Search results for " determination"

showing 10 items of 538 documents

Production, isolation and characterization of radiochemically pure 163Ho samples for the ECHo-project

2018

Abstract Several experiments on the study of the electron neutrino mass are based on high-statistics measurements of the energy spectrum following electron capture of the radionuclide 163Ho. They rely on the availability of large, radiochemically pure samples of 163Ho. Here, we describe the production, separation, characterization, and sample production within the Electron Capture in Holmium-163 (ECHo) project. 163Ho has been produced by thermal neutron activation of enriched, prepurified 162Er targets in the high flux reactor of the Institut Laue-Langevin, Grenoble, France, in irradiations lasting up to 54 days. Irradiated targets were chemically processed by means of extraction chromatogr…

ChromatographyChemistryEcho (computing)lanthanide separationneutron activation[PHYS.NEXP]Physics [physics]/Nuclear Experiment [nucl-ex]010403 inorganic & nuclear chemistryIsolation (microbiology)7. Clean energy01 natural sciencesNeutrino mass determination0104 chemical sciencesCharacterization (materials science)163Ho0103 physical sciencesextraction chromatographyPhysical and Theoretical Chemistry010306 general physicsNeutron activationRadiochimica Acta
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Indirect Quantitative Determination of Organolithium Compounds by Gas Chromatography

1976

ChromatographyChemistryOrganolithium compoundsGeneral MedicineGas chromatographyQuantitative determinationAnalytical ChemistryJournal of Chromatographic Science
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Extraktionschromatographische trennung der freien uroporphyrinisomere i und iii und deren simultane quantitative bestimmung

1968

Abstract Separation and simultaneous quantitative determination of the free uroporphyrin isomers I and III by means of extraction chromatography Separation and quantitative determination of the uroporphyrin isomers I and III in the acid from can be performed simultaneously in the partition system tri-n-butylphosphate/I N hydrochloric acid using columns with a large number of theoretical plates (N) = 300-450). The eluent is passed through a flow cuvette and the transmission is recorded continuously. The transmission peaks of the isomers are digitized and transformed into extinction values. By integrating the extinction peaks, the amount of the uroporphyrins can be evaluated from the correspo…

ChromatographyElutionOrganic ChemistryAnalytical chemistryHydrochloric acidGeneral MedicineUroporphyrinsBiochemistryQuantitative determinationAnalytical ChemistryCuvettechemistry.chemical_compoundColumn chromatographychemistryPartition (number theory)Theoretical plateJournal of Chromatography A
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Hard cap espresso extraction-stir bar preconcentration of polychlorinated biphenyls in soil and sediments.

2017

Abstract A Nespresso © hard cap espresso machine has been employed for the quantitative extraction of polychlorinated biphenyls (PCBs) from sediments and soils. Sample extraction was performed from five grams of sample in less than 40 s, with 200 mL ethanol 40% (v/v) in water and PCBs were concentrated using stir bar sorptive extraction (SBSE) and determined by thermal desorption-gas chromatography-tandem mass spectrometry (TD-GC-MS-MS). Eleven PCB congeners (28, 52, 77, 80, 81, 101, 118, 138, 153,169, and 180) were determined in soils and sediments with limits of quantification in the 0.03–0.08 ng g −1 range. Extraction efficiency was established by the analysis of soil samples spiked with…

ChromatographySoil testChemistry010401 analytical chemistryExtraction (chemistry)010501 environmental sciencesMass spectrometry01 natural sciencesBiochemistryQuantitative determination0104 chemical sciencesAnalytical ChemistryEspressoCertified reference materialsEnvironmental chemistrySoil waterEnvironmental ChemistrySpectroscopy0105 earth and related environmental sciencesBar (unit)Analytica chimica acta
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VIII: Statistik in klinischen Publikationen: Checklisten für Autoren

2003

The "Material and Methods" section of clinical research papers should reference major aspects concerning statistical planning and evaluation of the study design and the resulting clinical data. Particular focus is laid on the listing of methods for description and significance evaluation of the trial data, as well as on design-associated study determinants (randomisation and masking strategy, response rate evaluation, primary endpoints, power and sample size determination, multiple testing, software and methods for statistical analysis). Suggestions for the minimum content to be mentioned in a trial publication are listed in author check lists and are illustrated by means of the study synop…

Clinical trialOphthalmologymedicine.medical_specialtyComputer scienceSample size determinationMultiple comparisons problemmedicineMedical physicsStatistical analysisKlinische Monatsblätter für Augenheilkunde
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Fallzahlplanung bei ophthalmologischen Studien*

2000

An essential aspect in the cooperation of clinic and biometry consists in designing of studies, e.g. during the preparation of grant applications or for review by official drug surveillance institutions. A central aspect in study planning is the design-adequate and well-documented prediction of sample size, which should be recommended for any intended study. Based on several examples for sample size planning in study designs, which are of common relevance for ophthalmology, guidelines are derived to enable clinical researchers to perform sample size planning on their own. The latter can be based on the various available software packages for sample size prediction.

