Spatially-constrained clustering of ecological networks

Spatial ecological networks are widely used to model interactions between georeferenced biological entities (e.g., populations or communities). The analysis of such data often leads to a two-step approach where groups containing similar biological entities are firstly identified and the spatial information is used afterwards to improve the ecological interpretation. We develop an integrative approach to retrieve groups of nodes that are geographically close and ecologically similar. Our model-based spatially-constrained method embeds the geographical information within a regularization framework by adding some constraints to the maximum likelihood estimation of parameters. A simulation study and the analysis of real data demonstrate that our approach is able to detect complex spatial patterns that are ecologically meaningful. The model-based framework allows us to consider external information (e.g., geographic proximities, covariates) in the analysis of ecological networks and appears to be an appealing alternative to consider such data

Strategies for online inference of model-based clustering in large and growing networks

In this paper we adapt online estimation strategies to perform model-based clustering on large networks. Our work focuses on two algorithms, the first based on the SAEM algorithm, and the second on variational methods. These two strategies are compared with existing approaches on simulated and real data. We use the method to decipher the connexion structure of the political websphere during the US political campaign in 2008. We show that our online EM-based algorithms offer a good trade-off between precision and speed, when estimating parameters for mixture distributions in the context of random graphs.Comment: Published in at http://dx.doi.org/10.1214/10-AOAS359 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Academic workforce in France and the UK in historical perspectives

This historical exploration of the development of the academic workforce in the UK and France was triggered by the observation of significant similarities in contemporary debates on casualisation, and segmentation despite their distinctive HE systems. We develop a quantitative history of academic staff to understand why the differences in the two HE systems are not as significant in respect to labour market and working conditions. The new data show that connected processes of casualisation, professional segmentation, and sectorial differentiation are used to manage tensions between massification and staff recruitment in both countries, in a context of declining and increasingly unequal distribution of resources, producing inequalities within institutions, as within the profession itself. The reorganisation of the academic workforce during three periods of growth of HE systems under traditional, Fordist and managerial influences has incrementally produced three groups of permanent, casualised, and precarised staff and a dual academic labour market

Maxiset comparisons of procedures, application to choosing priors in a Bayesian nonparametric setting

In this paper our aim is to provide tools for easily calculating the maxisets of several procedures. Then we apply these results to perform a comparison between several Bayesian estimators in a non parametric setting. We obtain that many Bayesian rules can be described through a general behavior such as being shrinkage rules, limited, and/or elitist rules. This has consequences on their maxisets which happen to be automatically included in some Besov or weak Besov spaces, whereas other properties such as cautiousness imply that their maxiset conversely contains some of the spaces quoted above. We compare Bayesian rules taking into account the sparsity of the signal with priors which are combination of a Dirac with a standard distribution. We consider the case of Gaussian and heavy tail priors. We prove that the heavy tail assumption is not necessary to attain maxisets equivalent to the thresholding methods. Finally we provide methods using the tree structure of the dyadic aspect of the multiscale analysis, and related to Lepki's procedure, achieving strictly larger maxisets than those of thresholding methods

Étude de catalyseurs hydrosolubles pour la génération d’hydrogène vert par méthodes photocatalytiques

