Search results for "WORK"

showing 10 items of 14511 documents

A spin-crossover complex based on a 2,6-bis(pyrazol-1-yl)pyridine (1-bpp) ligand functionalized with a carboxylate group

2014

Combining Fe(ii) with the carboxylate-functionalized 2,6-bis(pyrazol-1-yl)pyridine (bppCOOH) ligand results in the spin-crossover compound [Fe(bppCOOH)2](ClO4)2 which shows an abrupt spin transition with a T1/2 of ca. 380 K and a TLIESST of 60 K due to the presence of a hydrogen-bonded linear network of complexes.

010405 organic chemistryStereochemistryLigandSpin transition010402 general chemistry01 natural sciencesMedicinal chemistry3. Good health0104 chemical sciencesInorganic Chemistrychemistry.chemical_compoundLinear networkBPP ligandchemistrySpin crossoverGroup (periodic table)PyridineCarboxylateDalton Transactions
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A comprehensive in situ and remote sensing data set from the Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) campaign

2019

The Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) campaign was carried out north-west of Svalbard (Norway) between 23 May and 6 June 2017. The objective of ACLOUD was to study Arctic boundary layer and mid-level clouds and their role in Arctic amplification. Two research aircraft (Polar 5 and 6) jointly performed 22 research flights over the transition zone between open ocean and closed sea ice. Both aircraft were equipped with identical instrumentation for measurements of basic meteorological parameters, as well as for turbulent and radiative energy fluxes. In addition, on Polar 5 active and passive remote sensing instruments were installed, while Polar 6 …

010504 meteorology & atmospheric sciences02 engineering and technology01 natural sciencesRadiative fluxddc:5500202 electrical engineering electronic engineering information engineeringSea icelcsh:Environmental sciences0105 earth and related environmental sciencesRemote sensinglcsh:GE1-350[SDU.OCEAN]Sciences of the Universe [physics]/Ocean AtmosphereData processinggeographygeography.geographical_feature_categorybusiness.industrylcsh:QE1-996.5020206 networking & telecommunicationsTrace gaslcsh:GeologyEarth sciencesArctic13. Climate actionRemote sensing (archaeology)Polar amplificationGeneral Earth and Planetary SciencesEnvironmental scienceData centerbusiness
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Machine learning regression algorithms for biophysical parameter retrieval: Opportunities for Sentinel-2 and -3

2012

Abstract ESA's upcoming satellites Sentinel-2 (S2) and Sentinel-3 (S3) aim to ensure continuity for Landsat 5/7, SPOT-5, SPOT-Vegetation and Envisat MERIS observations by providing superspectral images of high spatial and temporal resolution. S2 and S3 will deliver near real-time operational products with a high accuracy for land monitoring. This unprecedented data availability leads to an urgent need for developing robust and accurate retrieval methods. Machine learning regression algorithms may be powerful candidates for the estimation of biophysical parameters from satellite reflectance measurements because of their ability to perform adaptive, nonlinear data fitting. By using data from …

010504 meteorology & atmospheric sciencesArtificial neural networkMean squared errorbusiness.industryComputer science0211 other engineering and technologiesSoil ScienceGeology02 engineering and technologyMachine learningcomputer.software_genre01 natural sciencesRegressionSupport vector machineTemporal resolutionGround-penetrating radarCurve fittingArtificial intelligenceComputers in Earth SciencesbusinessImage resolutioncomputer021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingRemote Sensing of Environment
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A 3-Year Sample of Almost 1,600 Elves Recorded Above South America by the Pierre Auger Cosmic-Ray Observatory

2020

The time and location of the 1,598 verified and reconstructed elves, used for the analysis showcased in this paper, are publicly available on the website of the Pierre Auger Observatory (https://www.auger.org/ index.php/science/data). We wish to thank the World Wide Lightning Location Network (http://wwlln.net), a collaboration among over 50 universities and institutions, for providing the lightning location data used in this paper. We acknowledge Robert Marshall for providing one of the most advanced elve simulations to the public, a key tool in understanding the elves observed by the Pierre Auger Observatory. The successful installation, commissioning, and operation of the Pierre Auger Ob…

