74 research outputs found
Polka des mineurs : pour le piano / par Maxime Barat ; [ill. par] G. Fraipont
No full textTitre uniforme : Barat, Maxime (18..-19.. ; compositeur). Compositeur. [Polka des mineurs. Piano]Polkas (piano) -- +* 1800......- 1899......+:19e siècle:Piano, Musique de -- +* 1800......- 1899......+:19e siècle
L'Unionum definitiones (CPG 7697, 18) attribué à Maxime le Confesseur : étude et édition du traité
No full textIn the present article devoted to the Unionum definitiones (CPG 7697, 18) attributed to Maximus the Confessor, the author examines the content (title and authenticity of the work) and its transmission, both direct and indirect. The latter, which is extremely important, attests of the great diffusion of the text. The article ends with the critical edition and the translation of the opuscule.REB 58 2000 France p. 123-147
Peter Van Deun, L'Unionum definitiones (CPG 7697, 18) attribué à Maxime le Confesseur : étude et édition du traité. — Dans cet article, consacré à l'Unionum definitiones (CPG 7697, 18), attribué à Maxime le Confesseur, l'auteur examine le contenu (titre et authenticité de l'ouvrage) et sa transmission, directe et indirecte. Celle-ci, très importante, témoigne de la large diffusion du texte. L'article se clôt par l'édition critique et la traduction de l'opuscule.Van Deun Peter. L'Unionum definitiones (CPG 7697, 18) attribué à Maxime le Confesseur : étude et édition du traité. In: Revue des études byzantines, tome 58, 2000. pp. 123-147
Weak KAM theory for nonregular commuting Hamiltonians
No full textIn this paper we consider the notion of commutation for a pair of continuous and convex Hamiltonians, given in terms of commutation of their Lax-Oleinik semigroups. This is equivalent to the solvability of an associated multi-time Hamilton-Jacobi equation. We examine the weak KAM theoretic aspects of the commutation property and show that the two Hamiltonians have the same weak KAM solutions and the same Aubry set, thus generalizing a result recently obtained by the second author for Tonelli Hamiltonians. We make a further step by proving that the Hamiltonians admit a common critical subsolution, strict outside their Aubry set. This subsolution can be taken of class C-1,C-1 in the Tonelli case. To prove our main results in full generality, it is crucial to establish suitable differentiability properties of the critical subsolutions on the Aubry set. These latter results are new in the purely continuous case and of independent interest
Advanced imaging for the characterization and optimization of the management of adrenocortical tumors
No full textLes carcinome corticosurrénaliens (CCSs) sont des cancers rares de la surrénale, associés à un pronostic sombre. Les facteur pronostiques majeurs du CCS sont le stade au moment du diagnostic, la taille de la tumeur, et le caractère complet de la chirurgie. Les autres facteurs pronostiques disponibles sont principalement histologiques et moléculaires, et nécessitent pour être évalués un prélèvement par biopsie ou par résection. Une optimisation de l'évaluation précoce de l'imagerie préthérapeutique non invasive en utilisant des outils novateurs tel que la radiomique et l'intelligence artificielle pourrait permettre une stratégie personnalisée de la prise en charge des patients atteints de CCS. L'objectif de cette thèse était d'évaluer les capacités de l'imagerie préthérapeutique non invasive pour optimiser la stratification pronostique et la prise en charge des patients atteints de CCS. Cette thèse a eu lieu en deux parties. Tout d'abord deux revues systématiques sur l'état de l'art de l'imagerie des surrénales en général et plus spécifiquement sur la place de l'intelligence artificielle dans l'imagerie des surrénales ont été réalisées. Dans un second temps, tous les patients de plus de 18 ans traités chirurgicalement pour un CCS à l'hôpital Cochin ont été inclus entre 2007 et 2022. L'intégralité des dossiers a été revue, en particulier pour analyser les caractéristiques démographiques des patients, les paramètres pronostiques validés et la survie. Plusieurs évaluations ont ensuite été réalisées sur la prédiction de la résection hépatique des CCSs droits, la capacité de l'IRM à distinguer les CCS des adénomes surrénaliens pauvres en graisse et sur la stratification du