Search results for " data"

showing 10 items of 7516 documents

Assisted baseline subtraction in complex chromatograms using the BEADS algorithm.

2017

The data processing step of complex signals in high-performance liquid chromatography may constitute a bottleneck to obtain significant information from chromatograms. Data pre-processing should be preferably done with little (or no) user supervision, for a maximal benefit and highest speed. In this work, a tool for the configuration of a state-of-the-art baseline subtraction algorithm, called BEADS (Baseline Estimation And Denoising using Sparsity) is developed and verified. A quality criterion based on the measurement of the autocorrelation level was designed to select the most suitable working parameters to obtain the best baseline. The use of a log transformation of the signal attenuate…

AcetonitrilesNoise reduction02 engineering and technology01 natural sciencesBiochemistrySignalAnalytical ChemistryPolyethylene GlycolsBaseline (configuration management)Chromatography High Pressure LiquidData processingElectronic Data ProcessingChromatographyElutionChemistry010401 analytical chemistryOrganic ChemistryAutocorrelationProcess (computing)General Medicine021001 nanoscience & nanotechnologySample (graphics)0104 chemical sciences0210 nano-technologyAlgorithmAlgorithmsJournal of chromatography. A
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Synthesis of 3-Oxa-guaianolides from Santonin

2000

Abstract This article reports on the transformation of santonin into two C10-epimeric 3-oxa-guaianolides which are 8-deoxyderivatives of several natural 3-oxaguaianolides isolated from Achillea species. The synthesis involved the photochemical rearrangement of the eudesmane skeleton into a guaiane skeleton and the transformation of the cyclopentane ring into a furan moiety with the concomitant loss of C3. Comparison of the NMR data of the synthetic products with those of the natural products confirms the β orientation of the hydroxyl group at C10 in the products isolated from Achillea.

AchilleabiologyStereochemistryOrganic Chemistrybiology.organism_classificationRing (chemistry)BiochemistryNmr datachemistry.chemical_compoundchemistryFuranDrug DiscoveryOrganic chemistryMoietyCyclopentaneSantoninTetrahedron
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Achlya spiralis, a new aquatic oomycete with bent oogonial stalks, isolated from the Burgundian region of France

2008

Achlya spiralis sp. nov. was isolated from water samples collected in the river Tille in the Burgundian region of France. The new oomycete is described, illustrated and compared with related species of the genus Achlya. It is characterized by the presence of smooth-walled oogonia that are usually borne on bent or twisted oogonial stalks; mainly monoclinous, androgynous and diclinous antheridial branches and eccentric oospores which generally do not mature or mature after a long period of time. The internal transcribed spacer (ITS) region of its rRNA is comprised of 671 bases. The taxonomic description of this new species, its comparison with related oomycetes and the sequence of the ITS reg…

Achlya spiralisAntheridiaMolecular Sequence DataFresh WaterMicrobiologyDNA AlgalOogoniaRiversGenusDNA Ribosomal SpacerBotanyGeneticsAchlya spiralisCiencias NaturalesInternal transcribed spacerrRNAMolecular BiologyOomyceteMicroscopybiologyITS regionSequence Analysis DNAAchlyaOosporesRibosomal RNAbiology.organism_classificationAchlyaAntheridiumOosporeFrance
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Mutations in the Cone Photoreceptor G-Protein α-Subunit Gene GNAT2 in Patients with Achromatopsia

2002

Achromatopsia is an autosomal recessively inherited visual disorder that is present from birth and that features the absence of color discrimination. We here report the identification of five independent families with achromatopsia that segregate protein-truncation mutations in the GNAT2 gene, located on chromosome 1p13. GNAT2 encodes the cone photoreceptor-specific alpha-subunit of transducin, a G-protein of the phototransduction cascade, which couples to the visual pigment(s). Our results demonstrate that GNAT2 is the third gene implicated in achromatopsia.

