Search results for " forest"

showing 10 items of 1940 documents

Piro-piro piccolo, Actitis hypoleucos Linnaeus 1758, che si alimenta in ambiente urbano a Pantelleria

2011

AdattamentoSettore AGR/05 - Assestamento Forestale E Selvicoltura
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A finite element-based machine learning approach for modeling the mechanical behavior of the breast tissues under compression in real-time

2017

[EN] This work presents a data-driven method to simulate, in real-time, the biomechanical behavior of the breast tissues in some image-guided interventions such as biopsies or radiotherapy dose delivery as well as to speed up multimodal registration algorithms. Ten real breasts were used for this work. Their deformation due to the displacement of two compression plates was simulated off-line using the finite element (FE) method. Three machine learning models were trained with the data from those simulations. Then, they were used to predict in real-time the deformation of the breast tissues during the compression. The models were a decision tree and two tree-based ensemble methods (extremely…

AdultFinite element methodsMean squared errorComputer scienceQuantitative Biology::Tissues and OrgansINGENIERIA MECANICAFinite Element AnalysisPhysics::Medical PhysicsDecision treeBreast compressionHealth Informatics02 engineering and technologyMachine learningcomputer.software_genreModels Biological030218 nuclear medicine & medical imagingSet (abstract data type)03 medical and health sciencesImaging Three-Dimensional0302 clinical medicineMachine learning0202 electrical engineering electronic engineering information engineeringHumansBreastbusiness.industryModelingEnsemble learningFinite element methodComputer Science ApplicationsRandom forestEuclidean distanceTree (data structure)Female020201 artificial intelligence & image processingArtificial intelligenceBreast biomechanicsbusinesscomputerLENGUAJES Y SISTEMAS INFORMATICOS
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MRI radiomics-based machine-learning classification of bone chondrosarcoma.

2019

Abstract Purpose To evaluate the diagnostic performance of machine learning for discrimination between low-grade and high-grade cartilaginous bone tumors based on radiomic parameters extracted from unenhanced magnetic resonance imaging (MRI). Methods We retrospectively enrolled 58 patients with histologically-proven low-grade/atypical cartilaginous tumor of the appendicular skeleton (n = 26) or higher-grade chondrosarcoma (n = 32, including 16 appendicular and 16 axial lesions). They were randomly divided into training (n = 42) and test (n = 16) groups for model tuning and testing, respectively. All tumors were manually segmented on T1-weighted and T2-weighted images by drawing bidimensiona…

AdultMalemedicine.medical_specialtyArtificial intelligenceAppendicular skeletonChondrosarcomaFeature selectionBone NeoplasmsBone and BonesMachine LearningImage Interpretation Computer-AssistedmedicineHumansRadiology Nuclear Medicine and imagingRetrospective StudiesLearning classifier systemReceiver operating characteristicmedicine.diagnostic_testbusiness.industryReproducibility of ResultsMagnetic resonance imagingGeneral MedicineMiddle Agedmedicine.diseaseMagnetic Resonance ImagingRandom forestStatistical classificationmedicine.anatomical_structureTexture analysisROC CurveCartilaginous tumorFemaleRadiologyChondrosarcomaRadiomicNeoplasm GradingbusinessEuropean journal of radiology
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Effects of Particulate Matter on the Incidence of Respiratory Diseases in the Pisan Longitudinal Study

2020

The current study aimed at assessing the effects of exposure to Particulate Matter (PM) on the incidence of respiratory diseases in a sub-sample of participants in the longitudinal analytical epidemiological study in Pisa, Italy. Three hundred and five subjects living at the same address from 1991 to 2011 were included. Individual risk factors recorded during the 1991 survey were considered, and new cases of respiratory diseases were ascertained until 2011. Average PM10 and PM2.5 exposures (&micro

