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International audience; Tipping point dynamics are fundamental drivers for sustainable transition pathways of social-ecological systems (SES). Current research predominantly analyzes how crossing tipping points causes regime shifts, however, the analysis of potential transition pathways from these social and ecological tipping points is often overlooked. In this paper, we analyze transition pathways and the potential outcomes that these may lead to via a stylized model of a system composed of interacting agents exploiting resources and, by extension, the overall ecosystem. Interactions between the social and the ecological system are based on a perception-exploitation framework. We show that the presence of tipping points in SES may yield counter-intuitive social-ecological transition pathways. For example, the high perception of an alarming ecological state among agents can provide short-term ecological benefits, but can be less effective in the long term, compared to a low-perception condition. This work also highlights how understanding non-linear interactions is critical for defining suitable transition pathways of any SES.

International audience; Small hydrophobic chemical compounds require solvents to produce suitable solutions for toxicological studies. However, some solvents can modify the biological properties of substances and therefore their toxicity. This specific issue has been raised for PEG-400 as an anti-inflammatory and anti-oxidative compound. Recently, in the context of the REACH Regulation, PEG-400 was used to test the in vivo genotoxicity of trimethylolpropane triacrylate (TMPTA) in the comet assay. TMPTA failed to increase DNA damage whereas it induces genotoxicity in vitro in DMSO. Therefore, we questioned whether PEG-400 could modify the genotoxicity of TMPTA. The aim of this study was to determine the potential impact of PEG-400 on the in vitro genotoxicity of TMPTA, compared to DMSO. TMPTA was dissolved in either PEG-400 or DMSO, and the induction of γH2AX and Caspase-3 was analyzed in HepG2 cells. TMPTA induced γH2AX and Caspase-3 with both PEG-400 and DMSO. However, TMPTA induced effects at 4-fold lower concentrations when PEG-400 is used as the solvent compared to DMSO. While genotoxic effects are observed at much lower concentrations with PEG-400, it does not modify the in vitro genotoxicity of TMPTA. However, further in vitro studies with small hydrophobic compounds should be done to clarify the effect of PEG-400. Moreover, in vivo studies should be performed to confirm that PEG-400 remains suitable for in vivo genotoxicity tests.

Due to several gaps remaining in the toxicological evaluation of nanomaterials (NMs), consumers and public health agencies have shown increasing concern for human health protection. In addition to aluminum (Al) microparticles, Al-containing nanomaterials (Al NMs) have been applied by food industry as additives and contact materials. Due to the limited amount of literature on the toxicity of Al NMs, this study aimed to evaluate the in vivo genotoxic potential of Al0 and Al2O3 NMs after acute oral exposure. Male Sprague-Dawley rats were administered three successive gavages at 6, 12.5 and 25 mg/kg bw. A comparison with AlCl3 was done in order to assess the potential effect of dissolution into Al ions. Both DNA strand breaks and oxidative DNA damage were investigated in six organs/tissues (duodenum, liver, kidney, spleen, blood and bone marrow) with the alkaline and the Fpg-modified comet assays. Concomitantly, chromosomal damage was investigated in bone marrow and colon with the micronucleus assay. The comet assay only showed DNA damage with Al2O3 NMs in bone marrow (BM), while AlCl3 induced slight but non-significant oxidative DNA damage in blood. No increase of chromosomal mutations was observed after treatment with the two Al MNs either in the BM or in the colons of rats.

We revisit some ideas of why farmers do not convert to organic farming from our previous article with a dynamic individual-based model. In this model, an agent’s decision on transitioning to organic is based on the comparison between the satisfaction with its current situation and the potential satisfaction with an alternative farming strategy. A farmer agent’s satisfaction is modeled with the theory of reasoned action. It is computed by comparing the agent’s outcomes over time and comparing its current outcome against those of other agents to whom it lends great credibility (“important others”). The first study is based on prototypical farm populations. In this chapter, the predicted conversion rate is studied with some French “cantons” having different practice intensities. The model is initialized with dairy farmers’ data in these “cantons” in 2000. The results show that the “cantons” characteristics have great impact on the virtual adoption rate. Intensive “cantons” convert less than extensive ones. Extensive farms having not very good environmental outcomes seem to convert the most.

This work aims to study the interaction effect of farm characteristics and social dynamics on the conversion to organic farming with an agent-based model. In the model, an agent’s decision on the conversion to organic farming is based on the comparison between the satisfaction with its current situation and the potential satisfaction with an alternative farming strategy. A farmer agent’s satisfaction is modeled with the Theory of Reasoned Action. It is computed by comparing the agent’s outcomes over time and comparing its outcomes against those of other agents to whom it lends great credibility (‘important others’). We initialize the model with the Agricultural Census’ data about the farm characteristics in 27 French “cantons”. The analysis of the simulations shows that farm characteristics are very important to predict the conversion. However, their distribution in the population can also strongly influence the simulation results due to social dynamics. Indeed the interaction between farms having similar or different characteristics can decrease or increase the adoption rate compared to what can be inferred only from farm characteristics.