La synthèse de l'hydrogène est une alternative viable à l'utilisation du pétrole. Les méthodes telles que l’électrocatalyse font appel à une source d’énergie primaire, ce qui favorise les déchets générés par ces méthodes, de même que le gaspillage d’énergie. Bien qu’ayant de très faibles rendements, les systèmes photocatalytiques permettent la synthèse d’un hydrogène propre et quasi sans déchets. Une perspective permettant d’améliorer encore leur potentiel serait d’éliminer les solvants organiques tels que le DMF, qui sont nocif pour l’environnement et la santé des êtres vivants. Étant donné que le solvant doit être changé, il faut prendre garde à modifier le donneur d’électron sacrificiel et le photosensibilisateur en conséquence. La production de tels solvants est également source de pollution, ce qui atténue le potentiel environnemental de ces méthodes. L’objectif de ce travail est de développer et de tester de nouveaux catalyseurs hydro-solubles variés permettant une amélioration des performances photo-catalytiques actuelles ainsi qu’une performance acceptable dans l’eau. L’étude des propriétés catalytiques est réalisée par l’étude de systèmes homogènes conjugués principalement avec le [Ru(bpy)3]2+ en tant que photosensibilisateur et avec le triethanolamine (dans le DMF) et l’acide ascorbique (dans l’eau) en tant que donneur d’électron sacrificiel. Les catalyseurs présentés lors de ce travail sont des catalyseurs à base de polypyridyl, de cobaloximes et de N-imidoylamidine. Les catalyseurs à base de poly-pyridyl ont d’abord été étudiés puisqu’ils sont réputés pour leur performance en milieux aqueux. La seconde approche consistait à produire des catalyseurs à base de cobaloxime qui aient une performance relativement constante tout d’abord dans les solvants organiques, puis d’adapter ces performances en milieu aqueux. La troisième approche a été de tester des catalyseurs à base de N-imidoylamidine, ce type de catalyseurs n’ayant jamais été testé pour la production d’hydrogène, puis d’en étudier les performances dans l’objectif de paver la voie pour de futures recherches sur le sujet.The synthesis of hydrogen is a viable alternative to the use of petroleum. Methods such as electrocatalysis use a primary energy source, which reduces the waste generated by these methods, as well as the waste of energy. Although having very low yields, photocatalytic systems allow the synthesis of clean hydrogen with virtually no waste. One prospect to further improve their potential would be to eliminate organic solvents such as DMF, which are harmful to the environment and the health of living beings. Giving the fact that we change the solvent, we need to change the electron sacrificial donor and the photosensitizer as well. The production of such solvents is also a source of pollution, which reduces the environmental potential of these methods. The objective of this work is to develop and test various new water-soluble catalysts allowing an improvement of the current photo-catalytic performances as well as an acceptable performance in water. The study of the catalytic properties is carried out by the study of homogeneous conjugated systems mainly with [Ru(bpy)3]2+ as photosensitizer and with triethanolamine (in DMF) and ascorbic acid (in water) as a sacrificial electron donor. The catalysts presented during this work are catalysts based on polypyridyl, cobaloximes, and N-imidoylamidine. Poly-pyridyl-based catalysts were first studied because they are known for their performance in aqueous media. The second approach was to produce cobaloxime-based catalysts that had relatively constant performance first in organic solvents and then to match this performance in aqueous media. The third approach was to test catalysts based on N-imidoylamidine, as this type of catalyst have never been tested to produce hydrogen, then to study their performance to pave the way for future research on the subject

Adaptive Lasso and group-Lasso for functional Poisson regression

International audienceHigh dimensional Poisson regression has become a standard framework for the analysis of massive counts datasets. In this work we estimate the intensity function of the Poisson regression model by using a dictionary approach, which generalizes the classical basis approach , combined with a Lasso or a group-Lasso procedure. Selection depends on penalty weights that need to be calibrated. Standard methodologies developed in the Gaussian framework can not be directly applied to Poisson models due to heteroscedasticity. Here we provide data-driven weights for the Lasso and the group-Lasso derived from concentration inequalities adapted to the Poisson case. We show that the associated Lasso and group-Lasso procedures satisfy fast and slow oracle inequalities. Simulations are used to assess the empirical performance of our procedure, and an original application to the analysis of Next Generation Sequencing data is provided

Lung transplantation for interstitial lung disease in idiopathic inflammatory myositis: A cohort study

Connective tissue disease; Idiopathic inflammatory myopathy; Interstitial lung diseaseEnfermedad del tejido conectivo; Miopatía inflamatoria idiopática; Enfermedad pulmonar intersticialMalaltia del teixit conjuntiu; Miopatia inflamatòria idiopàtica; Malaltia pulmonar intersticialIn patients with interstitial lung disease (ILD) complicating classical or amyopathic idio-pathic inflammatory myopathy (IIM), lung transplantation outcomes might be affected by the disease and treatments. Here, our objective was to assess survival and prog-nostic factors in lung transplant recipients with IIM-ILD. We retrospectively reviewed data for 64 patients who underwent lung transplantation between 2009 and 2021 at 19 European centers. Patient survival was the primary outcome. At transplantation, the median age was 53 [46–59] years, 35 (55%) patients were male, 31 (48%) had clas-sical IIM, 25 (39%) had rapidly progressive ILD, and 21 (33%) were in a high- priority transplant allocation program. Survival rates after 1, 3, and 5 years were 78%, 73%, and 70%, respectively. During follow-up (median, 33 [7–63] months), 23% of patients developed chronic lung allograft dysfunction. Compared to amyopathic IIM, classical IIM was characterized by longer disease duration, higher-intensity immunosuppres-sion before transplantation, and significantly worse posttransplantation survival. Five (8%) patients had a clinical IIM relapse, with mild manifestations. No patient expe-rienced ILD recurrence in the allograft. Posttransplantation survival in IIM-ILD was similar to that in international all- cause- transplantation registries. The main factor as-sociated with worse survival was a history of muscle involvement (classical IIM). In lung transplant recipients with idiopathic inflammatory myopathy, survival was similar to that in all-cause transplantation and was worse in patients with muscle involvement compared to those with the amyopathic disease