Effect of essential oils extracted from Satureja calamintha, Mentha pulegium and Juniperus phoenicea on in vitro methanogenesis and fermentation traits of vetch-oat hay

The impact of inclusion of essential oils (EO) extracted from Juniperus phoenicea, Satureja calamintha and Mentha pulegium at three levels: 0, 1.66, 3.33 and 6.66 μl/ml of incubation medium, on methane production and rumen fermentation traits of vetch-oat hay was studied in in vitro gas production test, using 200 mg of substrate in a 60 ml graduated syringes. Gas production was recorded at 3, 6, 9, 24, 48, 72 and 96 h. Methane was measured at 3, 24 and 96 h, while pH and ammonia N were analyzed just at 24 h of incubation. At 24 h of fermentation, all doses of EO reduced significantly total gas and methane production (P < 0.05). At the highest concentration and after 24 h, methanogenesis was decreased by 60.98, 57.70 and 64.64% for J. phoenicea, M. pulegium and S. calamintha, respectively. This effect was more pronounced at the end of fermentation (96 h) where reduction in methane production was superior to 72%. However, addition of EO increased pH and decreased significantly ammonia concentration, mainly, for high EO concentrations. The results indicate that these EO had a potential to reduce methanogenesis in the rumen, but further in vitro and in vivo trials are required to search optimum dose which reduce methane production without adversely changing dietary fermentation and rumen function.Key words: Methane, ammonia, essential oils, Satureja calamintha (Calament), Mentha pulegium (fliou, Menthe pouliot), Juniperus phoenicea (Arar, Genévrier), in vitro gas production test

System architecture and GNC algorithms for lunar surface precision landing and transfer trajectories optimization

Space Exploration is currently at the center of a renewed wave of interest, with particular attention devoted to manned missions towards the Moon, Mars and beyond.In line with ESA Exploration Roadmap, current efforts are being focused on the concept of a Moonvillage, capable of functioning as a permanent human outpost and thought as intermediate step for further exploration towards more remote destinations. The sustained human presence at the outpost demands for frequent transfers between the lunar surface and the Deep Space Gateway (DSG) required for the provision of resources to the village and for crew transportation.The landing and take-off of transfer vehicles is expected to exploit spaceport facilities, built in specific locations on the lunar surface and, therefore, requiring the landing procedure to be as precise and reliable as possible, with the aim of reducing the risk of damage to structures or vehicles.A further constraint concerns the minimization of propellant consumption during transfers between the surface and the lunar orbit.Approaches based on Convex Optimization have already been successfully employed in space applications to increase performances and reliability of landing procedures. Characterised by efficient and deterministic convergence capabilities, the associated algorithms are able to provide numerical solutions to minimization problems with computational times compatible with real-time onboard applications.The purpose of this paper is to provide an overview of the architecture of the systems involved in the guidance, navigation and control of transfer elements required to travel between the lunar surface and the DSG. Specific attention is devoted to Convex Optimization algorithms for trajectory optimization and control, analysing both the landing and the DSG targeting processes

Molecular genetic differentiation of native populations of Mediterranean blue mussels, Mytilus galloprovincialis Lamarck, 1819, and the relationship with environmental variables

publishedVersio

Elements About Exploratory, Knowledge-Based, Hybrid, and Explainable Knowledge Discovery

International audienceKnowledge Discovery in Databases (KDD) and especially pattern mining can be interpreted along several dimensions, namely data, knowledge, problem-solving and interactivity. These dimensions are not disconnected and have a direct impact on the quality, applicability, and efficiency of KDD. Accordingly, we discuss some objectives of KDD based on these dimensions, namely exploration, knowledge orientation, hybridization, and explanation. The data space and the pattern space can be explored in several ways, depending on specific evaluation functions and heuristics, possibly related to domain knowledge. Furthermore, numerical data are complex and supervised numerical machine learning methods are usually the best candidates for efficiently mining such data. However, the work and output of numerical methods are most of the time hard to understand, while symbolic methods are usually more intelligible. This calls for hybridization, combining numerical and symbolic mining methods to improve the applicability and interpretability of KDD. Moreover, suitable explanations about the operating models and possible subsequent decisions should complete KDD, and this is far from being the case at the moment. For illustrating these dimensions and objectives, we analyze a concrete case about the mining of biological data, where we characterize these dimensions and their connections. We also discuss dimensions and objectives in the framework of Formal Concept Analysis and we draw some perspectives for future research

Simulations Analysis with Comparative Study of a PMSG Performances for Small WT Application by FEM

International audiencePermanent magnet synchronous generators (PMSGs) have a bright prospect in the small wind turbine (WT) applications; PMSGs co mpared to the conventional electrically excitated generators have many advantages, that's why they have attracted many and a strong interest of research. In this paper, a co mparative PMSG performance study' s is presented, these performances is studied as a function of physical material like the type of permanent magnet (high, poor, average and linear), as a function of the environ mental conditions as rotor speed, finally, as a function of the design and geometrical parameters (rotor length, number of poles, nu mber of stator slots). These results are obtained by finite element method (FEM); this approach is a powerful and useful tool to study and design PMSGs, as represented in this paper

Design and simulation analysis of outer stator inner rotor DFIG by 2D and 3D finite element methods

International audienceIn this paper, a time stepping 2D and 3D FEM is performed for modeling and analysis interior rotor DFIG .The finite element method currently represents the state-of-the-art in the numerical magnetic field computation relating to electrical machines. FEM is a numerical method to solve the partial differential equations (PDE) that expresses the physical quantities of interest, in this case Maxwell's equations. This will result in a more accurate result compared to analytical modeling, which can be regarded as a simplification of the PDE. FEM analysis is used for transient mode, magnetic field calculation, the magnetic flux density and vector potential of machine is obtained. In this model we including, non linear material characteristics, eddy current effect, torque-speed characteristics, ambient temperature effect and magnetic analysis are investigated