AdultMalemedicine.medical_specialtyLongitudinal studyPercentilelong-term exposureair pollution;Health Toxicology and Mutagenesisair pollutionRespiratory Tract Diseaseslcsh:Medicinerandom forest;010501 environmental sciencesLogistic regression01 natural sciencesArticle03 medical and health sciences0302 clinical medicinequestionnaire;Environmental healthEpidemiologyMedicineHumansLongitudinal StudiesRespiratory systemRespiratory healthrespiratory symptoms/diseases0105 earth and related environmental sciencesAgedparticulate matterAir Pollutantsbusiness.industryIncidence (epidemiology)questionnaireIncidencelcsh:RPublic Health Environmental and Occupational HealthEnvironmental ExposureParticulatesMiddle Aged030228 respiratory systemItalyFemalebusinessrandom forestparticulate matter;International Journal of Environmental Research and Public Health
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Subgrouping factors influencing migraine intensity in women: A semi-automatic methodology based on machine learning and information geometry

2019

[EN] Background Migraine is a heterogeneous condition with multiple clinical manifestations. Machine learning algorithms permit the identification of population groups, providing analytical advantages over other modeling techniques. Objective The aim of this study was to analyze critical features that permit the differentiation of subgroups of patients with migraine according to the intensity and frequency of attacks by using machine learning algorithms. Methods Sixty-seven women with migraine participated. Clinical features of migraine, related disability (Migraine Disability Assessment Scale), anxiety/depressive levels (Hospital Anxiety and Depression Scale), anxiety state/trait levels (S…

AdultMigraine DisordersMachine learningcomputer.software_genreMachine LearningDisability Evaluation03 medical and health sciences0302 clinical medicine030202 anesthesiologyMachine learningHumansMedicine03.- Garantizar una vida saludable y promover el bienestar para todos y todas en todas las edadesInformation geometryPhysical ExaminationMigraineMultisource variabilityThesaurus (information retrieval)business.industryMiddle Agedmedicine.diseaseAnesthesiology and Pain MedicineMigraineFISICA APLICADAFemaleArtificial intelligenceSemi automaticbusinessMATEMATICA APLICADAcomputer030217 neurology & neurosurgeryRandom forest
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Updated measurements in vineyards improves accuracy of soil erosion rates

2018

All rights reserved. Vineyards have proven to be one of the most degraded agricultural ecosystems due to very high erosion rates, which are typically measured at fine temporal and spatial scales. Long-term soil erosion measures are rare, but this information may be indispensable for a proper understanding of the vineyard soil system, landscape evolution, and crop production. The stock unearthing method (SUM) is a common topographical measurement technique developed to assess long-term erosion rates. The reliance of the SUM has been questioned and should be replaced by an improved measurement technique. In this paper, we demonstrate the added value (improved accurate, low cost, and faster th…

Agricultural ecosystemsSoil science04 agricultural and veterinary sciences010501 environmental sciencesBodemfysica en LandbeheerPE&RC01 natural sciencesVineyardTillageSoil Physics and Land ManagementSoil lossAgronomy040103 agronomy & agricultureErosionLand degradation0401 agriculture forestry and fisheriesEnvironmental scienceLife ScienceAgronomy and Crop ScienceStock (geology)Soil movement0105 earth and related environmental sciences
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Agricultural management affects the response of soil bacterial community structure and respiration to water-stress

2013

International audience; Soil microorganisms are responsible for organic matter decomposition processes that regulate soil carbon storage and mineralisation to CO2. Climate change is predicted to increase the frequency of drought events, with uncertain consequences for soil microbial communities. In this study we tested the hypothesis that agricultural management used to enhance soil carbon stocks would increase the stability of microbial community structure and activity in response to water-stress. Soil was sampled from a long-term field trial with three soil carbon management systems and was used in a laboratory study of the effect of a dry wet cycle on organic C mineralisation and microbi…

