Gaussian Mixture Regression model with logistic weights, a penalized maximum likelihood approach

We wish to estimate conditional density using Gaussian Mixture Regression model with logistic weights and means depending on the covariate. We aim at selecting the number of components of this model as well as the other parameters by a penalized maximum likelihood approach. We provide a lower bound on penalty, proportional up to a logarithmic term to the dimension of each model, that ensures an oracle inequality for our estimator. Our theoretical analysis is supported by some numerical experiments

Statistical learning for wind power : a modeling and stability study towards forecasting

We focus on wind power modeling using machine learning techniques. We show on real data provided by the wind energy company Ma{\"i}a Eolis, that parametric models, even following closely the physical equation relating wind production to wind speed are outperformed by intelligent learning algorithms. In particular, the CART-Bagging algorithm gives very stable and promising results. Besides, as a step towards forecast, we quantify the impact of using deteriorated wind measures on the performances. We show also on this application that the default methodology to select a subset of predictors provided in the standard random forest package can be refined, especially when there exists among the predictors one variable which has a major impact

Utilisation des activités exoenzymatiques microbiennes dans l'étude d'écosystèmes aquatiques

Les activités exoenzymatiques participent de façon importante à la transformation des composés organiques dans les milieux aquatiques, en particulier par hydrolyse de composés à haut poids moléculaire qui sont réduits en monomères ou en petits oligomères assimilables par les bactéries. Cette étape est un processus clé dans le fonctionnement de la boucle microbienne. De nature très diverse, les exoenzymes ont une localisation variable selon le Gram de la bactérie ; leur régulation se situe soit au niveau de leur synthèse, soit au niveau de l'expression de leur activité. Bien que certaines exoenzymes soient constitutives, l'inductibilité semble être le mode de fonctionnement le plus fréquent. L'intégration de ce processus dans des études globales sur le potentiel hydrolytique de milieux aquatiques nécessite quelques précautions dans la réalisation expérimentale et dans l'interprétation des données : variabilité intrinsèque différente selon l'exoenzyme considérée (de 7 % pour la glucosidase à 16 % pour la phosphatase), variabilité géographique importante (pouvant atteindre +/- 50 % à un mètre de distance) dans les milieux sédimentaires, ce qui nécessite la connaissance topographique du milieu étudié et la définition d'une stratégie d'échantillonnage préalable. Les méthodologies de prélèvements, en particulier en sédiments ou en substratums grossiers, présentent une certaine complexité de mise en oeuvre que n'ont pas, au moins à faible échelle, les prélèvements en colonne d'eau (hétérogénéité du milieu à l'échelle centi- voire millimétrique, densité de population très variable, diffusion de substrat nutritifs,...). Une standardisation du protocole expérimental est proposé.Dans l'optique d'études sur les capacités d'assimilation et de biodégradation de matière organique des systèmes aquatiques, les données d'activités exoenzymatiques nécessitent d'être couplées à d'autres mesures biologiques ou biochimiques : biomasse bactérienne et/ou phytoplanctonique (en particulier pour la phosphatase), analyse fine de la matière organique assimilable (par exemple, par classes : lipides, glucides, protides, dans leurs fractions dissoutes et particulaires).Exoenzymes play an important role in the transformation of organic compounds in aquatic environments : these biomolecules convert high molecular weight compounds by hydrolysis into monomeric or oligomeric compounds that are then assimilable by bacteria. This step is a key process in the microbial food web and microorganisms that produce exoenzymes are probably good competitors in aquatic environments.The different exoenzymes are located in different places on the cell membrane with respect to the bacterial cell wall type : exoenzymes of the gram negative bacteria are rather located on the outside of the cytoplasmic membrane or in the periplasm. Their regulation can be either at the level of exoenzyme synthesis or at the level of enzymatic expression. Their activity is generally described with a Michaelis-Menten equation. Most exoenzymes are inducible (phosphatase), but some are constitutive (aminopeptidase).The use of exoenzyme methods in the aquatic environment needs some care, both during application and interpretation. The intrinsic variability of enzyme activity differs with the type of exoenzyme : the more the activity is inducible, the higher is its variability : e. g. phosphatase (inducible : 16 %) in comparison with glucosidase (constitutive : 7 %). Experimental enzymatic substrates are in tact « model » molecules that are supposed to have the same behaviour as « natural » substrates : this is not always true.Spatial variability is also important in sedimentary environments : significant variations in activity exist, especially with depth and stratification of sediment, at a scale of 1 - 10 cm (± 50 %). A topographie knowledge of the studied environment and the definition of a suitable sampling strategy are thus very important. Sampling methodotogies in sediment, silt or coarse substrates are more difficult to set up than are those for the water column (heterogenous environment at the centimetre scale, variation of microbial population density, nutrient diffusion, gradients). The sampling of sediments with a corer, and the subsequent fractionation of the sediment into different layers for incubation in the laboratory, may modify the physicochemistry of the sediment and could influence bacterial activity (experimental artefact). A technique has been developed for incubation inside the corer in order to minimize perturbations but this technique is limited by the sediment granulometry. Conversely, homogenization of sediments allows a better standardization of experiments and yields more reproducible results.For studies on the assimilation capacity of aquatic ecosystems and biodegradation of organic matter, exoenzymatic activities data need to be associated with other biological or biochemical parameters : bacterial and/or phytoplanctonic biomass; precise analysis of assimilable organic matter in the particulate or dissolved phases; physicochemical data... Data concerning the modelling of exoenzyme activities in relation to parameters such as temperature or oxygen level are lacking. Integration of these data will afford a better overall understanding of the role of exoenzymes in the metabolism of aquatic environments, and will help establish the limits of the validity of this technique for global studies of the assimilation capacities and organic matter biodegradation in aquatic ecosystems

