Search results for "Process"

showing 10 items of 22310 documents

The effect of maze complexity on maze-solving time in a desert ant

2019

One neglected aspect of research on foraging behavior is that of the effect of obstacles that increase habitat complexity on foraging efficiency. Here, we explored how long it takes individually foraging desert ant workers (Cataglyphis niger) to reach a food reward in a maze, and examined whether maze complexity affects maze-solving time (the time elapsed till the first worker reached the food reward). The test mazes differed in their complexity level, or the relative number of correct paths leading to the food reward, vs. wrong paths leading to dead-ends. Maze-solving time steeply increased with maze complexity, but was unaffected by colony size, despite the positive correlation between co…

0106 biological sciencesTime FactorsForagingPositive correlation010603 evolutionary biology01 natural sciencesBehavioral NeuroscienceRandom searchRewardStatisticsAnimals0501 psychology and cognitive sciences050102 behavioral science & comparative psychologyMaze LearningMathematicsbiologyAnts05 social sciencesFeeding BehaviorGeneral Medicinebiology.organism_classificationFoodCataglyphisExploratory BehaviorAnimal Science and ZoologyCataglyphis nigerpsychological phenomena and processesBehavioural Processes
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The irreducible uncertainty of the demography–environment interaction in ecology

2002

The interpretation of ecological data has been greatly improved by bridging the gap between ecological and statistical models. The major challenge is to separate competing hypotheses concerning demography, or other ecological relationships, and environmental variability (noise). In this paper we demonstrate that this may be an arduous, if not impossible, task. It is the lack of adequate ecological theory, rather than statistical sophistication, which leads to this problem. A reconstruction of underlying ecological processes can only be done if we are certain of either the demographic or the noise model, which is something that can only be achieved by an improved theory of stochastic ecologi…

0106 biological sciencesTime Factorsmedia_common.quotation_subjectPopulation DynamicsBiologyEcological systems theoryModels Biological010603 evolutionary biology01 natural sciencesGeneral Biochemistry Genetics and Molecular BiologyEcological relationshipEconometricsAnimalsNatural ecosystemEnvironmental noiseSophisticationEcosystemGeneral Environmental Sciencemedia_commonStochastic ProcessesModels StatisticalGeneral Immunology and MicrobiologyEcologyStochastic process010604 marine biology & hydrobiologySystem identificationStatistical modelGeneral MedicineBiological Sciences13. Climate actionGeneral Agricultural and Biological SciencesResearch ArticleDemographyProceedings of the Royal Society of London. Series B: Biological Sciences
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Combining spatial prioritization and expert knowledge facilitates effectiveness of large-scale mire protection process in Finland

2019

Conservation resource allocation involves a complex set of considerations including species, habitats, connectivity, local to global biodiversity objectives, alternative protection and restoration actions, while requiring cost-efficiency and effective implementation. We present a national scale spatial conservation prioritization analysis for complementing the network of protected mires in Finland. We show how spatial prioritization coupled with regional targets and expert knowledge can facilitate structured decision-making. In our application, discussion between experts was structured around the prioritization model enabling integration of quantitative analysis with expert knowledge. The u…

0106 biological sciencesTrade-offsProcess (engineering)Computer science010604 marine biology & hydrobiologyScale (chemistry)MiresRestoration prioritization15. Life on land010603 evolutionary biology01 natural sciencesUnit (housing)Quantitative analysis (finance)13. Climate actionImplementationKey (cryptography)Expert knowledgeResource allocationSpatial prioritizationKnowledge transferEnvironmental planningEcology Evolution Behavior and Systematics1172 Environmental sciencesNature and Landscape ConservationGlobal biodiversity
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Guidance for the risk assessment of the presence at low level of genetically modified plant material in imported food and feed under Regulation (EC) …

2017

Abstract This document provides guidance for the risk assessment under Regulation (EC) No 1829/2003 of the unintended, adventitious or technically unavoidable presence in food and feed of low level of genetically modified plant material intended for markets other than in the European Union. In this context, the presence at low level is defined to be maximum 0.9% of genetically modified plant material per ingredient. This guidance is intended to assist applicants by indicating which scientific requirements of Annex II of Regulation (EU) No 503/2013 are considered necessary for the risk assessment of the presence at low levels of genetically modified plant material in food and feed.

