Experimental and modelling approach to the legume-Rhizobium interaction: test of plant-host sanctions in co-inoculated plants with fixing and non-fixing strains

Ponencia presentada en la II Conferencia Iberoamericana de Interacciones Beneficiosas Microorganismo-Planta-Ambiente (IBEMPA). XIV Reunión Nacional de la Sociedad Española de Fijación de Nitrógeno (SEFIN). XXVI Reunión Latinoamericana de Rizobiología (ALAR). III Congreso Hispano-Portugués de Fijación de Nitrógeno. “Microorganismos para una Agricultura de futuro”. Sevilla, España, 2 al 6 de septiembre de 2013We tested the plant host sanction hypothesis using soybean plants co-inoculated with two rhizobial strains, a normally N2 fixing strain and a mutant derivative that lacks nitrogenase activity but has the same nodulation abilities. We found no evidence of functioning plant host sanctions to cheater rhizobia based on nodular rhizobia viability in co-inoculated plants.Fil: Marco, Diana. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; Argentina.Fil: Marco, Diana. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET); Argentina.Fil: Talbi, Choura. Consejo Superior de Investigaciones Científicas (CSIC). Estación Experimental del Zaidín. Departamento de Microbiología del Suelo y Sistemas Simbióticos; España.Fil: Bedmar, Eulogio J. Consejo Superior de Investigaciones Científicas (CSIC). Estación Experimental del Zaidín. Departamento de Microbiología del Suelo y Sistemas Simbióticos; España

A MOS-based Dynamic Memetic Differential Evolution Algorithm for Continuous Optimization: A Scalability Test

Continuous optimization is one of the areas with more activity in the field of heuristic optimization. Many algorithms have been proposed and compared on several benchmarks of functions, with different performance depending on the problems. For this reason, the combination of different search strategies seems desirable to obtain the best performance of each of these approaches. This contribution explores the use of a hybrid memetic algorithm based on the multiple offspring framework. The proposed algorithm combines the explorative/exploitative strength of two heuristic search methods that separately obtain very competitive results. This algorithm has been tested with the benchmark problems and conditions defined for the special issue of the Soft Computing Journal on Scalability of Evolutionary Algorithms and other Metaheuristics for Large Scale Continuous Optimization Problems. The proposed algorithm obtained the best results compared with both its composing algorithms and a set of reference algorithms that were proposed for the special issue

The IRAM-30m line survey of the Horsehead PDR: II. First detection of the l-C3H+ hydrocarbon cation

We present the first detection of the l-C3H+ hydrocarbon in the interstellar medium. The Horsehead WHISPER project, a millimeter unbiased line survey at two positions, namely the photo-dissociation region (PDR) and the nearby shielded core, revealed a consistent set of eight unidentified lines toward the PDR position. Six of them are detected with a signal-to-noise ratio from 6 to 19, while the two last ones are tentatively detected. Mostly noise appears at the same frequency toward the dense core, located less than 40" away. We simultaneously fit 1) the rotational and centrifugal distortion constants of a linear rotor, and 2) the Gaussian line shapes located at the eight predicted frequencies. The observed lines can be accurately fitted with a linear rotor model, implying a 1Sigma ground electronic state. The deduced rotational constant value is Be= 11244.9512 +/- 0.0015 MHz, close to that of l-C3H. We thus associate the lines to the l-C3H+ hydrocarbon cation, which enables us to constrain the chemistry of small hydrocarbons. A rotational diagram is then used to infer the excitation temperature and the column density. We finally compare the abundance to the results of the Meudon PDR photochemical model.Comment: 9 pages, 7 PostScript figures. Accepted for publication in Astronomy \& Astrophysics. Uses aa LaTeX macro

Reaction Networks For Interstellar Chemical Modelling: Improvements and Challenges

We survey the current situation regarding chemical modelling of the synthesis of molecules in the interstellar medium. The present state of knowledge concerning the rate coefficients and their uncertainties for the major gas-phase processes -- ion-neutral reactions, neutral-neutral reactions, radiative association, and dissociative recombination -- is reviewed. Emphasis is placed on those reactions that have been identified, by sensitivity analyses, as 'crucial' in determining the predicted abundances of the species observed in the interstellar medium. These sensitivity analyses have been carried out for gas-phase models of three representative, molecule-rich, astronomical sources: the cold dense molecular clouds TMC-1 and L134N, and the expanding circumstellar envelope IRC +10216. Our review has led to the proposal of new values and uncertainties for the rate coefficients of many of the key reactions. The impact of these new data on the predicted abundances in TMC-1 and L134N is reported. Interstellar dust particles also influence the observed abundances of molecules in the interstellar medium. Their role is included in gas-grain, as distinct from gas-phase only, models. We review the methods for incorporating both accretion onto, and reactions on, the surfaces of grains in such models, as well as describing some recent experimental efforts to simulate and examine relevant processes in the laboratory. These efforts include experiments on the surface-catalysed recombination of hydrogen atoms, on chemical processing on and in the ices that are known to exist on the surface of interstellar grains, and on desorption processes, which may enable species formed on grains to return to the gas-phase.Comment: Accepted for publication in Space Science Review

