Search results for "Carlo"

showing 10 items of 1845 documents

Quantifying geological uncertainty in metamorphic phase equilibria modelling; a Monte Carlo assessment and implications for tectonic interpretations

2016

AbstractPseudosection modelling is rapidly becoming an essential part of a petrologist's toolkit and often forms the basis of interpreting the tectonothermal evolution of a rock sample, outcrop, or geological region. Of the several factors that can affect the accuracy and precision of such calculated phase diagrams, “geological” uncertainty related to natural petrographic variation at the hand sample- and/or thin section-scale is rarely considered. Such uncertainty influences the sample's bulk composition, which is the primary control on its equilibrium phase relationships and thus the interpreted pressure–temperature (P–T) conditions of formation. Two case study examples—a garnet–cordierit…

010504 meteorology & atmospheric sciencesMetamorphic rockMonte Carlo methodMineralogyPseudosectionEarth and Planetary Sciences(all)3705 Geologysub-05010502 geochemistry & geophysics01 natural sciencesKyaniteGeological uncertaintyMatrix (geology)ErrorPetrographyMonte Carlo0105 earth and related environmental sciencesMnNCKFMASHTOlcsh:QE1-996.5Schist37 Earth Scienceslcsh:GeologyTectonicsvisual_artStaurolitevisual_art.visual_art_mediumGeneral Earth and Planetary Sciences3706 GeophysicsGeologyGeoscience Frontiers
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Economic performance and risk of farming systems specialized in perennial crops: An analysis of Italian hazelnut production

2019

Abstract Assessing farm profitability and economic risk is important to support farmers' decisions. Several factors affect yields and product prices, in turn influencing farmers' income level and economic risk. However, the literature has often neglected to explicitly account for the role of product quality. This is particularly important for crops such as hazelnut because farmers' prices vary according to the quality of the harvested product. Furthermore, it seems fundamental to disentangle the role of parameters influencing farm results, noticeably yield, product price and quality. This is because farmers select their risk management tools to satisfy their needs, but these are often suita…

010504 meteorology & atmospheric sciencesmedia_common.quotation_subjectDistribution (economics)Risk management toolsGross margin01 natural sciencesGross marginAgricultural scienceSettore AGR/01 - Economia Ed Estimo RuraleMarket priceProduction (economics)Monte Carlo analysiQuality (business)Product (category theory)Risk assessment0105 earth and related environmental sciencesmedia_commonbusiness.industrySensitivity analysis.Stochastic simulation04 agricultural and veterinary sciencesStepwise regression040103 agronomy & agriculture0401 agriculture forestry and fisheriesAnimal Science and ZoologyProfitability indexBusinessAgronomy and Crop ScienceAgricultural Systems
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Alder pollen in Finland ripens after a short exposure to warm days in early spring, showing biennial variation in the onset of pollen ripening

2017

Abstract We developed a temperature sum model to predict the daily pollen release of alder, based on pollen data collected with pollen traps at seven locations in Finland over the years 2000–2014. We estimated the model parameters by minimizing the sum of squared errors (SSE) of the model, with weights that put more weight on binary recognition of daily presence or absence of pollen. The model results suggest that alder pollen ripens after a couple of warm days in February, while the whole pollen release period typically takes up to 4 weeks. We tested the model residuals against air humidity, precipitation and wind speed, but adding these meteorological features did not improve the model pr…

0106 biological sciencesAtmospheric Science010504 meteorology & atmospheric sciencesta1171Atmospheric sciencesmedicine.disease_causeAlnus01 natural sciencesAlderPollenotorhinolaryngologic diseasesmedicineMonte Carlo resamplingPrecipitationsiitepöly0105 earth and related environmental sciencespollen seasonGlobal and Planetary Changefloweringbiologyta114kukintaAnomaly (natural sciences)ta1183food and beveragesHumidityForestryRipeningennusteetmodelingalderbiology.organism_classificationta4112leppäMonte Carlo -menetelmätAlder pollenClimatologyta1181Short exposureAgronomy and Crop Science010606 plant biology & botanyAgricultural and Forest Meteorology
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The Bias of combining variables on fish's aggressive behavior studies.