risque de survie par l'utilisation de la radiomique. Pour la prédiction de la résection hépatique des CCSs droits, deux signes hautement reproductibles entre observateurs ont été trouvés. Il s'agissait du bombement focal du CCS dans le foie (OR : 60,00 ; IC à 95 % : 4,60-782,40 ; p < 0,001), et l'interruption des contours du CCS au contact du foie (OR : 126,00 ; 95 % IC : 6,82-2328,21 ; p < 0,001). Pour la distinction des CCS et des adénomes pauvres en graisse en IRM, un arbre diagnostique comprenant le coefficient apparent de diffusion et la chute de signal sur l'imagerie de déplacement chimique mesurée par l'index d'intensité du signal montrait une sensibilité de 75 % (IC à 95 % : 55-88), une spécificité de 76 % (IC à 95 % : 60-87) et une précision de 75 % (IC à 95 % : 55-88) sur une cohorte de validation externe. Enfin, concernant la prédiction de la survie par la radiomique, un modèle intégrant la taille de la tumeur, le stade ENSAT et le paramètre radiomique Shape Elongation mesurés sur l'imagerie pré-opératoire permettait de distinguer entre les patients ayant un bon pronostic et ceux ayant un mauvais pronostic. Ces données ont été confirmée sur une cohorte de validation externe issue du MD Anderson Cancer Center (Houston, TX, USA). Une analyse détaillée de l'imagerie non invasive pré-thérapeutique permet de mieux stratifier le pronostic des patients atteints de CCS et ouvre la voie à une prise en charge plus personnaliséeIntroduction : Adrenocortical carcinomas (ACCs) are rare cancers of the adrenal gland, associated with a poor prognosis. The major prognostic factors for ACCs are stage at diagnosis, tumor size, and completeness of surgery. Other prognostic factors available are mainly histological and molecular, requiring biopsy or resection sampling to be assessed. An optimization of the early evaluation of non-invasive pre-therapeutic imaging using innovative tools such as radiomics and artificial intelligence could allow a personalized strategy for the management of patients with ACCs. The objective of this work was to evaluate the capabilities of non-invasive pre-therapeutic imaging to optimize prognostic stratification and management of patients with ACC. Materials and methods : This thesis took place in two parts. First of all, two systematic reviews on the state of the art of adrenal imaging in general and more specifically on the place of artificial intelligence in adrenal imaging were carried out. Secondly, all patients over the age of 18 treated surgically for ACCs at Cochin Hospital were included between 2007 and 2022. All patient files were reviewed, in particular to analyze the demographic characteristics of the patients, validated prognostic parameters and survival. Several evaluations were then carried out on the prediction of hepatic resection of right ACCs, the ability of MRI to distinguish ACCs from lipid-poor adrenal adenomas and on the stratification of survival risk by the use of radiomics. Results : For the prediction of hepatic resection of right ACCs, two highly reproducible signs between observers were found. These were the focal bulging of the CCS in the liver (OR: 60.00; 95% CI: 4.60-782.40; p < 0.001), and the interruption of the contours of the CCS in contact with the liver ( OR: 126.00; 95% CI: 6.82-2328.21; p<0.001). For the distinction of SCCs and fat-poor adenomas on MRI, a diagnostic tree including apparent diffusion coefficient and signal drop on chemical shift imaging measured using signal intensity index showed a sensitivity of 75 % (95% CI: 55-88), specificity of 76% (95% CI: 60-87) and precision of 75% (95% CI: 55-88) on an external validation cohort. Finally, concerning the prediction of survival by radiomics, a model integrating the size of the tumor, the ENSAT stage and the radiomics parameter Shape Elongation measured on the preoperative imaging made it possible to distinguish between patients with a good prognosis and those with a poor prognosis. These data were confirmed on an external validation cohort from the MD Anderson Cancer Center (Houston, TX, USA). Conclusion : Detailed analysis of pre-treatment non-invasive imaging allows better stratification of the prognosis of patients with CCS and paves the way for more personalized management
Field/works #7: Natalija Miodragović and guest Ivana Franke.
