Search results for "Bay"

showing 10 items of 1187 documents

Intertidal epilithic bacteria diversity changes along a naturally occurring carbon dioxide and pH gradient.

2014

Intertidal epilithic bacteria communities are important components of coastal ecosystems, yet few studies have assessed their diversity and how it may be affected by changing environmental parameters. Submarine CO2 seeps produce localised areas of CO2-enriched seawater with reduced pH levels. We utilised the seawater pH/CO2 gradient at Levante Bay (Italy) to test the hypothesis that epilithic bacteria communities are modified by exposure to seawater with the varying chemical parameters. Biofilms were sampled from three sites exposed to seawater with different pH/CO2 levels and diversity determined using high-throughput sequencing of 16S rRNA genes. Seawater pCO2 concentrations were increase…

CyanobacteriaIntertidal zoneBiologyCyanobacteriaApplied Microbiology and BiotechnologyMicrobiologybiofilmdiversityMarine ecosystemEcosystemSeawater14. Life underwaterEcosystemEcologyBacteriaEcologypHOcean acidificationBiodiversityCarbon DioxideHydrogen-Ion Concentrationbiology.organism_classificationepilithicBays13. Climate actionBiofilmsAlpha diversitySeawaterProteobacteriaFEMS microbiology ecology
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Environmental distribution of prokaryotic taxa

2010

14 pages, 5 figures, 1 table, 10 additional files avalaible [http://www.biomedcentral.com/content/supplementary/1471-2180-10- 85-S10.PDF ]

DNA BacterialMicrobiology (medical)BacteriaEcologybusiness.industrylcsh:QR1-502BiodiversityDistribution (economics)Bayes TheoremBiodiversityBiologyGeneralist and specialist speciesArchaeaMicrobiologylcsh:MicrobiologyTaxonFresh waterGenes BacterialRNA Ribosomal 16SResearch articleDatabases GeneticEnvironmental MicrobiologyPoisson DistributionbusinessBMC Microbiology
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The rise and the fall of a Pseudomonas aeruginosa endemic lineage in a hospital

2021

The biological features that allow a pathogen to survive in the hospital environment are mostly unknown. The extinction of bacterial epidemics in hospitals is mostly attributed to changes in medical practice, including infection control, but the role of bacterial adaptation has never been documented. We analysed a collection of Pseudomonas aeruginosa isolates belonging to the Besançon Epidemic Strain (BES), responsible for a 12year nosocomial outbreak, using a genotype-to-phenotype approach. Bayesian analysis estimated the emergence of the clone in the hospital 5 years before its opening, during the creation of its water distribution network made of copper. BES survived better than the refe…

DNA Bacterialparallel evolutionLineage (genetic)Genomic IslandsPathogens and EpidemiologyBiologymedicine.disease_causeAmoeba (operating system)Disease OutbreaksMicrobiology03 medical and health sciencesAntibiotic resistanceDrug Resistance Multiple BacterialGenomic islandbacterial pathogensmedicineHumansPseudomonas InfectionsPathogenGenome size[SDV.MP] Life Sciences [q-bio]/Microbiology and ParasitologyResearch Articles030304 developmental biology0303 health sciencesoutbreak030306 microbiologyPseudomonas aeruginosahigh-risk cloneOutbreakBayes TheoremSequence Analysis DNAGeneral MedicineHospitals3. Good healthPhenotype[SDV.MP]Life Sciences [q-bio]/Microbiology and ParasitologyPseudomonas aeruginosa
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Machine learning at the interface of structural health monitoring and non-destructive evaluation

2020

While both non-destructive evaluation (NDE) and structural health monitoring (SHM) share the objective of damage detection and identification in structures, they are distinct in many respects. This paper will discuss the differences and commonalities and consider ultrasonic/guided-wave inspection as a technology at the interface of the two methodologies. It will discuss how data-based/machine learning analysis provides a powerful approach to ultrasonic NDE/SHM in terms of the available algorithms, and more generally, how different techniques can accommodate the very substantial quantities of data that are provided by modern monitoring campaigns. Several machine learning methods will be illu…