Achromatopsiagenetic structuresMolecular Sequence DataColor Vision DefectsBiologymedicine.disease_causeRetinal Cone Photoreceptor CellsReportGNAT2 geneGeneticsmedicineHumansGenetics(clinical)TransducinGeneGenetics (clinical)GeneticsGNAT2Mutationmedicine.diseaseRod monocromacyeye diseasesPedigreeColor Vision DefectsMutationRetinal Cone Photoreceptor CellsAchromatopsiaTransducinsense organsVisual phototransductionThe American Journal of Human Genetics
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Complete genome sequence of the strain Defluviitoga tunisiensis L3, isolated from a thermophilic, production-scale biogas plant.

2015

An anaerobic, thermophilic bacterium belonging to the phylum Thermotogae was isolated from a rural, thermophilic biogas plant (54 degrees C) producing methane-rich biogas from maize silage, barley, cattle and pig manure. Here we report the first complete genome sequence of the Defluviitoga tunisiensis strain L3, an isolate from the family Thermotogaceae. The strain L3 encodes several genes predicted to be involved in utilization of a large diversity of complex carbohydrates including cellobiose and xylan for the production of acetate, hydrogen (H-2) and carbon dioxide (CO2). The genome sequence of D. tunisiensis L3 provides the basis for biotechnological exploitation of genetic determinants…

AcidogenesisSilageMolecular Sequence DataBioengineeringCellobioseRenewable primary productsApplied Microbiology and Biotechnologychemistry.chemical_compoundBiogasBotanyAlphaproteobacteriaWhole genome sequencingThermotogaebiologyBase SequenceThermophileGeneral MedicineSequence Analysis DNAAcidogenesisbiology.organism_classificationBiogas productionchemistryGenes BacterialThermotogaeCarbohydrate utilizationFermentationGenome BacterialBiotechnologyJournal of biotechnology
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Dissemination of a Carbapenem-Resistant Acinetobacter baumannii Strain Belonging to International Clone II/Sequence Type 2 and Harboring a Novel AbaR…

2013

ABSTRACT An outbreak of hospital-acquired Acinetobacter baumannii infections, caused by a bla OXA-23 -positive carbapenem-resistant strain belonging to international clone II/ST2, was detected in Latvia. The strain was partially equipped with the armA gene and the intI1-aacA4-catB8-aadA1-qacE Δ 1 class 1 integron. In addition, the strain carried AbaR25, a novel AbaR4-like resistance island of ∼46,500 bp containing structures similar to the previously described AbaR22 and Tn 6167 islands. AbaR25 was characterized by the occurrence of a second copy of Tn 6022a interrupted by Tn 2006 carrying the bla OXA-23 gene.

Acinetobacter baumanniiclone (Java method)Genomic IslandsMolecular Sequence DataMicrobial Sensitivity TestsIntegronbeta-Lactam Resistancebeta-LactamasesDisease OutbreaksIntegronsMicrobiologyMechanisms of ResistancePharmacology (medical)GeneVDP::Medical disciplines: 700::Basic medical dental and veterinary science disciplines: 710::Medical molecular biology: 711Sequence (medicine)PharmacologyCross InfectionMolecular EpidemiologyMolecular epidemiologyStrain (chemistry)biologyOutbreakMethyltransferasesVDP::Medical disciplines: 700::Basic medical dental and veterinary science disciplines: 710::Medical microbiology: 715biology.organism_classificationLatviaAnti-Bacterial AgentsBacterial Typing TechniquesAcinetobacter baumanniiInfectious DiseasesCarbapenemsVDP::Medisinske Fag: 700::Basale medisinske odontologiske og veterinærmedisinske fag: 710::Medisinsk immunologi: 716VDP::Medisinske Fag: 700::Basale medisinske odontologiske og veterinærmedisinske fag: 710::Medisinsk mikrobiologi: 715DNA Transposable Elementsbiology.proteinGenes MDRVDP::Medical disciplines: 700::Basic medical dental and veterinary science disciplines: 710::Medical immunology: 716VDP::Medisinske Fag: 700::Basale medisinske odontologiske og veterinærmedisinske fag: 710::Medisinsk molekylærbiologi: 711Acinetobacter Infections
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Estimation of fibre orientation from digital images

2001

In this paper, estimation of fibre orientation is studied for fibre systems observable as a blurred greyscale image. The estimation method is based on scaled variograms observed along a set of sampling lines in different directions. The parameters of the orientation distribution are obtained numerically. Simulated data are used to study the statistical properties of the method.