No full textThis talk is part of the Field/Works Talks series, curated by Jen Clarke and Maxime Le Calvé and associated with the Field/Works exhibition ( https://antart.easaonline.org/ ). Softicity. The future architecture is soft. We developed a habit to inhabit the noisy reverb of sleek surface and the superimposed reflections in glass. The imaginary for the soft city needs diving into the mycelium scale. The soft city is more silent. The soft city is slower and it smells different. The soft city is interwoven with bodies, clothes and objects and it needs your attention, like your companion species do. We need courage and imagination to house the human earthlings in the post fossil, post concrete, fiber-based architectures. Online video performance has soft fungi environments collected during the fieldwork as background. It is a study for possible symbiotic cohabitation with new urban materiality. The instructions will engage public online to question the sensory modalities, the materiality and the intra-climate of personal habitat. The online collages and videos serve as the imaginary of a different, softer city. Until 2021, the online exhibition will become part of speculative research in atmospheres of fiber architectures. The Starting point for the interdisciplinary and experimental work of Natalija Miodragović M.A. (SCI-ARCH) are art and space as vehicles for social change. She works in cooperation with artists, scientists and in the field of academic research. The focus of the work is perception and understanding of space, lightweight, flexible, unfoldable and textile structures ( www.miodrago.net ). Currrently Excellenzcluster Matters of Activity, Image Space Material research group Object Space Agency 2016-2018 Foldable, Insulating Textiles in Architecture Prof. Lueling. Teaching: 2014-19 Institute for Architecture based Art TU Braunschweig, 2018 Weissensee academy of art berlin. Author with dreidreidrei Organ for Zionskirche Berlin, Serbian Pavilion EXPO 2010 and 2002–2015 with artist Tomas Saraceno, architect and co-author of series of projects and exhibitions like Geodesic Solar Ballloon, Biospheres etc. Ivana Franke is a visual artist based in Berlin. Her investigations with light approach the interface between consciousness and environment, focusing on perceptual thresholds. Recently her on-going project LIMITS OF PERCEPTION LAB continued in Savvy Berlin 2020 and "Resonance of the Unforeseen" were part of Yokohama Triennale 2020
L'Unionum definitiones (CPG 7697, 18) attribué à Maxime le Confesseur : étude et édition du traité
No full textIn the present article devoted to the Unionum definitiones (CPG 7697, 18) attributed to Maximus the Confessor, the author examines the content (title and authenticity of the work) and its transmission, both direct and indirect. The latter, which is extremely important, attests of the great diffusion of the text. The article ends with the critical edition and the translation of the opuscule.</jats:p
Forecasting of SARS-Cov-2 Infections within Dutch Municipalities using Spatio-Temporal Graph Neural Networks
No full textThis paper presents a novel approach to regional forecasting of SARS-Cov-2 infections one week ahead, which involves developing a municipality level COVID-19 dataset of the Netherlands and using a spatio-temporal graph neural network (GNN) to predict the number of infections. The developed model captures the spread of infectious diseases within municipalities over time using Gated Recurrent Units (GRUs) and the spatial interactions between municipalities using GATv2 layers. To the best of our knowledge, this model is the first to incorporate sewage data, the stringency index, and commuting information into GNN-based infection prediction. In experiments on the developed real-world dataset, we demonstrate that the model outperforms simple baselines and purely spatial or temporal models for the COVID-19 wild type, alpha, and delta variants. In combination with an average R2 of 0.795 for forecasting infections and of 0.899 for predicting the associated trend of these variants, we conclude that the model is well suited for predicting the spread of infectious diseases with similar disease dynamics in real world applications. To increase prediction performance and to improve the generalizability of the model for infectious diseases with more complex diseasedynamics, we recommend using additional (synthetic) data or expanding the regional forecasting scale in future work.Mechanical Engineering | Vehicle Engineering | Cognitive Robotic
