqrt{p}) execution time with O( k x \sqrt{p}) communication rounds, where p is the number of processors and k is the number of times the size of blocks is subdivided. An experimental study conducted to evaluate the performance of this CGM-based parallel solution showed that compared to the solution based on the irregular partitioning technique where the speedup factor is up to x10.39 on one hundred and twenty-eight processors with 40960 keys when k = 2, the speedup factor of this solution is up to x13.12 and rises up to x14.93 when k = 5.
While best practices have been proposed on how to engage men in family planning (FP), the limited options of male hormonal contraceptives (MHC) are a barrier to reaching men as clients of FP programs. The lack of alternative MHC is preventing the global health community from providing holistic reproductive healthcare. A qualitative grounded theory study was conducted in 2020 to explore MHC experts' perceptions around the development and theoretical acceptability of MHCs. Individual in-depth interviews were conducted with 15 key informants. The informants cited evidence that there is a demand for MHC. The inability to access this data by the pharmaceutical industry was acknowledged. Many informants expressed concern of the possibility for MHC to increase male power in a predominantly patriarchal world. To most informants, at least for the initial introduction of MHC, fertility sharing is something that will largely happen among couples alone rather than individually. There is proven demand among women and men for MHC, however industries may still be reluctant to invest. Effort is needed by the sexual and reproductive health and rights community to include male engagement in FP and to advocate for the development and use of MHC as a tool for women's empowerment.
The number of deaths worldwide caused by COVID-19 continues to increase and the variants of the virus whose process we do not yet master are aggravating this situation. To deal with this global pandemic, early diagnosis has become important. New investigation methods are needed to improve diagnostic performance. A very large number of patients with COVID-19 have with cardiac arrhythmias often with ST segment elevation or depression on an electrocardiogram. Can ST-segment changes contribute to automatic diagnosis of COVID-19? In this article, we have tried to answer this question. We propose in this work a method for the automatic identification of COVID patients which exploits in particular the modifications of the ST segment observed on recordings of the ECG signal. Two sources of data allowed the development of the database for this study: 300 ECGs from the "physioNet" database with prior measurement of the ST segments, and 100 paper ECGs of patients from the cardiology department of the hospital X in Tunis registered on (non-covid) topics and covid topics. Four learning algorithms (ANN, CNN-LSTM, Xgboost, Random forest) were then applied on this database. The evaluation results show that CNN-LSTM and Xgboost present better accuracy in terms of classifying covid and non-covid patients with an accuracy rate of 87% and 88.7% respectively.
Pancreatic diseases, such as pancreatitis or pancreatic ductal adenocarcinoma, are characterized by the presence of activated pancreatic stellate cells (PSCs). These cells represent key actors in the tumor stroma, as they actively participate in disease development and progression: reprograming these PSCs into a quiescent phenotype has even been proposed as a promising strategy for restoring the hallmarks of a healthy pancreas. Since TRPM7 channels have been shown to regulate hepatic stellate cells proliferation and survival, we aimed to study the role of these magnesium channels in PSC activation and proliferation. PS-1 cells (isolated from a healthy pancreas) were used as a model of healthy PSCs: quiescence or activation were induced using all-trans retinoic acid or conditioned media of pancreatic cancer cells, respectively. The role of TRPM7 was studied by RNA silencing or by pharmacological inhibition. TRPM7 expression was found to be correlated with the activation status of PS-1 cells. TRPM7 expression was able to regulate proliferation through modulation of cell cycle regulators and most importantly p53, via the PI3K/Akt pathway, in a magnesium-dependent manner. Finally, the analysis of TCGA database showed the overexpression of TRPM7 in cancer-associated fibroblasts. Taken together, we provide strong evidences that TRPM7 can be considered as a marker of activated PSCs.
While the term hikikomori (HKM) has spread internationally to describe a chronic and severe form of social withdrawal, its place in current nosography and its transposition into non-Asian cultures are still debated. A retrospective chart review was conducted to determine the rate and the clinical profiles of HKM among a French sample of adolescent inpatients. Data were obtained from 191 adolescents aged 12–18 years ( M = 15.0, 44% boys) consecutively admitted in two inpatient units from January 2017 to December 2019. Using a retrospective diagnosis of HKM based on Teo and Gaw's criteria, we compared socio-demographic characteristics, clinical features, and treatment outcomes between HKM patients and those with other forms of social withdrawal and/or school refusal (SW/SR). At admission, 7% of participants met HKM criteria ( n = 14, M = 14.3, 64% boys), one out of six adolescents with SW/SR. Among those with SW/SR, HKM + vs. HKM- participants had higher rates of anxiety disorder (Odd Ratio, OR = 35.2) and lower disruptive behavioral disorder ( OR = 0.03). A minority of the participants with anxiety and depressive disorders met the HKM criteria (respectively, 15% and 9%), but those with HKM had a longer duration of symptoms, longer hospitalization, and required more daily care facilities at discharge compared to HKM-. While HKM syndrome could not be delimitated from anxiety disorder, it was associated with specific clinical features and treatment outcomes. The clinical characteristics observed were consistent with the features reported in Asian HKM adults, supporting face validity of this clinical concept in adolescent inpatients with different cultural contexts.
Some patients with subjective cognitive decline (SCD) progress to neurocognitive disorders (NCD), whereas others remain stable; however, the neuropsychological determinants of this progression have not been identified. Our objective was to examine baseline neuropsychological indicators that could discriminate between stable SCD Versus progression toward an NCD. We retrospectively included patients consulting for SCD at a university medical center's memory center (Amiens, France) who had undergone 3 or more neuropsychological assessments. Among the 80 patients with SCD, 11 had progressed to an NCD. The combination of age, memory, and speed scores at the baseline assessment predicted the progression of SCD with a sensitivity of 91%, and a negative predictive value of 98%. The present results constitute a first step (pending prospective studies) toward helping physicians to identify cases of SCD at risk of progression and, in particular, identifying patients with SCD who will not progress by examining baseline neuropsychological indicators. ClinicalTrials.gov ID: NCT04880252.
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2,958 members
Sophie Richardot
  • Département de Sciences de l'éducation
Ahmed El hajjaji
  • MIS - Modélisation, information et systèmes
Pierre-Marie Leprêtre
  • Research Unit of Sport Sciences and Physical Activities (UFR-STAPS) Lab. APERE - Adaptations physiologiques à l'exercice et réadaptation à l'effort
Yannick Gounden
  • CRP-CPO - Centre de recherche en psychologie : cognition, psychisme et organisations
33 rue saint Leu, 80000, Amiens, France