Pressure Dependent Low Temperature Kinetics for CN + CH3CN: Competition between Chemical Reaction and van der Waals Complex Formation

International audienceThe gas phase reaction between the CN radical and acetonitrile CH3CN was investigated experimentally, at low temperatures, with the CRESU apparatus and a slow flow reactor to explore the temperature dependence of its rate coefficient from 354 K down to 23 K. Whereas a standard Arrhenius behavior was found at T > 200 K, indicating the presence of an activation barrier, a dramatic increase in the rate coefficient by a factor of 130 was observed when the temperature was decreased from 168 to 123 K. The reaction was found to be pressure independent at 297 K unlike the experiments carried out at 52 and 132 K. The work was complemented by ab initio transition state theory based master equation calculations using reaction pathways investigated with highly accurate thermochemical protocols. The role of collisional stabilization of a CN⋯CH3CN van der Waals complex and of tunneling induced H atom abstractions were also considered. The experimental pressure dependence at 52 and 132 K is well reproduced by the theoretical calculations provided that an anharmonic state density is considered for the van der Waals complex CH3CN⋯CN and its Lennard-Jones radius is adjusted. Furthermore, these calculations indicate that the experimental observations correspond to the fall-off regime and that tunneling remains small in the low-pressure regime. Hence, the studied reaction is essentially an association process at very low temperature. Implications for the chemistry of interstellar clouds and Titan are discussed

A parameterized scheme of metaheuristics with exact methods for determining the Principle of Least Action in Data Envelopment Analysis

Data Envelopment Analysis (DEA) is a nonparametric methodology for estimating technical efficiency of a set of Decision Making Units (DMUs) from a dataset of inputs and outputs. This paper is devoted to computational aspects of DEA models under the application of the Principle of Least Action. This principle guarantees that the efficient closest targets are determined as benchmarks for each assessed unit. Usually, these models have been addressed in the literature by applying unsatisfactory techniques, based fundamentally on combinatorial NPhard problems. Recently, some heuristics have been developed to partially solve these DEA models. This paper improves the heuristic methods used in previous works by applying a combination of metaheuristics and an exact method. Also, a parameterized scheme of metaheuristics is developed in order to implement metaheuristics and hybridations/combinations, adapting them to the particular problem proposed here. In this scheme, some parameters are used to study several types of metaheuristics, like Greedy Random Adaptative Search Procedure, Genetic Algorithms or Scatter Search. The exact method is included inside the metaheuristic to solve the particular model presented in this paper. A hyperheuristic is used on top of the parameterized scheme in order to search, in the space of metaheuristics, for metaheuristics that provide solutions close to the optimum. The method is competitive with exact methods, obtaining fitness close to the optimum with low computational timeJ. Aparicio and M. González thank the financial support from the Spanish ‘Ministerio de Economa, Industria y Competitividad’ (MINECO), the ‘Agencia Estatal de Investigacion’ and the ‘Fondo Europeo de Desarrollo Regional’ under grant MTM2016-79765-P (AEI/FEDER, UE).Additionally, D. Giméenez thanks the financial support from the Spanish MINECO, as well as by European Commission FEDER funds, under grant TIN2015-66972-C5-3-R

Solving the Uncapacitated Single Allocation p-Hub Median Problem on GPU

A parallel genetic algorithm (GA) implemented on GPU clusters is proposed to solve the Uncapacitated Single Allocation p-Hub Median problem. The GA uses binary and integer encoding and genetic operators adapted to this problem. Our GA is improved by generated initial solution with hubs located at middle nodes. The obtained experimental results are compared with the best known solutions on all benchmarks on instances up to 1000 nodes. Furthermore, we solve our own randomly generated instances up to 6000 nodes. Our approach outperforms most well-known heuristics in terms of solution quality and time execution and it allows hitherto unsolved problems to be solved

Cooperation between Branch and Bound and Evolutionary Approaches to Solve a Bi-objective Flow Shop Problem

Over the years, many techniques have been established to solve NP-Hard Optimization Problems and in particular multiobjective problems. Each of them are efficient on several types of problems or instances. We can distinguish exact methods dedicated to solve small instances, from heuristics – and particularly metaheuristics – that approximate best solutions on large instances. In this article, we firstly present an efficient exact method, called the two-phases method. We apply it to a biobjective Flow Shop Problem to find the optimal set of solutions. Exact methods are limited by the size of the instances, so we propose an original cooperation between this exact method and a Genetic Algorithm to obtain good results on large instances. Results obtained are promising and show that cooperation between antagonist optimization methods could be very efficient

Review of important reactions for the nitrogen chemistry in the interstellar medium

Predictions of astrochemical models depend strongly on the reaction rate coefficients used in the simulations. We reviewed a number of key reactions for the chemistry of nitrogen-bearing species in the dense interstellar medium and proposed new reaction rate coefficients for those reactions. The details of the reviews are given in the form of a datasheet associated with each reaction. The new recommended rate coefficients are given with an uncertainty and a temperature range of validity and will be included in KIDA (http://kida.obs.u-bordeaux1.fr).Comment: 39 pages, not published in refereed journal, datasheets are given in KID