Neurological and psychiatric risk trajectories after SARS-CoV-2 infection: an analysis of 2-year retrospective cohort studies including 1 284 437 patients
Get PDFBACKGROUND: COVID-19 is associated with increased risks of neurological and psychiatric sequelae in the weeks and months thereafter. How long these risks remain, whether they affect children and adults similarly, and whether SARS-CoV-2 variants differ in their risk profiles remains unclear. METHODS: In this analysis of 2-year retrospective cohort studies, we extracted data from the TriNetX electronic health records network, an international network of de-identified data from health-care records of approximately 89 million patients collected from hospital, primary care, and specialist providers (mostly from the USA, but also from Australia, the UK, Spain, Bulgaria, India, Malaysia, and Taiwan). A cohort of patients of any age with COVID-19 diagnosed between Jan 20, 2020, and April 13, 2022, was identified and propensity-score matched (1:1) to a contemporaneous cohort of patients with any other respiratory infection. Matching was done on the basis of demographic factors, risk factors for COVID-19 and severe COVID-19 illness, and vaccination status. Analyses were stratified by age group (age <18 years [children], 18–64 years [adults], and ≥65 years [older adults]) and date of diagnosis. We assessed the risks of 14 neurological and psychiatric diagnoses after SARS-CoV-2 infection and compared these risks with the matched comparator cohort. The 2-year risk trajectories were represented by time-varying hazard ratios (HRs) and summarised using the 6-month constant HRs (representing the risks in the earlier phase of follow-up, which have not yet been well characterised in children), the risk horizon for each outcome (ie, the time at which the HR returns to 1), and the time to equal incidence in the two cohorts. We also estimated how many people died after a neurological or psychiatric diagnosis during follow-up in each age group. Finally, we compared matched cohorts of patients diagnosed with COVID-19 directly before and after the emergence of the alpha (B.1.1.7), delta (B.1.617.2), and omicron (B.1.1.529) variants. FINDINGS: We identified 1 487 712 patients with a recorded diagnosis of COVID-19 during the study period, of whom 1 284 437 (185 748 children, 856 588 adults, and 242 101 older adults; overall mean age 42·5 years [SD 21·9]; 741 806 [57·8%] were female and 542 192 [42·2%] were male) were adequately matched with an equal number of patients with another respiratory infection. The risk trajectories of outcomes after SARS-CoV-2 infection in the whole cohort differed substantially. While most outcomes had HRs significantly greater than 1 after 6 months (with the exception of encephalitis; Guillain-Barré syndrome; nerve, nerve root, and plexus disorder; and parkinsonism), their risk horizons and time to equal incidence varied greatly. Risks of the common psychiatric disorders returned to baseline after 1–2 months (mood disorders at 43 days, anxiety disorders at 58 days) and subsequently reached an equal overall incidence to the matched comparison group (mood disorders at 457 days, anxiety disorders at 417 days). By contrast, risks of cognitive deficit (known as brain fog), dementia, psychotic disorders, and epilepsy or seizures were still increased at the end of the 2-year follow-up period. Post-COVID-19 risk trajectories differed in children compared with adults: in the 6 months after SARS-CoV-2 infection, children were not at an increased risk of mood (HR 1·02 [95% CI 0·94–1·10) or anxiety (1·00 [0·94–1·06]) disorders, but did have an increased risk of cognitive deficit, insomnia, intracranial haemorrhage, ischaemic stroke, nerve, nerve root, and plexus disorders, psychotic disorders, and epilepsy or seizures (HRs ranging from 1·20 [1·09–1·33] to 2·16 [1·46–3·19]). Unlike adults, cognitive deficit in children had a finite risk horizon (75 days) and a finite time to equal incidence (491 days). A sizeable proportion of older adults who received a neurological or psychiatric diagnosis, in either cohort, subsequently died, especially those diagnosed with dementia or epilepsy or seizures. Risk profiles were similar just before versus just after the emergence of the alpha variant (n=47 675 in each cohort). Just after (vs just before) the emergence of the delta variant (n=44 835 in each cohort), increased risks of ischaemic stroke, epilepsy or seizures, cognitive deficit, insomnia, and anxiety disorders were observed, compounded by an increased death rate. With omicron (n=39 