Search results for "POPULATIONS"

showing 10 items of 493 documents

Dominance of wine Saccharomyces cerevisiae strains over S. kudriavzevii in industrial fermentation competitions is related to an acceleration of nutr…

2019

Grape must is a sugar‐rich habitat for a complex microbiota which is replaced by Saccharomyces cerevisiae strains during the first fermentation stages. Interest on yeast competitive interactions has recently been propelled due to the use of alternative yeasts in the wine industry to respond to new market demands. The main issue resides in the persistence of these yeasts due to the specific competitive activity of S. cerevisiae. To gather deeper knowledge of the molecular mechanisms involved, we performed a comparative transcriptomic analysis during fermentation carried out by a wine S. cerevisiae strain and a strain representative of the cryophilic S. kudriavzevii, which exhibits high genet…

Grape juicemedia_common.quotation_subjectAdaptive evolutionSaccharomyces cerevisiaeWineIndustrial fermentationSaccharomyces cerevisiaeMicrobiologyYeast populationsCompetition (biology)Saccharomyces03 medical and health sciencesMessenger-RNAMechanismsVitisGene-expressionFood scienceAdaptationEcological interactionsEcology Evolution Behavior and Systematics030304 developmental biologymedia_commonWine0303 health sciencesbiology030306 microbiologyProteinStrain (biology)food and beveragesNutrientsbiology.organism_classificationAdaptation PhysiologicalYeastPhenotypeFermentationFermentationAdaptationPopulation genomicsEnvironmental Microbiology
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Bridging landscape graphs and genetic graphs for analysing habitat ecological connectivity

2021

Several key ecological processes for maintaining biodiversity rely upon the ecological connectivity of habitat. Accordingly, connectivity modelling methods have been developed for understanding precisely the influence of connectivity and deriving sound biodiversity conservation measures. Among them, landscape graphs represent habitat networks as sets of habitat patches (nodes) connected by potential dispersal paths (links). Yet, the ecological relevance of these tools required validation from biological data reflecting closely the influence of habitat connectivity. Genetic data allow for such validation as population genetic structure partly depends on dispersal-driven gene flow between hab…

Graph theory[SDV.SA] Life Sciences [q-bio]/Agricultural sciencesGénétique des populationsPopulation geneticsLandscape ecologyÉcologie du paysageThéorie des graphesHabitat connectivityNetworksRéseauxConnectivité des habitats
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"Table 24" of "Search for magnetic monopoles and stable high-electric-charge objects in 13 TeV proton-proton collisions with the ATLAS detector"

2019

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=20$ of mass 1500 GeV.

HECO13000.0Computer Science::Information RetrievalQuantitative Biology::Populations and EvolutionEFFComputer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing)High Energy Physics::ExperimentMEfficiencyNuclear Experiment
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"Table 47" of "Search for magnetic monopoles and stable high-electric-charge objects in 13 TeV proton-proton collisions with the ATLAS detector"

2019

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=80$ of mass 1000 GeV.

HECO13000.0Computer Science::Information RetrievalQuantitative Biology::Populations and EvolutionEFFComputer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing)High Energy Physics::ExperimentMEfficiencyNuclear Experiment
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"Table 34" of "Search for magnetic monopoles and stable high-electric-charge objects in 13 TeV proton-proton collisions with the ATLAS detector"

2019

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=40$ of mass 2500 GeV.

HECO13000.0Computer Science::Information RetrievalQuantitative Biology::Populations and EvolutionEFFComputer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing)High Energy Physics::ExperimentMEfficiencyNuclear Experiment
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"Table 22" of "Search for magnetic monopoles and stable high-electric-charge objects in 13 TeV proton-proton collisions with the ATLAS detector"

2019

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=20$ of mass 500 GeV.

HECO13000.0Computer Science::Information RetrievalQuantitative Biology::Populations and EvolutionEFFComputer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing)High Energy Physics::ExperimentMEfficiencyNuclear Experiment
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"Table 52" of "Search for magnetic monopoles and stable high-electric-charge objects in 13 TeV proton-proton collisions with the ATLAS detector"

2019

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=80$ of mass 4000 GeV.

HECO13000.0Computer Science::Information RetrievalQuantitative Biology::Populations and EvolutionEFFComputer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing)High Energy Physics::ExperimentMEfficiencyNuclear Experiment
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"Table 26" of "Search for magnetic monopoles and stable high-electric-charge objects in 13 TeV proton-proton collisions with the ATLAS detector"

2019

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=20$ of mass 2500 GeV.

HECO13000.0Computer Science::Information RetrievalQuantitative Biology::Populations and EvolutionEFFComputer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing)High Energy Physics::ExperimentMEfficiencyNuclear Experiment
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"Table 21" of "Search for magnetic monopoles and stable high-electric-charge objects in 13 TeV proton-proton collisions with the ATLAS detector"

2019

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=20$ of mass 200 GeV.

HECO13000.0Computer Science::Information RetrievalQuantitative Biology::Populations and EvolutionEFFComputer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing)High Energy Physics::ExperimentMEfficiencyNuclear Experiment
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"Table 36" of "Search for magnetic monopoles and stable high-electric-charge objects in 13 TeV proton-proton collisions with the ATLAS detector"

2019

Total selection efficiency (i.e., the fraction of MC HECOs surviving the trigger and offline selection criteria) as a function of transverse kinetic energy $E^\text{kin}_\text{T}=E_\text{kin}\sin\theta$ and pseudorapidity $|\eta|$ for HECOs of charge $|z|=40$ of mass 4000 GeV.

HECO13000.0Computer Science::Information RetrievalQuantitative Biology::Populations and EvolutionEFFComputer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing)High Energy Physics::ExperimentMEfficiencyNuclear Experiment
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