Damage detectionComputer scienceTKGeneral MathematicsInterface (computing)General Physics and AstronomyCompressive sensing machine learning non-destructive evaluation structural health monitoring transfer learning ultrasoundMachine learningcomputer.software_genreMachine LearningSettore ING-IND/14 - Progettazione Meccanica E Costruzione Di MacchineEngineeringManufacturing and Industrial FacilitiesNon destructiveHumansUltrasonicsFeature databusiness.industryUltrasonic testingGeneral EngineeringBayes TheoremSignal Processing Computer-AssistedArticlesRoboticsData CompressionIdentification (information)Regression AnalysisStructural health monitoringArtificial intelligenceTransfer of learningbusinesscomputerAlgorithmsPhilosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
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Network reconstruction for trans acting genetic loci using multi-omics data and prior information.

2022

Background: Molecular measurements of the genome, the transcriptome, and the epigenome, often termed multi-omics data, provide an in-depth view on biological systems and their integration is crucial for gaining insights in complex regulatory processes. These data can be used to explain disease related genetic variants by linking them to intermediate molecular traits (quantitative trait loci, QTL). Molecular networks regulating cellular processes leave footprints in QTL results as so-called trans-QTL hotspots. Reconstructing these networks is a complex endeavor and use of biological prior information can improve network inference. However, previous efforts were limited in the types of priors…

Data Integrationeducation.field_of_studyComputer scienceScale (chemistry)Bayesian probabilityPopulationQuantitative Trait LociBiological databaseInferenceData Integration ; Machine Learning ; Multi-omics ; Network Inference ; Personalized Medicine ; Prior Information ; Simulation ; Systems BiologyComputational biologyQuantitative trait locusReplication (computing)Machine LearningPrior probabilityCohortGeneticsMolecular MedicineHumans:Medicine [Science]Gene Regulatory NetworkseducationTranscriptomeMolecular BiologyGenetics (clinical)Genome medicine
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Data Augmentation Approach in Bayesian Modelling of Presence-only Data

2011

Abstract Ecologists are interested in prediction of potential distribution of species in suitable areas, essential for planning conservation and management strategies. Unfortunately, often the only available information in such studies is the true presence of the species at few locations of the study area and the associated environmental covariates over the entire area, referred as presence-only data. We propose a Bayesian approach to estimate logistic linear regressions adapted to presence-only data through the introduction of a random approximation of the correction factor in the adjusted logistic model that allows us to overcome the need to know a priori the prevalence of the species.

Data augmentationPresence-only dataComputer scienceBayesian probabilityLogistic regressionBayesian inferencePseudo-absence approachBayesian statisticsBayesian model; Data augmentation; MCMC algorithm; Potential distribution; Presence-only data; Pseudo-absence approachBayesian model Data augmentation MCMC algorithm Presence-only data Pseudo-absence approach Potential distributionpotentialdistributionBayesian modelBayesian multivariate linear regressionPotential distributionStatisticsCovariateEconometricsGeneral Earth and Planetary Sciencespseudo-absence approach; potentialdistribution.; data augmentation; presence-only data; potential distribution; mcmc algorithm; bayesian modelBayesian linear regressionBayesian averageMCMC algorithmGeneral Environmental ScienceProcedia Environmental Sciences
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Diagnóstico de Enfermedades Card´ıacas con los algoritmos supervisados Naives Bayesian

2020

Las enfermedades cardíacas son la principal causa de muerte en la actualidad. Este paper contrasta la performance de los diferentes algoritmos supervisados de Machine Learning, que tienen aplicaciones en el a´rea de la medicina, con los algoritmos supervisados Naives Bayes para ayudar a clasificar pacientes propensos a sufrir enfermedades cardíacas. Como fuente de datos se usan 303 instancias de pacientes con diferentes características que fueron analizados al procesar los datos con los respectivos algoritmos. Los resultados con el algoritmo de Naives Bayes son pro- metedores, obteniendo una precisio´n del 86,81 %, usando la fuente de datos mencionada. Esta familia de algoritmos tiene un me…