845 in each cohort), there was a lower death rate than just before emergence of the variant, but the risks of neurological and psychiatric outcomes remained similar. INTERPRETATION: This analysis of 2-year retrospective cohort studies of individuals diagnosed with COVID-19 showed that the increased incidence of mood and anxiety disorders was transient, with no overall excess of these diagnoses compared with other respiratory infections. In contrast, the increased risk of psychotic disorder, cognitive deficit, dementia, and epilepsy or seizures persisted throughout. The differing trajectories suggest a different pathogenesis for these outcomes. Children have a more benign overall profile of psychiatric risk than do adults and older adults, but their sustained higher risk of some diagnoses is of concern. The fact that neurological and psychiatric outcomes were similar during the delta and omicron waves indicates that the burden on the health-care system might continue even with variants that are less severe in other respects. Our findings are relevant to understanding individual-level and population-level risks of neurological and psychiatric disorders after SARS-CoV-2 infection and can help inform our responses to them. FUNDING: National Institute for Health and Care Research Oxford Health Biomedical Research Centre, The Wolfson Foundation, and MQ Mental Health Research
A PROOF OF THE CAFFARELLI CONTRACTION THEOREM VIA ENTROPIC REGULARIZATION
Get PDFWe give a new proof of the Caffarelli contraction theorem, which states that the Brenier optimal transport map sending the standard Gaussian measure onto a uniformly log-concave probability measure is Lipschitz. The proof combines a recent variational characterization of Lipschitz transport map by the second author and Juillet with a convexity property of optimizers in the dual formulation of the entropy-regularized optimal transport (or Schrödinger) problem
Large-Scale Phenotyping Inferences: From Trees to Forest through Machine Learning
No full textThe genomics revolution has provided rapid gains in crop productivity by shortening the breeding
cycle of many commercial species. Genomic data is most useful when carefully linked to crop
phenotypic expression and environmental conditions (Dungey, et al., 2018). Within forests, individual
tree phenotyping is exceptionally challenging due to their considerable size, the long breeding cycle,
and the high variability of growing conditions (Pont, 2016). Advances in remote sensing and the
emergence of sophisticated methods for large data analytics provide a means for describing and
analysing phenotypic and environmental variation at a forest scale. This study outlines the development and implementation of a phenotyping system that provides
spatial estimates of stand productivity across a large plantation forest. Using a machine learning
method forest productivity was modelled from an extensive set of 18 million observations of 93
variables describing climate, forest management, genetics and terrain, extracted from environmental
surfaces, management records and LiDAR data (Watt, et al., 2013). The most important determinants
of productivity were the genetic information and seasonal air temperatures, followed by variables
describing the silvicultural treatment. The phenotyping method developed here can be used to
identify superior and inferior genotypes and estimate a productivity index for each site, which will
improve tree breeding and increase overall productivity across the forest. References Dungey, H. S., Dash, J. P., Pont, D., Clinton, P. W., Watt, M. S., & Telfer, E. J. (2018). Phenotyping Whole Forests Will Help to Track Genetic Performance. Trends in plant science. Pont, D. (2016). Assessment of individual trees using aerial laser scanning in New Zealand radiata pine forests. Watt, P., & Watt, M. S. (2013). Development of a national model of Pinus radiata stand volume from LiDAR metrics for New Zealand. International journal of remote sensing, 34(16), 5892-5904.ABOUT THE AUTHOR Maxime Bombrun is a data scientist in the Data Analytics team at Scion. He received a PhD in
image processing and geology from the University of Clermont-Ferrand, France, in 2015, and
completed a two-year post-doctoral fellowship in biomedicine at the University of Uppsala, Sweden.
His research interests include image processing, statistical learning and their application in data
science. He has published more than 15 papers, mostly in the field of image processing and data
analysis.</div
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