FLAG-ERA FP7/H2020 project FuturICT 2.0 (2017-2020) "Large scale experiments and simulations for the second generation of FuturICT" was aimed to promote collaboration among engineering and social sciences. The Proceedings of Annotations involves the abstracts of articles published by project research groups and indexed in Scopus and/or Web of Science.

The drivers of conversion to organic farming, which is still a residual choice in agriculture, are poorly understood. Many scholars argue that farm characteristics can determine this choice but do not exclude the role of social dynamics. To study this issue, we developed an agent-based model in which agents' decisions to shift to organic farming are based on a comparison between satisfaction with the current situation and potential satisfaction with an alternative farming strategy. A farmer agent’s satisfaction is modelled using the Theory of Reasoned Action. This makes it necessary to compare an agent's productions over time with those of other agents to whom the former attributes considerable credibility (“important others†). Moreover, farmers make technical changes that affect their productions by imitating other credible farmers. While we first used this model to examine simple and abstract farm populations, here we also adapted it for use with data from an Agricultural Census concerning the farm characteristics of dairy farming in 27 French “cantons†. Based on domain expertise, data and previous research, we propose certain laws for modelling the impact of conversion on the farm production of milk and the environment. The simulations with “real†populations of farms confirm the important impact of farm characteristics. However, our results also suggest a complex impact of social dynamics that can favour or impede the diffusion of organic farming through dynamic implicit networks of similarity and credibility. We confirm the great importance of demographic changes in farm characteristics.

The development of nonparametric procedures for testing shape constraint (monotonicity, convexity, unimodality, etc.) has received increasing interest. Nevertheless, testing the k -monotonicity of a discrete density for k larger than 2 has received little attention. To deal with this issue, several testing procedures based on the empirical distribution of the observations have been developed. They are non-parametric, easy to implement and proven to be asymptotically of the desired level and consistent. An estimator of the degree of k -monotonicity of the distribution is presented. An application to the estimation of the total number of classes in a population is proposed. A large simulation study makes it possible to assess the performances of the various procedures.

Many efforts have been made in the last 30 years to develop more relevant in vitro models to study genotoxic responses of drugs and environmental contaminants. While 2D HepaRG cells are one of the most promising models for liver toxicology, a switch to 3D cultures that integrate both in vivo architecture and cell-cell interactions has occurred to achieve even more predictive models. Preliminary studies have indicated that 3D HepaRG cells are suitable for liver toxicity screening. Our study aimed to evaluate the response of HepaRG spheroids exposed to various genotoxic compounds using the single cell gel electrophoresis assay. HepaRG spheroids were used at 10 days after seeding and exposed for 24 and 48 hours to certain selected chemical compounds (methylmethansulfonate (MMS), etoposide, benzo[a]pyrene (B[a]P), cyclophosphamide (CPA), 7,12-dimethylbenz[a]anthracene (DMBA), 2-acetylaminofluorene (2-AAF), 4-nitroquinoline (4-NQO), 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP), 2-amino-3-methylimidazo[4,5-f]quinolone (IQ), acrylamide, and 2-4-diaminotoluene (2,4-DAT)). After treatment, the comet assay was performed on single cell suspensions and cytotoxicity was determined by the ATP assay. Comet formation was observed for all compounds except IQ, etoposide and 2,4-DAT. Treatment of spheroids with rifampicin increased CYP3A4 activity, demonstrating the metabolic capacity of HepaRG spheroids. These data on genotoxicity in 3D HepaRG spheroids are promising, but further experiments are required to prove that this model can improve the predictivity of in vitro models to detect human carcinogens.

National audience

Introduction: The Covid-19 epidemic has disrupted the management of chronic diseases and disrupted the majority of patient education programs in France. Adaptations via digital technology have been put in place. Objectives: Exploratory study evaluating feasibility and relevance of a web-based patient education program during the first lock-down related to Covid-19;reflections on the interest of web-workshops compared to face-to-face sessions. Method: Adaptation of a program on chronic polypathology led by a transverse patient education unit, for a weekly web-program with 5 web-workshops, self-training and organization of the team to the practice of web-workshops, collective reflections on the interest and limits of web-workshops. Results: From April 1st to the end of May 2020, 51 patients were included, and 32 completed an educational cycle (minimum 3 web-workshops). Out of an average of 6,1 educational objectives agreed at the beginning, 92,2% were totally or partially acquired. The average satisfaction at the end of each of the web-workshops was between 8.42 and 9.53 out of 10. Patients felt psychological support and a chance to break out of social isolation. Among the advantages and limitations of the web-workshops: better accessibility (geographical, availability), maintenance of remote group dynamics, technical limitations to be taken into account. Conclusion: The polypathology web-program with 5 web-workshops was deemed feasible, acceptable and relevant by patients and caregivers. The remote workshops appear to meet the needs of patients during a pandemic and beyond. © 2021 SETE. Introduction : L'epidemie a Covid-19 a bouleverse la prise en charge des maladies chroniques et a perturbe la majorite des programmes d'education therapeutique (ETP) en France. Des adaptations via le numerique se sont mises en place. Objectifs : Etude exploratoire evaluant la faisabilite et la pertinence d'un web-programme d'ETP pendant le premier confinement lie a la Covid-19 ;reflexions sur l'interet des web-ateliers par rapport au presentiel. Methode : Adaptation d'un programme sur la polypathologie chronique porte par une unite transversale d'education du patient (UTEP), pour un web-programme hebdomadaire avec 5 web-ateliers, auto-formation et organisation de l'equipe a la pratique des webateliers, reflexions collectives sur l'interet et les limites des web-ateliers. Resultats : Du 1er avril a fin mai 2020, 51 patients ont ete inclus, et 32 ont termine un cycle educatif (minimum 3 web-ateliers). Sur en moyenne 6,1 objectifs pedagogiques convenus au depart, 92,2% ont ete totalement ou partiellement acquis. La satisfaction moyenne a l'issue de chacun des web-ateliers se situait entre 8,42 et 9,53 sur 10. Les patients ont ressenti un soutien psychologique et une possibilite de sortir de l'isolement social. Parmi les avantages et limites des web-ateliers : meilleure accessibilite (geographique, disponibilite), maintien de la dynamique de groupe a distance, limites techniques a prendre en compte. Discussion et conclusion : Le web-programme polypathologie avec 5 web-ateliers a ete juge faisable, acceptable et pertinent par les patients et intervenants. Les ateliers en distanciel paraissent repondre aux besoins des patients en periode de pandemie et au-dela. © 2021 SETE. © 2021 BMJ Publishing Group. All rights reserved.