2019

Made available in DSpace on 2019-10-06T16:27:42Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-07-01 Quantifying animal aggressive behavior by behavioral units, either displays or attacks, is a common practice in animal behavior studies. However, this practice can generate a bias in data analysis, especially when the variables have different temporal patterns. This study aims to use Bayesian Hierarchical Linear Models (B-HLMs) to analyze the feasibility of pooling the aggressive behavior variables of four cichlids species. Additionally, this paper discusses the feasibility of combining variables by examining the usage of different sample sizes and family distributions to aggressive …

0106 biological sciencesBayesian probabilityPosterior probabilityBayesian analysisPoisson distribution010603 evolutionary biology01 natural sciencesBehavioral Neurosciencesymbols.namesakeBiasPrior probabilityStatisticsAnimals0501 psychology and cognitive sciences050102 behavioral science & comparative psychologyPterophyllum scalareMathematicsProbabilitybiologyBehavior Animal05 social sciencesMultilevel modelBayes TheoremGeneral MedicineCichlidsbiology.organism_classificationAggressive behaviourMarkov ChainsAggressionVariable (computer science)Sample size determinationData Interpretation StatisticalsymbolsAnimal Science and ZoologyPooled dataMonte Carlo MethodBehavioural processes
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Accounting for preferential sampling in species distribution models

2019

D. C., A. L. Q. and F. M. would like to thank the Ministerio de Educación y Ciencia (Spain) for financial support (jointly financed by the European Regional Development Fund) via Research Grants MTM2013‐42323‐P and MTM2016‐77501‐P, and ACOMP/2015/202 from Generalitat Valenciana (Spain). Species distribution models (SDMs) are now being widely used in ecology for management and conservation purposes across terrestrial, freshwater, and marine realms. The increasing interest in SDMs has drawn the attention of ecologists to spatial models and, in particular, to geostatistical models, which are used to associate observations of species occurrence or abundance with environmental covariates in a fi…

0106 biological sciencesComputer scienceQH301 BiologySpecies distributionPoint processesStochastic partial differential equation01 natural scienceshttp://aims.fao.org/aos/agrovoc/c_6774EspèceAbundance (ecology)StatisticsPesqueríasQAOriginal Researchhttp://aims.fao.org/aos/agrovoc/c_241990303 health sciencesEcologyU10 - Informatique mathématiques et statistiquesSampling (statistics)Integrated nested Laplace approximationstochastic partial differential equationVariable (computer science)symbolsÉchantillonnageSpecies Distribution Models (SDMs)Modèle mathématiqueBayesian probabilityNDASDistribution des populations010603 evolutionary biologyQH30103 medical and health sciencessymbols.namesakeCovariateQA MathematicsSDG 14 - Life Below WaterCentro Oceanográfico de Murciaspecies distribution modelsRelative species abundanceEcology Evolution Behavior and Systematicspoint processes030304 developmental biologyNature and Landscape Conservationhttp://aims.fao.org/aos/agrovoc/c_6113http://aims.fao.org/aos/agrovoc/c_7280Markov chain Monte Carlointegrated nested Laplace approximationU30 - Méthodes de rechercheBayesian modelling
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Bayesian analysis improves experimental studies about temporal patterning of aggression in fish.

2017

Made available in DSpace on 2018-12-11T17:15:13Z (GMT). No. of bitstreams: 0 Previous issue date: 2017-12-01 Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) This study aims to describe a Bayesian Hierarchical Linear Model (HLM) approach for longitudinal designs in fish's experimental aggressive behavior studies as an alternative to classical methods In particular, we discuss the advantages of Bayesian analysis in dealing with combined variables, non-statistically significant results and required sample size using an experiment of angelfish (Pterophyllum scalare) species as case study. Groups of 3 individuals were subjected to daily observations recorded for 10 min durin…

0106 biological sciencesMonte Carlo methodBayesian probabilityBayesian analysisAquaculture010603 evolutionary biology01 natural sciencesStability (probability)Behavioral NeuroscienceStatisticsAnimals0501 psychology and cognitive sciences050102 behavioral science & comparative psychologyPterophyllum scalareProbabilitybiologyMarkov chain05 social sciencesMultilevel modelAggressive behaviorBayes TheoremGeneral MedicineCichlidsbiology.organism_classificationLongitudinal designMarkov ChainsAggressionVariable (computer science)Sample size determinationResearch DesignAnimal Science and ZoologyPsychologyMonte Carlo MethodBehavioural processes
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Hierarchical log Gaussian Cox process for regeneration in uneven-aged forests

2021

We propose a hierarchical log Gaussian Cox process (LGCP) for point patterns, where a set of points x affects another set of points y but not vice versa. We use the model to investigate the effect of large trees to the locations of seedlings. In the model, every point in x has a parametric influence kernel or signal, which together form an influence field. Conditionally on the parameters, the influence field acts as a spatial covariate in the intensity of the model, and the intensity itself is a non-linear function of the parameters. Points outside the observation window may affect the influence field inside the window. We propose an edge correction to account for this missing data. The par…