Clinical trialOphthalmologymedicine.medical_specialtySoftwareSample size determinationbusiness.industryClinical study designmedicineMedical physicsRelevance (information retrieval)businessStudy planningSurgeryKlinische Monatsblätter für Augenheilkunde
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Comparison of Metrics for the Classification of Soils Under Variable Geometrical Conditions Using Hyperspectral Data

2008

International audience; The objective of this letter is to find a distance metric between reflectance spectra that is not sensitive to the variations on the soil reflectance induced by the geometry of solar-view angles. This is motivated by the fact that differences between spectra measured for the same soil under different observation and illumination configurations can lead to misclassifications. Using 26 soils of different compositions simulated with Hapke’s model and 92 soils of different compositions measured under 28 solarview angle geometries in laboratory conditions, we tested three metrics, namely, root-mean-square error, spectral angle mapper, and R2 (the coefficient of determinat…

Coefficient of determination010504 meteorology & atmospheric sciencesMean squared error0211 other engineering and technologiesSOIL IDENTIFICATION02 engineering and technologySolid modeling01 natural sciencesSpectral lineCLASSIFICATION[SPI]Engineering Sciences [physics]HYPERSPECTRALSurface roughnessElectrical and Electronic EngineeringComputingMilieux_MISCELLANEOUS021101 geological & geomatics engineering0105 earth and related environmental sciencesMathematicsRemote sensingHyperspectral imagingSoil classificationGeotechnical Engineering and Engineering GeologySOLAR-VIEW ANGLESoil waterSPECTRAL LIBRARYDISTANCE METRIC[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Using Aerial Platforms in Predicting Water Quality Parameters from Hyperspectral Imaging Data with Deep Neural Networks

2020

In near future it is assumable that automated unmanned aerial platforms are coming more common. There are visions that transportation of different goods would be done with large planes, which can handle over 1000 kg payloads. While these planes are used for transportation they could similarly be used for remote sensing applications by adding sensors to the planes. Hyperspectral imagers are one this kind of sensor types. There is need for the efficient methods to interpret hyperspectral data to the wanted water quality parameters. In this work we survey the performance of neural networks in the prediction of water quality parameters from remotely sensed hyperspectral data in freshwater basin…

Coefficient of determinationArtificial neural networkRemote sensing applicationvesien tilaspektrikuvausHyperspectral imagingneuroverkotvedenlaatuConvolutional neural networkwater qualityPearson product-moment correlation coefficientsymbols.namesakeremote sensinghyperspectralilmakuvakartoitusMultilayer perceptronconvolutional neural networkssymbolsEnvironmental scienceWater qualitykaukokartoitusRemote sensing
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Comparison of metrics to remove the influence of geometrical conditions on soil reflectance

2007

The objective of this work is to find the best metric to ignore the variations of soil reflectance induced by the solar-view angles geometry. Differences between spectra measured for the same soil under different observation and illumination configurations can leads to misclassifications. Using ninety two soils of different composition measured under twenty eight solar- view angles geometries, we tested 3 metrics : RMSE, SAM, R2 (the coefficient of determination) and we compared their performances. The best metric seems to be the coefficient of determination with 93 % of good classifications.

Coefficient of determinationMean squared errorSoil waterMultispectral imageMetric (mathematics)Surface roughnessHyperspectral imagingReflectivityRemote sensingMathematics2007 IEEE International Geoscience and Remote Sensing Symposium
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A modified applicative criterion of the physical model concept for evaluating plot soil erosion predictions

2015

Abstract In this paper, the physical model concept by Nearing (1998. Catena 32: 15–22) was assessed. Soil loss data collected on plots of different  widths (2–8 m), lengths (11–44 m) and steepnesses (14.9–26.0%), equipped in south and central Italy, were used. Differences in width between plots of given length and steepness determined a lower data correlation and more deviation of the fitted regression line from the identity one. A coefficient of determination between measured, M , and predicted, P , soil losses of 0.77 was representative of the best-case prediction scenario, according to Nearing (1998). The relative differences, Rdiff  = ( P − M ) / ( P + M ), decreased in absolute value a…

Coefficient of determinationSoil loss dataAbsolute value (algebra)Plot measurementPlot (graphics)Soil erosion; Plot measurements; Soil loss data; Physical modelPhysical modelSoil lossLinear regressionStatisticsErosionRange (statistics)Soil erosionPlot measurementsSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-ForestaliEquivalence (measure theory)Earth-Surface ProcessesMathematics
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