224 research outputs found

    A highly osmotolerant rhizobial strain confers a better tolerance of nitrogen fixation and enhances protective activities to nodules of Phaseolus vulgaris under drought stress

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    The effect of water deficiency on nodules of common bean (Phaseolus vulgaris) inoculated with three rhizobial strains differing in their osmotolerance, was investigated in two different experiments on sterile sand. In the first experiment, the control plants were maintained at 90% field capacity (FC) and water-deficient plants were grown at 35% FC. The nitrogen fixation and growth parameters drastically decreased under water deficiency, however the three rhizobial strains, Rhizobium etli A32 (sensitive), Rhizobium tropici CIAT899 (tolerant), and Ensifer meliloti 4H41 (highly tolerant), showed different symbiotic performances. E. meliloti 4H41 allowed the best acetylene reduction activity (ARA) and biomass production and the highest number of large-sized nodules, while no significant effect was observed on lipid peroxidation, protein and legheamoglobin contents. The effect on antioxidant activities was the lowest. In the second experiment, plants were maintained at 90% FC during 45 days and then watering was stopped. The results showed that, the response to water deficit was quite similar for the three analyzed symbioses until 35% FC, but below this value of FC, symbiosis involving strain E. meliloti 4H41 was the most tolerant. This tolerance was accompanied, by in both experiments, by a stability of metabolic indices and protective antioxidant activities. These results suggest that, the relative tolerance of the nodules induced by strain 4H41 could be due to a constructive adaptation involving specific cortex structure and stress-adapted metabolic activities acquired during nodule formation and growth, rather than to a timely inducible response due to the stimulation of antioxidant enzymes. This suggestion should be confirmed through microscopic structure analysis and supplemental key enzymes in nodule metabolism such as sucrose synthase and malate dehydrogenase.Key words: Antioxidant activities, in pots experiment, leghemoglobin content, nodule, rhizobia, osmotolerance, symbiotic efficiency, water deficiency

    Impact du zooplancton métazoaire sur le phytoplancton et les protozoaires ciliés dans le réservoir Sahela (Maroc)

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    L'impact du zooplancton métazoaire sur le phytoplancton et les protozoaires ciliés a été mesuré durant la période de juillet à décembre 1999 dans le réservoir Sahela sous climat méditerranéen semi-aride.Les expériences ont été réalisées à l'aide de chambres de diffusion immergées in situ pendant 7 heures en absence (chambres témoins) et en présence (chambres expérimentales) du zooplancton.Les résultats indiquent que la mortalité moyenne à 4 m des algues est de 0,13 + 0,03 h-1, et celle des protozoaires ciliés de 0,07 + 0,03 h-1. Cryptomonas ovata et Halteria grandinella ont subi la plus forte prédation, respectivement, 0,31 + 0,14 h-1 et 0,11 + 0,04 h-1 à 4 m. Toutefois, les algues de grande taille (Pediastrum sp, Ceratium hirundinella et Peridinium cinctum) n'ont été que très peu ou pas consommées.The Sahela reservoir, located in Taounate at 90 km from Fès, lying at an altitude of 325 m, was built to provide drinking water for the population of Taounate and to contribute to irrigate neighbouring farming perimeters.In order to assess the impact of metazoan zooplankton on phytoplankton and protozoan ciliates in the Sahela reservoir under semi-arid climate, we conducted experiments during the period from July to December 1999 at the deepest point in the lake (15 m).Sampling and measurements were carried out in diffusion chambers submerged in situ over a period of 7 h without (control chambers) and with (experimental chambers) zooplankton. During these experiments, counts were conducted on phytoplankton and ciliates to determine the abundance and the mortality of these organisms due to zooplankton in each diffusion chambers at t=0 and t=7 h incubation. The metazooplankton were counted and dry weight of each taxa was calculated.In summer the highest zooplankton biomass (150 µg·L-1) mainly composed of cyclopoid Tropocyclops prasinus, caused mortality of the small-sized ciliates, such as Halteria grandinella (0.10 h-1). In Autumn, the zooplankton biomass (75 µg·l-1), dominated by Daphnia longispina, induced a higher mortality for phytoplankton (0.10 h-1) than for ciliates (0.05 h-1). In Winter, the zooplankton biomass (100 µg·L-1), also represented by Daphnia longispina, had a low impact on ciliate mortality (< 0.02 h-1).The study showed that a heavy predation by the metazoan zooplankton was exerted on small-sized phytoplankton and ciliates and clearly demonstrated the relationships between protozoans and metazoan zooplankton to transfering the matter and energy in aquatic food webs

    Design of dynamic experiments for black-box model discrimination

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    Diverse domains of science and engineering require and use mechanistic mathematical models, e.g. systems of differential algebraic equations. Such models often contain uncertain parameters to be estimated from data. Consider a dynamic model discrimination setting where we wish to chose: (i) what is the best mechanistic, time-varying model and (ii) what are the best model parameter estimates. These tasks are often termed model discrimination/selection/validation/verification. Typically, several rival mechanistic models can explain data, so we incorporate available data and also run new experiments to gather more data. Design of dynamic experiments for model discrimination helps optimally collect data. For rival mechanistic models where we have access to gradient information, we extend existing methods to incorporate a wider range of problem uncertainty and show that our proposed approach is equivalent to historical approaches when limiting the types of considered uncertainty. We also consider rival mechanistic models as dynamic black boxes that we can evaluate, e.g. by running legacy code, but where gradient or other advanced information is unavailable. We replace these black-box models with Gaussian process surrogate models and thereby extend the model discrimination setting to additionally incorporate rival black-box model. We also explore the consequences of using Gaussian process surrogates to approximate gradient-based methods