Acoustics and UltrasonicsMaterials Science (miscellaneous)General MathematicsGrayscaleSet (abstract data type)Digital imageimage analysisRadiology Nuclear Medicine and imagingComputer visionInstrumentationMathematicslcsh:R5-920Boolean modelbusiness.industryOrientation (computer vision)lcsh:MathematicsSampling (statistics)Boolean modelObservablesimulationlcsh:QA1-939Distribution (mathematics)fibre orientationdigitizationComputer Science::Computer Vision and Pattern RecognitionSignal ProcessingstereologyComputer Vision and Pattern RecognitionArtificial intelligencebusinesslcsh:Medicine (General)Biotechnology
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Active learning strategies for the deduplication of electronic patient data using classification trees.

2012

Graphical abstractDisplay Omitted Highlights? Active learning for medical record linkage is used on a large data set. ? We compare a simple active learning strategy with a more sophisticated variant. ? The active learning method of Sarawagi and Bhamidipaty (2002) 6] is extended. ? We deliver insights into the variations of the results due to random sampling in the active learning strategies. IntroductionSupervised record linkage methods often require a clerical review to gain informative training data. Active learning means to actively prompt the user to label data with special characteristics in order to minimise the review costs. We conducted an empirical evaluation to investigate whether…

Active learningComputer scienceActive learning (machine learning)Information Storage and RetrievalContext (language use)Health InformaticsSemi-supervised learningMachine learningcomputer.software_genreSet (abstract data type)Artificial IntelligenceBaggingData deduplicationElectronic Health RecordsHumansbusiness.industryString (computer science)Decision TreesOnline machine learningComputer Science ApplicationsData miningArtificial intelligenceMedical Record LinkageString metricbusinesscomputerAlgorithmsJournal of biomedical informatics
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Remote sensing image segmentation by active queries

2012

Active learning deals with developing methods that select examples that may express data characteristics in a compact way. For remote sensing image segmentation, the selected samples are the most informative pixels in the image so that classifiers trained with reduced active datasets become faster and more robust. Strategies for intelligent sampling have been proposed with model-based heuristics aiming at the search of the most informative pixels to optimize model's performance. Unlike standard methods that concentrate on model optimization, here we propose a method inspired in the cluster assumption that holds in most of the remote sensing data. Starting from a complete hierarchical descri…

Active learningComputer scienceActive learning (machine learning)SvmMultispectral image0211 other engineering and technologies02 engineering and technologyMultispectral imageryClusteringMultispectral pattern recognitionArtificial Intelligence0202 electrical engineering electronic engineering information engineeringSegmentationCluster analysis021101 geological & geomatics engineeringRetrievalPixelbusiness.industryLinkageHyperspectral imagingPattern recognitionRemote sensingSupport vector machineMultiscale image segmentationHyperspectral imageryPixel ClassificationSignal Processing020201 artificial intelligence & image processingHyperspectral Data ClassificationComputer Vision and Pattern RecognitionArtificial intelligencebusinessAlgorithmsSoftwareModel
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Discovering single classes in remote sensing images with active learning

2012

When dealing with supervised target detection, the acquisition of labeled samples is one of the most critical phases: the samples must be yet representative of the class of interest, but must also be found among a vast majority of non-target examples. Moreover, the efficiency of the search is also an issue, since the samples labeled as background are not used by target detectors such as the support vector data description (SVDD). In this work we propose a competitive and effective approach to identify the most relevant training samples for one-class classification based on the use of an active learning strategy. The SVDD classifier is first trained with insufficient target examples. It is t…

Active learningComputer scienceActive learning (machine learning)business.industryPattern recognitionSemi-supervised learningRemote sensingMachine learningcomputer.software_genreSupport vector machineActive learningLife ScienceSupport Vector Data DescriptionArtificial intelligencebusinessClassifier (UML)computerChange detection2012 IEEE International Geoscience and Remote Sensing Symposium
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