Market trends of seafood products under international constraints: contractualisation, marketing strategies and new behaviours

In the developed countries, especially in the European Union, demand for seafood products has increased very quickly (faster than that of meat products). This growth may be explained by the recurring problems of animal health impacts on other products (bovine spongiform encephalopathy (BSE), avian influenza (bird flu)...) and to the impacts of the environmental problems (dioxins...) which are less prevalent in seafood products. In addition, seafood products profit from an increasingly positive image positioned on the axis of nutrition- health. The enhancement of the markets is influenced more and more by the retailing channel (hyper and supermarkets). Indeed, France profits from being a pioneer in retailing, (more than 70% of the seafood market is through retailers) who can be seen as axis of development with other sectors and in other countries. To satisfy the demand, the national platforms of the retailers rely upon imported products to supplement their supplies from local fishermen and fish farmers. These local actors must adapt to the constraints imposed by the platforms, which constitutes a major innovation in the contractual relationship with the hyper and supermarket stores. The international context weighs heavily in the determination of these constraints. This paper deals with this framework of the new forms of contractualisation between the actors imposed by the evolution of the international context. It also describes the implications in term of setting in market and marketing strategies. Lastly, it takes into account the emergence characteristics of new food buying behaviours.seafood products, contractualisation, price, sale promotions, marketing, behaviours, Marketing,

Is current irrigation sustainable in the United States? An integrated assessment of climate change impact on water resources and irrigated crop yields.

While climate change impacts on crop yields has been extensively studied, estimating the impact of water shortages on irrigated crop yields is challenging because the water resources management system is complex. To investigate this issue, we integrate a crop yield reduction module and a water resources model into the MIT Integrated Global System Modeling framework, an integrated assessment model linking a global economic model to an Earth system model. We assess the effects of climate and socioeconomic changes on water availability for irrigation in the U.S. as well as subsequent impacts on crop yields by 2050, while accounting for climate change projection uncertainty. We find that climate and socioeconomic changes will increase water shortages and strongly reduce irrigated yields for specific crops (i.e., cotton and forage), or in specific regions (i.e., the Southwest) where irrigation is not sustainable. Crop modeling studies that do not represent changes in irrigation availability can thus be misleading. Yet, since the most water-stressed basins represent a relatively small share of U.S. irrigated areas, the overall reduction in U.S. crop yields is small. The response of crop yields to climate change and water stress also suggests that some level of adaptation will be feasible, like relocating croplands to regions with sustainable irrigation or switching to less irrigation intensive crops. Finally, additional simulations show that greenhouse gas (GHG) mitigation can alleviate the effect of water stress on irrigated crop yields, enough to offset the reduced CO2 fertilization effect compared to an unconstrained GHG emission scenario

Analysis of the Monte-Carlo Error in a Hybrid Semi-Lagrangian Scheme

We consider Monte-Carlo discretizations of partial differential equations based on a combination of semi-lagrangian schemes and probabilistic representations of the solutions. The goal of this paper is two-fold. First we give rigorous convergence estimates for our algorithm: In a simple setting, we show that under an anti-Courant-Friedrichs-Lewy condition on the time step $\delta t$ and on the mesh size $\delta x$ and for a reasonably large number of independent realizations $N$, we control the Monte-Carlo error by a term of order $\mathcal {O}(\sqrt {\delta t /N})$. Then, we show various applications of the numerical method in very general situations (nonlinear, different boundary conditions, higher dimension) and numerical examples showing that the theoretical bound obtained in the simple case seems to persist in more complex situation

Analysis of the Monte-Carlo error in a hybrid semi-Lagrangian scheme

International audienceWe consider Monte-Carlo discretizations of partial differential equations based on a combination of semi-lagrangian schemes and probabilistic representations of the solutions. We study the Monte-Carlo error in a simple case, and show that under an anti-CFL condition on the time-step $\delta t$ and on the mesh size $\delta x$ and for $N$ - the number of realizations - reasonably large, we control this error by a term of order $\mathcal{O}(\sqrt{\delta t /N})$. We also provide some numerical experiments to confirm the error estimate, and to expose some examples of equations which can be treated by the numerical method

SMALL AND MEDIUM PORTS' ACTIVITIES MODELLING: INTRODUCTION TO THE PIXEL APPROACH

[EN] Port activities undeniably have an impact on their environment, the city and citizens living nearby. To have a better understanding of these impacts, the ports of the future will require tools allowing suitable modelling, simulation and data analysis. This challenge is also tied to another current reality: the heterogeneous data coming from different stakeholders converging into ports are not optimally exploited due to lack of interoperability. Thus, the forthcoming research and development initiatives must address these demands from a holistic point of view. PIXEL (H2020-funded project) aims at creating the first smart, flexible and scalable solution reducing the environmental impact while enabling optimization of operations in port ecosystems. PIXEL brings the most innovative IoT and ICT technology to ports and demonstrate their capacity to take advantage of modern approaches. Using an interoperable open IoT platform, data is acquired and integrated into an information hub comprised of small, low-level sensors up to virtual sensors able to extract relevant data from high level services. Finally, this hub integrates smart models to analyse port processes for prediction and optimization purposes: (i) a model of consumption and energy production of the port with the aim of moving towards green energy production; (ii) a model of congestion of multi-modal transport networks to reduce the impact of port traffic on the network; and (iii) models of environmental pollution of the port to reduce the environmental impacts of the port on the city and its citizens. The main issue tackled by PIXEL is to provide interoperability between these models and allow real integration and communication in the context of an environmental management model. Besides that, PIXEL devotes to decouple port¿s size and its ability to deploy environmental impact mitigation specifying an innovative methodology and an integrated metric for the assessment of the overall environmental impact of ports.The PIXEL project, the results of which are presented in this paper, is being funded from the European Union s Horizon 2020 research and innovation programme under grant agreement no. 769355 Port IoT for Environmental Leverage (PIXEL)Simon, E.; Garnier, C.; Lacalle, I.; Costa, JP.; Palau Salvador, CE. (2019). SMALL AND MEDIUM PORTS' ACTIVITIES MODELLING: INTRODUCTION TO THE PIXEL APPROACH. WIT Transactions on the Built Environment (Online). 187:149-163. https://doi.org/10.2495/MT190141S14916318

Concevoir un assistant conversationnel de manière itérative et semi-supervisée avec le clustering interactif

National audienceThe design of a dataset needed to train a chatbot is most often the result of manual and tedious step. To guarantee the efficiency of the annotation, we propose the interactive clustering method, an active learning method based on constraints annotation. It’s an iterative approach, relying on a constrained clustering algorithm and using annotator knowledge to lead clustering. In this paper, we expose the process to design a chatbot with the interactive clustering method.La création d'un jeu de données nécessaire à la conception d'un assistant conversationnel résulte le plus souvent d'une étape manuelle et fastidieuse qui manque de techniques destinées à l'assister. Pour accélérer cette étape d'annotation, nous proposons une méthode de clustering interactif : il s'agit d'une approche itérative inspirée de l'apprentissage actif, reposant sur un algorithme de clustering et tirant parti d'une annotation de contraintes pour guider le regroupement des questions en une structure d'intentions. Dans cet article, nous exposons la méthodologie à mettre en oeuvre pour concevoir un assistant conversationnel opérationnel à l'aide du clustering interactif