010504 meteorology & atmospheric sciencesAstronomyField of view010502 geochemistry & geophysics01 natural sciences7. Clean energyAugerlcsh:QB1-991ObservatoryultravioletStormddc:550UHE Cosmic Raystime resolutionCosmic-ray observatoryPhysicslcsh:QE1-996.5astro-ph.GeologyAugerwidth [beam]IonosphereField of viewGeologylcsh:AstronomyUHE [cosmic radiation]Environmental Science (miscellaneous)horizonLightningddc:530High Energy PhysicsIonosphereCosmic-ray observatory0105 earth and related environmental sciencesfluorescence [detector]backgroundFísicaAstronomyStormsensitivityLightningopticslcsh:GeologyElves UV fluorescence detectorsThunderstorm13. Climate actionExperimental High Energy PhysicsnetworkThunderstormGeneral Earth and Planetary SciencesElvesObservatory
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Boulder coastal deposits at Favignana Island rocky coast (Sicily, Italy): Litho-structural and hydrodynamic control

2018

Boulders are frequently dislodged from rock platforms, transported and deposited along coastal zones by high-magnitude storm waves or tsunamis. Their size and shape are often controlled by the thickness of bedding planes as well as by high-angle to bedding fracture network. We investigate these processes along two coastal areas of Favignana Island by integrating geological data for 81 boulders, 49 rupture surfaces (called sockets) and fracture orientation and spacing with four radiocarbon dates, numerical hydrodynamic analysis, and hindcast numerical simulation data. Boulders are scattered along the carbonate platform as isolated blocks or in small groups, which form, as a whole, a disconti…

010504 meteorology & atmospheric sciencesBeddingSettore GEO/02 - Geologia Stratigrafica E SedimentologicaLithologyCarbonate platformSettore GEO/03 - Geologia StrutturaleStorm wave010502 geochemistry & geophysics01 natural sciencesHydrodynamic equationsBoulders; Fracture network; Hydrodynamic equations; Storm waves; Earth-Surface ProcessesBedBouldersGeomorphologyBoulder0105 earth and related environmental sciencesEarth-Surface ProcessesBoulders.Fracture network Hydrodynamic equations Storm wavesBermStorm wavesStormHydrodynamic equationClastic rockFracture (geology)Fracture networkFracture network;Storm waves;Boulders;Hydrodynamic equationsGeology
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A roadmap for amphibious drilling at the Campi Flegrei caldera: insights from a MagellanPlus workshop

2019

Large calderas are among the Earth's major volcanic features. They are associated with large magma reservoirs and elevated geothermal gradients. Caldera-forming eruptions result from the withdrawal and collapse of the magma chambers and produce large-volume pyroclastic deposits and later-stage deformation related to post-caldera resurgence and volcanism. Unrest episodes are not always followed by an eruption; however, every eruption is preceded by unrest. The Campi Flegrei caldera (CFc), located along the eastern Tyrrhenian coastline in southern Italy, is close to the densely populated area of Naples. It is one of the most dangerous volcanoes on Earth and represents a key example of an acti…

010504 meteorology & atmospheric sciencesCalderasGeochemistryEnergy Engineering and Power TechnologyPyroclastic rockVolcanologyMagma chamberVolcanism010502 geochemistry & geophysics01 natural sciencesdrillingsouthern ItalycalderaCaldera14. Life underwater0105 earth and related environmental sciencesgeographygeography.geographical_feature_categoryMechanical Engineeringlcsh:QE1-996.5VolcanologyMagellanPlus workshopInternational Ocean Discovery Programlcsh:GeologyCampi Flegrei calderaVolcanoItaly13. Climate actionEruptionMagmacaldera Campi Flegrei monitopring system hydrothermal system IODPCampi FlegreiGeology
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The joint sets on the Lilstock Benches, UK. Observations based on mapping a full resolution UAV-based image

2021

Outcrop studies of fracture networks are important to understand fractured reservoirs in the subsurface, but complete maps of all fractures in large outcrops are rare due to limitations of outcrop and image resolution. We manually mapped the first full-resolution UAV-based, Gigapixel dataset and DEM of the wave-cut Lilstock Benches in the southern Bristol Channel basin, a classic outcrop of layer-bound fracture networks in limestones. We present a map of the patterns and age relationships of successive sets of joints in dm-thick limestone layers separated by claystone beds. Using interpretation criteria based on crosscutting relationships, abutting and joint length, up to eight successive s…