National audience

[Departement_IRSTEA]Territoires; International audience; We propose an agent-based model leading to a decrease or an increase of hostility between agents after a major cultural threat such as a terrorist attack. The model is inspired from the Terror Management Theory and the Social Judgement Theory. An agent has a cultural identity defined through its acceptance segments about each of three different cultural worldviews (i.e., Atheist, Muslim, Christian) of the considered society. An agent's acceptance segment is composed from its acceptable positions toward a cultural worldview, including its most acceptable position. An agent forms an attitude about another agent depending on the similarity between their cultural identities. When a terrorist attack is perpetrated in the name of an extreme cultural identity, the negatively perceived agents from this extreme cultural identity point of view tend to decrease the width of their acceptance segments in order to differentiate themselves more from the threatening cultural identity. We generated a set of populations with cultural identities compatible with data from a survey on attitudes among a large sample representative of the population of France; we then simulated the reaction of these agents facing a terrorist attack from Muslim extremists. For most populations, the average attitude toward Muslims becomes more negative. However, for some specific populations, we noticed the opposite effect as the average attitude of the population toward Muslims becomes less negative. In these populations, the Muslim agents strongly differentiate themselves from the terrorists' extreme cultural identity, and the other agents are aware of these changes. These reactions are due to particular properties of their cultural identities that are identified in this paper.

International audience; Plant breeding has always sought to develop crops able to withstand environmental stresses, but this is all the more urgent now as climate change is affecting the agricultural regions of the world. It is currently difficult to screen genetic material to determine how well a crop will tolerate various stresses. Multi-environment trials (MET) which include a particular stress condition could be used to train a genomic selection model thanks to molecular marker information that is now readily available. Our study focuses on understanding how and predicting whether a plant is adapted to a particular environmental stress. We propose a way to use genomic random regression, an extension of factorial regression, to model the reaction norms of a genotype to an environmental stress: the factorial regression genomic best linear unbiased predictor (FR-gBLUP). Twenty-eight wheat trials in France (3 years, 12 locations, nitrogen or water stress treatments) were split into two METs where different stresses limited grain number and yield. In MET1, drought at flowering was responsible for 46.7% of the genotype-by-environment (G x E) interactions for yield while in MET2, heat stress during booting was identified as the main factor responsible for G x E interactions, but that explained less of the interaction variance (33.6%). Since drought at flowering explained a fairly large variance in G x E in MET1, the FR-gBLUP model was more accurate than the additive gBLUP across all types of cross validation. Accuracy gains varied from 2.4% to 12.9% for the genomic regression to drought. In MET2 accuracy gains were modest, varying from 5.7% to 2.4%. When a major stress influencing G x E is identified, the FR-gBLUP strategy makes it possible to predict the level of adaptation of genotyped individuals to varying stress intensities, and thus to select them in silico. Our study demonstrates how genome-wide selection can facilitate breeding for adaptation.

