La Maxe, Metz – 2 rue de la Grange-aux-Dames

Préalablement à la construction d’un bureau et de silos, le groupe Soufflet Agriculture a déposé un permis de construire le 18 juillet 2017 auprès des mairies de La Maxe et de Metz. Compte tenu de la proximité de l’opération avec la fouille menée en 1999 par l’équipe d’Amaury Masquilier (cf. Bilan scientifique régional Lorraine 1999, p. 80) ayant livré de probables vestiges gallo-romains mais surtout un ensemble bâti associé à une ferme fossoyée du Moyen Âge et perdurant aux périodes moderne ..

Pouilly – Chèvre Haie 1, rue du Petit Chemin

L’opération de diagnostic archéologique menée par le Pôle d’Archéologie préventive de Metz Métropole au lieu-dit Chèvre Haie, rue du Petit Chemin, sur la commune de Pouilly s’est déroulée préalablement à un projet immobilier prévoyant la construction de lotissements. L’emprise du terrain visé par le diagnostic représente une surface de 8 604 m2. Trente sondages ont été réalisés, soit 9,59 % de la surface prescrite. Les tranchées positives ont révélé la présence de quatre structures en creux :..

A specialist-generalist classification of the arable flora and its response to changes in agricultural practices

<p>Abstract</p> <p>Background</p> <p>Theory in ecology points out the potential link between the degree of specialisation of organisms and their responses to disturbances and suggests that this could be a key element for understanding the assembly of communities. We evaluated this question for the arable weed flora as this group has scarcely been the focus of ecological studies so far and because weeds are restricted to habitats characterised by very high degrees of disturbance. As such, weeds offer a case study to ask how specialization relates to abundance and distribution of species in relation to the varying disturbance regimes occurring in arable crops.</p> <p>Results</p> <p>We used data derived from an extensive national monitoring network of approximately 700 arable fields scattered across France to quantify the degree of specialisation of 152 weed species using six different ecological methods. We then explored the impact of the level of disturbance occurring in arable fields by comparing the degree of specialisation of weed communities in contrasting field situations.</p> <p>The classification of species as specialist or generalist was consistent between different ecological indices. When applied on a large-scale data set across France, this classification highlighted that monoculture harbour significantly more specialists than crop rotations, suggesting that crop rotation increases abundance of generalist species rather than sets of species that are each specialised to the individual crop types grown in the rotation. Applied to a diachronic dataset, the classification also shows that the proportion of specialist weed species has significantly decreased in cultivated fields over the last 30 years which suggests a biotic homogenization of agricultural landscapes.</p> <p>Conclusions</p> <p>This study shows that the concept of generalist/specialist species is particularly relevant to understand the effect of anthropogenic disturbances on the evolution of plant community composition and that ecological theories developed in stable environments are valid in highly disturbed environments such as agro-ecosystems. The approach developed here to classify arable weeds according to the breadth of their ecological niche is robust and applicable to a wide range of organisms. It is also sensitive to disturbance regime and we show here that recent changes in agricultural practices, i.e. increased levels of disturbance have favoured the most generalist species, hence leading to biotic homogenisation in arable landscapes.</p

A Generalized Arc-Consistency Algorithm for a Class of Counting Constraints: Revised Edition that Incorporates One Correction

This paper introduces the SEQ BIN meta-constraint with a polytime algorithm achieving general- ized arc-consistency according to some properties. SEQ BIN can be used for encoding counting con- straints such as CHANGE, SMOOTH or INCREAS- ING NVALUE. For some of these constraints and some of their variants GAC can be enforced with a time and space complexity linear in the sum of domain sizes, which improves or equals the best known results of the literature

Self-decomposable Global Constraints

International audienceScalability becomes more and more critical to decision support technologies. In order to address this issue in Constraint Programming, we introduce the family of self-decomposable constraints. These constraints can be satisfied by applying their own filtering algorithms on variable subsets only. We introduce a generic framework which dynamically decompose propagation, by filtering over variable subsets. Our experiments over the CUMULATIVE constraint illustrate the practical relevance of self-decomposition