010504 meteorology & atmospheric sciencesChannel (digital image)OutcropOrientation (computer vision)Geology010502 geochemistry & geophysics01 natural sciencesFracture (geology)Scale (map)Image resolutionJoint (geology)GeologySeismology0105 earth and related environmental sciencesNetwork model
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Statistical retrieval of atmospheric profiles with deep convolutional neural networks

2019

Abstract Infrared atmospheric sounders, such as IASI, provide an unprecedented source of information for atmosphere monitoring and weather forecasting. Sensors provide rich spectral information that allows retrieval of temperature and moisture profiles. From a statistical point of view, the challenge is immense: on the one hand, “underdetermination” is common place as regression needs to work on high dimensional input and output spaces; on the other hand, redundancy is present in all dimensions (spatial, spectral and temporal). On top of this, several noise sources are encountered in the data. In this paper, we present for the first time the use of convolutional neural networks for the retr…

010504 meteorology & atmospheric sciencesComputer science0211 other engineering and technologiesWeather forecasting02 engineering and technologycomputer.software_genreAtmospheric measurements01 natural sciencesConvolutional neural networkLinear regressionRedundancy (engineering)Information retrievalInfrared measurementsComputers in Earth SciencesEngineering (miscellaneous)021101 geological & geomatics engineering0105 earth and related environmental sciencesArtificial neural networkbusiness.industryDeep learningDimensionality reductionPattern recognitionAtomic and Molecular Physics and OpticsComputer Science Applications13. Climate actionNoise (video)Artificial intelligencebusinesscomputerNeural networksISPRS Journal of Photogrammetry and Remote Sensing
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Edge-Based Missing Data Imputation in Large-Scale Environments

2021

Smart cities leverage large amounts of data acquired in the urban environment in the context of decision support tools. These tools enable monitoring the environment to improve the quality of services offered to citizens. The increasing diffusion of personal Internet of things devices capable of sensing the physical environment allows for low-cost solutions to acquire a large amount of information within the urban environment. On the one hand, the use of mobile and intermittent sensors implies new scenarios of large-scale data analysis

010504 meteorology & atmospheric sciencesComputer scienceDistributed computingUrban sensingMobile sensingContext (language use)Information technology02 engineering and technology01 natural sciences[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Smart cityEdge intelligence11. Sustainability0202 electrical engineering electronic engineering information engineeringLeverage (statistics)Edge computingVoronoi tessellation0105 earth and related environmental sciencesSmart cityOut-of-order executionSettore INF/01 - InformaticaMulti-agent systemMissing data imputation020206 networking & telecommunicationsT58.5-58.64Variety (cybernetics)Multi-agent system[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]Mobile deviceInformation Systems
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Optimal modalities for radiative transfer-neural network estimation of canopy biophysical characteristics: Evaluation over an agricultural area with …

2011

International audience; Neural networks trained over radiative transfer simulations constitute the basis of several operational algorithms to estimate canopy biophysical variables from satellite reflectance measurements. However, only little attention was paid to the training process which has a major impact on retrieval performances. This study focused on the several modalities of the training process within neural network estimation of LAI, FCOVER and FAPAR biophysical variables. Performances were evaluated over both actual experimental observations and model simulations. The SAIL and PROSPECT radiative transfer models were used here to simulate the training and the synthetic test dataset…

010504 meteorology & atmospheric sciencesComputer scienceGaussian0211 other engineering and technologiesSoil ScienceCANOPY BIOPHYSICAL CHARACTERISTICS02 engineering and technologyNEURAL NETWORK01 natural sciencesTransfer functionsymbols.namesakeAtmospheric radiative transfer codesRadiative transferRange (statistics)Sensitivity (control systems)Computers in Earth Sciences021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingArtificial neural networkGeologySigmoid functionRELATION SOL-PLANTE-ATMOSPHEREMODEL INVERSION[SDE]Environmental SciencessymbolsINDICE FOLIAIRE
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