[Departement_IRSTEA]Ecotechnologies [TR1_IRSTEA]MOTIVE [ADD1_IRSTEA]Adaptation des territoires au changement global [ADD2_IRSTEA]Bioéconomie territoriale; In the coming decades, agricultural systems will have to adapt to tremendouschallenges. Behavioral models have important potential to better understandand steer changes toward sustainability brought about by this context. Relyingon a literature review, we distinguish incremental changes (extensions of whatis already done) and transformational changes, which involve the reorientationof a considerable amount of farming activities. Transformational changesare particularly important in the context of global change. Existing integratedmodelling frameworks based on behavioral theories are suited for incrementalchanges, but remain limited for transformational changes. Qualitative studiesprovide important insights on two key aspects of transformational changes,learning and social relations, but they have not been explicitly oriented towardcomputer modelling yet. Based on this literature and three seminal decision-makingapproaches, we propose a description of transformational changeprocesses in farm decision-making, as a first step toward an implementationin agent-based models

We consider the estimation of the number N of present species in a given area at a given time, based on the abundances of species that have been observed. We adopt a nonparametric approach where the true abundance distribution p is only supposed to be convex. A definition for convex abundance distributions is proposed. A least-squares estimate of the truncated version of p under the convexity constraint is used. Two estimators of N are deduced, the asymptotic distribution of which are derived. We propose three different procedures, including a bootstrap one, to obtain a confidence interval for N and a standard error for its estimator. The performances of the estimators are assessed in a simulation study and compared with competitors. The proposed method is illustrated on several examples.

International audience; In 1997, Robert Axelrod wondered in a highly influential paper "If people tend to become more alike in their beliefs, attitudes, and behavior when they interact, why do not all such differences eventually disappear?" Axelrod’s question highlighted an ongoing quest for formal theoretical answers joined by researchers from a wide range of disciplines. Numerous models have been developed to understand why and under what conditions diversity in beliefs, attitudes and behavior can co-exist with the fact that very often in interactions, social influence reduces differences between people. Reviewing three prominent approaches, we discuss the theoretical ingredients that researchers added to classic models of social influence as well as their implications. Then, we propose two main frontiers for future research. First, there is urgent need for more theoretical work comparing, relating and integrating alternative models. Second, the field suffers from a strong imbalance between a proliferation of theoretical studies and a dearth of empirical work. More empirical work is needed testing and underpinning micro-level assumptions about social influence as well as macro-level predictions. In conclusion, we discuss major roadblocks that need to be overcome to achieve progress on each frontier. We also propose that a new generation of empirically-based computational social influence models can make unique contributions for understanding key societal challenges, like the possible effects of social media on societal polarization.

International audience; Volume 280, Supplement 1, Pages S1-S346 (20 October 2017)Abstracts of the 53rd Congress of the European Societies of Toxicology (EUROTOX)Bratislava, Slovakia, 10th–13th September, 2017Edited by Mumtaz Iscan and Helena KandarovaP-03-02-16 Aluminum on different forms is found in several goods: food addi- tives, medication, beverage, water treatment as well as cooking utensils. EFSA has established a tolerable weekly intake (TWI) of 1 mg/kg bw for human oral exposure (EFSA, 2008). Since the 2000s, due to the increasing use of nanoparticles (NP), aluminum NPs are expected to be more largely involved in human exposure although their effects on human health has not been fully characterized. Nevertheless, aluminum was depicted to cross epithelial barriers and to include neurotoxicity and embryotoxic- ity. As aluminum NPs may not behave as Al ions, their toxic effects must be investigated. In this study, we investigated the genotoxicity of Al, Al 2 O 3 NPs and the ionic form AlCl 3 on intestine, the contact organ fol- lowing oral exposure, and on liver, the main target organ for Al accumulation using both the alkaline comet assay and the Fpg- modified comet assay for highlighting potential oxidative damage. We observed DNA damage on the human intestinal Caco2 and hepatic HepaRG cells (exposure from 0.6 to 256 g/cm 2 ). How- ever, no genotoxicity was detected in duodenum and liver of male Sprague Dawley rats after 3 gavages as well as after 28 days oral treatment with 6, 12 and 25 mg/kg bw/day. This project was funded by Agence Nationale de la Recherche (ANR-13-IS10-0005-01).

International audience; This study aims to better understand why farmers do not convert to organic farming by studying decision trajectories in a dynamic agent-based model. In this model, an agent's decision on transitioning to organic is based on the comparison between satisfaction with its current situation and potential satisfaction with an alternative farming strategy. A farmer's satisfaction was modeled by borrowing from the Theory of Reasoned Action and computed by comparing the farmer's performance over time against the farming practices of other farmers to which he/she lends great credibility (important others). Analysis identified five different reasons why a farmer does not change strategy. Three are due to satisfaction or recovered satisfaction with the current situation. The conversion to organic farming is effectively a major change and cannot be envisaged if the farmer is currently satisfied. Satisfaction can be recovered when evaluation by the farmer or important others finds an improvement of the current situation. A farmer's decision to not convert can also be due to negative evaluations of organic farming by important others, or to dissatisfaction with the current situation being too transient to prompt the effort to convert. Summary for Managers A farmer's decision on whether or not to convert to organic farming is deeply influenced by his/her satisfaction with the current strategy and potential satisfaction under an alternative farming strategy. A farmer's satisfaction is computed by comparing the farmer's performance over time against the farming practices of other farmers to which he/she lends great credibility. The conversion to organic farming is effectively a major change, and a farmer will not envisage a change of strategy if he/she is satisfied with their current situation. A farmer's satisfaction can be recovered when evaluation by the farmer or social peers finds an improvement of the current situation. If a farmer's credible peers have a negative assessment of organic farming or if his/her own dissatisfaction with the current situation is too short-lived, then farmer will not convert to organic farming.

