Search results for "texture"

showing 10 items of 402 documents

Développement de l'acceptabilité des aliments solides. A partir de quel âge les morceaux sont-ils acceptés par l'enfant sain ?

2019

Les aliments solides sont proposés aux nourrissons vers 4-6 mois, lorsque leurs besoins nutritionnels ne peuvent plus être uniquement assurés par le lait. Ces aliments (fruits, légumes, produits céréaliers…) sont généralement proposés sous forme de purée ou de bouillie. Au fil des mois, les purées sont ensuite remplacées par des textures de plus en plus consistantes et dures, permettant à l'enfant d'apprendre progressivement à manger les aliments de la table familiale. Cet apprentissage est dépendant du développement des capacités masticatoires de l'enfant, particulièrement dynamique dans la petite enfance. En effet, pour accepter un aliment, l'enfant doit être capable de le manger. Si, à l…

food oral processing[SDV.MHEP.PED]Life Sciences [q-bio]/Human health and pathology/Pediatricsmasticationalimentfoodstuff[SDV.AEN] Life Sciences [q-bio]/Food and Nutritionnourrisson[SDV.MHEP.PED] Life Sciences [q-bio]/Human health and pathology/Pediatricschildrencapacité d'absorptiondiversification alimentairerecommandationsdevelopmenttextureenfant[SDV.AEN]Life Sciences [q-bio]/Food and NutritionComputingMilieux_MISCELLANEOUSdéveloppement
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Biotic and abiotic soil properties influence survival of Listeria monocytogenes in soil

2013

International audience; Listeria monocytogenes is a food-borne pathogen responsible for the potentially fatal disease listeriosis and terrestrial ecosystems have been hypothesized to be its natural reservoir. Therefore, identifying the key edaphic factors that influence its survival in soil is critical. We measured the survival of L. monocytogenes in a set of 100 soil samples belonging to the French Soil Quality Monitoring Network. This soil collection is meant to be representative of the pedology and land use of the whole French territory. The population of L. monocytogenes in inoculated microcosms was enumerated by plate count after 7, 14 and 84 days of incubation. Analysis of survival pr…

french soil monitoring network;basic cation saturation ratio;endogenous microbiota;pH;survival;Listeria monocytogenesSoil texture[SDV]Life Sciences [q-bio]ScienceBiologysurvivalcomplex mixturesSoil03 medical and health sciencesSoil pH[SDV.BV]Life Sciences [q-bio]/Vegetal BiologySoil ecologyPedologyfrench soil monitoring networkSoil Microbiology030304 developmental biology2. Zero hunger0303 health sciencesMultidisciplinarypH030306 microbiologybasic cation saturation ratioQRSoil chemistryEdaphic15. Life on landBiotaListeria monocytogenesSoil qualityendogenous microbiotaAgronomy[SDE]Environmental SciencesMedicineSoil microbiologyResearch Article
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Validation and application of a PCR primer set to quantify fungal communities in the soil environment by real-time quantitative PCR

2011

Fungi constitute an important group in soil biological diversity and functioning. However, characterization and knowledge of fungal communities is hampered because few primer sets are available to quantify fungal abundance by real-time quantitative PCR (real-time Q-PCR). The aim in this study was to quantify fungal abundance in soils by incorporating, into a real-time Q-PCR using the SYBRGreen (R) method, a primer set already used to study the genetic structure of soil fungal communities. To satisfy the real-time Q-PCR requirements to enhance the accuracy and reproducibility of the detection technique, this study focused on the 18S rRNA gene conserved regions. These regions are little affec…

fungal abundance organic carbon content real-time Q-PCR length polymorphism SYBRGreen method type de sol[SDV]Life Sciences [q-bio]lcsh:MedicinePlant SciencePlant Roots18S ribosomal RNASYBRGreen methodtype de sol[ SDE ] Environmental SciencesSoilFungal Reproductionlcsh:ScienceDNA FungalPhylogenyorganic carbon content2. Zero hunger0303 health sciencesDiversityMultidisciplinaryfungal abundanceEcologyEcologyRevealsFungal geneticsPolymerase-chain-reactionAgricultureBiodiversityAmpliconSoil Ecologysoil texture amplification enzymatique de l'adnBacterial communitiesSamplesreal-time Q-PCRCommunity Ecology[SDE]Environmental SciencesRhizosphereResearch ArticleSoil textureIn silicoMolecular Sequence DataSoil ScienceComputational biologyMycologyBiologyReal-Time Polymerase Chain ReactionMicrobiologyMicrobial Ecology03 medical and health sciencesSpecies SpecificityMedicago truncatulaMicrobial communityRNA Ribosomal 18SSoil ecologyBiology030304 developmental biologyDNA PrimersRibosomal-Rna genes[ SDV ] Life Sciences [q-bio]030306 microbiologylcsh:RFungiBotanyReproducibility of Resultslength polymorphismsoil textureSequence Analysis DNADna15. Life on landamplification enzymatique de l'adnDNA extractionlcsh:QPrimer (molecular biology)
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Classification of SD-OCT Volumes Using Local Binary Patterns: Experimental Validation for DME Detection