0106 biological sciencesVeterinary (miscellaneous)[SDV]Life Sciences [q-bio]Context (language use)Plant ScienceGenetically modified crops010501 environmental sciences01 natural sciencesMicrobiologyRegulation (EU) No 503/2013Ingredientpresence at low level[SDV.IDA]Life Sciences [q-bio]/Food engineeringmedia_common.cataloged_instance[SDV.BV]Life Sciences [q-bio]/Vegetal BiologySettore AGR/18 - Nutrizione E Alimentazione Animale[SPI.GPROC]Engineering Sciences [physics]/Chemical and Process EngineeringEuropean unionfood/feed0105 earth and related environmental sciencesmedia_commonguidance;GMO;presence at low level;risk assessment;Regulation (EC) No 1829/2003;Regulation (EU) No 503/2013;food/feedbusiness.industryGMORegulation (EC) No 1829/2003risk assessmentguidance; GMO; presence at low level; risk assessment; Regulation (EC) No 1829/2003; Regulation (EU) No 503/2013; food/feed10079 Institute of Veterinary Pharmacology and ToxicologyFood safetyBiotechnologyRegulation (EU) No 503/2013Scientific OpinionSettore AGR/11 - Entomologia Generale E Applicata570 Life sciences; biologyAnimal Science and ZoologyParasitologyRisk assessmentbusinessguidanceRegulation (EC) No 1829/2003010606 plant biology & botanyFood Science
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Humusica 1, article 1: Essential bases – Vocabulary

2018

International audience; The Special Issue Humusica 1 corresponds to a field guide for the classification of terrestrial humus systems and forms. The present first article of the issue defines vocabulary, objects and concepts necessary for: (a) field investigation, (b) understanding the process of classification, (c) assigning ecological significance to the defined morpho-functional units, (d) discussing and exchanging scientific data about humus systems. The article starts with general considerations, as the necessity humans have to classify natural objects for sharing ideas and information on them. Then the article focuses on soil as functional element of every ecosystem. Historical and re…

0106 biological sciencesVocabularyComputer scienceProcess (engineering)media_common.quotation_subjectSoil Science[SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil study010603 evolutionary biology01 natural sciencesHumusHumus Humusica Humus form classification Humus system Humus vocabulary Soil classification Soil conceptSoil concept ABSTRACT[SDV.EE.ECO]Life Sciences [q-bio]/Ecology environment/EcosystemsSoil classificationSoil conceptNatural (music)Humus vocabularymedia_common2. Zero hungerHumus form classificationTopsoilEcologyEcology04 agricultural and veterinary sciences15. Life on landAgricultural and Biological Sciences (miscellaneous)HumusField (geography)EpistemologyVariety (cybernetics)040103 agronomy & agricultureHumusica0401 agriculture forestry and fisheriesSoil horizon[SDE.BE]Environmental Sciences/Biodiversity and EcologyHumus system
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Production of 3-hydroxy-γ-decalactone, the precursor of two decenolides with flavouring properties, by the yeast Yarrowia lipolytica

2009

3-Hydroxy-γ-decalactone is the precursor of dec-2 and dec-3-en-4-olides which are valuable aroma compounds not yet produced. To promote the accumulation of this lactone, the yeast Yarrowia lipolytica was placed in different environmental conditions aiming at altering β-oxidation fluxes. The concentration of substrate, pH, aeration and dissolved oxygen level were modified. We observed an important accumulation at low aeration (0.40 molar yields) and, to a lesser extent, at lower pH (0.15). As oxygen played a key-role, we evaluated its effect at fixed dissolved oxygen and at the pH which was the most favourable to the biotransformation (pH 4.5). At 5% and 30% dissolved oxygen, yields reached …

0106 biological sciencesYarrowia lipolyticachemistry.chemical_elementBioengineering3-Hydroxy-gamma-decalactone01 natural sciencesBiochemistryOxygenCatalysis03 medical and health sciencesBiotransformation010608 biotechnologyOrganic chemistryAroma030304 developmental biology2. Zero hungerchemistry.chemical_classification0303 health sciencesScience & TechnologybiologyProcess Chemistry and Technologyβ-Oxidation fluxesSubstrate (chemistry)Yarrowiabiology.organism_classificationYeastOxygenchemistry3-Hydroxy-γ-decalactoneAerationLactonebeta-Oxidation fluxes
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Satellite survey of seasonal trophic status and occasional anoxic 'malaigue' crises in the Thau lagoon using MERIS images

2011

International audience; The Thau lagoon, located in southern France, suffers episodically from anoxic crises locally known as 'malaigue'. Such crises mostly occur under warm conditions, low winds leading to a strong eutrophication of the lagoon. The development of a sulphur bacterium sometimes gives locally to the waters a 'milky turquoise' appearance and leads to shellfish mortality. One of the indicators of the eutrophication status of the lagoon can be surveyed by the chlorophyll product provided by remote sensing images such as Medium Resolution Imaging Spectrometer (MERIS). In this paper we compare chl2 (or algal2) estimations provided by MERIS level 2 products and the ground measureme…