    Postendovascular thoracic aortic repair subclavian steal syndrome revealed by severe headache

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    AbstractSubclavian steal syndrome (SCSS) has been known since 1960 in the medical literature. Its principal cause is atherosclerosis responsible of occlusion of the subclavian artery (SCA). It is the pathological process in which blood flows in reverse direction from the vertebral artery (VA) to the SCA. Usually asymptomatic, but a variety of symptoms may develop involving the vertebro-basilar and/or the carotid territories and may be precipitated by exercise of the upper extremity. In some circumstances it can be iatrogenic complicating the course of a thoracic endovascular aortic repair (TEVAR) when the left SCA is covered by the endoprosthesis, which is a necessity many times giving the frequent proximity of the acute thoracic pathologies to the origin of this vessel.We present a case of severe headache occurring after a TEVAR with intentional coverage of the origin of the left SCA. This headache was the only symptom from which the patient complained, and which disappeared immediately after carotid-SCA bypass. Other devastating complications can happen, which gave as a concern about the management of SCA when decision to practice a TEVAR is taken

    Towards the Formal Reliability Analysis of Oil and Gas Pipelines

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    It is customary to assess the reliability of underground oil and gas pipelines in the presence of excessive loading and corrosion effects to ensure a leak-free transport of hazardous materials. The main idea behind this reliability analysis is to model the given pipeline system as a Reliability Block Diagram (RBD) of segments such that the reliability of an individual pipeline segment can be represented by a random variable. Traditionally, computer simulation is used to perform this reliability analysis but it provides approximate results and requires an enormous amount of CPU time for attaining reasonable estimates. Due to its approximate nature, simulation is not very suitable for analyzing safety-critical systems like oil and gas pipelines, where even minor analysis flaws may result in catastrophic consequences. As an accurate alternative, we propose to use a higher-order-logic theorem prover (HOL) for the reliability analysis of pipelines. As a first step towards this idea, this paper provides a higher-order-logic formalization of reliability and the series RBD using the HOL theorem prover. For illustration, we present the formal analysis of a simple pipeline that can be modeled as a series RBD of segments with exponentially distributed failure times.Comment: 15 page

    Formal Availability Analysis using Theorem Proving

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    Availability analysis is used to assess the possible failures and their restoration process for a given system. This analysis involves the calculation of instantaneous and steady-state availabilities of the individual system components and the usage of this information along with the commonly used availability modeling techniques, such as Availability Block Diagrams (ABD) and Fault Trees (FTs) to determine the system-level availability. Traditionally, availability analyses are conducted using paper-and-pencil methods and simulation tools but they cannot ascertain absolute correctness due to their inaccuracy limitations. As a complementary approach, we propose to use the higher-order-logic theorem prover HOL4 to conduct the availability analysis of safety-critical systems. For this purpose, we present a higher-order-logic formalization of instantaneous and steady-state availability, ABD configurations and generic unavailability FT gates. For illustration purposes, these formalizations are utilized to conduct formal availability analysis of a satellite solar array, which is used as the main source of power for the Dong Fang Hong-3 (DFH-3) satellite.Comment: 16 pages. arXiv admin note: text overlap with arXiv:1505.0264

    Drought Impact Is Alleviated in Sugar Beets (Beta vulgaris L.) by Foliar Application of Fullerenol Nanoparticles

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    Over the past few years, significant efforts have been made to decrease the effects of drought stress on plant productivity and quality. We propose that fullerenol nanoparticles (FNPs, molecular formula C-60(OH)(24)) may help alleviate drought stress by serving as an additional intercellular water supply. Specifically, FNPs are able to penetrate plant leaf and root tissues, where they bind water in various cell compartments. This hydroscopic activity suggests that FNPs could be beneficial in plants. The aim of the present study was to analyse the influence of FNPs on sugar beet plants exposed to drought stress. Our results indicate that intracellular water metabolism can be modified by foliar application of FNPs in drought exposed plants. Drought stress induced a significant increase in the compatible osmolyte proline in both the leaves and roots of control plants, but not in FNP treated plants. These results indicate that FNPs could act as intracellular binders of water, creating an additional water reserve, and enabling adaptation to drought stress. Moreover, analysis of plant antioxidant enzyme activities (CAT, APx and GPx), MDA and GSH content indicate that fullerenol foliar application could have some beneficial effect on alleviating oxidative effects of drought stress, depending on the concentration of nanoparticles applied. Although further studies are necessary to elucidate the biochemical impact of FNPs on plants; the present results could directly impact agricultural practice, where available water supplies are often a limiting factor in plant bioproductivity

    Recent advances of metabolomics in plant biotechnology

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    Biotechnology, including genetic modification, is a very important approach to regulate the production of particular metabolites in plants to improve their adaptation to environmental stress, to improve food quality, and to increase crop yield. Unfortunately, these approaches do not necessarily lead to the expected results due to the highly complex mechanisms underlying metabolic regulation in plants. In this context, metabolomics plays a key role in plant molecular biotechnology, where plant cells are modified by the expression of engineered genes, because we can obtain information on the metabolic status of cells via a snapshot of their metabolome. Although metabolome analysis could be used to evaluate the effect of foreign genes and understand the metabolic state of cells, there is no single analytical method for metabolomics because of the wide range of chemicals synthesized in plants. Here, we describe the basic analytical advancements in plant metabolomics and bioinformatics and the application of metabolomics to the biological study of plants
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