In plant breeding, one of the major challenges of genomic selection is to account for genotype-by-environment (G × E) interactions, and more specifically how varieties are adapted to various environments. Crop growth models (CGM) were developed to model the response of plants to environmental conditions. They can be used to characterize eco-physiological stresses in relation to crop growth and developmental stages, and thereby help to dissect G × E interactions. Our study aims at demonstrating how environment characterization using crop models can be integrated to improve both the understanding and the genomic predictions of G × E interactions. We evaluated the usefulness of using CGM to characterize environments by comparing basic and CGM-based stress indicators, to assess how much of the G × E interaction can be explained and whether gains in prediction accuracy can be made. We carried out a case study in wheat (Triticum aestivum) to model nitrogen stress in a CGM in 12 environments defined by year × location × nitrogen treatment. Interactions between 194 varieties of a core collection and these 12 different nitrogen conditions were examined by analyzing grain number. We showed that (i) CGM based indicators captured the G × E interactions better than basic indicators and that (ii) genomic predictions were slightly improved by modeling the genomic interaction with the crop model based characterization of nitrogen stress. A framework was proposed to integrate crop model environment characterization into genomic predictions. We describe how this characterization promises to improve the prediction accuracy of adaptation to environmental stresses.

We propose to estimate a metamodel and the sensitivity indices of a complex model m in the Gaussian regression framework. Our approach combines methods for sensitivity analysis of complex models and statistical tools for sparse non-parametric estimation in multivariate Gaussian regression model. It rests on the construction of a metamodel for aproximating the Hoeffding-Sobol decomposition of m. This metamodel belongs to a reproducing kernel Hilbert space constructed as a direct sum of Hilbert spaces leading to a functional ANOVA decomposition. The estimation of the metamodel is carried out via a penalized least-squares minimization allowing to select the subsets of variables that contribute to predict the output. It allows to estimate the sensitivity indices of m. We establish an oracle-type inequality for the risk of the estimator, describe the procedure for estimating the metamodel and the sensitivity indices, and assess the performances of the procedure via a simulation study., Nous considérons l’estimation d’un méta-modèle d’un modèle complexe m à partir des observations d’un n-échantillon dans un modèle de régression gaussien. Nous en déduisons une estimation des indices de sensibilité de m. Notre approche combine les méthodes d’analyse de sensibilité de modèles complexes et les outils statistiques de l’estimation non-paramétrique en régression multivariée. Elle repose sur la construction d’un méta-modèle qui approche la décomposition de Hoeffding-Sobol de m. Ce méta-modèle appartient à un espace de Hilbert à noyau reproduisant qui est lui-même la somme directe d’espaces de Hilbert, permettant ainsi une décomposition de type ANOVA. On en déduit des estimateurs des indices de sensibilité de m. Nous établissons une inégalité de type oracle pour le risque de l’estimateur, nous décrivons la procédure pour estimer le méta-modèle et les indices de sensibilité, et évaluons les performances de notre méthode à l’aide d’une étude de simulations.

International audience; Using the bounded-confidence model, with fixed uncertainties and extremists, we investigate how resilient the moderate mean opinion of a population is to the arrival in it of a new group of agents, when the energy of the opinion of this group extremeness x group size) is varied. We say moderate mean opinion is resilient when, even though it may become temporarily more extreme after the arrival of the new agents, it later recovers its moderate value. We show that such resilience is displayed up to a threshold value of the equivalent energy of the group. We also show that when the agent-based model spontaneously converges to a single extreme, then this energy threshold is nill.

International audience; We propose a hybrid microsimulation and agent-based model of mobility integrating migration and residential mobility. We tested it on the evolution of the population of the Cantal, a French “département” with 150,000 inhabitants. We calibrated it using various data sources from 1990 to 2006, and tested its predictions on other data of the same period and on the period 2007-2012. The spatial heterogeneity of the evolution is well reproduced and the model makes surprisingly correct predictions despite numerous simplifying assumptions. From this calibration we learnt more about how to model residential mobility and migration considering an agent-based model approach.

Synthetic amorphous silica (SAS) in its nanosized form is now used in food applications although the potential risks for human health have not been evaluated. In this study, genotoxicity and oxidative DNA damage of two pyrogenic (NM-202 and 203) and two precipitated (NM-200 and -201) nanosized SAS were investigated in vivo in rats following oral exposure. Male Sprague Dawley rats were exposed to 5, 10, or 20 mg/kg b.w./day for three days by gavage. DNA strand breaks and oxidative DNA damage were investigated in seven tissues (blood, bone marrow from femur, liver, spleen, kidney, duodenum, and colon) with the alkaline and the (Fpg)-modified comet assays, respectively. Concomitantly, chromosomal damage was investigated in bone marrow and in colon with the micronucleus assay. Additionally, malondialdehyde (MDA), a lipid peroxidation marker, was measured in plasma. When required, a histopathological examination was also conducted. The results showed neither obvious DNA strand breaks nor oxidative damage with the comet assay, irrespective of the dose and the organ investigated. Similarly, no increases in chromosome damage in bone marrow or lipid peroxidation in plasma were detected. However, although the response was not dose-dependent, a weak increase in the percentage of micronucleated cells was observed in the colon of rats treated with the two pyrogenic SAS at the lowest dose (5 mg/kg b.w./day). Additional data are required to confirm this result, considering in particular, the role of agglomeration/aggregation of SAS NMs in their uptake by intestinal cells.

