169 research outputs found

    Measuring economic water scarcity in agriculture: a cross-country empirical investigation

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    High water availability enhances agricultural performance and food security. However, many countries where water is abundant according to hydrological indicators face difficulties in the utilization of water in agriculture, being in a situation of economic water scarcity (EWS), due to lack of institutional and material means for water management and governance. EWS faces a stronger challenge of measurability, if compared to physical water scarcity. Since the Sustainable Development Goal Indicator on Integrated management of domestic and transboundary water resources (IWRM) is a unique attempt to quantify information on water management at a national level, we explore whether it can represent a valid metric for EWS measurement. We first show that a high level of water management is neither necessarily associated to high economic power of the country nor to low physical water availability. Then, we analyze whether the indicator can predict typical EWS situations such as low agricultural productivity and inefficient water use. Although the importance of water institutions for agriculture is well known through case studies at the local level, we make the first attempt to quantify the strengths of this relation at a global scale for different crops in climatic diverse countries. We detect a positive and significant association between IWRM level and yield, and consequently a negative and equally significant association between the IWRM level and the crop water footprint. Statistical significance holds also when potentially confounding variables are included in a multiple regression analysis. We infer from this analysis that good water management, as detectable through the IWRM indicator, improves land productivity and water saving, in turn mitigating EWS. Our findings pave the way toward the use of the IWRM indicator as a valuable tool for measuring EWS in agriculture, bridging the measurability gap of economic water scarcity, with straightforward policy implications in favour of investments in water management as a lever for enhancing food security and development

    (127, k, d) Reed-Solomon code with erasures: simulation and field programmable gate arrays (FPGA) design

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    Telecommunication applications require transmitting data with different format such as sound, video, email, measures, signalling and help contents . This leads to a growing complexity of transmitting systems and to higher and higher data rates . On reception, the system must be able to quickly detect and correct errors due to the transmission channel noise (decreasing error rate) . Error detecting-correcting codes suited to applications reduce the error rate (cyclic codes, convolutional code . . .) . This paper presents an overview of the implementation of a (127, k, d) Reed-Solomon error-correcting code with erasures . The technology used to mark on symbols is described in details here . The coding algorithm computes the codewords and marks the symbols . The decoding algorithm detects and corrects either the errors t' = t, or the erasures e' = 2* t, or a combination of the two (e' + 2 * t' < d-1). The error detection is possible for a number of erasures exceeding 2 * t . The number of rectifiable errors is t . This work is the result of the collaboration between the LICM laboratory and TDF-C2R company . Many Hamming distances of a (127, k, d) Reed-Solomon error-correcting code with erasure have been tested with measure files, simulating different real environments . Results obtained from computer simulations using diversified environment models are in good agreement with analytical results . Moreover, the core of the «(127, 121, 7) Reed-Solomon code with erasures» coder/decoder has been implemented on an ALTERA/FLEX1 OK family FPGA from a VHDL specification . This core can be used to design applications with continuous data streams .Les applications actuelles de télécommunications nécessitent la transmission de données aussi diverses que le son, la vidéo, la messagerie et les données de mesures, de signalisations et d'assistance. Cela entraîne une complexité croissante des systèmes de transmission et un débit de plus en plus élevé. A la réception, le système doit pouvoir détecter et corriger rapidement les éventuelles erreurs dues au bruit de canal (diminution du taux d'erreurs). Une des techniques pour diminuer ce taux est d'utiliser un code détecteur correcteur d'erreurs adapté à l'application (codes cycliques, code convolutif, .,). Plus spécifiquement, cet article concerne un code détecteur correcteur d'erreurs Reed-Solomon (127, k, d) avec la description complète d'une technique de marquage des symboles pour la mise en oeuvre des effacements. L'algorithme de codage calcule les mots de code et marque les symboles. L'algorithme de décodage opère soit sur les erreurs t' = t, soit sur les effacements e' = 2 * t, soit sur un panachage des deux (e' + 2 * t' ≤ d-1), t étant le nombre maximum d'erreurs corrigibles. En plus la détection des erreurs est possible pour un nombre d'effacements supérieur à 2 * t. Dans le cadre d'une étude menée conjointement entre le laboratoire LICM et TDF-C2R, plusieurs distances Hamming du code Reed-Solomon (127, k, d) ont été simulées (entre autres à partir de mesures réelles). Les résultats de simulation permettent de quantifier la valeur ajoutée concernant les effacements. De plus, la conception sur FPGA d'un code de Reed-Solomon (127, 121, 7) est étudiée afin d'implanter une fonction « codeur/décodeur avec effacements », pouvant être réutilisée lors de la synthèse d'autres applications traitant des flots de données en continu

    Fluid geochemistry, local hydrology, and metabolic activity define methanogen community size and composition in deep-sea hydrothermal vents