0106 biological sciencesStatistics and ProbabilityFOS: Computer and information sciences62F15 (Primary) 62M30 60G55 (Secondary)MCMCGaussianBayesian inferenceMarkovin ketjutStatistics - Applications010603 evolutionary biology01 natural sciencesCox processMethodology (stat.ME)010104 statistics & probabilitysymbols.namesakeregeneraatio (biologia)Applied mathematicsApplications (stat.AP)0101 mathematicsLaplace approximationStatistics - MethodologyGeneral Environmental ScienceParametric statisticsMathematicsspatial random effectsbayesilainen menetelmäMarkov chain Monte CarloFunction (mathematics)15. Life on landMissing dataMonte Carlo -menetelmätcompetition kernelLaplace's methodKernel (statistics)symbolstree regenerationpuustometsänhoitomatemaattiset mallitStatistics Probability and Uncertainty
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Reducing waste and ecological impacts through a sustainable and efficient management of perishable food based on the Monte Carlo simulation

2019

Abstract In today’s competitive global market it is mandatory to improve warehousing operations integrating economic, environmental and social aspects. The recent advancement in monitoring technologies can greatly improve the performance of the food supply chain reducing product loss. In particular, in the perishable food supply chain, initially inventory operations are critical because they manage the material flows in very variable conditions. The deterioration level of the products as well as the market demand are the main factors that can influence warehouse strategy. This research aims to consider the application of sustainability principles in the context of warehouse storage, evaluat…

0106 biological sciencesTraceabilityComputer scienceSupply chainGeneral Decision SciencesContext (language use)010501 environmental sciences010603 evolutionary biology01 natural sciencesWarehouse managementSupply and demandSettore ING-IND/17 - Impianti Industriali MeccaniciMonte Carlo simulationEcology Evolution Behavior and Systematics0105 earth and related environmental sciencesEcologyEcological impacts Food waste reduction Monte Carlo simulation Shelf life model Sustainability Warehouse managementEnvironmental economicsEcological impactWarehouseProduct (business)SustainabilitySustainabilityShelf life modelCarbon footprintEcological impacts; Food waste reduction; Monte Carlo simulation; Shelf life model; Sustainability; Warehouse managementFood waste reductionEcological Indicators
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Liquid Crystal Phases in Suspensions of Charged Plate-Like Particles

2012

International audience; Anisotropic interactions in colloidal suspensions have recently emerged as a route for the design of new soft materials. Nonisotropic particles can form nematic, smectic, hexatic, and columnar liquid crystals. Although the formation of these phases is well rationalized when excluded volume is solely at play, the role of electrostatic interactions still remains unclear and even less so when particles present a charge heterogeneity, for example, clays. Here, we use Monte Carlo simulations of concentrated suspensions of charged disk-like particles to reveal the role of Coulomb interactions and charge anisotropy underlying liquid crystal formation and structures. We obse…

02 engineering and technology010402 general chemistry01 natural sciencesLiquid crystalCoulombGeneral Materials Scienceliquid crystalPhysical and Theoretical ChemistryAnisotropyMonte Carlo simulationcharged discotic particlesPhysics021001 nanoscience & nanotechnologyElectrostaticsGlasses Colloids Polymers and Soft Matter0104 chemical sciencesCondensed Matter::Soft Condensed Matter[ PHYS.PHYS.PHYS-CHEM-PH ] Physics [physics]/Physics [physics]/Chemical Physics [physics.chem-ph]Crystallographycolumnar phaseChemical physicsVolume fractionExcluded volumeParticle[PHYS.PHYS.PHYS-CHEM-PH]Physics [physics]/Physics [physics]/Chemical Physics [physics.chem-ph]0210 nano-technologyColumnar phaseThe Journal of Physical Chemistry Letters
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Evaluating the material resource efficiency of secondary aluminium production: A Monte Carlo-based decision-support tool

2019

The contamination of aluminium streams during the different life cycle stages by alloy mixing and/or accumulation of foreign elements, in combination with the limited melt purification options during remelting, represents an important limiting factor in recycling. Consequently, in secondary aluminium production, primary aluminium is used to dilute the concentration of the residual elements, and alloying elements are added to adjust the composition to the target alloy specifications. However, adding elements, for which their refinement in a subsequent recycling step is problematic, results in permanent down-cycling or ‘quality losses’. Hence, it is crucial to more efficiently control the com…

020209 energyStrategy and ManagementMonte Carlo methodResource efficiencychemistry.chemical_elementScrapAlloying element02 engineering and technologyIndustrial and Manufacturing EngineeringLife cycle assessmentAluminium0202 electrical engineering electronic engineering information engineeringProcess engineeringLife-cycle assessment0505 lawGeneral Environmental Science2300business.industryRenewable Energy Sustainability and the Environment05 social sciencesSortingAluminium recyclingMaterial efficiencyAluminium recyclingMaterial efficiencyScrap sortingStrategy and Management1409 Tourism Leisure and Hospitality Managementchemistry050501 criminologyEnvironmental sciencebusiness
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