International audience; We consider a simple model of agents modifying their opinion about themselves and about the others during random pair interactions. Two unexpected patterns emerge: (1) without gossips, starting from zero, agents' opinions tend to grow and stabilize on average at a positive value; (2) when introducing gossips, this pattern is inverted; the opinions tend to decrease and stabilize on average at a negative value. We show that these patterns can be explained by the relative influence of a positive bias on self-opinions and of a negative bias on opinions about others. Without gossips, the positive bias on self-opinions dominates, leading to a positive average opinion. Gossips increase the negative bias about others, which can dominate the positive bias on self-opinions, leading to a negative average opinion.

Social issues are generally discussed by highly-involved and less-involved people to build social norms defining what has to be thought and done about them. As self-involved agents share different attitude dynamics to other agents [Wood, W., Pool, G., Leck, K. and Purvis, D., Self-definition, defensive processing, and influence: The normative impact of majority and minority groups, J. Pers. Soc. Psychol. (1996) 1181–1193], we study the emergence and evolution of norms through an individual-based model involving these two types of agents. The dynamics of self-involved agents is drawn from [Huet, S. and Deffuant, G., Openness leads to opinion stability and narrowness to volatility, Adv. Complex Syst. 13 (2010) 405–423], and the dynamics of others, from [Deffuant, G., Neau, D., Amblard, F. and Weisbuch, G., Mixing beliefs among interacting agents, Adv. Complex Syst. 3 (2001) 87–98]. The attitude of an agent is represented as a segment on a continuous attitudinal space. Two agents are close if their attitude segments share sufficient overlap. Our agents discuss two different issues, one of which, called main issue, is more important for the self-involved agents than the other, called secondary issue. Self-involved agents are attracted to both issues if they are close to the main issue, but shift away from their peer’s opinion if they are only close on the secondary issue. Differently, non-self-involved agents are attracted by other agents when they are close on both the main and secondary issues. We observe the emergence of various types of extreme minor clusters. In one or different groups of attitudes, they can lead to an already-built moderate norm or a norm polarized on secondary and/or main issues. They can also push disagreeing agents gathered in different groups to a global moderate consensus.

[Departement_IRSTEA]DS [TR1_IRSTEA]METHODO / MODELIX; International audience; The test bed for evaluation and diagnosis (BED) is a simple device designed to perform a quick and automatic diagnosis of the engine of agricultural tractors. It compares the present performance of a tractor to the OECD test. Firstly, a test of the tractor is performed which measures the power take-off speed, the engine torque, the fuel consumption and several environmental variables. The performance curves of the tractor are then plotted against their official reference curves. A rule-based system (Scorpio) compares the present performance to the reference, analyses the differences and suggests which parts may be responsible for the lack of performance. A statistical validation of the expert system was carried out using a database of tests collected over 10 years. The output of the system was compared to the expert decision, which was available for more than a thousand records. This validation of the BED was confirmed by an in situ validation protocol conducted by a tractor repairer. The basic principles of the BED and the results of the validation studies are described.

International audience; 1. Many cultivated species can escape from fields and colonize seminatural habitats as feral populations. Of these, feral oilseed rape is a widespread feature of field margins and roadside verges. Although considered in several studies, the general processes leading to the escape and persistence of feral oilseed rape are still poorly known. Notably, it remains unclear whether these annuals form transient populations resulting mainly from seed immigration (either from neighbouring fields or during seed transport), or whether they show real ability to persist (either through self-recruitment or seed banks). 2. We conducted a 4-year large-scale study of factors involved in the presence of feral oilseed rape populations in a typical open-field area of France. The results were subjected to statistical methods suitable for analysing large data sets, based on a regression approach. We subsequently addressed the relative contribution of the ecological processes identified as being involved in the presence of feral populations. 3. Many feral oilseed rape populations resulted from seed immigration from neighbouring fields (about 35–40% of the observed feral populations). Immigration occurred at harvest time rather than at sowing. Around 15% of such populations were attributed to immigration through seed transport. 4. The other half resulted from processes of persistence, mainly through persistent seed banks (35–40% of the observed feral populations). This was all the more unexpected because seed banks have not yet been documented on road verges (despite being frequent within fields). Local recruitment was rare, accounting for no more than 10% of the feral populations. 5. Synthesis and applications. Understanding the dynamics of feral oilseed rape populations is crucial for evaluating gene flow over an agro-ecosystem. Our results show that, while many feral populations do come from annual seed dispersal, a significant number also result from seeds stored in the soil for several years. In the current context of coexistence and management of transgenic with non-transgenic crops, feral persistence and, especially, the seed bank contribution to the dynamics of feral populations need to be considered seriously. The latter, combined with self-recruitment, indicates a high potential for the persistence of transgenes and the possible emergence of gene-stacking