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    The size and biogeochemical impact of the subseafloor biosphere in oceanic crust remain largely unknown due to sampling limitations. We used reactive transport modeling to estimate the size of the subseafloor methanogen population, volume of crust occupied, fluid residence time, and nature of the subsurface mixing zone for two low-temperature hydrothermal vents at Axial Seamount. Monod CH4 production kinetics based on chemostat H2 availability and batch-culture Arrhenius growth kinetics for the hyperthermophile Methanocaldococcus jannaschii and thermophile Methanothermococcus thermolithotrophicus were used to develop and parameterize a reactive transport model, which was constrained by field measurements of H2, CH4, and metagenome methanogen concentration estimates in 20–40 °C hydrothermal fluids. Model results showed that hyperthermophilic methanogens dominate in systems where a narrow flow path geometry is maintained, while thermophilic methanogens dominate in systems where the flow geometry expands. At Axial Seamount, the residence time of fluid below the surface was 29–33 h. Only 1011 methanogenic cells occupying 1.8–18 m3 of ocean crust per m2 of vent seafloor area were needed to produce the observed CH4 anomalies. We show that variations in local geology at diffuse vents can create fluid flow paths that are stable over space and time, harboring persistent and distinct microbial communities

    Computing the shortest elementary flux modes in genome-scale metabolic networks

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    This article is available open access through the publisher’s website through the link below. Copyright @ The Author 2009.Motivation: Elementary flux modes (EFMs) represent a key concept to analyze metabolic networks from a pathway-oriented perspective. In spite of considerable work in this field, the computation of the full set of elementary flux modes in large-scale metabolic networks still constitutes a challenging issue due to its underlying combinatorial complexity. Results: In this article, we illustrate that the full set of EFMs can be enumerated in increasing order of number of reactions via integer linear programming. In this light, we present a novel procedure to efficiently determine the K-shortest EFMs in large-scale metabolic networks. Our method was applied to find the K-shortest EFMs that produce lysine in the genome-scale metabolic networks of Escherichia coli and Corynebacterium glutamicum. A detailed analysis of the biological significance of the K-shortest EFMs was conducted, finding that glucose catabolism, ammonium assimilation, lysine anabolism and cofactor balancing were correctly predicted. The work presented here represents an important step forward in the analysis and computation of EFMs for large-scale metabolic networks, where traditional methods fail for networks of even moderate size. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online (http://bioinformatics.oxfordjournals.org/cgi/content/full/btp564/DC1).Fundação Calouste Gulbenkian, Fundação para a CiĂŞncia e a Tecnologia (FCT) and Siemens SA Portugal

    Seafloor incubation experiment with deep-sea hydrothermal vent fluid reveals effect of pressure and lag time on autotrophic microbial communities

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    © The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Fortunato, C. S., Butterfield, D. A., Larson, B., Lawrence-Slavas, N., Algar, C. K., Zeigler Allen, L., Holden, J. F., Proskurowski, G., Reddington, E., Stewart, L. C., Topçuoğlu, B. D., Vallino, J. J., & Huber, J. A. Seafloor incubation experiment with deep-sea hydrothermal vent fluid reveals effect of pressure and lag time on autotrophic microbial communities. Applied and Environmental Microbiology, 87, (2021): e00078-21, https://doi.org/10.1128/AEM.00078-21Depressurization and sample processing delays may impact the outcome of shipboard microbial incubations of samples collected from the deep sea. To address this knowledge gap, we developed a remotely operated vehicle (ROV)-powered incubator instrument to carry out and compare results from in situ and shipboard RNA stable isotope probing (RNA-SIP) experiments to identify the key chemolithoautotrophic microbes and metabolisms in diffuse, low-temperature venting fluids from Axial Seamount. All the incubations showed microbial uptake of labeled bicarbonate primarily by thermophilic autotrophic Epsilonbacteraeota that oxidized hydrogen coupled with nitrate reduction. However, the in situ seafloor incubations showed higher abundances of transcripts annotated for aerobic processes, suggesting that oxygen was lost from the hydrothermal fluid samples prior to shipboard analysis. Furthermore, transcripts for thermal stress proteins such as heat shock chaperones and proteases were significantly more abundant in the shipboard incubations, suggesting that depressurization induced thermal stress in the metabolically active microbes in these incubations. Together, the results indicate that while the autotrophic microbial communities in the shipboard and seafloor experiments behaved similarly, there were distinct differences that provide new insight into the activities of natural microbial assemblages under nearly native conditions in the ocean.This work was funded by Gordon and Betty Moore Foundation grant GBMF3297; the NSF Center for Dark Energy Biosphere Investigations (C-DEBI) (OCE-0939564), contribution number 562; NOAA/PMEL, contribution number 5182; and the Joint Institute for the Study of the Atmosphere and Ocean (JISAO) under NOAA cooperative agreement NA15OAR4320063, contribution number 2020-1113. The RNA-SIP methodology used in this work was developed during cruise FK010-2013 aboard the R/V Falkor supported by the Schmidt Ocean Institute. The NOAA/PMEL supported this work with ship time in 2014 and through funding to the Earth Ocean Interactions group. NSF provided ship time for the 2015 expedition through OCE-1546695 to D.A.B. and OCE-1547004 to J.F.H

    Unique arbuscular mycorrhizal fungal communities uncovered in date palm plantations and surrounding desert habitats of Southern Arabia