Effects of organic herbicides on phototrophic microbial communities in freshwater ecosystems

Over the past 15 years, significant research efforts have been channelled into assessing the effects of organic herbicides on freshwater phototrophic microbial communities. The results of this research are reviewed herein. Main conclusions could be summarized into 5 points: - Most relevant assessments of this sort have dealt with the effects of triazine and phenylurea herbicides. Herbicides from these chemical classes are often considered to be model compounds when photosystem-II inhibitors are studied. - Until the early 2000s, the vast majority of investigations conducted to evaluate herbicide effects on phototropic microbes were performed in micro- or meso-cosms. In such studies, herbicides were usually applied alone, and often at concentrations much higher than those detected in the environment. More recently, the trend has been towards more realistic and relevant studies, in which lower herbicide concentrations were considered, and compound mixtures or successive treatments were tested. Increasingly, in situ studies are being designed to directly evaluate microbial community responses, following chemical exposures in contaminated aquatic environments. - Several biological endpoints are used to evaluate how organisms in the phototrophic microbial community respond to herbicide exposure. These endpoints allow the detection of quantitative changes, such as chl a concentrations, total cell counts or periphytic biomass, qualitative changes such as community structure to algal diversity, or functional changes such as photosynthesis, respiration, etc. They could give different and complementary information concerning the responses of microbial communities. - In addition, PICT approaches, which have generally combined functional and structural measurements, may prove to be valuable for assessing both an immediate impact, and for factoring in the contamination history of an ecosystem at the community level. - A relevant assessment of pesticides effects should include details on environmental characterization, such as abiotic parameters (light, flow speed, nutrients content) or biotic parameters (diversity and structure of biofilms), as they control the bioavailability of pesticides and the exposure of microbial communities. To improve the value of ecotoxicological risk assessments, future research is needed in two key areas: first, the effects of pollutants at the community level must be detailed (new tools and new end points), and second, more effort must be directed to reinforcing the ecological relevance of toxicological investigations