Microcystin-LR (MC-LR), involved in human and animal poisonings by cyanobacteria, has been shown to be both a potent tumour promoter in rat liver and an inhibitor of serine/threonine protein phosphatases, specifically PP1 and PP2A. The research on the genotoxic potential of MC-LR counts only few in vivo studies. In order to determine the target organs for DNA-damage induction by MC-LR, the single-cell gel electrophoresis (SCGE) or comet assay was performed in mice. Following a single oral administration of 2 and 4mg/kg bw of MC-LR, a statistically significant induction of DNA damage in blood cells was obtained after 3h. However, after an intra-peritoneal injection (ip), DNA lesions were mainly induced in the liver, but were also reported in the kidney, the intestine and the colon. The sensitivity of the ip route compared to the oral route suggested a difference in the bio-disponibility of the toxin. In any case, DNA damage was induced by MC-LR irrespective of the administration route. Among the target organs, the DNA damage induced in the intestinal tissues (ileum and colon) may contribute to an increased cancer risk.

International audience; This report proposes for a simple individual-based model of information filtering, while focusing in particular on some of its implications for the attitude toward an object. The model assumes that a filter selects only important features, with a higher threshold of importance when the attitude toward the feature is incongruent with the global attitude toward the object. Individuals transmit only features that are congruent with their global attitude. This article considers two variants of the model. To both applies that different orders of feature reception can lead to different attitudes. For instance, a positive attitude toward an object can at a certain point become negative, even though the object is globally neutral (the sum of the feature attitudes is zero). The interactions among individuals can significantly increase the probability of such non-rational attitudes.

[Departement_IRSTEA]Eaux [TR1_IRSTEA]QUASARE; We estimated the spatial distribution of 6 Mustelidae species in France using the data collected by the French national hunting and wildlife agency under the "small carnivorous species logbooks" program. The 1500 national wildlife protection officers working for this agency spend 80% of their working time traveling in the spatial area in which they have authority. During their travels, they occasionally detect dead or living small and medium size carnivorous animals. Between 2002 and 2005, each car operated by this agency was equipped with a logbook in which officers recorded information about the detected animals (species, location, dead or alive, date). Thus, more than 30000 dead or living animals were detected during the study period. Because a large number of detected animals in a region could have been the result of a high sampling pressure there, we modeled the number of detected animals as a function of the sampling effort to allow for unbiased estimation of the species density. For dead animals -- mostly roadkill -- we supposed that the effort in a given region was proportional to the distance traveled by the officers. For living animals, we had no way to measure the sampling effort. We demonstrated that it was possible to use the whole dataset (dead and living animals) to estimate the following: (i) the relative density -- i.e., the density multiplied by an unknown constant -- of each species of interest across the different French agricultural regions, (ii) the sampling effort for living animals for each region, and (iii) the relative detection probability for various species of interest.

The authors propose an individual‐based model of innovation diffusion and explore its main dynamical properties. In the model, individuals assign an a priori social value to an innovation which evolves during their interactions with the “relative agreement” influence model. This model offers the possibility of including a minority of “extremists” with extreme and very definite opinions. Individuals who give a high social value to the innovation tend to look for information that allows them to evaluate more precisely the individual benefit of adoption. If the social value they assign is low, they neither consider the information nor transmit it. The main finding is that innovations with high social value and low individual benefit have a greater chance of succeeding than innovations with low social value and high individual benefit. Moreover, in some cases, a minority of extremists can have a very important impact on the propagation by polarizing the social value.

We propose a test of a qualitative hypothesis on the mean of a n -Gaussian vector. The testing procedure is available when the variance of the observations is unknown and does not depend on any prior information on the alternative. The properties of the test are non-asymptotic. For testing positivity or monotonicity, we establish separation rates with respect to the Euclidean distance, over subsets of which are related to Holderian balls in functional spaces. We provide a simulation study in order to evaluate the procedure when the purpose is to test monotonicity in a functional regression model and to check the robustness of the procedure to non-Gaussian errors.

Background: Many different simulation frameworks, in different topics, need to treat realistic datasets to initialize and calibrate the system. A precise reproduction of initial states is extremely important to obtain reliable forecast from the model. Methodology/Principal Findings: This paper proposes an algorithm to create an artificial population where individuals are described by their age, and are gathered in households respecting a variety of statistical constraints (distribution of household types, sizes, age of household head, difference of age between partners and among parents and children). Such a population is often the initial state of microsimulation or (agent) individual-based models. To get a realistic distribution of households is often very important, because this distribution has an impact on the demographic evolution. Usual techniques from microsimulation approach cross different sources of aggregated data for generating individuals. In our case the number of combinations of different households (types, sizes, age of participants) makes it computationally difficult to use directly such methods. Hence we developed a specific algorithm to make the problem more easily tractable. Conclusions/Significance: We generate the populations of two pilot municipalities in Auvergne region (France), to illustrate the approach. The generated populations show a good agreement with the available statistical datasets (not used for the generation) and are obtained in a reasonable computational time., 16 oages, 11 figures