2016

International audience; This paper addresses the problem of automatic classification of Spectral Domain OCT (SD-OCT) data for automatic identification of patients with Diabetic Macular Edema (DME) versus normal subjects. Optical Coherence Tomography (OCT) has been a valuable diagnostic tool for DME, which is among the most common causes of irreversible vision loss in individuals with diabetes. Here, a classification framework with five distinctive steps is proposed and we present an extensive study of each step. Our method considers combination of various pre-processings in conjunction with Local Binary Patterns (LBP) features and different mapping strategies. Using linear and non-linear cl…

genetic structures[INFO.INFO-IM] Computer Science [cs]/Medical Imaging[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]0302 clinical medicine[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Segmentationlcsh:OphthalmologySpeckleLBPDiagnosisPrevalencePreprocessorComputer visionSegmentationmedicine.diagnostic_test[ INFO.INFO-IM ] Computer Science [cs]/Medical ImagingExperimental validationDiabetic Macular Edema[ SDV.MHEP.OS ] Life Sciences [q-bio]/Human health and pathology/Sensory OrgansOptical Coherence Tomography[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingResearch ArticleArticle SubjectLocal binary patterns03 medical and health sciencesSpeckle patternOptical coherence tomography[ SDV.MHEP ] Life Sciences [q-bio]/Human health and pathologyMedical imagingmedicineDME[INFO.INFO-IM]Computer Science [cs]/Medical ImagingCoherence (signal processing)Texture[SDV.MHEP.OS]Life Sciences [q-bio]/Human health and pathology/Sensory OrgansRetinopathy[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingbusiness.industry[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Pattern recognitioneye diseasesOphthalmologyOCTlcsh:RE1-994030221 ophthalmology & optometryImagesArtificial intelligencebusiness030217 neurology & neurosurgery[SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
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Impact of climate, soil properties and grassland cover on soil water repellency

2021

Abstract Numerous soil water repellency (SWR) studies have investigated the possible causes of this temporal phenomenon, yet there remains a lack of knowledge on the order of importance of the main driving forces of SWR in the context of changing environmental conditions under grassland ecosystems. To study the separate and combined effects of soil texture, climate, and grassland cover type on inducing or altering SWR, four sites from different climatic and soil regions were selected: Ciavolo (CI, IT), Csolyospalos (CSP, HU), Pwllpeiran (PW, UK), Sekule (SE, SK). The investigated parameters were the extent (determined by repellency indices RI, RIc and RIm) and persistence (determined by wat…

geographygeography.geographical_feature_categoryHydrophobic soilSoil textureSorptivitySoil ScienceSoil properties Soil water repellency Grass Length of dry periods Climate factors04 agricultural and veterinary sciences010501 environmental sciences01 natural sciencesSink (geography)GrasslandAgronomyHydraulic conductivitySoil water040103 agronomy & agriculture0401 agriculture forestry and fisheriesEnvironmental scienceSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-ForestaliSoil fertility0105 earth and related environmental sciences
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A pedotransfer function for estimating the soil erodibility factor in Sicily

2009

The soil erodibility factor, K, of the Universal Soil Loss Equation (USLE) is a simple descriptor of the soil susceptibility to rill and interrill erosion. The original procedure for determining K needs a knowledge of soil particle size distribution (PSD), soil organic matter, OM, content, and soil structure and permeability characteristics. However, OM data are often missing and soil structure and permeability are not easily evaluated in regional analyses. The objective of this investigation was to develop a pedotransfer function (PTF) for estimating the K factor of the USLE in Sicily (south Italy) using only soil textural data. The nomograph soil erodibility factor and its associated firs…

geographygeography.geographical_feature_categorySoil textureMechanical EngineeringSoil organic matterlcsh:SBioengineeringSoil sciencelcsh:S1-972Industrial and Manufacturing EngineeringSoil gradationRilllcsh:AgricultureSoil erosion Soil erodibility Pedotransfer functionsUniversal Soil Loss EquationSoil structurePedotransfer functionErosionSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-Forestalilcsh:Agriculture (General)Mathematics
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Experiments for testing soil texture effects on flow resistance in mobile bed rills