Inégalités d'oracle et mélanges

This manuscript focuses on two functional estimation problems. A non asymptotic guarantee of the proposed estimator’s performances is provided for each problem through an oracle inequality.In the conditional density estimation setting, mixtures of Gaussian regressions with exponential weights depending on the covariate are used. Model selection principle through penalized maximum likelihood estimation is applied and a condition on the penalty is derived. If the chosen penalty is proportional to the model dimension, then the condition is satisfied. This procedure is accompanied by an algorithm mixing EM and Newton algorithm, tested on synthetic and real data sets. In the regression with sub-Gaussian noise framework, aggregating linear estimators using exponential weights allows to obtain an oracle inequality in deviation,thanks to pac-bayesian technics. The main advantage of the proposed estimator is to be easily calculable. Furthermore, taking the infinity norm of the regression function into account allows to establish a continuum between sharp and weak oracle inequalities.Ce manuscrit se concentre sur deux problèmes d'estimation de fonction. Pour chacun, une garantie non asymptotique des performances de l'estimateur proposé est fournie par une inégalité d'oracle. Pour l'estimation de densité conditionnelle, des mélanges de régressions gaussiennes à poids exponentiels dépendant de la covariable sont utilisés. Le principe de sélection de modèle par maximum de vraisemblance pénalisé est appliqué et une condition sur la pénalité est établie. Celle-ci est satisfaite pour une pénalité proportionnelle à la dimension du modèle. Cette procédure s'accompagne d'un algorithme mêlant EM et algorithme de Newton, éprouvé sur données synthétiques et réelles. Dans le cadre de la régression à bruit sous-gaussien, l'agrégation à poids exponentiels d'estimateurs linéaires permet d'obtenir une inégalité d'oracle en déviation, au moyen de techniques PAC-bayésiennes. Le principal avantage de l'estimateur proposé est d'être aisément calculable. De plus, la prise en compte de la norme infinie de la fonction de régression permet d'établir un continuum entre inégalité exacte et inexacte

Enhanced co-tolerance and co-sensitivity from long-term metal exposures of heterotrophic and autotrophic components of fluvial biofilms

Understanding the interactive effects of multiple stressors on ecosystems has started to become a major concern. The aim of our study was therefore to evaluate the consequences of a long-term exposure to environmental concentrations of Cu, Zn and As on the pollution induced community tolerance (PICT) of lotic biofilm communities in artificial indoor channels. Moreover, the specificity of the PICT was assessed by evaluating the positive and negative co-tolerance between these metals. Photosynthetic efficiency and substrate-induced respiration (SIR), targeting the autotrophic and heterotrophic communities respectively were used in short-term inhibition bioassays with Cu, Zn and As to assess sensitivities of preexposed biofilms to the metals tested. Diversity profiles of a phototrophic, eukaryotic and prokaryotic community in biofilms following the different treatments were determined and analyzed with principal component analysis. The results demonstrated that pre-exposure to metals induced structural shifts in the community and led to tolerance enhancements in the phototrophic and heterotrophic communities. On the other hand, whatever the functional parameter used (i.e. photosynthesis and SIR), communities exposed to Cu were more tolerant to Zn and vice versa. Furthermore, only phototrophic communities pre-exposed to As developed tolerance to Cu but not to Zn, whereas no co-tolerance between Cu and As was observed in the heterotrophic communities. Finally, phototrophic and heterotrophic communities exposed to Cu and Zn became more sensitive to As, reflecting a negative co tolerance between these metals. Overall, our findings support the fact that although the mode of action of the different metals is an important driver for the structure and thus the tolerance of the communities, it appears that the detoxification modes are the most important factors for the occurrence of positive or negative co-tolerance

Water-sediment exchanges control microbial processes associated with leaf litter degradation in the hyporheic zone: a microcosm study

The present study aimed to experimentally quantify the influence of a reduction of surface sediment permeability on microbial characteristics and ecological processes (respiration and leaf litter decomposition) occurring in the hyporheic zone (i.e. the sedimentary interface between surface water and groundwater). The physical structure of the water-sediment interface was manipulated by adding a 2-cm layer of coarse sand (unclogged systems) or fine sand (clogged systems) at the sediment surface of slow filtration columns filled with a heterogeneous gravel/sand sedimentary matrix. The influence of clogging was quantified through measurements of hydraulic conductivity, water chemistry, microbial abundances and activities and associated processes (decomposition of alder leaf litter inserted at a depth of 9 cm in sediments, oxygen and nitrate consumption by microorganisms). Fine sand deposits drastically reduced hydraulic conductivity (by around 8-fold in comparison with unclogged systems topped by coarse sand) and associated water flow, leading to a sharp decrease in oxygen (reaching less than 1 mg L(-1) at 3 cm depth) and nitrate concentrations with depth in sediments. The shift from aerobic to anaerobic conditions in clogged systems favoured the establishment of denitrifying bacteria living on sediments. Analyses performed on buried leaf litter showed a reduction by 30% of organic matter decomposition in clogged systems in comparison with unclogged systems. This reduction was linked to a negative influence of clogging on the activities and abundances of leaf-associated microorganisms. Finally, our study clearly demonstrated that microbial processes involved in organic matter decomposition were dependent on hydraulic conductivity and oxygen availability in the hyporheic zone