Data sourceNaive Bayes classifierBayes' theoremArtificial neural networkComputer sciencebusiness.industryGeneral MedicineMedicine fieldArtificial intelligenceMachine learningcomputer.software_genrebusinesscomputerCiencia y Tecnología
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Comparing normal means: new methods for an old problem

2007

Comparing the means of two normal populations is an old problem in mathematical statistics, but there is still no consensus about its most appropriate solution. In this paper we treat the problem of comparing two normal means as a Bayesian decision problem with only two alternatives: either to accept the hypothesis that the two means are equal, or to conclude that the observed data are, under the assumed model, incompatible with that hypothesis. The combined use of an information-theory based loss function, the intrinsic discrepancy (Bernardo and Rueda 2002}, and an objective prior function, the reference prior \citep{Bernardo 1979; Berger and Bernardo 1992), produces a new solution to this…

Database Expansion ItemStatistics and Probabilityreference priorApplied MathematicsCombined useBayesian probabilityMathematical statisticsBayes factorFunction (mathematics)Decision problemBRCBayes factorcomparison of normal meanstwo sided testsApplied mathematicsprecise hypothesis testingAlgorithmintrinsic discrepancyMathematicsBayesian Analysis
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FABC: Retinal Vessel Segmentation Using AdaBoost

2010

This paper presents a method for automated vessel segmentation in retinal images. For each pixel in the field of view of the image, a 41-D feature vector is constructed, encoding information on the local intensity structure, spatial properties, and geometry at multiple scales. An AdaBoost classifier is trained on 789 914 gold standard examples of vessel and nonvessel pixels, then used for classifying previously unseen images. The algorithm was tested on the public digital retinal images for vessel extraction (DRIVE) set, frequently used in the literature and consisting of 40 manually labeled images with gold standard. Results were compared experimentally with those of eight algorithms as we…

Databases FactualComputer scienceFeature vectorFeature extractionNormal DistributionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processingModels BiologicalEdge detectionArtificial IntelligenceImage Processing Computer-AssistedHumansSegmentationComputer visionAdaBoostFluorescein AngiographyElectrical and Electronic EngineeringTraining setPixelContextual image classificationSettore INF/01 - Informaticabusiness.industryReproducibility of ResultsRetinal VesselsWavelet transformBayes TheoremPattern recognitionGeneral MedicineImage segmentationComputer Science ApplicationsComputingMethodologies_PATTERNRECOGNITIONROC CurveTest setAdaBoost classifier retinal images vessel segmentationArtificial intelligencebusinessAlgorithmsBiotechnology
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Early stages of the acute physical stress response increase loss aversion and learning on decision making: A Bayesian approach

2021

Abstract When the cortisol peak is reached after a stressor people learn slower and make worse decisions in the Iowa Gambling Task (IGT). However, the effects of the early stress response have not received as much attention. Since physical exercise is an important neuroendocrine stressor, this study aimed to fill this gap using an acute physical stressor. We hypothesized that this stress stage would promote an alertness that may increase feedback-sensitivity and, therefore, reward-learning during IGT, leading to a greater overall decision-making. 90 participants were divided into two groups: 47 were exposed to an acute intense physical stressor (cycloergometer) and 43 to a distractor 5 min …

Decision MakingStressorBayesian probabilityBayes TheoremExperimental and Cognitive PsychologyPhysical exerciseIowa gambling taskDevelopmental psychologyBehavioral NeuroscienceAlertnessRewardLoss aversionGamblingStress (linguistics)HumansLearningCognitive skillPsychologyPhysiology & Behavior
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