Anticipated regret and self-esteem in the Allais paradox

Our experiment aims at studying the impact of self-esteem on risk-prone choices in an Allais-type decision context using hypothetical money. We use an Internet protocol in order to reach a large heterogeneous student population sample. An anticipated regret explanation for the certainty effect implies that self-esteem is a crucial psychological variable in what concerns risky decision, but only when the choice is between a safe option and a risky option. Thus, in our experiment, we hypothesize that low self-esteem people will choose more frequently the safe option (rather than the risky-prone option) than high self-esteem people, whereas low self-esteem and high self-esteem individuals will show the same pattern of choices between two different risk-based options. Our data confirm our hypothesis. Regarding risky choices preferences, we also observe that females, non economists and older people significantly exhibit safer choice preferences than other participants. We find also that men and students in economics are more likely to conform to expected utility theory than females and other social science students respectively. We then discuss what these findings mean for economic regret theory, and suggest that a complete theory of decision-making under risk should introduce both situational and motivational explanations of individual behaviour.Allais paradox; Risk; Regret aversion; Self-esteem; Internet experiment; Gender differences

Online Language Learning to Perform and Describe Actions for Human-Robot Interaction

International audienceThe goal of this research is to provide a real-time and adaptive spoken langue interface between humans and a humanoid robot. The system should be able to learn new grammatical constructions in real-time, and then use them immediately following or in a later interactive session. In order to achieve this we use a recurrent neural network of 500 neurons-echo state network with leaky neurons [1]. The model processes sentences as grammatical constructions, in which the semantic words (nouns and verbs) are extracted and stored in working memory, and the grammatical words (prepositions, auxiliary verbs, etc.) are inputs to the network. The trained network outputs code the role (predicate, agent, object/location) that each semantic word takes. In the final output, the stored semantic words are then mapped onto their respective roles. The model thus learns the mappings between the grammatical structure of sentences and their meanings. The humanoid robot is an iCub [2] who interacts around a instrumented tactile table (ReacTable TM) on which objects can be manipulated by both human and robot. A sensory system has been developed to extract spatial relations. A speech recognition and text to speech off-the-shelf tool allows spoken communication. In parallel, the robot has a small set of actions (put(object, location), grasp(object), point(object)). These spatial relations, and action definitions form the meanings that are to be linked to sentences in the learned grammatical constructions. The target behavior of the system is to learn two conditions. In action performing (AP), the system should learn to generate the proper robot command, given a spoken input sentence. In scene description (SD), the system should learn to describe scenes given the extracted spatial relation. Training corpus for the neural model can be generated by the interaction with the user teaching the robot by describing spatial relations or actions, creating pairs. It could also be edited by hand to avoid speech recognition errors. These interactions between the different components of the system are shown in the Figure 1. The neural model processes grammatical constructions where semantic words (e.g. put, grasp, toy, left, right) are replaced by a common marker. This is done with only a predefined set of grammatical words (after, and, before, it, on, the, then, to, you). Therefore the model is able to deal with sentences that have the same constructions than previously seen sentences. In the AP condition, we demonstrate that the model can learn and generalize to complex sentences including "Before you put the toy on the left point the drums."; the robot will first point the drums and then put the toy on the left: showing here that the network is able to establish the proper chronological order of actions. Likewise, in the SD condition, the system can be exposed to a new scene and produce a description such as "To the left of the drums and to the right of the toy is the trumpet." In future research we can exploit this learning system in the context of human language development. In addition, the neural model could enable errors recovery from speech to text recognition. Index Terms: human-robot interaction, echo state network, online learning, iCub, language learning. References [1] H. Jaeger, "The "echo state" approach to analysing and training recurrent neural networks", Tech. Rep. GMD model has been developed with Oger toolbox: http://reservoir-computing.org/organic/engine. Figure 1: Communication between the speech recognition tool (that also controls the robotic platform) and the neural model

El principio de proporcionalidad en Derecho público francés

Eulalia W. Petit de Gabriel es la traductora de este artículo de Xavier Philipp

La contrainte Increasing NValue

National audienceCet article introduit la contrainte Increasing NValue, qui restreint le nombre de valeurs distinctes affectées à une séquence de variables, de sorte que chaque variable de la séquence soit inférieure ou égale à la variable la succédant immédiatement. Cette contrainte est une spécialisation de la contrainte NValue, motivée par le besoin de casser des symétries. Il est bien connu que propager la contrainte NValue est un problème NP-Difficile. Nous montrons que la spécialisation au cas d'une séquence ordonnée de variables rend le problème polynomial. Nous proposons un algorithme d'arc-consistance ayant une complexité temporelle en O(sum D), où sum D est la somme des tailles des domaines. Cet algorithme est une amélioration significative, en termes de complexité, des algorithmes issus d'une représentation de la contrainte Increasing NValue à l'aide d'automates ou de la contrainte SLIDE. Nous utilisons notre contrainte dans le cadre d'un problème d'allocation de ressources