Synthetic amorphous silica (SAS) in its nanosized form is now used in food applications although the potential risks for human health have not been evaluated. In this study, genotoxicity and oxidative DNA damage of two pyrogenic (NM-202 and 203) and two precipitated (NM-200 and -201) nanosized SAS were investigated in vivo in rats following oral exposure. Male Sprague Dawley rats were exposed to 5, 10, or 20 mg/kg b.w./day for three days by gavage. DNA strand breaks and oxidative DNA damage were investigated in seven tissues (blood, bone marrow from femur, liver, spleen, kidney, duodenum, and colon) with the alkaline and the (Fpg)-modified comet assays, respectively. Concomitantly, chromosomal damage was investigated in bone marrow and in colon with the micronucleus assay. Additionally, malondialdehyde (MDA), a lipid peroxidation marker, was measured in plasma. When required, a histopathological examination was also conducted. The results showed neither obvious DNA strand breaks nor oxidative damage with the comet assay, irrespective of the dose and the organ investigated. Similarly, no increases in chromosome damage in bone marrow or lipid peroxidation in plasma were detected. However, although the response was not dose-dependent, a weak increase in the percentage of micronucleated cells was observed in the colon of rats treated with the two pyrogenic SAS at the lowest dose (5 mg/kg b.w./day). Additional data are required to confirm this result, considering in particular, the role of agglomeration/aggregation of SAS NMs in their uptake by intestinal cells.

Genetic toxicity information is critical for the safety assessment of all xenobiotics. In the absence of carcinogenicity data, genetic toxicity studies may be used to draw conclusions about the carcinogenicity potential of chemicals. However, current in vitro assays have many limitations as they produce a high rate of irrelevant positive data and possible false negative data due to the weakness of the in vitro models used. Based on the knowledge that the majority of human genotoxic carcinogens require metabolic activation to become genotoxic, it is necessary to develop in vitro cell models that mimic human liver metabolism to replace the use of liver S9 fraction, which, though helpful for predicting the potential carcinogenicity of chemicals in rodents, is questionable in humans. We therefore investigate whether the recently described human hepatoma HepaRG cells, which express the major characteristics of liver functions similarly to primary human hepatocytes, could be a suitable model for human genotoxicity assessment. We determine the performance of comet and micronucleus assays in HepaRG cells to predict in vivo genotoxins based on the list of compounds published by European Centre for the Validation of Alternative Methods (ECVAM). Twenty compounds were tested in HepaRG cells with comet and micronucleus assays over a 24-h period. The specificity, the sensitivity, and the accuracy of the two tests were determined. We found that the comet assay had higher specificity (100%) than the micronucleus (MN) test (80%), whereas the latter was far more sensitive (73%) than the former (44%), resulting nonetheless in an accuracy of 72% for the comet assay and 75% for the MN test. Taken together, our data suggest that the HepaRG cell line can be of use in genetic toxicology and that efforts to develop competent human liver cell models should be increased.

We consider the problem of estimating the mean $f$ of a Gaussian vector $Y$ with independent components of common unknown variance $\sigma^{2}$. Our estimation procedure is based on estimator selection. More precisely, we start with an arbitrary and possibly infinite collection $\FF$ of estimators of $f$ based on $Y$ and, with the same data $Y$, aim at selecting an estimator among $\FF$ with the smallest Euclidean risk. No assumptions on the estimators are made and their dependencies with respect to $Y$ may be unknown. We establish a non-asymptotic risk bound for the selected estimator. As particular cases, our approach allows to handle the problems of aggregation and model selection as well as those of choosing a window and a kernel for estimating a regression function, or tuning the parameter involved in a penalized criterion. We also derive oracle-type inequalities when $\FF$ consists of linear estimators. For illustration, we carry out two simulation studies. One aims at comparing our procedure to cross-validation for choosing a tuning parameter. The other shows how to implement our approach to solve the problem of variable selection in practice., Comment: 44 pages

The alkaline single cell gel electrophoresis (comet) assay was used to assess in vitro and in vivo genotoxicity of etoposide, a topoisomerase II inhibitor known to induce DNA strand breaks, and chlorothalonil, a fungicide widely used in agriculture. For in vivo studies, rats were sacrificed at various times after treatment and the induction of DNA strand breaks was assessed in whole blood, bone marrow, thymus, liver, kidney cortex and in the distal part of the intestine. One hour after injection, etoposide induced DNA damage in all organs studied except kidney, especially in bone marrow, thymus (presence of HDC) and whole blood. As observed during in vitro comet assay on Chinese hamster ovary (CHO) cells, dose- and time-dependent DNA effects occurred in vivo with a complete disappearance of damage 24 h after administration. Even though apoptotic cells were detected in vitro 48 h after cell exposure to etoposide, such a result was not found in vivo. After chlorothalonil treatment, no DNA strand breaks were observed in rat organs whereas a clear dose-related DNA damage was observed in vitro. The discrepancy between in vivo and in vitro models could be explained by metabolic and mechanistic reasons. Our results show that the in vivo comet assay is able to detect the target organs of etoposide and suggest that chlorothalonil is devoid of appreciable in vivo genotoxic activity under the protocol used.