Agricultural land use010504 meteorology & atmospheric sciencesSoil biodiversity[SDV]Life Sciences [q-bio]Soil biologySoil Science01 natural sciencesMicrobiologyDrying-rewettingFUNCTIONAL STABILITYSoil retrogression and degradation[SDV.BV]Life Sciences [q-bio]/Vegetal BiologyOrganic matterGlobal changeNITROGEN MINERALIZATION0105 earth and related environmental sciences2. Zero hungerchemistry.chemical_classificationC mineralisationCLIMATE-CHANGEMICROBIAL COMMUNITYEcologySoil organic matterLAND-USE CHANGE04 agricultural and veterinary sciencesSoil carbonRESILIENCE15. Life on landDRYING-REWETTING FREQUENCYORGANIC-MATTERAgronomychemistryMicrobial population biology13. Climate action[SDE]Environmental Sciences040103 agronomy & agricultureBacterial community structure0401 agriculture forestry and fisheriesEnvironmental scienceCATABOLIC DIVERSITYCARBON STOCKSMicrocosmStabilitySoil Biology and Biochemistry
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The contribution of the European Society for Soil Conservation (ESSC) to scientific knowledge, education and sustainability

2019

Soil is an integral component of the global environmental system which supports the quality and diversity of terrestrial life on Earth. Therefore, it is vital to consider the processes and impacts of soil degradation on society, especially on the provision of environmental goods and services, including food security and climate change mitigation and adaptation. Scientific societies devoted to soil science play significant roles in reducing soil degradation and promoting soil conservation by advancing scientific knowledge, education and environmental sustainability. The ESSC was founded on 4 November 1988, with the aims to: 1. Support research on soil degradation, soil protection and soil an…

Agriculture and Food Sciences[SDV]Life Sciences [q-bio]0208 environmental biotechnologySoil Science02 engineering and technology[SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil studySoil functionsSoil educationSoil degradationSoil functionsSoil retrogression and degradationSoil health11. SustainabilityNature and Landscape ConservationWater Science and Technology2. Zero hungerSoil healthFood securitybusiness.industryEnvironmental resource management04 agricultural and veterinary sciences15. Life on landsoil functions6. Clean water020801 environmental engineeringlcsh:TA1-204013. Climate actionSustainable managementSoil knowledgeSettore AGR/14 - PedologiaEarth and Environmental SciencesSustainabilitySoil waterSoil function040103 agronomy & agriculture0401 agriculture forestry and fisheriesEnvironmental sciencelcsh:Engineering (General). Civil engineering (General)businessSoil conservationAgronomy and Crop Science
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The decline of the cork oak growing in Sicily is accompanied by the loss of the functions proper to agroforestry systems

2021

The cork oak is one of the most important tree species in the Mediterranean basin, where it covers more than 2 million hectares. Among evergreen oaks, Quercus suber stands out for the variety of cultural systems in which it has been successfully employed, including typical agroforestry systems. Accordingly, a wide range of ecosystem services may be associated to cork oak, including the preservation of biodiversity, carbon sequestration and forage production. In the Mediterranean, the cork oak represents a key species for many natural and seminatural landscapes and habitats, as well as playing a prominent role for the economic and social development of local communities. However, there is in…

Agriculture Mediterranean vegetation Quercus suber Sicily WildfiresSettore BIO/07 - EcologiaSettore AGR/05 - Assestamento Forestale E SelvicolturaSettore AGR/06 - Tecnologia Del Legno E Utilizzazioni Forestali
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Corrigendum to “Conservation value of forest plantations for bird communities in western Kenya” [Forest Ecol. Manag. 255 (2008) 3885–3892]

2009

A re-analysis of the bird data revealed a mistake within the database query. Only bird individuals that were heard were integrated in the results leading to lower total richness and number of individuals. In total 115 species and 13,331 individuals were detected of which 41 were forest specialists (43% of all individuals), 40 forest generalists (41%) and 34 forest visitors (16%). The statistical analyses remain very similar. We recorded significant differences in mean bird species richness, number of individuals and relative species richness among the five forest types (Table 1). Multiple pairwise comparisons showed significantly higher numbers of species in natural forest, mixed indigenous…

AgroforestryForestryForestryVegetationManagement Monitoring Policy and LawGeneralist and specialist speciesIndigenousGeographySecondary forestOrdinationSpecies richnessMonocultureNature and Landscape ConservationGlobal biodiversityForest Ecology and Management
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