2018

Abstract In this paper a recently theoretically deduced rill flow resistance equation, based on a power-velocity profile, was tested experimentally on plots of varying slopes and soil texture in which mobile bed rills are incised. Measurements of flow velocity, water depth, cross section area, wetted perimeter and bed slope conducted in rill reaches incised on experimental plots, having different slope values (9, 14, 22, 24 and 26%) and soil texture (clay fraction ranging from 42 to 73%), and literature data were used to calibrate the flow resistance equation. In particular, the relationship between the velocity profile parameter Γ, the channel slope, the flow Froude number and texture frac…

geographygeography.geographical_feature_categorySoil textureRill hydraulic0208 environmental biotechnologyFlow (psychology)Soil science02 engineering and technologyPlot measurement020801 environmental engineeringRillWetted perimetersymbols.namesakeVelocity profileFlow resistanceFlow velocitySoil textureSoil waterSoil erosionFroude numbersymbolsSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-ForestaliTexture (crystalline)GeologyEarth-Surface ProcessesCATENA
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Does oral health affect food comfortability and bolus properties during consumption of dairy products in elderly population?

2017

The elderly population is growing increasingly. In 2030, 1/3 of the population will be over 60 years old. However this population has specific nutritional needs and often, oral impairments such as loss of tooth and/or decrease of salivary flow. Therefore it is necessary to develop foods adapted for the elderly, in terms of organoleptic properties and nutritional composition. In this context, the purpose of this work is to study the impact of oral impairments of elderly persons on food comfortability and bolus properties during the consumption of dairy products.76 elderly persons (ages 66 to 88, 42 women and 34 men), with or without oral health problems in terms of dental and/or salivary sta…

goût alimentairesaveurinnovation alimentaire[ SDV.AEN ] Life Sciences [q-bio]/Food and Nutrition[ SDV.IDA ] Life Sciences [q-bio]/Food engineeringsanté humaine[SDV.IDA] Life Sciences [q-bio]/Food engineeringdigestionhuman healthaliment pour personne agéesaveur de l'alimenttaste[SDV.AEN] Life Sciences [q-bio]/Food and Nutritionstomatognathic diseasestexture de l'alimentnutritionperception de la texture[SDV.IDA]Life Sciences [q-bio]/Food engineeringsanté humain[SDV.AEN]Life Sciences [q-bio]/Food and Nutrition
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Digital Correlation Method Based on Micro-geometrical Texture Pattern for Strain Field Measurement

2011

International audience; Image correlation methods are widely used in experimental mechanics to obtain displacement field measurements. Currently, these methods are applied using digital images of the initial and deformed surfaces sprayed with black or white paint. Speckle patterns are then captured and the correlation is performed with a high degree of accuracy to an order of 0.01 pixels. In 3D, however, stereo-correlation leads to a lower degree of accuracy. Correlation techniques are based on the search for a sub-image (or pattern) displacement field. The work presented in this paper introduces a new correlation-based approach for 3D displacement field measurement that uses an additional …

laser scanner[ SPI.MECA.GEME ] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanical engineering [physics.class-ph]C.M.M.[PHYS.MECA.GEME] Physics [physics]/Mechanics [physics]/Mechanical engineering [physics.class-ph][ PHYS.MECA.GEME ] Physics [physics]/Mechanics [physics]/Mechanical engineering [physics.class-ph]image correlation[PHYS.MECA.GEME]Physics [physics]/Mechanics [physics]/Mechanical engineering [physics.class-ph]micro-geometric texture[SPI.MECA.GEME] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanical engineering [physics.class-ph]C.M.Mroughness pattern[SPI.MECA.GEME]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanical engineering [physics.class-ph]3D displacement field measurement
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HIGH QUALITY TEXTURE MAPPING PROCESS AIMED AT THE OPTIMIZATION OF 3D STRUCTURED LIGHT MODELS

2019

Abstract. This article presents the evaluation of a pipeline to develop a high-quality texture mapping implementation which makes it possible to carry out a semantic high-quality 3D textured model. Due to geometric errors such as camera parameters or limited image resolution or varying environmental parameters, the calculation of a surface texture from 2D images could present several color errors. And, sometimes, it needs adjustments to the RGB or lightness information on a defined part of the texture. The texture mapping procedure is composed of mesh parameterization, mesh partitioning, mesh segmentation unwraps, UV map and projection of island, UV layout optimization, mesh packing and mes…

lcsh:Applied optics. Photonics010504 meteorology & atmospheric sciencesComputer scienceMesh parameterizationComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technologyTexture Mapping Structured Light Scanning Restoration 3D Visualization Photogrammetry 3D modeling01 natural scienceslcsh:Technology0202 electrical engineering electronic engineering information engineeringSegmentationComputer visionImage resolution0105 earth and related environmental sciencesComputingMethodologies_COMPUTERGRAPHICSUV mappingbusiness.industrylcsh:Tlcsh:TA1501-1820020207 software engineering3D modelingVisualizationPhotogrammetrylcsh:TA1-2040RGB color modelSettore ICAR/17 - DisegnoArtificial intelligencebusinesslcsh:Engineering (General). Civil engineering (General)Texture mappingStructured lightThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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