0106 biological sciences[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing010504 meteorology & atmospheric sciencesEcology[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing010604 marine biology & hydrobiology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing01 natural sciencesAnoxic waters6. Clean waterMedium resolutionOceanography[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing13. Climate actionGeneral Earth and Planetary SciencesEnvironmental scienceSatellite14. Life underwaterEutrophication[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing0105 earth and related environmental sciencesTrophic level[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
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GenExP, un logiciel simulateur de paysages agricoles pour l'étude de la diffusion de transgènes

2007

 ; The software GENEXP allows to simulate 2-dimensional agricultural landscapes by using a traditional algorithmic geometry. Based on real or realistic field-patterns, GENEXP provides multiannual maps of agricultural landscapes, which are used by softwares simulating the dispersal of GM pollen grains and seeds at various scales.; GENEXP est un simulateur de paysages agricoles qui engendre des découpages parcellaires en utilisant une géométrie algorithmique classique. GENEXP fournit, sur la base de parcellaires réels ou réalistes, des cartes pluriannuelles de paysages agricoles utilisables par des logiciels qui simulent la dispersion des pollens et des graines d'OGM à différentes échelles.

0106 biological sciences[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]010603 evolutionary biology01 natural sciencesVORONOÏ TESSELATION[ SDV.EE ] Life Sciences [q-bio]/Ecology environmentAGRICULTURAL LANDSCAPE[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]diagrammes de Voronoi[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]DIAGRAMMES DE VORONOÏpaysage agricole[SDV.EE]Life Sciences [q-bio]/Ecology environmentFIELD PATTERN[INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]voronoi tesselationPROCESSUS PONCTUEL MARKOVIEN04 agricultural and veterinary sciencesGeneral Medicineflux de genes15. Life on landsimulationPARCELLAIRE[SDV.EE] Life Sciences [q-bio]/Ecology environmentagricultural landscape field-pattern germs distribution markov point process gene flowpaysage agricole parcellaire simulation diagrammes de Voronoi distribution de germes processus ponctuel markovien flux de genes voronoi tesselation INFORMATIQUEGERMS DISTRIBUTIONINFORMATIQUE040103 agronomy & agricultureMARKOV POINT PROCESS0401 agriculture forestry and fisheriesfield-patterngene flowDISTRIBUTION DE GERMES
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Protocol for the Definition of a Multi-Spectral Sensor for Specific Foliar Disease Detection: Case of “Flavescence Dorée”

2018

Flavescence Doree (FD) is a contagious and incurable grapevine disease that can be perceived on leaves. In order to contain its spread, the regulations obligate winegrowers to control each plant and to remove the suspected ones. Nevertheless, this monitoring is performed during the harvest and mobilizes many people during a strategic period for viticulture. To solve this problem, we aim to develop a Multi-Spectral (MS) imaging device ensuring an automated grapevine disease detection solution. If embedded on a UAV, the tool can provide disease outbreaks locations in a geographical information system allowing localized and direct treatment of infected vines. The high-resolution MS camera aims…

0106 biological sciences[SDE] Environmental SciencesDisease detectionComputer science[SDV]Life Sciences [q-bio]Multispectral imageradiometric/geometric correctionsFeature selectionMulti spectral01 natural sciencesfeature selection[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal Biologytexture analysisProtocol (science)Artificial neural networkbusiness.industrymultispectral sensorOutbreakPattern recognition04 agricultural and veterinary sciencesFlavescence Dorée3. Good health[SDV] Life Sciences [q-bio]Identification (information)classification[SDE]Environmental Sciences040103 agronomy & agriculture0401 agriculture forestry and fisheriesFlavescence doréeArtificial intelligencebusiness010606 plant biology & botany
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New challenges and opportunities of food fermentation processes: Application of conventional and innovative techniques.

2019

International audience

0106 biological sciences[SDV.BIO]Life Sciences [q-bio]/BiotechnologyFood Handling[SDV]Life Sciences [q-bio]Food technology01 natural sciencesFood handling0404 agricultural biotechnology010608 biotechnologyFood IndustryHumans[SPI.GPROC]Engineering Sciences [physics]/Chemical and Process EngineeringFermentation in food processingComputingMilieux_MISCELLANEOUSbusiness.industry[SDE.IE]Environmental Sciences/Environmental EngineeringResearch04 agricultural and veterinary sciences040401 food scienceFoodFermentationFood TechnologyFermentationBusinessBiochemical engineeringFermented Foods[SDV.AEN]Life Sciences [q-bio]/Food and NutritionFood ScienceBiotechnologyFood research international (Ottawa, Ont.)
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