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    The main objective of this study was to shed light on the previously unknown arbuscular mycorrhizal fungal (AMF) communities in Southern Arabia. We explored AMF communities in two date palm (Phoenix dactylifera) plantations and the natural vegetation of their surrounding arid habitats. The plantations were managed traditionally in an oasis and according to conventional guidelines at an experimental station. Based on spore morphotyping, the AMF communities under the date palms appeared to be quite diverse at both plantations and more similar to each other than to the communities under the ruderal plant, Polygala erioptera, growing at the experimental station on the dry strip between the palm trees, and to the communities uncovered under the native vegetation (Zygophyllum hamiense, Salvadora persica, Prosopis cineraria, inter-plant area) of adjacent undisturbed arid habitat. AMF spore abundance and species richness were higher under date palms than under the ruderal and native plants. Sampling in a remote sand dune area under Heliotropium kotschyi yielded only two AMF morphospecies and only after trap culturing. Overall, 25 AMF morphospecies were detected encompassing all study habitats. Eighteen belonged to the genus Glomus including four undescribed species. Glomus sinuosum, a species typically found in undisturbed habitats, was the most frequently occurring morphospecies under the date palms. Using molecular tools, it was also found as a phylogenetic taxon associated with date palm roots. These roots were associated with nine phylogenetic taxa, among them eight from Glomus group A, but the majority could not be assigned to known morphospecies or to environmental sequences in public databases. Some phylogenetic taxa seemed to be site specific. Despite the use of group-specific primers and efficient trapping systems with a bait plant consortium, surprisingly, two of the globally most frequently found species, Glomus intraradices and Glomus mosseae, were not detected neither as phylogenetic taxa in the date palm roots nor as spores under the date palms, the intermediate ruderal plant, or the surrounding natural vegetation. The results highlight the uniqueness of AMF communities inhabiting these diverse habitats exposed to the harsh climatic conditions of Southern Arabia

    OptCom: A Multi-Level Optimization Framework for the Metabolic Modeling and Analysis of Microbial Communities

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    Microorganisms rarely live isolated in their natural environments but rather function in consolidated and socializing communities. Despite the growing availability of high-throughput sequencing and metagenomic data, we still know very little about the metabolic contributions of individual microbial players within an ecological niche and the extent and directionality of interactions among them. This calls for development of efficient modeling frameworks to shed light on less understood aspects of metabolism in microbial communities. Here, we introduce OptCom, a comprehensive flux balance analysis framework for microbial communities, which relies on a multi-level and multi-objective optimization formulation to properly describe trade-offs between individual vs. community level fitness criteria. In contrast to earlier approaches that rely on a single objective function, here, we consider species-level fitness criteria for the inner problems while relying on community-level objective maximization for the outer problem. OptCom is general enough to capture any type of interactions (positive, negative or combinations thereof) and is capable of accommodating any number of microbial species (or guilds) involved. We applied OptCom to quantify the syntrophic association in a well-characterized two-species microbial system, assess the level of sub-optimal growth in phototrophic microbial mats, and elucidate the extent and direction of inter-species metabolite and electron transfer in a model microbial community. We also used OptCom to examine addition of a new member to an existing community. Our study demonstrates the importance of trade-offs between species- and community-level fitness driving forces and lays the foundation for metabolic-driven analysis of various types of interactions in multi-species microbial systems using genome-scale metabolic models

    Whole blood gene expression profiling in preclinical and clinical cattle infected with atypical bovine spongiform encephalopathy

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    Prion diseases, such as bovine spongiform encephalopathies (BSE), are transmissible neurodegenerative disorders affecting humans and a wide variety of mammals. Variant Creutzfeldt-Jakob disease (vCJD), a prion disease in humans, has been linked to exposure to BSE prions. This classical BSE (cBSE) is now rapidly disappearing as a result of appropriate measures to control animal feeding. Besides cBSE, two atypical forms (named Hand L-type BSE) have recently been described in Europe, Japan, and North America. Here we describe the first wide-spectrum microarray analysis in whole blood of atypical BSEinfected cattle. Transcriptome changes in infected animals were analyzed prior to and after the onset of clinical signs. The microarray analysis revealed gene expression changes in blood prior to the appearance of the clinical signs and during the progression of the disease. A set of 32 differentially expressed genes was found to be in common between clinical and preclinical stages and showed a very similar expression pattern in the two phases. A 22-gene signature showed an oscillating pattern of expression, being differentially expressed in the preclinical stage and then going back to control levels in the symptomatic phase. One gene, SEL1L3, was downregulated during the progression of the disease. Most of the studies performed up to date utilized various tissues, which are not suitable for a rapid analysis of infected animals and patients. Our findings suggest the intriguing possibility to take advantage of whole blood RNA transcriptional profiling for the preclinical identification of prion infection. Further, this study highlighted several pathways, such as immune response and metabolism that may play an important role in peripheral prion pathogenesis. Finally, the gene expression changes identified in the present study may be further investigated as a fingerprint for monitoring the progression of disease and for developing targeted therapeutic interventions. \ua9 2016 Xerxa et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
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